repo_id
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0000cd/wolf-set
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themes/bluf/static/js/APlayer.min.js
|
!function(e,t){"object"==typeof exports&&"object"==typeof module?module.exports=t():"function"==typeof define&&define.amd?define("APlayer",[],t):"object"==typeof exports?exports.APlayer=t():e.APlayer=t()}(window,function(){return function(e){var t={};function n(i){if(t[i])return t[i].exports;var a=t[i]={i:i,l:!1,exports:{}};return e[i].call(a.exports,a,a.exports,n),a.l=!0,a.exports}return n.m=e,n.c=t,n.d=function(e,t,i){n.o(e,t)||Object.defineProperty(e,t,{configurable:!1,enumerable:!0,get:i})},n.r=function(e){Object.defineProperty(e,"__esModule",{value:!0})},n.n=function(e){var t=e&&e.__esModule?function(){return e.default}:function(){return e};return n.d(t,"a",t),t},n.o=function(e,t){return Object.prototype.hasOwnProperty.call(e,t)},n.p="/",n(n.s=41)}([function(e,t,n){"use strict";Object.defineProperty(t,"__esModule",{value:!0});var i=/mobile/i.test(window.navigator.userAgent),a={secondToTime:function(e){var t=Math.floor(e/3600),n=Math.floor((e-3600*t)/60),i=Math.floor(e-3600*t-60*n);return(t>0?[t,n,i]:[n,i]).map(function(e){return e<10?"0"+e:""+e}).join(":")},getElementViewLeft:function(e){var t=e.offsetLeft,n=e.offsetParent,i=document.body.scrollLeft+document.documentElement.scrollLeft;if(document.fullscreenElement||document.mozFullScreenElement||document.webkitFullscreenElement)for(;null!==n&&n!==e;)t+=n.offsetLeft,n=n.offsetParent;else for(;null!==n;)t+=n.offsetLeft,n=n.offsetParent;return t-i},getElementViewTop:function(e,t){for(var n,i=e.offsetTop,a=e.offsetParent;null!==a;)i+=a.offsetTop,a=a.offsetParent;return n=document.body.scrollTop+document.documentElement.scrollTop,t?i:i-n},isMobile:i,storage:{set:function(e,t){localStorage.setItem(e,t)},get:function(e){return localStorage.getItem(e)}},nameMap:{dragStart:i?"touchstart":"mousedown",dragMove:i?"touchmove":"mousemove",dragEnd:i?"touchend":"mouseup"},randomOrder:function(e){return function(e){for(var t=e.length-1;t>=0;t--){var n=Math.floor(Math.random()*(t+1)),i=e[n];e[n]=e[t],e[t]=i}return e}([].concat(function(e){if(Array.isArray(e)){for(var t=0,n=Array(e.length);t<e.length;t++)n[t]=e[t];return n}return Array.from(e)}(Array(e))).map(function(e,t){return t}))}};t.default=a},function(e,t,n){var i=n(2);e.exports=function(e){"use strict";e=e||{};var t="",n=i.$each,a=e.audio,r=(e.$value,e.$index,i.$escape),o=e.theme,s=e.index;return n(a,function(e,n){t+='\n<li>\n <span class="aplayer-list-cur" style="background-color: ',t+=r(e.theme||o),t+=';"></span>\n <span class="aplayer-list-index">',t+=r(n+s),t+='</span>\n <span class="aplayer-list-title">',t+=r(e.name),t+='</span>\n <span class="aplayer-list-author">',t+=r(e.artist),t+="</span>\n</li>\n"}),t}},function(e,t,n){"use strict";e.exports=n(15)},function(e,t,n){"use strict";Object.defineProperty(t,"__esModule",{value:!0});var i=g(n(33)),a=g(n(32)),r=g(n(31)),o=g(n(30)),s=g(n(29)),l=g(n(28)),u=g(n(27)),c=g(n(26)),p=g(n(25)),d=g(n(24)),h=g(n(23)),y=g(n(22)),f=g(n(21)),v=g(n(20)),m=g(n(19));function g(e){return e&&e.__esModule?e:{default:e}}var w={play:i.default,pause:a.default,volumeUp:r.default,volumeDown:o.default,volumeOff:s.default,orderRandom:l.default,orderList:u.default,menu:c.default,loopAll:p.default,loopOne:d.default,loopNone:h.default,loading:y.default,right:f.default,skip:v.default,lrc:m.default};t.default=w},function(e,t,n){"use strict";var i,a="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(e){return typeof e}:function(e){return e&&"function"==typeof Symbol&&e.constructor===Symbol&&e!==Symbol.prototype?"symbol":typeof e};i=function(){return this}();try{i=i||Function("return this")()||(0,eval)("this")}catch(e){"object"===("undefined"==typeof window?"undefined":a(window))&&(i=window)}e.exports=i},function(e,t,n){"use strict";var i,a,r="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(e){return typeof e}:function(e){return e&&"function"==typeof Symbol&&e.constructor===Symbol&&e!==Symbol.prototype?"symbol":typeof e};void 0===(a="function"==typeof(i=function(){if("object"===("undefined"==typeof window?"undefined":r(window))&&void 0!==document.querySelectorAll&&void 0!==window.pageYOffset&&void 0!==history.pushState){var e=function(e,t,n,i){return n>i?t:e+(t-e)*((a=n/i)<.5?4*a*a*a:(a-1)*(2*a-2)*(2*a-2)+1);var a},t=function(t,n,i,a){n=n||500;var r=(a=a||window).scrollTop||window.pageYOffset;if("number"==typeof t)var o=parseInt(t);else var o=function(e,t){return"HTML"===e.nodeName?-t:e.getBoundingClientRect().top+t}(t,r);var s=Date.now(),l=window.requestAnimationFrame||window.mozRequestAnimationFrame||window.webkitRequestAnimationFrame||function(e){window.setTimeout(e,15)};!function u(){var c=Date.now()-s;a!==window?a.scrollTop=e(r,o,c,n):window.scroll(0,e(r,o,c,n)),c>n?"function"==typeof i&&i(t):l(u)}()},n=function(e){if(!e.defaultPrevented){e.preventDefault(),location.hash!==this.hash&&window.history.pushState(null,null,this.hash);var n=document.getElementById(this.hash.substring(1));if(!n)return;t(n,500,function(e){location.replace("#"+e.id)})}};return document.addEventListener("DOMContentLoaded",function(){for(var e,t=document.querySelectorAll('a[href^="#"]:not([href="#"])'),i=t.length;e=t[--i];)e.addEventListener("click",n,!1)}),t}})?i.call(t,n,t,e):i)||(e.exports=a)},function(e,t,n){"use strict";Object.defineProperty(t,"__esModule",{value:!0});var i=function(){function e(e,t){for(var n=0;n<t.length;n++){var i=t[n];i.enumerable=i.enumerable||!1,i.configurable=!0,"value"in i&&(i.writable=!0),Object.defineProperty(e,i.key,i)}}return function(t,n,i){return n&&e(t.prototype,n),i&&e(t,i),t}}(),a=s(n(1)),r=s(n(0)),o=s(n(5));function s(e){return e&&e.__esModule?e:{default:e}}var l=function(){function e(t){!function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}(this,e),this.player=t,this.index=0,this.audios=this.player.options.audio,this.bindEvents()}return i(e,[{key:"bindEvents",value:function(){var e=this;this.player.template.list.addEventListener("click",function(t){var n=void 0;n="LI"===t.target.tagName.toUpperCase()?t.target:t.target.parentElement;var i=parseInt(n.getElementsByClassName("aplayer-list-index")[0].innerHTML)-1;i!==e.index?(e.switch(i),e.player.play()):e.player.toggle()})}},{key:"show",value:function(){this.player.events.trigger("listshow"),this.player.template.list.classList.remove("aplayer-list-hide"),this.player.template.listOl.scrollTop=33*this.index}},{key:"hide",value:function(){this.player.events.trigger("listhide"),this.player.template.list.classList.add("aplayer-list-hide")}},{key:"toggle",value:function(){this.player.template.list.classList.contains("aplayer-list-hide")?this.show():this.hide()}},{key:"add",value:function(e){this.player.events.trigger("listadd",{audios:e}),"[object Array]"!==Object.prototype.toString.call(e)&&(e=[e]),e.map(function(e){return e.name=e.name||e.title||"Audio name",e.artist=e.artist||e.author||"Audio artist",e.cover=e.cover||e.pic,e.type=e.type||"normal",e});var t=!(this.audios.length>1),n=0===this.audios.length;this.player.template.listOl.innerHTML+=(0,a.default)({theme:this.player.options.theme,audio:e,index:this.audios.length+1}),this.audios=this.audios.concat(e),t&&this.audios.length>1&&this.player.container.classList.add("aplayer-withlist"),this.player.randomOrder=r.default.randomOrder(this.audios.length),this.player.template.listCurs=this.player.container.querySelectorAll(".aplayer-list-cur"),this.player.template.listCurs[this.audios.length-1].style.backgroundColor=e.theme||this.player.options.theme,n&&("random"===this.player.options.order?this.switch(this.player.randomOrder[0]):this.switch(0))}},{key:"remove",value:function(e){if(this.player.events.trigger("listremove",{index:e}),this.audios[e])if(this.audios.length>1){var t=this.player.container.querySelectorAll(".aplayer-list li");t[e].remove(),this.audios.splice(e,1),this.player.lrc&&this.player.lrc.remove(e),e===this.index&&(this.audios[e]?this.switch(e):this.switch(e-1)),this.index>e&&this.index--;for(var n=e;n<t.length;n++)t[n].getElementsByClassName("aplayer-list-index")[0].textContent=n;1===this.audios.length&&this.player.container.classList.remove("aplayer-withlist"),this.player.template.listCurs=this.player.container.querySelectorAll(".aplayer-list-cur")}else this.clear()}},{key:"switch",value:function(e){if(this.player.events.trigger("listswitch",{index:e}),void 0!==e&&this.audios[e]){this.index=e;var t=this.audios[this.index];this.player.template.pic.style.backgroundImage=t.cover?"url('"+t.cover+"')":"",this.player.theme(this.audios[this.index].theme||this.player.options.theme,this.index,!1),this.player.template.title.innerHTML=t.name,this.player.template.author.innerHTML=t.artist?" - "+t.artist:"";var n=this.player.container.getElementsByClassName("aplayer-list-light")[0];n&&n.classList.remove("aplayer-list-light"),this.player.container.querySelectorAll(".aplayer-list li")[this.index].classList.add("aplayer-list-light"),(0,o.default)(33*this.index,500,null,this.player.template.listOl),this.player.setAudio(t),this.player.lrc&&this.player.lrc.switch(this.index),this.player.lrc&&this.player.lrc.update(0),1!==this.player.duration&&(this.player.template.dtime.innerHTML=r.default.secondToTime(this.player.duration))}}},{key:"clear",value:function(){this.player.events.trigger("listclear"),this.index=0,this.player.container.classList.remove("aplayer-withlist"),this.player.pause(),this.audios=[],this.player.lrc&&this.player.lrc.clear(),this.player.audio.src="",this.player.template.listOl.innerHTML="",this.player.template.pic.style.backgroundImage="",this.player.theme(this.player.options.theme,this.index,!1),this.player.template.title.innerHTML="No audio",this.player.template.author.innerHTML="",this.player.bar.set("loaded",0,"width"),this.player.template.dtime.innerHTML=r.default.secondToTime(0)}}]),e}();t.default=l},function(e,t,n){"use strict";Object.defineProperty(t,"__esModule",{value:!0});var i=function(){function e(e,t){for(var n=0;n<t.length;n++){var i=t[n];i.enumerable=i.enumerable||!1,i.configurable=!0,"value"in i&&(i.writable=!0),Object.defineProperty(e,i.key,i)}}return function(t,n,i){return n&&e(t.prototype,n),i&&e(t,i),t}}();var a=function(){function e(){!function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}(this,e),this.events={},this.audioEvents=["abort","canplay","canplaythrough","durationchange","emptied","ended","error","loadeddata","loadedmetadata","loadstart","mozaudioavailable","pause","play","playing","progress","ratechange","seeked","seeking","stalled","suspend","timeupdate","volumechange","waiting"],this.playerEvents=["destroy","listshow","listhide","listadd","listremove","listswitch","listclear","noticeshow","noticehide","lrcshow","lrchide"]}return i(e,[{key:"on",value:function(e,t){this.type(e)&&"function"==typeof t&&(this.events[e]||(this.events[e]=[]),this.events[e].push(t))}},{key:"trigger",value:function(e,t){if(this.events[e]&&this.events[e].length)for(var n=0;n<this.events[e].length;n++)this.events[e][n](t)}},{key:"type",value:function(e){return-1!==this.playerEvents.indexOf(e)?"player":-1!==this.audioEvents.indexOf(e)?"audio":(console.error("Unknown event name: "+e),null)}}]),e}();t.default=a},function(e,t,n){"use strict";Object.defineProperty(t,"__esModule",{value:!0});var i=function(){function e(e,t){for(var n=0;n<t.length;n++){var i=t[n];i.enumerable=i.enumerable||!1,i.configurable=!0,"value"in i&&(i.writable=!0),Object.defineProperty(e,i.key,i)}}return function(t,n,i){return n&&e(t.prototype,n),i&&e(t,i),t}}();var a=function(){function e(t){!function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}(this,e),this.player=t,window.requestAnimationFrame=window.requestAnimationFrame||window.webkitRequestAnimationFrame||window.mozRequestAnimationFrame||window.oRequestAnimationFrame||window.msRequestAnimationFrame||function(e){window.setTimeout(e,1e3/60)},this.types=["loading"],this.init()}return i(e,[{key:"init",value:function(){var e=this;this.types.forEach(function(t){e["init"+t+"Checker"]()})}},{key:"initloadingChecker",value:function(){var e=this,t=0,n=0,i=!1;this.loadingChecker=setInterval(function(){e.enableloadingChecker&&(n=e.player.audio.currentTime,i||n!==t||e.player.audio.paused||(e.player.container.classList.add("aplayer-loading"),i=!0),i&&n>t&&!e.player.audio.paused&&(e.player.container.classList.remove("aplayer-loading"),i=!1),t=n)},100)}},{key:"enable",value:function(e){this["enable"+e+"Checker"]=!0,"fps"===e&&this.initfpsChecker()}},{key:"disable",value:function(e){this["enable"+e+"Checker"]=!1}},{key:"destroy",value:function(){var e=this;this.types.forEach(function(t){e["enable"+t+"Checker"]=!1,e[t+"Checker"]&&clearInterval(e[t+"Checker"])})}}]),e}();t.default=a},function(e,t,n){"use strict";Object.defineProperty(t,"__esModule",{value:!0});var i=function(){function e(e,t){for(var n=0;n<t.length;n++){var i=t[n];i.enumerable=i.enumerable||!1,i.configurable=!0,"value"in i&&(i.writable=!0),Object.defineProperty(e,i.key,i)}}return function(t,n,i){return n&&e(t.prototype,n),i&&e(t,i),t}}(),a=o(n(0)),r=o(n(3));function o(e){return e&&e.__esModule?e:{default:e}}var s=function(){function e(t){!function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}(this,e),this.player=t,this.initPlayButton(),this.initPlayBar(),this.initOrderButton(),this.initLoopButton(),this.initMenuButton(),a.default.isMobile||this.initVolumeButton(),this.initMiniSwitcher(),this.initSkipButton(),this.initLrcButton()}return i(e,[{key:"initPlayButton",value:function(){var e=this;this.player.template.pic.addEventListener("click",function(){e.player.toggle()})}},{key:"initPlayBar",value:function(){var e=this,t=function(t){var n=((t.clientX||t.changedTouches[0].clientX)-a.default.getElementViewLeft(e.player.template.barWrap))/e.player.template.barWrap.clientWidth;n=Math.max(n,0),n=Math.min(n,1),e.player.bar.set("played",n,"width"),e.player.lrc&&e.player.lrc.update(n*e.player.duration),e.player.template.ptime.innerHTML=a.default.secondToTime(n*e.player.duration)},n=function n(i){document.removeEventListener(a.default.nameMap.dragEnd,n),document.removeEventListener(a.default.nameMap.dragMove,t);var r=((i.clientX||i.changedTouches[0].clientX)-a.default.getElementViewLeft(e.player.template.barWrap))/e.player.template.barWrap.clientWidth;r=Math.max(r,0),r=Math.min(r,1),e.player.bar.set("played",r,"width"),e.player.seek(e.player.bar.get("played","width")*e.player.duration),e.player.disableTimeupdate=!1};this.player.template.barWrap.addEventListener(a.default.nameMap.dragStart,function(){e.player.disableTimeupdate=!0,document.addEventListener(a.default.nameMap.dragMove,t),document.addEventListener(a.default.nameMap.dragEnd,n)})}},{key:"initVolumeButton",value:function(){var e=this;this.player.template.volumeButton.addEventListener("click",function(){e.player.audio.muted?(e.player.audio.muted=!1,e.player.switchVolumeIcon(),e.player.bar.set("volume",e.player.volume(),"height")):(e.player.audio.muted=!0,e.player.switchVolumeIcon(),e.player.bar.set("volume",0,"height"))});var t=function(t){var n=1-((t.clientY||t.changedTouches[0].clientY)-a.default.getElementViewTop(e.player.template.volumeBar,e.player.options.fixed))/e.player.template.volumeBar.clientHeight;n=Math.max(n,0),n=Math.min(n,1),e.player.volume(n)},n=function n(i){e.player.template.volumeBarWrap.classList.remove("aplayer-volume-bar-wrap-active"),document.removeEventListener(a.default.nameMap.dragEnd,n),document.removeEventListener(a.default.nameMap.dragMove,t);var r=1-((i.clientY||i.changedTouches[0].clientY)-a.default.getElementViewTop(e.player.template.volumeBar,e.player.options.fixed))/e.player.template.volumeBar.clientHeight;r=Math.max(r,0),r=Math.min(r,1),e.player.volume(r)};this.player.template.volumeBarWrap.addEventListener(a.default.nameMap.dragStart,function(){e.player.template.volumeBarWrap.classList.add("aplayer-volume-bar-wrap-active"),document.addEventListener(a.default.nameMap.dragMove,t),document.addEventListener(a.default.nameMap.dragEnd,n)})}},{key:"initOrderButton",value:function(){var e=this;this.player.template.order.addEventListener("click",function(){"list"===e.player.options.order?(e.player.options.order="random",e.player.template.order.innerHTML=r.default.orderRandom):"random"===e.player.options.order&&(e.player.options.order="list",e.player.template.order.innerHTML=r.default.orderList)})}},{key:"initLoopButton",value:function(){var e=this;this.player.template.loop.addEventListener("click",function(){e.player.list.audios.length>1?"one"===e.player.options.loop?(e.player.options.loop="none",e.player.template.loop.innerHTML=r.default.loopNone):"none"===e.player.options.loop?(e.player.options.loop="all",e.player.template.loop.innerHTML=r.default.loopAll):"all"===e.player.options.loop&&(e.player.options.loop="one",e.player.template.loop.innerHTML=r.default.loopOne):"one"===e.player.options.loop||"all"===e.player.options.loop?(e.player.options.loop="none",e.player.template.loop.innerHTML=r.default.loopNone):"none"===e.player.options.loop&&(e.player.options.loop="all",e.player.template.loop.innerHTML=r.default.loopAll)})}},{key:"initMenuButton",value:function(){var e=this;this.player.template.menu.addEventListener("click",function(){e.player.list.toggle()})}},{key:"initMiniSwitcher",value:function(){var e=this;this.player.template.miniSwitcher.addEventListener("click",function(){e.player.setMode("mini"===e.player.mode?"normal":"mini")})}},{key:"initSkipButton",value:function(){var e=this;this.player.template.skipBackButton.addEventListener("click",function(){e.player.skipBack()}),this.player.template.skipForwardButton.addEventListener("click",function(){e.player.skipForward()}),this.player.template.skipPlayButton.addEventListener("click",function(){e.player.toggle()})}},{key:"initLrcButton",value:function(){var e=this;this.player.template.lrcButton.addEventListener("click",function(){e.player.template.lrcButton.classList.contains("aplayer-icon-lrc-inactivity")?(e.player.template.lrcButton.classList.remove("aplayer-icon-lrc-inactivity"),e.player.lrc&&e.player.lrc.show()):(e.player.template.lrcButton.classList.add("aplayer-icon-lrc-inactivity"),e.player.lrc&&e.player.lrc.hide())})}}]),e}();t.default=s},function(e,t,n){var i=n(2);e.exports=function(e){"use strict";e=e||{};var t="",n=i.$each,a=e.lyrics,r=(e.$value,e.$index,i.$escape);return n(a,function(e,n){t+="\n <p",0===n&&(t+=' class="aplayer-lrc-current"'),t+=">",t+=r(e[1]),t+="</p>\n"}),t}},function(e,t,n){"use strict";Object.defineProperty(t,"__esModule",{value:!0});var i,a=function(){function e(e,t){for(var n=0;n<t.length;n++){var i=t[n];i.enumerable=i.enumerable||!1,i.configurable=!0,"value"in i&&(i.writable=!0),Object.defineProperty(e,i.key,i)}}return function(t,n,i){return n&&e(t.prototype,n),i&&e(t,i),t}}(),r=n(10),o=(i=r)&&i.__esModule?i:{default:i};var s=function(){function e(t){!function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}(this,e),this.container=t.container,this.async=t.async,this.player=t.player,this.parsed=[],this.index=0,this.current=[]}return a(e,[{key:"show",value:function(){this.player.events.trigger("lrcshow"),this.player.template.lrcWrap.classList.remove("aplayer-lrc-hide")}},{key:"hide",value:function(){this.player.events.trigger("lrchide"),this.player.template.lrcWrap.classList.add("aplayer-lrc-hide")}},{key:"toggle",value:function(){this.player.template.lrcWrap.classList.contains("aplayer-lrc-hide")?this.show():this.hide()}},{key:"update",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:this.player.audio.currentTime;if(this.index>this.current.length-1||e<this.current[this.index][0]||!this.current[this.index+1]||e>=this.current[this.index+1][0])for(var t=0;t<this.current.length;t++)e>=this.current[t][0]&&(!this.current[t+1]||e<this.current[t+1][0])&&(this.index=t,this.container.style.transform="translateY("+16*-this.index+"px)",this.container.style.webkitTransform="translateY("+16*-this.index+"px)",this.container.getElementsByClassName("aplayer-lrc-current")[0].classList.remove("aplayer-lrc-current"),this.container.getElementsByTagName("p")[t].classList.add("aplayer-lrc-current"))}},{key:"switch",value:function(e){var t=this;if(!this.parsed[e])if(this.async){this.parsed[e]=[["00:00","Loading"]];var n=new XMLHttpRequest;n.onreadystatechange=function(){e===t.player.list.index&&4===n.readyState&&(n.status>=200&&n.status<300||304===n.status?t.parsed[e]=t.parse(n.responseText):(t.player.notice("LRC file request fails: status "+n.status),t.parsed[e]=[["00:00","Not available"]]),t.container.innerHTML=(0,o.default)({lyrics:t.parsed[e]}),t.update(0),t.current=t.parsed[e])};var i=this.player.list.audios[e].lrc;n.open("get",i,!0),n.send(null)}else this.player.list.audios[e].lrc?this.parsed[e]=this.parse(this.player.list.audios[e].lrc):this.parsed[e]=[["00:00","Not available"]];this.container.innerHTML=(0,o.default)({lyrics:this.parsed[e]}),this.update(0),this.current=this.parsed[e]}},{key:"parse",value:function(e){if(e){for(var t=(e=e.replace(/([^\]^\n])\[/g,function(e,t){return t+"\n["})).split("\n"),n=[],i=t.length,a=0;a<i;a++){var r=t[a].match(/\[(\d{2}):(\d{2})(\.(\d{2,3}))?]/g),o=t[a].replace(/.*\[(\d{2}):(\d{2})(\.(\d{2,3}))?]/g,"").replace(/<(\d{2}):(\d{2})(\.(\d{2,3}))?>/g,"").replace(/^\s+|\s+$/g,"");if(r)for(var s=r.length,l=0;l<s;l++){var u=/\[(\d{2}):(\d{2})(\.(\d{2,3}))?]/.exec(r[l]),c=60*u[1]+parseInt(u[2])+(u[4]?parseInt(u[4])/(2===(u[4]+"").length?100:1e3):0);n.push([c,o])}}return(n=n.filter(function(e){return e[1]})).sort(function(e,t){return e[0]-t[0]}),n}return[]}},{key:"remove",value:function(e){this.parsed.splice(e,1)}},{key:"clear",value:function(){this.parsed=[],this.container.innerHTML=""}}]),e}();t.default=s},function(e,t,n){"use strict";Object.defineProperty(t,"__esModule",{value:!0});var i,a=function(){function e(e,t){for(var n=0;n<t.length;n++){var i=t[n];i.enumerable=i.enumerable||!1,i.configurable=!0,"value"in i&&(i.writable=!0),Object.defineProperty(e,i.key,i)}}return function(t,n,i){return n&&e(t.prototype,n),i&&e(t,i),t}}(),r=n(0),o=(i=r)&&i.__esModule?i:{default:i};var s=function(){function e(t){!function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}(this,e),this.storageName=t.options.storageName,this.data=JSON.parse(o.default.storage.get(this.storageName)),this.data||(this.data={}),this.data.volume=this.data.volume||t.options.volume}return a(e,[{key:"get",value:function(e){return this.data[e]}},{key:"set",value:function(e,t){this.data[e]=t,o.default.storage.set(this.storageName,JSON.stringify(this.data))}}]),e}();t.default=s},function(e,t,n){"use strict";Object.defineProperty(t,"__esModule",{value:!0});var i=function(){function e(e,t){for(var n=0;n<t.length;n++){var i=t[n];i.enumerable=i.enumerable||!1,i.configurable=!0,"value"in i&&(i.writable=!0),Object.defineProperty(e,i.key,i)}}return function(t,n,i){return n&&e(t.prototype,n),i&&e(t,i),t}}();var a=function(){function e(t){!function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}(this,e),this.elements={},this.elements.volume=t.volume,this.elements.played=t.played,this.elements.loaded=t.loaded}return i(e,[{key:"set",value:function(e,t,n){t=Math.max(t,0),t=Math.min(t,1),this.elements[e].style[n]=100*t+"%"}},{key:"get",value:function(e,t){return parseFloat(this.elements[e].style[t])/100}}]),e}();t.default=a},function(e,t,n){"use strict";(function(t){e.exports=!1;try{e.exports="[object process]"===Object.prototype.toString.call(t.process)}catch(e){}}).call(this,n(4))},function(e,t,n){"use strict";(function(t){var i=n(14),a=Object.create(i?t:window),r=/["&'<>]/;a.$escape=function(e){return function(e){var t=""+e,n=r.exec(t);if(!n)return e;var i="",a=void 0,o=void 0,s=void 0;for(a=n.index,o=0;a<t.length;a++){switch(t.charCodeAt(a)){case 34:s=""";break;case 38:s="&";break;case 39:s="'";break;case 60:s="<";break;case 62:s=">";break;default:continue}o!==a&&(i+=t.substring(o,a)),o=a+1,i+=s}return o!==a?i+t.substring(o,a):i}(function e(t){"string"!=typeof t&&(t=void 0===t||null===t?"":"function"==typeof t?e(t.call(t)):JSON.stringify(t));return t}(e))},a.$each=function(e,t){if(Array.isArray(e))for(var n=0,i=e.length;n<i;n++)t(e[n],n);else for(var a in e)t(e[a],a)},e.exports=a}).call(this,n(4))},function(e,t,n){var i=n(2);e.exports=function(e){"use strict";var t="",a=(e=e||{}).options,r=e.cover,o=i.$escape,s=e.icons,l=(arguments[1],function(e){return t+=e}),u=e.getObject;e.theme,e.audio,e.index;return a.fixed?(t+='\n<div class="aplayer-list',a.listFolded&&(t+=" aplayer-list-hide"),t+='"',a.listMaxHeight&&(t+=' style="max-height: ',t+=o(a.listMaxHeight),t+='"'),t+=">\n <ol",a.listMaxHeight&&(t+=' style="max-height: ',t+=o(a.listMaxHeight),t+='"'),t+=">\n ",l(n(1)(u({theme:a.theme,audio:a.audio,index:1}))),t+='\n </ol>\n</div>\n<div class="aplayer-body">\n <div class="aplayer-pic" style="',r&&(t+="background-image: url("",t+=o(r),t+="");"),t+="background-color: ",t+=o(a.theme),t+=';">\n <div class="aplayer-button aplayer-play">',t+=s.play,t+='</div>\n </div>\n <div class="aplayer-info" style="display: none;">\n <div class="aplayer-music">\n <span class="aplayer-title">No audio</span>\n <span class="aplayer-author"></span>\n </div>\n <div class="aplayer-controller">\n <div class="aplayer-bar-wrap">\n <div class="aplayer-bar">\n <div class="aplayer-loaded" style="width: 0"></div>\n <div class="aplayer-played" style="width: 0; background: ',t+=o(a.theme),t+=';">\n <span class="aplayer-thumb" style="background: ',t+=o(a.theme),t+=';">\n <span class="aplayer-loading-icon">',t+=s.loading,t+='</span>\n </span>\n </div>\n </div>\n </div>\n <div class="aplayer-time">\n <span class="aplayer-time-inner">\n <span class="aplayer-ptime">00:00</span> / <span class="aplayer-dtime">00:00</span>\n </span>\n <span class="aplayer-icon aplayer-icon-back">\n ',t+=s.skip,t+='\n </span>\n <span class="aplayer-icon aplayer-icon-play">\n ',t+=s.play,t+='\n </span>\n <span class="aplayer-icon aplayer-icon-forward">\n ',t+=s.skip,t+='\n </span>\n <div class="aplayer-volume-wrap">\n <button type="button" class="aplayer-icon aplayer-icon-volume-down">\n ',t+=s.volumeDown,t+='\n </button>\n <div class="aplayer-volume-bar-wrap">\n <div class="aplayer-volume-bar">\n <div class="aplayer-volume" style="height: 80%; background: ',t+=o(a.theme),t+=';"></div>\n </div>\n </div>\n </div>\n <button type="button" class="aplayer-icon aplayer-icon-order">\n ',"list"===a.order?t+=s.orderList:"random"===a.order&&(t+=s.orderRandom),t+='\n </button>\n <button type="button" class="aplayer-icon aplayer-icon-loop">\n ',"one"===a.loop?t+=s.loopOne:"all"===a.loop?t+=s.loopAll:"none"===a.loop&&(t+=s.loopNone),t+='\n </button>\n <button type="button" class="aplayer-icon aplayer-icon-menu">\n ',t+=s.menu,t+='\n </button>\n <button type="button" class="aplayer-icon aplayer-icon-lrc">\n ',t+=s.lrc,t+='\n </button>\n </div>\n </div>\n </div>\n <div class="aplayer-notice"></div>\n <div class="aplayer-miniswitcher"><button class="aplayer-icon">',t+=s.right,t+='</button></div>\n</div>\n<div class="aplayer-lrc">\n <div class="aplayer-lrc-contents" style="transform: translateY(0); -webkit-transform: translateY(0);"></div>\n</div>\n'):(t+='\n<div class="aplayer-body">\n <div class="aplayer-pic" style="',r&&(t+="background-image: url("",t+=o(r),t+="");"),t+="background-color: ",t+=o(a.theme),t+=';">\n <div class="aplayer-button aplayer-play">',t+=s.play,t+='</div>\n </div>\n <div class="aplayer-info">\n <div class="aplayer-music">\n <span class="aplayer-title">No audio</span>\n <span class="aplayer-author"></span>\n </div>\n <div class="aplayer-lrc">\n <div class="aplayer-lrc-contents" style="transform: translateY(0); -webkit-transform: translateY(0);"></div>\n </div>\n <div class="aplayer-controller">\n <div class="aplayer-bar-wrap">\n <div class="aplayer-bar">\n <div class="aplayer-loaded" style="width: 0"></div>\n <div class="aplayer-played" style="width: 0; background: ',t+=o(a.theme),t+=';">\n <span class="aplayer-thumb" style="background: ',t+=o(a.theme),t+=';">\n <span class="aplayer-loading-icon">',t+=s.loading,t+='</span>\n </span>\n </div>\n </div>\n </div>\n <div class="aplayer-time">\n <span class="aplayer-time-inner">\n <span class="aplayer-ptime">00:00</span> / <span class="aplayer-dtime">00:00</span>\n </span>\n <span class="aplayer-icon aplayer-icon-back">\n ',t+=s.skip,t+='\n </span>\n <span class="aplayer-icon aplayer-icon-play">\n ',t+=s.play,t+='\n </span>\n <span class="aplayer-icon aplayer-icon-forward">\n ',t+=s.skip,t+='\n </span>\n <div class="aplayer-volume-wrap">\n <button type="button" class="aplayer-icon aplayer-icon-volume-down">\n ',t+=s.volumeDown,t+='\n </button>\n <div class="aplayer-volume-bar-wrap">\n <div class="aplayer-volume-bar">\n <div class="aplayer-volume" style="height: 80%; background: ',t+=o(a.theme),t+=';"></div>\n </div>\n </div>\n </div>\n <button type="button" class="aplayer-icon aplayer-icon-order">\n ',"list"===a.order?t+=s.orderList:"random"===a.order&&(t+=s.orderRandom),t+='\n </button>\n <button type="button" class="aplayer-icon aplayer-icon-loop">\n ',"one"===a.loop?t+=s.loopOne:"all"===a.loop?t+=s.loopAll:"none"===a.loop&&(t+=s.loopNone),t+='\n </button>\n <button type="button" class="aplayer-icon aplayer-icon-menu">\n ',t+=s.menu,t+='\n </button>\n <button type="button" class="aplayer-icon aplayer-icon-lrc">\n ',t+=s.lrc,t+='\n </button>\n </div>\n </div>\n </div>\n <div class="aplayer-notice"></div>\n <div class="aplayer-miniswitcher"><button class="aplayer-icon">',t+=s.right,t+='</button></div>\n</div>\n<div class="aplayer-list',a.listFolded&&(t+=" aplayer-list-hide"),t+='"',a.listMaxHeight&&(t+=' style="max-height: ',t+=o(a.listMaxHeight),t+='"'),t+=">\n <ol",a.listMaxHeight&&(t+=' style="max-height: ',t+=o(a.listMaxHeight),t+='"'),t+=">\n ",l(n(1)(u({theme:a.theme,audio:a.audio,index:1}))),t+="\n </ol>\n</div>\n"),t}},function(e,t,n){"use strict";Object.defineProperty(t,"__esModule",{value:!0});var i=function(){function e(e,t){for(var n=0;n<t.length;n++){var i=t[n];i.enumerable=i.enumerable||!1,i.configurable=!0,"value"in i&&(i.writable=!0),Object.defineProperty(e,i.key,i)}}return function(t,n,i){return n&&e(t.prototype,n),i&&e(t,i),t}}(),a=o(n(3)),r=o(n(16));function o(e){return e&&e.__esModule?e:{default:e}}var s=function(){function e(t){!function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}(this,e),this.container=t.container,this.options=t.options,this.randomOrder=t.randomOrder,this.init()}return i(e,[{key:"init",value:function(){var e="";this.options.audio.length&&(e="random"===this.options.order?this.options.audio[this.randomOrder[0]].cover:this.options.audio[0].cover),this.container.innerHTML=(0,r.default)({options:this.options,icons:a.default,cover:e,getObject:function(e){return e}}),this.lrc=this.container.querySelector(".aplayer-lrc-contents"),this.lrcWrap=this.container.querySelector(".aplayer-lrc"),this.ptime=this.container.querySelector(".aplayer-ptime"),this.info=this.container.querySelector(".aplayer-info"),this.time=this.container.querySelector(".aplayer-time"),this.barWrap=this.container.querySelector(".aplayer-bar-wrap"),this.button=this.container.querySelector(".aplayer-button"),this.body=this.container.querySelector(".aplayer-body"),this.list=this.container.querySelector(".aplayer-list"),this.listOl=this.container.querySelector(".aplayer-list ol"),this.listCurs=this.container.querySelectorAll(".aplayer-list-cur"),this.played=this.container.querySelector(".aplayer-played"),this.loaded=this.container.querySelector(".aplayer-loaded"),this.thumb=this.container.querySelector(".aplayer-thumb"),this.volume=this.container.querySelector(".aplayer-volume"),this.volumeBar=this.container.querySelector(".aplayer-volume-bar"),this.volumeButton=this.container.querySelector(".aplayer-time button"),this.volumeBarWrap=this.container.querySelector(".aplayer-volume-bar-wrap"),this.loop=this.container.querySelector(".aplayer-icon-loop"),this.order=this.container.querySelector(".aplayer-icon-order"),this.menu=this.container.querySelector(".aplayer-icon-menu"),this.pic=this.container.querySelector(".aplayer-pic"),this.title=this.container.querySelector(".aplayer-title"),this.author=this.container.querySelector(".aplayer-author"),this.dtime=this.container.querySelector(".aplayer-dtime"),this.notice=this.container.querySelector(".aplayer-notice"),this.miniSwitcher=this.container.querySelector(".aplayer-miniswitcher"),this.skipBackButton=this.container.querySelector(".aplayer-icon-back"),this.skipForwardButton=this.container.querySelector(".aplayer-icon-forward"),this.skipPlayButton=this.container.querySelector(".aplayer-icon-play"),this.lrcButton=this.container.querySelector(".aplayer-icon-lrc")}}]),e}();t.default=s},function(e,t,n){"use 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0!==arguments[2])||arguments[2])&&this.list.audios[t]&&(this.list.audios[t].theme=e),this.template.listCurs[t]&&(this.template.listCurs[t].style.backgroundColor=e),t===this.list.index&&(this.template.pic.style.backgroundColor=e,this.template.played.style.background=e,this.template.thumb.style.background=e,this.template.volume.style.background=e)}},{key:"seek",value:function(e){e=Math.max(e,0),e=Math.min(e,this.duration),this.audio.currentTime=e,this.bar.set("played",e/this.duration,"width"),this.template.ptime.innerHTML=r.default.secondToTime(e)}},{key:"setUIPlaying",value:function(){var e=this;if(this.paused&&(this.paused=!1,this.template.button.classList.remove("aplayer-play"),this.template.button.classList.add("aplayer-pause"),this.template.button.innerHTML="",setTimeout(function(){e.template.button.innerHTML=o.default.pause},100),this.template.skipPlayButton.innerHTML=o.default.pause),this.timer.enable("loading"),this.options.mutex)for(var t=0;t<m.length;t++)this!==m[t]&&m[t].pause()}},{key:"play",value:function(){var e=this;this.setUIPlaying();var t=this.audio.play();t&&t.catch(function(t){console.warn(t),"NotAllowedError"===t.name&&e.setUIPaused()})}},{key:"setUIPaused",value:function(){var e=this;this.paused||(this.paused=!0,this.template.button.classList.remove("aplayer-pause"),this.template.button.classList.add("aplayer-play"),this.template.button.innerHTML="",setTimeout(function(){e.template.button.innerHTML=o.default.play},100),this.template.skipPlayButton.innerHTML=o.default.play),this.container.classList.remove("aplayer-loading"),this.timer.disable("loading")}},{key:"pause",value:function(){this.setUIPaused(),this.audio.pause()}},{key:"switchVolumeIcon",value:function(){this.volume()>=.95?this.template.volumeButton.innerHTML=o.default.volumeUp:this.volume()>0?this.template.volumeButton.innerHTML=o.default.volumeDown:this.template.volumeButton.innerHTML=o.default.volumeOff}},{key:"volume",value:function(e,t){return e=parseFloat(e),isNaN(e)||(e=Math.max(e,0),e=Math.min(e,1),this.bar.set("volume",e,"height"),t||this.storage.set("volume",e),this.audio.volume=e,this.audio.muted&&(this.audio.muted=!1),this.switchVolumeIcon()),this.audio.muted?0:this.audio.volume}},{key:"on",value:function(e,t){this.events.on(e,t)}},{key:"toggle",value:function(){this.template.button.classList.contains("aplayer-play")?this.play():this.template.button.classList.contains("aplayer-pause")&&this.pause()}},{key:"switchAudio",value:function(e){this.list.switch(e)}},{key:"addAudio",value:function(e){this.list.add(e)}},{key:"removeAudio",value:function(e){this.list.remove(e)}},{key:"destroy",value:function(){m.splice(m.indexOf(this),1),this.pause(),this.container.innerHTML="",this.audio.src="",this.timer.destroy(),this.events.trigger("destroy")}},{key:"setMode",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"normal";this.mode=e,"mini"===e?this.container.classList.add("aplayer-narrow"):"normal"===e&&this.container.classList.remove("aplayer-narrow")}},{key:"notice",value:function(e){var t=this,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:2e3,i=arguments.length>2&&void 0!==arguments[2]?arguments[2]:.8;this.template.notice.innerHTML=e,this.template.notice.style.opacity=i,this.noticeTime&&clearTimeout(this.noticeTime),this.events.trigger("noticeshow",{text:e}),n&&(this.noticeTime=setTimeout(function(){t.template.notice.style.opacity=0,t.events.trigger("noticehide")},n))}},{key:"prevIndex",value:function(){if(!(this.list.audios.length>1))return 0;if("list"===this.options.order)return this.list.index-1<0?this.list.audios.length-1:this.list.index-1;if("random"===this.options.order){var e=this.randomOrder.indexOf(this.list.index);return 0===e?this.randomOrder[this.randomOrder.length-1]:this.randomOrder[e-1]}}},{key:"nextIndex",value:function(){if(!(this.list.audios.length>1))return 0;if("list"===this.options.order)return(this.list.index+1)%this.list.audios.length;if("random"===this.options.order){var e=this.randomOrder.indexOf(this.list.index);return e===this.randomOrder.length-1?this.randomOrder[0]:this.randomOrder[e+1]}}},{key:"skipBack",value:function(){this.list.switch(this.prevIndex())}},{key:"skipForward",value:function(){this.list.switch(this.nextIndex())}},{key:"duration",get:function(){return isNaN(this.audio.duration)?0:this.audio.duration}}],[{key:"version",get:function(){return"1.10.1"}}]),e}();t.default=g},,function(e,t,n){},function(e,t,n){"use strict";Object.defineProperty(t,"__esModule",{value:!0}),n(40);var i,a=n(38),r=(i=a)&&i.__esModule?i:{default:i};console.log("\n %c APlayer v1.10.1 af84efb %c http://aplayer.js.org \n","color: #fadfa3; background: #030307; padding:5px 0;","background: #fadfa3; padding:5px 0;"),t.default=r.default}]).default});
//# sourceMappingURL=APlayer.min.js.map
|
000haoji/deep-student
| 16,604 |
src/components/KnowledgeGraphManagement.tsx
|
import React, { useState, useEffect } from 'react';
import { invoke } from '@tauri-apps/api/core';
import {
ProblemCard,
SearchRequest,
SearchResult,
CreateCardRequest,
GraphConfig,
Recommendation,
RecommendationRequest,
Tag
} from '../types/cogni-graph';
import GraphVisualization from './GraphVisualization';
import TagManagement from './TagManagement';
import './KnowledgeGraphManagement.css';
const KnowledgeGraphManagement: React.FC = () => {
const [isInitialized, setIsInitialized] = useState(false);
const [config, setConfig] = useState<GraphConfig>({
neo4j: {
uri: 'neo4j://127.0.0.1:7687',
username: 'neo4j',
password: '',
database: undefined
},
vector_dimensions: 1536,
similarity_threshold: 0.7,
max_search_results: 100,
recommendation_limit: 10
});
const [searchQuery, setSearchQuery] = useState('');
const [searchResults, setSearchResults] = useState<SearchResult[]>([]);
const [selectedCard, setSelectedCard] = useState<ProblemCard | null>(null);
const [recommendations, setRecommendations] = useState<Recommendation[]>([]);
const [allTags, setAllTags] = useState<Tag[]>([]);
const [activeTab, setActiveTab] = useState<'cards' | 'visualization' | 'tags'>('cards');
const [newCard, setNewCard] = useState<CreateCardRequest>({
content_problem: '',
content_insight: '',
tags: [],
source_excalidraw_path: undefined
});
const [loading, setLoading] = useState(false);
const [error, setError] = useState<string | null>(null);
// Initialize knowledge graph
const initializeGraph = async () => {
try {
setLoading(true);
setError(null);
const result = await invoke<string>('initialize_knowledge_graph', { config });
console.log('Graph initialized:', result);
setIsInitialized(true);
// Load initial data
await loadAllTags();
} catch (err) {
setError(`Failed to initialize: ${err}`);
console.error('Initialization error:', err);
} finally {
setLoading(false);
}
};
// Test Neo4j connection
const testConnection = async () => {
try {
setLoading(true);
setError(null);
const result = await invoke<string>('test_neo4j_connection', { config });
alert(`连接测试成功: ${result}`);
} catch (err) {
const errorMsg = `连接失败: ${err}`;
setError(errorMsg);
// Provide helpful error guidance
if (String(err).includes('authentication failure')) {
setError(errorMsg + '\n\n请检查:\n1. Neo4j是否正在运行\n2. 用户名和密码是否正确\n3. 默认密码可能需要重置');
} else if (String(err).includes('Connection refused')) {
setError(errorMsg + '\n\n请检查:\n1. Neo4j服务是否启动\n2. 端口7687是否开放\n3. 连接地址是否正确');
}
} finally {
setLoading(false);
}
};
// Create new problem card
const createCard = async () => {
if (!newCard.content_problem.trim() || !newCard.content_insight.trim()) {
setError('Please fill in both problem and insight fields');
return;
}
try {
setLoading(true);
setError(null);
const cardId = await invoke<string>('create_problem_card', { request: newCard });
console.log('Card created:', cardId);
// Reset form
setNewCard({
content_problem: '',
content_insight: '',
tags: [],
source_excalidraw_path: undefined
});
// Refresh tags
await loadAllTags();
alert(`Card created successfully with ID: ${cardId}`);
} catch (err) {
setError(`Failed to create card: ${err}`);
} finally {
setLoading(false);
}
};
// Search knowledge graph
const searchGraph = async () => {
if (!searchQuery.trim()) return;
try {
setLoading(true);
setError(null);
const request: SearchRequest = {
query: searchQuery,
limit: 20
};
const results = await invoke<SearchResult[]>('search_knowledge_graph', { request });
setSearchResults(results);
} catch (err) {
setError(`Search failed: ${err}`);
} finally {
setLoading(false);
}
};
// Get card details and recommendations
const selectCard = async (card: ProblemCard) => {
try {
setSelectedCard(card);
setLoading(true);
setError(null);
// Get AI recommendations
const request: RecommendationRequest = {
card_id: card.id,
limit: 5
};
const recs = await invoke<Recommendation[]>('get_ai_recommendations', { request });
setRecommendations(recs);
} catch (err) {
setError(`Failed to get recommendations: ${err}`);
} finally {
setLoading(false);
}
};
// Load all tags
const loadAllTags = async () => {
try {
const tags = await invoke<Tag[]>('get_all_tags');
setAllTags(tags);
} catch (err) {
console.error('Failed to load tags:', err);
}
};
return (
<div className="knowledge-graph-management">
<h2>CogniGraph 知识图谱管理</h2>
{error && (
<div className="error-message">
错误: {error}
</div>
)}
{!isInitialized ? (
<div className="initialization-section">
<h3>Neo4j 配置</h3>
<div className="setup-help">
<h4>快速设置 Neo4j</h4>
<div className="help-option">
<strong>Neo4j Desktop (当前推荐):</strong>
<div>1. URI: <code>neo4j://127.0.0.1:7687</code> 或 <code>bolt://127.0.0.1:7687</code></div>
<div>2. 用户名: <code>neo4j</code></div>
<div>3. 密码: 你设置的数据库密码</div>
</div>
<div className="help-option">
<strong>Docker方式:</strong>
<code>
docker run --name neo4j-cogni --publish=7474:7474 --publish=7687:7687 --env=NEO4J_AUTH=neo4j/password neo4j:latest
</code>
</div>
<div className="help-option">
<strong>下载 Neo4j Desktop:</strong>
<a href="https://neo4j.com/download/" target="_blank" rel="noopener noreferrer">
https://neo4j.com/download/
</a>
</div>
</div>
<div className="config-form">
<div className="form-group">
<label>数据库地址:</label>
<input
type="text"
value={config.neo4j.uri}
onChange={(e) => setConfig({
...config,
neo4j: { ...config.neo4j, uri: e.target.value }
})}
placeholder="neo4j://127.0.0.1:7687"
/>
</div>
<div className="form-group">
<label>用户名:</label>
<input
type="text"
value={config.neo4j.username}
onChange={(e) => setConfig({
...config,
neo4j: { ...config.neo4j, username: e.target.value }
})}
/>
</div>
<div className="form-group">
<label>密码:</label>
<input
type="password"
value={config.neo4j.password}
onChange={(e) => setConfig({
...config,
neo4j: { ...config.neo4j, password: e.target.value }
})}
placeholder="输入你在Neo4j Desktop中设置的密码"
/>
</div>
<div className="button-group">
<button onClick={testConnection} disabled={loading}>
测试连接
</button>
<button onClick={initializeGraph} disabled={loading}>
初始化图谱
</button>
</div>
</div>
</div>
) : (
<div className="main-interface">
{/* Tab navigation */}
<div className="tab-navigation">
<button
className={`tab-button ${activeTab === 'cards' ? 'active' : ''}`}
onClick={() => setActiveTab('cards')}
>
📋 问题卡片管理
</button>
<button
className={`tab-button ${activeTab === 'visualization' ? 'active' : ''}`}
onClick={() => setActiveTab('visualization')}
>
🔍 图谱可视化
</button>
<button
className={`tab-button ${activeTab === 'tags' ? 'active' : ''}`}
onClick={() => setActiveTab('tags')}
>
🏷️ 标签管理
</button>
</div>
{/* Tab content */}
{activeTab === 'cards' && (
<div className="tab-content">
{/* Create new card section */}
<div className="create-card-section">
<h3>创建新题目卡片</h3>
<div className="form-group">
<label>题目描述:</label>
<textarea
value={newCard.content_problem}
onChange={(e) => setNewCard({
...newCard,
content_problem: e.target.value
})}
placeholder="请输入题目内容..."
rows={3}
/>
</div>
<div className="form-group">
<label>解题灵感/方法:</label>
<textarea
value={newCard.content_insight}
onChange={(e) => setNewCard({
...newCard,
content_insight: e.target.value
})}
placeholder="请输入解题思路和关键洞察..."
rows={3}
/>
</div>
<div className="form-group">
<label>标签 (用逗号分隔):</label>
<input
type="text"
value={newCard.tags.join(', ')}
onChange={(e) => setNewCard({
...newCard,
tags: e.target.value.split(',').map(tag => tag.trim()).filter(tag => tag)
})}
placeholder="例如: 微积分, 求导, 高等数学"
/>
</div>
<button onClick={createCard} disabled={loading}>
创建卡片
</button>
</div>
{/* Search section */}
<div className="search-section">
<h3>搜索知识图谱</h3>
<div className="search-form">
<input
type="text"
value={searchQuery}
onChange={(e) => setSearchQuery(e.target.value)}
placeholder="输入搜索关键词..."
onKeyPress={(e) => e.key === 'Enter' && searchGraph()}
/>
<button onClick={searchGraph} disabled={loading || !searchQuery.trim()}>
搜索
</button>
</div>
{searchResults.length > 0 && (
<div className="search-results">
<h4>搜索结果 ({searchResults.length})</h4>
{searchResults.map((result, index) => (
<div
key={result.card.id}
className="search-result-item"
onClick={() => selectCard(result.card)}
>
<div className="result-score">
相似度: {(result.score * 100).toFixed(1)}%
</div>
<div className="result-content">
<strong>题目:</strong> {result.card.content_problem.substring(0, 100)}...
</div>
<div className="result-insight">
<strong>解法:</strong> {result.card.content_insight.substring(0, 100)}...
</div>
<div className="result-meta">
匹配方式: {result.matched_by.join(', ')} |
访问次数: {result.card.access_count} |
状态: {result.card.status}
</div>
</div>
))}
</div>
)}
</div>
{/* Selected card and recommendations */}
{selectedCard && (
<div className="selected-card-section">
<h3>卡片详情</h3>
<div className="card-details">
<div className="card-problem">
<strong>题目:</strong>
<p>{selectedCard.content_problem}</p>
</div>
<div className="card-insight">
<strong>解题洞察:</strong>
<p>{selectedCard.content_insight}</p>
</div>
<div className="card-meta">
<span>状态: {selectedCard.status}</span>
<span>访问次数: {selectedCard.access_count}</span>
<span>创建时间: {new Date(selectedCard.created_at).toLocaleString()}</span>
</div>
</div>
{recommendations.length > 0 && (
<div className="recommendations">
<h4>AI 推荐的相关题目</h4>
{recommendations.map((rec, index) => (
<div key={rec.card.id} className="recommendation-item">
<div className="rec-header">
<span className="rec-type">{rec.relationship_type}</span>
<span className="rec-confidence">
置信度: {(rec.confidence * 100).toFixed(1)}%
</span>
</div>
<div className="rec-content">
<strong>题目:</strong> {rec.card.content_problem.substring(0, 150)}...
</div>
<div className="rec-reasoning">
<strong>推荐理由:</strong> {rec.reasoning}
</div>
</div>
))}
</div>
)}
</div>
)}
{/* Tags overview */}
{allTags.length > 0 && (
<div className="tags-section">
<h3>标签概览 ({allTags.length})</h3>
<div className="tags-list">
{allTags.map((tag, index) => (
<span key={index} className={`tag tag-${tag.tag_type}`}>
{tag.name}
</span>
))}
</div>
</div>
)}
</div>
)}
{/* Graph Visualization Tab */}
{activeTab === 'visualization' && (
<div className="tab-content">
{!isInitialized ? (
<div className="visualization-setup-hint">
<h3>📊 图谱可视化</h3>
<div className="setup-message">
<p>🔧 要使用图谱可视化功能，请先完成以下步骤：</p>
<ol>
<li>返回 <strong>"问题卡片管理"</strong> 标签页</li>
<li>完成 Neo4j 数据库配置</li>
<li>点击 <strong>"测试连接"</strong> 确保连接成功</li>
<li>点击 <strong>"初始化图谱"</strong> 完成设置</li>
</ol>
<p>💡 <strong>Neo4j 快速设置：</strong></p>
<ul>
<li>下载 Neo4j Desktop: <a href="https://neo4j.com/download/" target="_blank" rel="noopener noreferrer">https://neo4j.com/download/</a></li>
<li>创建数据库，设置密码</li>
<li>使用 URI: <code>neo4j://127.0.0.1:7687</code></li>
</ul>
</div>
<div className="nav-hint">
<button
onClick={() => setActiveTab('cards')}
className="nav-button"
>
⬅️ 前往配置 Neo4j
</button>
</div>
</div>
) : (
<GraphVisualization
config={config}
isInitialized={isInitialized}
/>
)}
</div>
)}
{/* Tag Management Tab */}
{activeTab === 'tags' && (
<div className="tab-content">
<TagManagement
isInitialized={isInitialized}
/>
</div>
)}
</div>
)}
{loading && (
<div className="loading-overlay">
<div className="loading-spinner">处理中...</div>
</div>
)}
</div>
);
};
export default KnowledgeGraphManagement;
|
0000cd/wolf-set
| 6,469 |
themes/bluf/static/js/js-confetti.js
|
var JSConfetti=function(){"use strict";function t(t,e){if(!(t instanceof e))throw new TypeError("Cannot call a class as a function")}function e(t,e){for(var i=0;i<e.length;i++){var n=e[i];n.enumerable=n.enumerable||!1,n.configurable=!0,"value"in n&&(n.writable=!0),Object.defineProperty(t,n.key,n)}}function i(t,i,n){return i&&e(t.prototype,i),n&&e(t,n),t}function n(t){return+t.replace(/px/,"")}function s(t,e){var i=arguments.length>2&&void 0!==arguments[2]?arguments[2]:0,n=Math.random()*(e-t)+t;return Math.floor(n*Math.pow(10,i))/Math.pow(10,i)}function o(t){return t[s(0,t.length)]}var a=["#fcf403","#62fc03","#f4fc03","#03e7fc","#03fca5","#a503fc","#fc03ad","#fc03c2"];function r(t){return Math.log(t)/Math.log(1920)}var h=function(){function e(i){t(this,e);var n=i.initialPosition,a=i.direction,h=i.confettiRadius,c=i.confettiColors,u=i.emojis,l=i.emojiSize,d=i.canvasWidth,f=s(.9,1.7,3)*r(d);this.confettiSpeed={x:f,y:f},this.finalConfettiSpeedX=s(.2,.6,3),this.rotationSpeed=u.length?.01:s(.03,.07,3)*r(d),this.dragForceCoefficient=s(5e-4,9e-4,6),this.radius={x:h,y:h},this.initialRadius=h,this.rotationAngle="left"===a?s(0,.2,3):s(-.2,0,3),this.emojiSize=l,this.emojiRotationAngle=s(0,2*Math.PI),this.radiusYUpdateDirection="down";var m="left"===a?s(82,15)*Math.PI/180:s(-15,-82)*Math.PI/180;this.absCos=Math.abs(Math.cos(m)),this.absSin=Math.abs(Math.sin(m));var v=s(-150,0),p={x:n.x+("left"===a?-v:v)*this.absCos,y:n.y-v*this.absSin};this.currentPosition=Object.assign({},p),this.initialPosition=Object.assign({},p),this.color=u.length?null:o(c),this.emoji=u.length?o(u):null,this.createdAt=(new Date).getTime(),this.direction=a}return i(e,[{key:"draw",value:function(t){var e=this.currentPosition,i=this.radius,n=this.color,s=this.emoji,o=this.rotationAngle,a=this.emojiRotationAngle,r=this.emojiSize,h=window.devicePixelRatio;n?(t.fillStyle=n,t.beginPath(),t.ellipse(e.x*h,e.y*h,i.x*h,i.y*h,o,0,2*Math.PI),t.fill()):s&&(t.font="".concat(r,"px serif"),t.save(),t.translate(h*e.x,h*e.y),t.rotate(a),t.textAlign="center",t.fillText(s,0,0),t.restore())}},{key:"updatePosition",value:function(t,e){var i=this.confettiSpeed,n=this.dragForceCoefficient,s=this.finalConfettiSpeedX,o=this.radiusYUpdateDirection,a=this.rotationSpeed,r=this.createdAt,h=this.direction,c=e-r;i.x>s&&(this.confettiSpeed.x-=n*t),this.currentPosition.x+=i.x*("left"===h?-this.absCos:this.absCos)*t,this.currentPosition.y=this.initialPosition.y-i.y*this.absSin*c+.00125*Math.pow(c,2)/2,this.rotationSpeed-=this.emoji?1e-4:1e-5*t,this.rotationSpeed<0&&(this.rotationSpeed=0),this.emoji?this.emojiRotationAngle+=this.rotationSpeed*t%(2*Math.PI):"down"===o?(this.radius.y-=t*a,this.radius.y<=0&&(this.radius.y=0,this.radiusYUpdateDirection="up")):(this.radius.y+=t*a,this.radius.y>=this.initialRadius&&(this.radius.y=this.initialRadius,this.radiusYUpdateDirection="down"))}},{key:"getIsVisibleOnCanvas",value:function(t){return this.currentPosition.y<t+100}}]),e}();function c(){var t=document.createElement("canvas");return t.style.position="fixed",t.style.width="100%",t.style.height="100%",t.style.top="0",t.style.left="0",t.style.zIndex="1000",t.style.pointerEvents="none",document.body.appendChild(t),t}function u(t){var e=t.confettiRadius,i=void 0===e?6:e,n=t.confettiNumber,s=void 0===n?t.confettiesNumber||(t.emojis?40:250):n,o=t.confettiColors,r=void 0===o?a:o,h=t.emojis,c=void 0===h?t.emojies||[]:h,u=t.emojiSize,l=void 0===u?80:u;return t.emojies&&console.error("emojies argument is deprecated, please use emojis instead"),t.confettiesNumber&&console.error("confettiesNumber argument is deprecated, please use confettiNumber instead"),{confettiRadius:i,confettiNumber:s,confettiColors:r,emojis:c,emojiSize:l}}var l=function(){function e(i){var n=this;t(this,e),this.canvasContext=i,this.shapes=[],this.promise=new Promise((function(t){return n.resolvePromise=t}))}return i(e,[{key:"getBatchCompletePromise",value:function(){return this.promise}},{key:"addShapes",value:function(){var t;(t=this.shapes).push.apply(t,arguments)}},{key:"complete",value:function(){var t;return!this.shapes.length&&(null===(t=this.resolvePromise)||void 0===t||t.call(this),!0)}},{key:"processShapes",value:function(t,e,i){var n=this,s=t.timeDelta,o=t.currentTime;this.shapes=this.shapes.filter((function(t){return t.updatePosition(s,o),t.draw(n.canvasContext),!i||t.getIsVisibleOnCanvas(e)}))}}]),e}();return function(){function e(){var i=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{};t(this,e),this.activeConfettiBatches=[],this.canvas=i.canvas||c(),this.canvasContext=this.canvas.getContext("2d"),this.requestAnimationFrameRequested=!1,this.lastUpdated=(new Date).getTime(),this.iterationIndex=0,this.loop=this.loop.bind(this),requestAnimationFrame(this.loop)}return i(e,[{key:"loop",value:function(){var t,e,i,s,o;this.requestAnimationFrameRequested=!1,t=this.canvas,e=window.devicePixelRatio,i=getComputedStyle(t),s=n(i.getPropertyValue("width")),o=n(i.getPropertyValue("height")),t.setAttribute("width",(s*e).toString()),t.setAttribute("height",(o*e).toString());var a=(new Date).getTime(),r=a-this.lastUpdated,h=this.canvas.offsetHeight,c=this.iterationIndex%10==0;this.activeConfettiBatches=this.activeConfettiBatches.filter((function(t){return t.processShapes({timeDelta:r,currentTime:a},h,c),!c||!t.complete()})),this.iterationIndex++,this.queueAnimationFrameIfNeeded(a)}},{key:"queueAnimationFrameIfNeeded",value:function(t){this.requestAnimationFrameRequested||this.activeConfettiBatches.length<1||(this.requestAnimationFrameRequested=!0,this.lastUpdated=t||(new Date).getTime(),requestAnimationFrame(this.loop))}},{key:"addConfetti",value:function(){for(var t=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{},e=u(t),i=e.confettiRadius,n=e.confettiNumber,s=e.confettiColors,o=e.emojis,a=e.emojiSize,r=this.canvas.getBoundingClientRect(),c=r.width,d=r.height,f=5*d/7,m={x:0,y:f},v={x:c,y:f},p=new l(this.canvasContext),y=0;y<n/2;y++){var g=new h({initialPosition:m,direction:"right",confettiRadius:i,confettiColors:s,confettiNumber:n,emojis:o,emojiSize:a,canvasWidth:c}),C=new h({initialPosition:v,direction:"left",confettiRadius:i,confettiColors:s,confettiNumber:n,emojis:o,emojiSize:a,canvasWidth:c});p.addShapes(g,C)}return this.activeConfettiBatches.push(p),this.queueAnimationFrameIfNeeded(),p.getBatchCompletePromise()}},{key:"clearCanvas",value:function(){this.activeConfettiBatches=[]}},{key:"destroyCanvas",value:function(){this.canvas.remove()}}]),e}()}();
|
000haoji/deep-student
| 46,167 |
src/components/CreateReviewAnalysisView.tsx
|
import React, { useState, useEffect } from 'react';
import { ReviewSessionTask, MistakeConsolidationData, ConsolidatedMistakeData } from '../types/index';
import type { MistakeItem } from '../utils/tauriApi';
import { useNotification } from '../hooks/useNotification';
import { TauriAPI } from '../utils/tauriApi';
import { useSubject } from '../contexts/SubjectContext';
interface CreateReviewAnalysisViewProps {
onCancel: () => void;
onCreateSuccess: (sessionId: string) => void;
}
const CreateReviewAnalysisView: React.FC<CreateReviewAnalysisViewProps> = ({
onCancel,
onCreateSuccess,
}) => {
const [step, setStep] = useState<'setup' | 'select_mistakes' | 'configure_prompt' | 'creating'>('setup');
const [formData, setFormData] = useState({
name: '',
subject: '',
overallPrompt: '',
});
const [availableMistakes, setAvailableMistakes] = useState<MistakeItem[]>([]);
const [selectedMistakeIds, setSelectedMistakeIds] = useState<string[]>([]);
const [loading, setLoading] = useState(false);
const [searchTerm, setSearchTerm] = useState('');
const [subjectFilter, setSubjectFilter] = useState('');
const { showNotification } = useNotification();
const { currentSubject, getEnabledSubjects } = useSubject();
// 🎯 同步全局科目状态到本地表单（优先级更高，避免循环）
useEffect(() => {
if (currentSubject && currentSubject !== formData.subject) {
console.log('🔄 [回顾分析] 同步全局科目到表单:', currentSubject);
setFormData(prev => ({ ...prev, subject: currentSubject }));
}
}, [currentSubject]);
// 移除双向同步，避免循环更新
// 用户只能通过标题栏科目选择器更改科目，表单中的科目选择框变为只读显示
useEffect(() => {
if (step === 'select_mistakes') {
loadAvailableMistakes();
}
}, [step, formData.subject]);
const loadAvailableMistakes = async () => {
try {
setLoading(true);
const mistakes = await TauriAPI.getMistakes();
const filteredMistakes = formData.subject
? mistakes.filter(mistake => mistake.subject === formData.subject)
: mistakes;
setAvailableMistakes(filteredMistakes);
} catch (error) {
console.error('加载错题列表失败:', error);
showNotification('error', '加载错题列表失败');
} finally {
setLoading(false);
}
};
const getSubjects = () => {
const subjects = new Set(availableMistakes.map(mistake => mistake.subject));
return Array.from(subjects);
};
const filteredMistakes = availableMistakes.filter(mistake => {
const matchesSearch = !searchTerm ||
mistake.user_question.toLowerCase().includes(searchTerm.toLowerCase()) ||
mistake.ocr_text.toLowerCase().includes(searchTerm.toLowerCase()) ||
mistake.tags.some(tag => tag.toLowerCase().includes(searchTerm.toLowerCase()));
const matchesSubject = !subjectFilter || mistake.subject === subjectFilter;
return matchesSearch && matchesSubject;
});
const handleNextStep = () => {
if (step === 'setup') {
if (!formData.name.trim() || !formData.subject.trim()) {
showNotification('warning', '请填写回顾分析名称和科目');
return;
}
setStep('select_mistakes');
} else if (step === 'select_mistakes') {
if (selectedMistakeIds.length === 0) {
showNotification('warning', '请至少选择一个错题');
return;
}
setStep('configure_prompt');
} else if (step === 'configure_prompt') {
if (!formData.overallPrompt.trim()) {
showNotification('warning', '请输入分析指引');
return;
}
handleCreateReviewAnalysis();
}
};
const handlePrevStep = () => {
if (step === 'select_mistakes') {
setStep('setup');
} else if (step === 'configure_prompt') {
setStep('select_mistakes');
}
};
const consolidateMistakeData = (selectedMistakes: MistakeItem[]): ConsolidatedMistakeData => {
if (!selectedMistakes || selectedMistakes.length === 0) {
throw new Error('没有选中的错题数据');
}
const consolidationData: MistakeConsolidationData[] = selectedMistakes.map(mistake => {
if (!mistake) {
throw new Error('错题数据为空');
}
return {
mistakeId: mistake.id || '',
ocr_text: mistake.ocr_text || '',
user_question: mistake.user_question || '',
chat_history: (mistake.chat_history || []).map(msg => ({
role: (msg?.role as 'user' | 'assistant' | 'system') || 'user',
content: msg?.content || '',
timestamp: msg?.timestamp || new Date().toISOString(),
thinking_content: msg?.thinking_content,
})),
};
});
let consolidatedText = '';
consolidationData.forEach((data, index) => {
const mistake = selectedMistakes[index];
consolidatedText += `--- 错题 ${index + 1} (ID: ${data.mistakeId}) ---\\n`;
consolidatedText += `题目内容:\\n${data.ocr_text}\\n\\n`;
consolidatedText += `我的原始问题:\\n${data.user_question}\\n\\n`;
// 🎯 关键改进：优先使用AI生成的结构化总结
if (mistake.mistake_summary && mistake.user_error_analysis) {
consolidatedText += `题目解析总结:\\n${mistake.mistake_summary}\\n\\n`;
consolidatedText += `错误分析总结:\\n${mistake.user_error_analysis}\\n\\n`;
} else if (data.chat_history && data.chat_history.length > 0) {
// 降级方案：如果没有总结，使用聊天记录（但会提示需要生成总结）
consolidatedText += `⚠️ 注意：此错题缺少AI总结，建议先生成总结以提高回顾分析质量\\n`;
consolidatedText += `历史交流（原始记录）:\\n`;
// 只包含关键的几条对话，避免过长
const keyMessages = data.chat_history.slice(-3); // 只取最后3条对话
keyMessages.forEach(message => {
const roleDisplay = message.role === 'user' ? '用户' : '助手';
const contentStr = typeof message.content === 'string' ? message.content : JSON.stringify(message.content);
const truncatedContent = contentStr.length > 200
? contentStr.substring(0, 200) + '...'
: contentStr;
consolidatedText += `${roleDisplay}: ${truncatedContent}\\n`;
});
consolidatedText += '\\n';
} else {
consolidatedText += `⚠️ 注意：此错题缺少分析记录和总结\\n\\n`;
}
consolidatedText += '\\n';
});
return {
selectedMistakes: consolidationData,
consolidatedText,
userOverallPrompt: formData.overallPrompt || '',
};
};
const handleCreateReviewAnalysis = async () => {
try {
setStep('creating');
setLoading(true);
// 验证数据完整性
if (!formData.name || !formData.subject || !formData.overallPrompt) {
throw new Error('缺少必要的表单数据');
}
if (selectedMistakeIds.length === 0) {
throw new Error('没有选择任何错题');
}
// 关键修复：根据ID获取每个错题的完整详情，以确保包含总结字段
const selectedMistakesPromises = selectedMistakeIds.map(id =>
TauriAPI.getMistakeDetails(id)
);
const selectedMistakesWithDetails = await Promise.all(selectedMistakesPromises);
const selectedMistakes = selectedMistakesWithDetails.filter(
(mistake): mistake is MistakeItem => mistake !== null
);
if (selectedMistakes.length !== selectedMistakeIds.length) {
showNotification('warning', '部分选中的错题无法加载详情，可能已被删除。');
}
if (selectedMistakes.length === 0) {
throw new Error('选中的错题数据不存在或无法加载');
}
const consolidatedData = consolidateMistakeData(selectedMistakes);
// 调用后端API创建回顾分析会话（复用错题分析的数据库存储模式）
const response = await TauriAPI.startConsolidatedReviewAnalysis({
subject: formData.subject,
consolidatedInput: consolidatedData.consolidatedText,
overallPrompt: formData.overallPrompt,
enableChainOfThought: true,
mistakeIds: selectedMistakeIds, // 🔧 修复：传递选中的错题ID列表
});
if (!response || !response.review_session_id) {
throw new Error('API响应无效，未获得会话ID');
}
const reviewSessionId = response.review_session_id;
console.log('✅ 回顾分析会话创建成功 (数据库模式):', {
reviewSessionId: reviewSessionId,
name: formData.name,
subject: formData.subject,
mistakeCount: selectedMistakeIds.length
});
showNotification('success', '回顾分析创建成功');
// 短暂显示成功状态
setLoading(false);
// 延迟一下再跳转，让用户看到成功状态
setTimeout(() => {
console.log('🔄 正在跳转到会话页面，reviewSessionId:', reviewSessionId);
// 使用后端返回的review_session_id作为前端的sessionId，完全复用错题分析模式
onCreateSuccess(reviewSessionId);
}, 1500);
} catch (error) {
console.error('创建回顾分析失败:', error);
const errorMessage = error instanceof Error ? error.message : '创建回顾分析失败';
showNotification('error', errorMessage);
setStep('configure_prompt');
setLoading(false);
}
};
const renderSetupStep = () => (
<div>
<div style={{
background: 'linear-gradient(135deg, rgba(102, 126, 234, 0.1) 0%, rgba(118, 75, 162, 0.1) 100%)',
padding: '24px',
borderRadius: '16px',
marginBottom: '32px',
border: '1px solid rgba(102, 126, 234, 0.1)'
}}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '12px' }}>
<svg style={{ width: '24px', height: '24px', color: '#667eea', marginRight: '12px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M10.325 4.317c.426-1.756 2.924-1.756 3.35 0a1.724 1.724 0 002.573 1.066c1.543-.94 3.31.826 2.37 2.37a1.724 1.724 0 001.065 2.572c1.756.426 1.756 2.924 0 3.35a1.724 1.724 0 00-1.066 2.573c.94 1.543-.826 3.31-2.37 2.37a1.724 1.724 0 00-2.572 1.065c-.426 1.756-2.924 1.756-3.35 0a1.724 1.724 0 00-2.573-1.066c-1.543.94-3.31-.826-2.37-2.37a1.724 1.724 0 00-1.065-2.572c-1.756-.426-1.756-2.924 0-3.35a1.724 1.724 0 001.066-2.573c-.94-1.543.826-3.31 2.37-2.37.996.608 2.296.07 2.572-1.065z" />
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M15 12a3 3 0 11-6 0 3 3 0 016 0z" />
</svg>
<h3 style={{ fontSize: '20px', fontWeight: '700', color: '#1f2937', margin: 0 }}>基本设置</h3>
</div>
<p style={{ fontSize: '14px', color: '#6b7280', margin: 0, lineHeight: '1.5' }}>
设置回顾分析的基本信息，包括名称和科目等
</p>
</div>
<div style={{ display: 'flex', flexDirection: 'column', gap: '24px' }}>
<div>
<label style={{
display: 'block',
fontSize: '14px',
fontWeight: '600',
color: '#374151',
marginBottom: '8px'
}}>
回顾分析名称 *
</label>
<input
type="text"
value={formData.name}
onChange={(e) => setFormData(prev => ({ ...prev, name: e.target.value }))}
placeholder="例如：期中数学复习 - 函数部分"
style={{
width: '100%',
padding: '16px 20px',
border: '2px solid #e2e8f0',
borderRadius: '12px',
fontSize: '16px',
background: 'white',
transition: 'all 0.2s ease',
outline: 'none'
}}
onFocus={(e) => {
e.target.style.borderColor = '#667eea';
e.target.style.boxShadow = '0 0 0 4px rgba(102, 126, 234, 0.1)';
}}
onBlur={(e) => {
e.target.style.borderColor = '#e2e8f0';
e.target.style.boxShadow = 'none';
}}
/>
<p style={{ fontSize: '12px', color: '#9ca3af', marginTop: '4px' }}>
请输入一个有意义的名称，方便后续管理
</p>
</div>
<div>
<label style={{
display: 'block',
fontSize: '14px',
fontWeight: '600',
color: '#374151',
marginBottom: '8px'
}}>
科目 *
</label>
<div style={{ position: 'relative' }}>
<div
style={{
width: '100%',
padding: '16px 20px',
border: '2px solid #e2e8f0',
borderRadius: '12px',
fontSize: '16px',
background: '#f8fafc',
color: '#374151',
cursor: 'not-allowed',
display: 'flex',
alignItems: 'center',
justifyContent: 'space-between'
}}
>
<span>{formData.subject || '请在标题栏选择科目'}</span>
<svg style={{
width: '20px',
height: '20px',
color: '#9ca3af'
}} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 15v2m-6 4h12a2 2 0 002-2v-6a2 2 0 00-2-2H6a2 2 0 00-2 2v6a2 2 0 002 2zm10-10V7a4 4 0 00-8 0v4h8z" />
</svg>
</div>
</div>
<p style={{ fontSize: '12px', color: '#9ca3af', marginTop: '4px' }}>
科目由标题栏下拉框控制，请在标题栏中选择所需科目
</p>
</div>
</div>
</div>
);
const renderSelectMistakesStep = () => (
<div>
<div style={{
background: 'linear-gradient(135deg, rgba(102, 126, 234, 0.1) 0%, rgba(118, 75, 162, 0.1) 100%)',
padding: '24px',
borderRadius: '16px',
marginBottom: '32px',
border: '1px solid rgba(102, 126, 234, 0.1)'
}}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '12px' }}>
<svg style={{ width: '24px', height: '24px', color: '#667eea', marginRight: '12px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" />
</svg>
<h3 style={{ fontSize: '20px', fontWeight: '700', color: '#1f2937', margin: 0 }}>
选择错题
<span style={{ color: '#667eea', fontWeight: '600', marginLeft: '8px' }}>({selectedMistakeIds.length} / {filteredMistakes.length})</span>
</h3>
</div>
<p style={{ fontSize: '14px', color: '#6b7280', margin: 0, lineHeight: '1.5' }}>
从下方列表中选择需要进行统一分析的错题
</p>
</div>
{/* 筛选器 */}
<div style={{
display: 'grid',
gridTemplateColumns: '2fr 1fr',
gap: '16px',
marginBottom: '24px'
}}>
<div style={{ position: 'relative' }}>
<svg style={{
position: 'absolute',
left: '16px',
top: '50%',
transform: 'translateY(-50%)',
width: '18px',
height: '18px',
color: '#9ca3af'
}} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M21 21l-6-6m2-5a7 7 0 11-14 0 7 7 0 0114 0z" />
</svg>
<input
type="text"
placeholder="搜索错题内容、问题或标签..."
value={searchTerm}
onChange={(e) => setSearchTerm(e.target.value)}
style={{
width: '100%',
padding: '12px 16px 12px 48px',
border: '2px solid #e2e8f0',
borderRadius: '12px',
fontSize: '14px',
transition: 'all 0.2s ease',
outline: 'none'
}}
onFocus={(e) => {
e.target.style.borderColor = '#667eea';
e.target.style.boxShadow = '0 0 0 4px rgba(102, 126, 234, 0.1)';
}}
onBlur={(e) => {
e.target.style.borderColor = '#e2e8f0';
e.target.style.boxShadow = 'none';
}}
/>
</div>
<div style={{ position: 'relative' }}>
<select
value={subjectFilter}
onChange={(e) => setSubjectFilter(e.target.value)}
style={{
width: '100%',
padding: '12px 16px',
border: '2px solid #e2e8f0',
borderRadius: '12px',
fontSize: '14px',
background: 'white',
cursor: 'pointer',
transition: 'all 0.2s ease',
outline: 'none',
appearance: 'none'
}}
onFocus={(e) => {
e.target.style.borderColor = '#667eea';
e.target.style.boxShadow = '0 0 0 4px rgba(102, 126, 234, 0.1)';
}}
onBlur={(e) => {
e.target.style.borderColor = '#e2e8f0';
e.target.style.boxShadow = 'none';
}}
>
<option value="">全部科目</option>
{getSubjects().map(subject => (
<option key={subject} value={subject}>{subject}</option>
))}
</select>
<svg style={{
position: 'absolute',
right: '16px',
top: '50%',
transform: 'translateY(-50%)',
width: '16px',
height: '16px',
color: '#9ca3af',
pointerEvents: 'none'
}} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M19 9l-7 7-7-7" />
</svg>
</div>
</div>
{loading ? (
<div style={{
display: 'flex',
justifyContent: 'center',
alignItems: 'center',
height: '200px',
gap: '12px'
}}>
<div style={{
width: '32px',
height: '32px',
border: '3px solid #f1f5f9',
borderTop: '3px solid #667eea',
borderRadius: '50%',
animation: 'spin 1s linear infinite'
}}></div>
<span style={{ color: '#6b7280', fontSize: '16px', fontWeight: '500' }}>加载中...</span>
</div>
) : filteredMistakes.length === 0 ? (
<div style={{
textAlign: 'center',
padding: '80px 24px',
background: '#f8fafc',
borderRadius: '16px',
border: '2px dashed #d1d5db'
}}>
<div style={{
width: '64px',
height: '64px',
background: '#e5e7eb',
borderRadius: '50%',
display: 'flex',
alignItems: 'center',
justifyContent: 'center',
margin: '0 auto 16px'
}}>
<svg style={{ width: '32px', height: '32px', color: '#9ca3af' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" />
</svg>
</div>
<h4 style={{ fontSize: '18px', fontWeight: '600', color: '#374151', marginBottom: '8px' }}>
{availableMistakes.length === 0 ? '暂无错题数据' : '没有找到符合条件的错题'}
</h4>
<p style={{ color: '#6b7280', fontSize: '14px' }}>
{availableMistakes.length === 0 ? '请先在错题库中添加一些错题' : '试试调整搜索条件或科目筛选'}
</p>
</div>
) : (
<div style={{
display: 'grid',
gridTemplateColumns: 'repeat(auto-fill, minmax(350px, 1fr))',
gap: '20px',
maxHeight: '500px',
overflow: 'auto',
padding: '4px'
}}>
{filteredMistakes.map((mistake) => {
const isSelected = selectedMistakeIds.includes(mistake.id);
return (
<div
key={mistake.id}
onClick={() => {
if (isSelected) {
setSelectedMistakeIds(prev => prev.filter(id => id !== mistake.id));
} else {
setSelectedMistakeIds(prev => [...prev, mistake.id]);
}
}}
style={{
background: isSelected ? 'linear-gradient(135deg, rgba(102, 126, 234, 0.1) 0%, rgba(118, 75, 162, 0.1) 100%)' : 'white',
border: isSelected ? '2px solid #667eea' : '2px solid #f1f5f9',
borderRadius: '16px',
padding: '20px',
cursor: 'pointer',
transition: 'all 0.3s ease',
position: 'relative',
overflow: 'hidden'
}}
onMouseOver={(e) => {
if (!isSelected) {
e.currentTarget.style.borderColor = '#d1d5db';
e.currentTarget.style.transform = 'translateY(-2px)';
e.currentTarget.style.boxShadow = '0 8px 25px rgba(0, 0, 0, 0.1)';
}
}}
onMouseOut={(e) => {
if (!isSelected) {
e.currentTarget.style.borderColor = '#f1f5f9';
e.currentTarget.style.transform = 'translateY(0)';
e.currentTarget.style.boxShadow = 'none';
}
}}
>
{/* 选中指示器 */}
{isSelected && (
<div style={{
position: 'absolute',
top: '0',
left: '0',
right: '0',
height: '4px',
background: 'linear-gradient(135deg, #667eea 0%, #764ba2 100%)'
}}></div>
)}
{/* 头部 */}
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '16px', gap: '12px' }}>
<div style={{
width: '20px',
height: '20px',
borderRadius: '4px',
border: isSelected ? '2px solid #667eea' : '2px solid #d1d5db',
background: isSelected ? '#667eea' : 'white',
display: 'flex',
alignItems: 'center',
justifyContent: 'center',
transition: 'all 0.2s ease'
}}>
{isSelected && (
<svg style={{ width: '12px', height: '12px', color: 'white' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={3} d="M5 13l4 4L19 7" />
</svg>
)}
</div>
<span style={{
fontSize: '12px',
color: '#667eea',
fontWeight: '600',
background: 'rgba(102, 126, 234, 0.1)',
padding: '4px 8px',
borderRadius: '8px'
}}>
{mistake.subject}
</span>
<span style={{ fontSize: '12px', color: '#9ca3af', marginLeft: 'auto' }}>
{new Date(mistake.created_at).toLocaleDateString()}
</span>
</div>
{/* 问题内容 */}
<p style={{
fontWeight: '600',
color: '#1f2937',
marginBottom: '12px',
lineHeight: '1.5',
fontSize: '14px',
overflow: 'hidden',
display: '-webkit-box',
WebkitLineClamp: 2,
WebkitBoxOrient: 'vertical'
}}>
{mistake.user_question}
</p>
{/* OCR内容 */}
<p style={{
color: '#6b7280',
fontSize: '13px',
lineHeight: '1.4',
marginBottom: '16px',
overflow: 'hidden',
display: '-webkit-box',
WebkitLineClamp: 3,
WebkitBoxOrient: 'vertical'
}}>
{mistake.ocr_text}
</p>
{/* 标签 */}
<div style={{ display: 'flex', flexWrap: 'wrap', gap: '6px' }}>
{mistake.tags.slice(0, 3).map((tag, index) => (
<span key={index} style={{
background: '#f3f4f6',
color: '#374151',
padding: '4px 8px',
borderRadius: '8px',
fontSize: '11px',
fontWeight: '500'
}}>
{tag}
</span>
))}
{mistake.tags.length > 3 && (
<span style={{ color: '#9ca3af', fontSize: '11px', padding: '4px 0' }}>+{mistake.tags.length - 3}</span>
)}
</div>
</div>
);
})}
</div>
)}
</div>
);
const renderConfigurePromptStep = () => (
<div>
<div style={{
background: 'linear-gradient(135deg, rgba(102, 126, 234, 0.1) 0%, rgba(118, 75, 162, 0.1) 100%)',
padding: '24px',
borderRadius: '16px',
marginBottom: '32px',
border: '1px solid rgba(102, 126, 234, 0.1)'
}}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '12px' }}>
<svg style={{ width: '24px', height: '24px', color: '#667eea', marginRight: '12px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z" />
</svg>
<h3 style={{ fontSize: '20px', fontWeight: '700', color: '#1f2937', margin: 0 }}>配置分析指引</h3>
</div>
<p style={{ fontSize: '14px', color: '#6b7280', margin: 0, lineHeight: '1.5' }}>
设置 AI 如何分析选中的错题，包括分析角度和重点关注的方面
</p>
</div>
{/* 分析指引输入 */}
<div style={{ marginBottom: '32px' }}>
<label style={{
display: 'block',
fontSize: '14px',
fontWeight: '600',
color: '#374151',
marginBottom: '8px'
}}>
总体分析指引 *
</label>
<textarea
value={formData.overallPrompt}
onChange={(e) => setFormData(prev => ({ ...prev, overallPrompt: e.target.value }))}
placeholder="例如：请总结这些二次函数错题的常见错误类型，并提供针对性的学习建议。请重点分析我在概念理解和计算方法上的薄弱环节。"
rows={6}
style={{
width: '100%',
padding: '16px 20px',
border: '2px solid #e2e8f0',
borderRadius: '12px',
fontSize: '14px',
lineHeight: '1.6',
background: 'white',
transition: 'all 0.2s ease',
outline: 'none',
resize: 'vertical',
minHeight: '120px'
}}
onFocus={(e) => {
e.target.style.borderColor = '#667eea';
e.target.style.boxShadow = '0 0 0 4px rgba(102, 126, 234, 0.1)';
}}
onBlur={(e) => {
e.target.style.borderColor = '#e2e8f0';
e.target.style.boxShadow = 'none';
}}
/>
<p style={{ fontSize: '12px', color: '#9ca3af', marginTop: '8px', lineHeight: '1.4' }}>
请描述您希望AI如何分析这些错题，比如总结共同问题、分析薄弱环节、提供学习建议等。
</p>
</div>
{/* 快速模板 */}
<div style={{ marginBottom: '32px' }}>
<label style={{
display: 'block',
fontSize: '14px',
fontWeight: '600',
color: '#374151',
marginBottom: '12px'
}}>
快速模板
</label>
<div style={{
display: 'grid',
gridTemplateColumns: 'repeat(auto-fit, minmax(280px, 1fr))',
gap: '12px'
}}>
{[
"请总结这些错题的共同问题和改进建议",
"分析我在这些知识点上的薄弱环节",
"比较这些错题的解题方法和思路差异",
"针对这些错题制定复习计划",
].map((template, index) => (
<button
key={index}
onClick={() => setFormData(prev => ({ ...prev, overallPrompt: template }))}
style={{
textAlign: 'left',
padding: '16px',
fontSize: '14px',
border: '2px solid #f1f5f9',
borderRadius: '12px',
background: 'white',
cursor: 'pointer',
transition: 'all 0.2s ease',
lineHeight: '1.4'
}}
onMouseOver={(e) => {
e.currentTarget.style.borderColor = '#667eea';
e.currentTarget.style.background = 'rgba(102, 126, 234, 0.05)';
e.currentTarget.style.transform = 'translateY(-1px)';
}}
onMouseOut={(e) => {
e.currentTarget.style.borderColor = '#f1f5f9';
e.currentTarget.style.background = 'white';
e.currentTarget.style.transform = 'translateY(0)';
}}
>
{template}
</button>
))}
</div>
</div>
{/* 选中错题预览 */}
<div style={{
background: '#f8fafc',
border: '2px solid #f1f5f9',
borderRadius: '16px',
padding: '24px'
}}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '16px' }}>
<svg style={{ width: '20px', height: '20px', color: '#667eea', marginRight: '8px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" />
</svg>
<h4 style={{ fontSize: '16px', fontWeight: '600', color: '#374151', margin: 0 }}>
已选中的错题
<span style={{ color: '#667eea', marginLeft: '8px' }}>({selectedMistakeIds.length} 个)</span>
</h4>
</div>
<div style={{
maxHeight: '200px',
overflow: 'auto',
background: 'white',
borderRadius: '12px',
padding: '16px'
}}>
{selectedMistakeIds.length === 0 ? (
<p style={{ color: '#9ca3af', fontSize: '14px', textAlign: 'center', margin: 0 }}>
尚未选择任何错题
</p>
) : (
selectedMistakeIds.map((id, index) => {
const mistake = availableMistakes.find(m => m.id === id);
return mistake ? (
<div key={id} style={{
display: 'flex',
alignItems: 'flex-start',
padding: '12px 0',
borderBottom: index < selectedMistakeIds.length - 1 ? '1px solid #f1f5f9' : 'none'
}}>
<span style={{
background: '#667eea',
color: 'white',
width: '24px',
height: '24px',
borderRadius: '50%',
display: 'flex',
alignItems: 'center',
justifyContent: 'center',
fontSize: '12px',
fontWeight: '600',
marginRight: '12px',
flexShrink: 0
}}>
{index + 1}
</span>
<div style={{ flex: 1 }}>
<div style={{ fontSize: '14px', color: '#1f2937', lineHeight: '1.4', marginBottom: '4px' }}>
{mistake.user_question.length > 60
? mistake.user_question.substring(0, 60) + '...'
: mistake.user_question}
</div>
<div style={{
fontSize: '12px',
color: '#667eea',
background: 'rgba(102, 126, 234, 0.1)',
padding: '2px 6px',
borderRadius: '6px',
display: 'inline-block'
}}>
{mistake.subject}
</div>
</div>
</div>
) : null;
})
)}
</div>
</div>
</div>
);
const renderCreatingStep = () => (
<div style={{
textAlign: 'center',
padding: '80px 24px',
display: 'flex',
flexDirection: 'column',
alignItems: 'center',
justifyContent: 'center',
position: 'relative'
}}>
{/* 加载指示器 */}
{loading && (
<div style={{
width: '80px',
height: '80px',
background: 'linear-gradient(135deg, #667eea 0%, #764ba2 100%)',
borderRadius: '50%',
display: 'flex',
alignItems: 'center',
justifyContent: 'center',
marginBottom: '24px',
position: 'relative'
}}>
<div style={{
width: '40px',
height: '40px',
border: '3px solid rgba(255, 255, 255, 0.3)',
borderTop: '3px solid white',
borderRadius: '50%',
animation: 'spin 1s linear infinite'
}}></div>
</div>
)}
{/* 成功指示器 */}
{!loading && (
<div style={{
width: '80px',
height: '80px',
background: 'linear-gradient(135deg, #10b981 0%, #059669 100%)',
borderRadius: '50%',
display: 'flex',
alignItems: 'center',
justifyContent: 'center',
marginBottom: '24px',
animation: 'fadeIn 0.5s ease-in'
}}>
<svg style={{ width: '40px', height: '40px', color: 'white' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={3} d="M5 13l4 4L19 7" />
</svg>
</div>
)}
<h3 style={{
fontSize: '24px',
fontWeight: '700',
color: loading ? '#1f2937' : '#10b981',
marginBottom: '12px',
margin: '0 0 12px 0',
transition: 'color 0.5s ease'
}}>
{loading ? '正在创建回顾分析...' : '创建成功！'}
</h3>
<p style={{
color: '#6b7280',
fontSize: '16px',
lineHeight: '1.5',
maxWidth: '400px',
margin: 0,
transition: 'all 0.5s ease'
}}>
{loading
? '正在整合错题数据并设置分析环境，请稍候...'
: '回顾分析已成功创建，正在跳转到分析页面...'}
</p>
<style>
{`
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
@keyframes fadeIn {
0% { opacity: 0; transform: scale(0.8); }
100% { opacity: 1; transform: scale(1); }
}
`}
</style>
</div>
);
return (
<div style={{
width: '100%',
height: '100%',
overflow: 'auto',
background: '#f8fafc',
display: 'flex',
flexDirection: 'column'
}}>
{/* 头部区域 - 统一白色样式 */}
<div style={{
background: 'white',
borderBottom: '1px solid #e5e7eb',
padding: '24px 32px',
position: 'relative'
}}>
<div style={{
position: 'absolute',
top: 0,
left: 0,
right: 0,
height: '4px',
background: 'linear-gradient(90deg, #667eea, #764ba2)'
}}></div>
<div style={{ position: 'relative', zIndex: 1 }}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '8px' }}>
<svg style={{ width: '32px', height: '32px', marginRight: '12px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 4v16m8-8H4" />
</svg>
<h1 style={{ fontSize: '28px', fontWeight: '700', margin: 0, color: '#1f2937' }}>创建回顾分析</h1>
</div>
<p style={{ fontSize: '16px', color: '#6b7280', margin: 0, lineHeight: '1.5' }}>
配置多错题统一分析，发现学习模式，制定改进计划
</p>
</div>
</div>
{/* 步骤指示器 - 重新设计 */}
<div style={{
background: 'white',
margin: '24px 24px 0 24px',
borderRadius: '16px',
padding: '24px',
boxShadow: '0 4px 20px rgba(0, 0, 0, 0.05)',
border: '1px solid #f1f5f9'
}}>
<div style={{
display: 'flex',
alignItems: 'center',
justifyContent: 'space-between',
position: 'relative'
}}>
{/* 连接线 */}
<div style={{
position: 'absolute',
top: '50%',
left: '60px',
right: '60px',
height: '2px',
background: '#e2e8f0',
zIndex: 1
}}></div>
{[
{ key: 'setup', label: '基本设置', icon: 'M10.325 4.317c.426-1.756 2.924-1.756 3.35 0a1.724 1.724 0 002.573 1.066c1.543-.94 3.31.826 2.37 2.37a1.724 1.724 0 001.065 2.572c1.756.426 1.756 2.924 0 3.35a1.724 1.724 0 00-1.066 2.573c.94 1.543-.826 3.31-2.37 2.37a1.724 1.724 0 00-2.572 1.065c-.426 1.756-2.924 1.756-3.35 0a1.724 1.724 0 00-2.573-1.066c-1.543.94-3.31-.826-2.37-2.37a1.724 1.724 0 00-1.065-2.572c-1.756-.426-1.756-2.924 0-3.35a1.724 1.724 0 001.066-2.573c-.94-1.543.826-3.31 2.37-2.37.996.608 2.296.07 2.572-1.065z M15 12a3 3 0 11-6 0 3 3 0 016 0z' },
{ key: 'select_mistakes', label: '选择错题', icon: 'M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z' },
{ key: 'configure_prompt', label: '配置指引', icon: 'M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z' },
{ key: 'creating', label: '创建中', icon: 'M4.318 6.318a4.5 4.5 0 000 6.364L12 20.364l7.682-7.682a4.5 4.5 0 00-6.364-6.364L12 7.636l-1.318-1.318a4.5 4.5 0 00-6.364 0z' },
].map((stepInfo, index) => {
const currentStepIndex = ['setup', 'select_mistakes', 'configure_prompt', 'creating'].indexOf(step);
const isActive = step === stepInfo.key;
const isCompleted = currentStepIndex > index;
const isPending = currentStepIndex < index;
return (
<div key={stepInfo.key} style={{
display: 'flex',
flexDirection: 'column',
alignItems: 'center',
position: 'relative',
zIndex: 2
}}>
<div style={{
width: '60px',
height: '60px',
borderRadius: '50%',
background: isActive
? 'linear-gradient(135deg, #667eea 0%, #764ba2 100%)'
: isCompleted
? 'linear-gradient(135deg, #10b981 0%, #059669 100%)'
: '#f1f5f9',
color: isActive || isCompleted ? 'white' : '#9ca3af',
display: 'flex',
alignItems: 'center',
justifyContent: 'center',
marginBottom: '12px',
transition: 'all 0.3s ease',
boxShadow: isActive
? '0 8px 25px rgba(102, 126, 234, 0.3)'
: isCompleted
? '0 4px 15px rgba(16, 185, 129, 0.2)'
: 'none'
}}>
{isCompleted ? (
<svg style={{ width: '24px', height: '24px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={3} d="M5 13l4 4L19 7" />
</svg>
) : (
<svg style={{ width: '24px', height: '24px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d={stepInfo.icon} />
</svg>
)}
</div>
<span style={{
fontSize: '14px',
fontWeight: '600',
color: isActive ? '#667eea' : isCompleted ? '#10b981' : '#6b7280',
textAlign: 'center'
}}>
{stepInfo.label}
</span>
</div>
);
})}
</div>
</div>
{/* 表单内容区域 - 重新设计 */}
<div style={{
background: 'white',
margin: '24px',
borderRadius: '16px',
boxShadow: '0 4px 20px rgba(0, 0, 0, 0.05)',
border: '1px solid #f1f5f9',
flex: 1,
display: 'flex',
flexDirection: 'column'
}}>
<div style={{
padding: '32px',
flex: 1,
overflow: 'auto'
}}>
{step === 'setup' && renderSetupStep()}
{step === 'select_mistakes' && renderSelectMistakesStep()}
{step === 'configure_prompt' && renderConfigurePromptStep()}
{step === 'creating' && renderCreatingStep()}
</div>
{/* 底部操作区域 - 重新设计 */}
{step !== 'creating' && (
<div style={{
padding: '24px 32px',
borderTop: '1px solid #f1f5f9',
background: '#fafbfc',
borderRadius: '0 0 16px 16px',
display: 'flex',
justifyContent: 'space-between',
alignItems: 'center'
}}>
<div>
{step !== 'setup' && (
<button
onClick={handlePrevStep}
style={{
background: 'white',
color: '#6b7280',
border: '2px solid #e5e7eb',
padding: '12px 24px',
borderRadius: '12px',
fontSize: '14px',
fontWeight: '600',
cursor: 'pointer',
display: 'inline-flex',
alignItems: 'center',
gap: '8px',
transition: 'all 0.2s ease'
}}
onMouseOver={(e) => {
e.currentTarget.style.background = '#f9fafb';
e.currentTarget.style.borderColor = '#d1d5db';
}}
onMouseOut={(e) => {
e.currentTarget.style.background = 'white';
e.currentTarget.style.borderColor = '#e5e7eb';
}}
>
<svg style={{ width: '16px', height: '16px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M15 19l-7-7 7-7" />
</svg>
上一步
</button>
)}
</div>
<div style={{ display: 'flex', gap: '12px' }}>
<button
onClick={onCancel}
style={{
background: 'white',
color: '#6b7280',
border: '2px solid #e5e7eb',
padding: '12px 24px',
borderRadius: '12px',
fontSize: '14px',
fontWeight: '600',
cursor: 'pointer',
transition: 'all 0.2s ease'
}}
onMouseOver={(e) => {
e.currentTarget.style.background = '#f9fafb';
e.currentTarget.style.borderColor = '#d1d5db';
}}
onMouseOut={(e) => {
e.currentTarget.style.background = 'white';
e.currentTarget.style.borderColor = '#e5e7eb';
}}
>
取消
</button>
<button
onClick={handleNextStep}
disabled={loading}
style={{
background: loading
? '#d1d5db'
: 'linear-gradient(135deg, #667eea 0%, #764ba2 100%)',
color: 'white',
border: 'none',
padding: '12px 32px',
borderRadius: '12px',
fontSize: '14px',
fontWeight: '600',
cursor: loading ? 'not-allowed' : 'pointer',
display: 'inline-flex',
alignItems: 'center',
gap: '8px',
transition: 'all 0.3s ease',
boxShadow: loading ? 'none' : '0 4px 15px rgba(102, 126, 234, 0.3)'
}}
onMouseOver={(e) => {
if (!loading) {
e.currentTarget.style.transform = 'translateY(-2px)';
e.currentTarget.style.boxShadow = '0 8px 25px rgba(102, 126, 234, 0.4)';
}
}}
onMouseOut={(e) => {
if (!loading) {
e.currentTarget.style.transform = 'translateY(0)';
e.currentTarget.style.boxShadow = '0 4px 15px rgba(102, 126, 234, 0.3)';
}
}}
>
{step === 'configure_prompt' ? (
<>
<svg style={{ width: '16px', height: '16px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M13 10V3L4 14h7v7l9-11h-7z" />
</svg>
创建分析
</>
) : (
<>
下一步
<svg style={{ width: '16px', height: '16px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 5l7 7-7 7" />
</svg>
</>
)}
</button>
</div>
</div>
)}
</div>
</div>
);
};
export default CreateReviewAnalysisView;
|
0000cd/wolf-set
| 56,300 |
themes/bluf/static/js/glightbox.min.js
|
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Array.isArray(e)}function L(e){return e&&e.length&&isFinite(e.length)}function I(e){return"object"===t(e)&&null!=e&&!C(e)&&!A(e)}function O(e){return null==e}function P(e,t){return null!==e&&hasOwnProperty.call(e,t)}function M(e){if(I(e)){if(e.keys)return e.keys().length;var t=0;for(var i in e)P(e,i)&&t++;return t}return e.length}function z(e){return!isNaN(parseFloat(e))&&isFinite(e)}function X(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:-1,t=document.querySelectorAll(".gbtn[data-taborder]:not(.disabled)");if(!t.length)return!1;if(1==t.length)return t[0];"string"==typeof e&&(e=parseInt(e));var i=[];r(t,(function(e){i.push(e.getAttribute("data-taborder"))}));var n=Math.max.apply(Math,i.map((function(e){return parseInt(e)}))),s=e<0?1:e+1;s>n&&(s="1");var l=i.filter((function(e){return e>=parseInt(s)})),o=l.sort()[0];return document.querySelector('.gbtn[data-taborder="'.concat(o,'"]'))}function Y(e){if(e.events.hasOwnProperty("keyboard"))return!1;e.events.keyboard=h("keydown",{onElement:window,withCallback:function(t,i){var n=(t=t||window.event).keyCode;if(9==n){var s=document.querySelector(".gbtn.focused");if(!s){var l=!(!document.activeElement||!document.activeElement.nodeName)&&document.activeElement.nodeName.toLocaleLowerCase();if("input"==l||"textarea"==l||"button"==l)return}t.preventDefault();var o=document.querySelectorAll(".gbtn[data-taborder]");if(!o||o.length<=0)return;if(!s){var r=X();return void(r&&(r.focus(),d(r,"focused")))}var a=X(s.getAttribute("data-taborder"));c(s,"focused"),a&&(a.focus(),d(a,"focused"))}39==n&&e.nextSlide(),37==n&&e.prevSlide(),27==n&&e.close()}})}var q=s((function e(t,n){var s=this,l=arguments.length>2&&void 0!==arguments[2]?arguments[2]:null;if(i(this,e),this.img=t,this.slide=n,this.onclose=l,this.img.setZoomEvents)return!1;this.active=!1,this.zoomedIn=!1,this.dragging=!1,this.currentX=null,this.currentY=null,this.initialX=null,this.initialY=null,this.xOffset=0,this.yOffset=0,this.img.addEventListener("mousedown",(function(e){return s.dragStart(e)}),!1),this.img.addEventListener("mouseup",(function(e){return s.dragEnd(e)}),!1),this.img.addEventListener("mousemove",(function(e){return s.drag(e)}),!1),this.img.addEventListener("click",(function(e){return s.slide.classList.contains("dragging-nav")?(s.zoomOut(),!1):s.zoomedIn?void(s.zoomedIn&&!s.dragging&&s.zoomOut()):s.zoomIn()}),!1),this.img.setZoomEvents=!0}),[{key:"zoomIn",value:function(){var e=this.widowWidth();if(!(this.zoomedIn||e<=768)){var t=this.img;if(t.setAttribute("data-style",t.getAttribute("style")),t.style.maxWidth=t.naturalWidth+"px",t.style.maxHeight=t.naturalHeight+"px",t.naturalWidth>e){var i=e/2-t.naturalWidth/2;this.setTranslate(this.img.parentNode,i,0)}this.slide.classList.add("zoomed"),this.zoomedIn=!0}}},{key:"zoomOut",value:function(){this.img.parentNode.setAttribute("style",""),this.img.setAttribute("style",this.img.getAttribute("data-style")),this.slide.classList.remove("zoomed"),this.zoomedIn=!1,this.currentX=null,this.currentY=null,this.initialX=null,this.initialY=null,this.xOffset=0,this.yOffset=0,this.onclose&&"function"==typeof this.onclose&&this.onclose()}},{key:"dragStart",value:function(e){e.preventDefault(),this.zoomedIn?("touchstart"===e.type?(this.initialX=e.touches[0].clientX-this.xOffset,this.initialY=e.touches[0].clientY-this.yOffset):(this.initialX=e.clientX-this.xOffset,this.initialY=e.clientY-this.yOffset),e.target===this.img&&(this.active=!0,this.img.classList.add("dragging"))):this.active=!1}},{key:"dragEnd",value:function(e){var t=this;e.preventDefault(),this.initialX=this.currentX,this.initialY=this.currentY,this.active=!1,setTimeout((function(){t.dragging=!1,t.img.isDragging=!1,t.img.classList.remove("dragging")}),100)}},{key:"drag",value:function(e){this.active&&(e.preventDefault(),"touchmove"===e.type?(this.currentX=e.touches[0].clientX-this.initialX,this.currentY=e.touches[0].clientY-this.initialY):(this.currentX=e.clientX-this.initialX,this.currentY=e.clientY-this.initialY),this.xOffset=this.currentX,this.yOffset=this.currentY,this.img.isDragging=!0,this.dragging=!0,this.setTranslate(this.img,this.currentX,this.currentY))}},{key:"onMove",value:function(e){if(this.zoomedIn){var t=e.clientX-this.img.naturalWidth/2,i=e.clientY-this.img.naturalHeight/2;this.setTranslate(this.img,t,i)}}},{key:"setTranslate",value:function(e,t,i){e.style.transform="translate3d("+t+"px, "+i+"px, 0)"}},{key:"widowWidth",value:function(){return window.innerWidth||document.documentElement.clientWidth||document.body.clientWidth}}]),N=s((function e(){var t=this,n=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{};i(this,e);var s=n.dragEl,l=n.toleranceX,o=void 0===l?40:l,r=n.toleranceY,a=void 0===r?65:r,h=n.slide,d=void 0===h?null:h,c=n.instance,u=void 0===c?null:c;this.el=s,this.active=!1,this.dragging=!1,this.currentX=null,this.currentY=null,this.initialX=null,this.initialY=null,this.xOffset=0,this.yOffset=0,this.direction=null,this.lastDirection=null,this.toleranceX=o,this.toleranceY=a,this.toleranceReached=!1,this.dragContainer=this.el,this.slide=d,this.instance=u,this.el.addEventListener("mousedown",(function(e){return t.dragStart(e)}),!1),this.el.addEventListener("mouseup",(function(e){return t.dragEnd(e)}),!1),this.el.addEventListener("mousemove",(function(e){return t.drag(e)}),!1)}),[{key:"dragStart",value:function(e){if(this.slide.classList.contains("zoomed"))this.active=!1;else{"touchstart"===e.type?(this.initialX=e.touches[0].clientX-this.xOffset,this.initialY=e.touches[0].clientY-this.yOffset):(this.initialX=e.clientX-this.xOffset,this.initialY=e.clientY-this.yOffset);var t=e.target.nodeName.toLowerCase();e.target.classList.contains("nodrag")||g(e.target,".nodrag")||-1!==["input","select","textarea","button","a"].indexOf(t)?this.active=!1:(e.preventDefault(),(e.target===this.el||"img"!==t&&g(e.target,".gslide-inline"))&&(this.active=!0,this.el.classList.add("dragging"),this.dragContainer=g(e.target,".ginner-container")))}}},{key:"dragEnd",value:function(e){var t=this;e&&e.preventDefault(),this.initialX=0,this.initialY=0,this.currentX=null,this.currentY=null,this.initialX=null,this.initialY=null,this.xOffset=0,this.yOffset=0,this.active=!1,this.doSlideChange&&(this.instance.preventOutsideClick=!0,"right"==this.doSlideChange&&this.instance.prevSlide(),"left"==this.doSlideChange&&this.instance.nextSlide()),this.doSlideClose&&this.instance.close(),this.toleranceReached||this.setTranslate(this.dragContainer,0,0,!0),setTimeout((function(){t.instance.preventOutsideClick=!1,t.toleranceReached=!1,t.lastDirection=null,t.dragging=!1,t.el.isDragging=!1,t.el.classList.remove("dragging"),t.slide.classList.remove("dragging-nav"),t.dragContainer.style.transform="",t.dragContainer.style.transition=""}),100)}},{key:"drag",value:function(e){if(this.active){e.preventDefault(),this.slide.classList.add("dragging-nav"),"touchmove"===e.type?(this.currentX=e.touches[0].clientX-this.initialX,this.currentY=e.touches[0].clientY-this.initialY):(this.currentX=e.clientX-this.initialX,this.currentY=e.clientY-this.initialY),this.xOffset=this.currentX,this.yOffset=this.currentY,this.el.isDragging=!0,this.dragging=!0,this.doSlideChange=!1,this.doSlideClose=!1;var t=Math.abs(this.currentX),i=Math.abs(this.currentY);if(t>0&&t>=Math.abs(this.currentY)&&(!this.lastDirection||"x"==this.lastDirection)){this.yOffset=0,this.lastDirection="x",this.setTranslate(this.dragContainer,this.currentX,0);var n=this.shouldChange();if(!this.instance.settings.dragAutoSnap&&n&&(this.doSlideChange=n),this.instance.settings.dragAutoSnap&&n)return this.instance.preventOutsideClick=!0,this.toleranceReached=!0,this.active=!1,this.instance.preventOutsideClick=!0,this.dragEnd(null),"right"==n&&this.instance.prevSlide(),void("left"==n&&this.instance.nextSlide())}if(this.toleranceY>0&&i>0&&i>=t&&(!this.lastDirection||"y"==this.lastDirection)){this.xOffset=0,this.lastDirection="y",this.setTranslate(this.dragContainer,0,this.currentY);var s=this.shouldClose();return!this.instance.settings.dragAutoSnap&&s&&(this.doSlideClose=!0),void(this.instance.settings.dragAutoSnap&&s&&this.instance.close())}}}},{key:"shouldChange",value:function(){var e=!1;if(Math.abs(this.currentX)>=this.toleranceX){var t=this.currentX>0?"right":"left";("left"==t&&this.slide!==this.slide.parentNode.lastChild||"right"==t&&this.slide!==this.slide.parentNode.firstChild)&&(e=t)}return e}},{key:"shouldClose",value:function(){var e=!1;return Math.abs(this.currentY)>=this.toleranceY&&(e=!0),e}},{key:"setTranslate",value:function(e,t,i){var n=arguments.length>3&&void 0!==arguments[3]&&arguments[3];e.style.transition=n?"all .2s ease":"",e.style.transform="translate3d(".concat(t,"px, ").concat(i,"px, 0)")}}]);function D(e,t,i,n){var s=e.querySelector(".gslide-media"),l=new Image,o="gSlideTitle_"+i,r="gSlideDesc_"+i;l.addEventListener("load",(function(){C(n)&&n()}),!1),l.src=t.href,""!=t.sizes&&""!=t.srcset&&(l.sizes=t.sizes,l.srcset=t.srcset),l.alt="",O(t.alt)||""===t.alt||(l.alt=t.alt),""!==t.title&&l.setAttribute("aria-labelledby",o),""!==t.description&&l.setAttribute("aria-describedby",r),t.hasOwnProperty("_hasCustomWidth")&&t._hasCustomWidth&&(l.style.width=t.width),t.hasOwnProperty("_hasCustomHeight")&&t._hasCustomHeight&&(l.style.height=t.height),s.insertBefore(l,s.firstChild)}function _(e,t,i,n){var s=this,l=e.querySelector(".ginner-container"),o="gvideo"+i,r=e.querySelector(".gslide-media"),a=this.getAllPlayers();d(l,"gvideo-container"),r.insertBefore(y('<div class="gvideo-wrapper"></div>'),r.firstChild);var h=e.querySelector(".gvideo-wrapper");w(this.settings.plyr.css,"Plyr");var c=t.href,u=null==t?void 0:t.videoProvider,g=!1;r.style.maxWidth=t.width,w(this.settings.plyr.js,"Plyr",(function(){if(!u&&c.match(/vimeo\.com\/([0-9]*)/)&&(u="vimeo"),!u&&(c.match(/(youtube\.com|youtube-nocookie\.com)\/watch\?v=([a-zA-Z0-9\-_]+)/)||c.match(/youtu\.be\/([a-zA-Z0-9\-_]+)/)||c.match(/(youtube\.com|youtube-nocookie\.com)\/embed\/([a-zA-Z0-9\-_]+)/)||c.match(/(youtube\.com|youtube-nocookie\.com)\/shorts\/([a-zA-Z0-9\-_]+)/))&&(u="youtube"),"local"===u||!u){u="local";var l='<video id="'+o+'" ';l+='style="background:#000; max-width: '.concat(t.width,';" '),l+='preload="metadata" ',l+='x-webkit-airplay="allow" ',l+="playsinline ",l+="controls ",l+='class="gvideo-local">',l+='<source src="'.concat(c,'">'),g=y(l+="</video>")}var r=g||y('<div id="'.concat(o,'" data-plyr-provider="').concat(u,'" data-plyr-embed-id="').concat(c,'"></div>'));d(h,"".concat(u,"-video gvideo")),h.appendChild(r),h.setAttribute("data-id",o),h.setAttribute("data-index",i);var 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e=this,t=this.getSelector();t&&(this.baseEvents=h("click",{onElement:t,withCallback:function(t,i){t.preventDefault(),e.open(i)}})),this.elements=this.getElements()}},{key:"open",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:null,t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:null;if(0===this.elements.length)return!1;this.activeSlide=null,this.prevActiveSlideIndex=null,this.prevActiveSlide=null;var i=z(t)?t:this.settings.startAt;if(E(e)){var n=e.getAttribute("data-gallery");n&&(this.fullElementsList=this.elements,this.elements=this.getGalleryElements(this.elements,n)),O(i)&&(i=this.getElementIndex(e))<0&&(i=0)}z(i)||(i=0),this.build(),v(this.overlay,"none"===this.settings.openEffect?"none":this.settings.cssEfects.fade.in);var s=document.body,l=window.innerWidth-document.documentElement.clientWidth;if(l>0){var o=document.createElement("style");o.type="text/css",o.className="gcss-styles",o.innerText=".gscrollbar-fixer {margin-right: 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t=e.querySelector(".ginner-container"),i=e.querySelector(".gslide-media"),n=e.querySelector(".gslide-description");t.style.transform="",i.style.transform="",c(i,"greset"),i.style.opacity="",n&&(n.style.opacity=""),c(e,"prev")}))}},{key:"getAllPlayers",value:function(){return this.videoPlayers}},{key:"getSlidePlayerInstance",value:function(e){var t="gvideo"+e,i=this.getAllPlayers();return!(!P(i,t)||!i[t])&&i[t]}},{key:"stopSlideVideo",value:function(e){if(E(e)){var t=e.querySelector(".gvideo-wrapper");t&&(e=t.getAttribute("data-index"))}console.log("stopSlideVideo is deprecated, use slidePlayerPause");var i=this.getSlidePlayerInstance(e);i&&i.playing&&i.pause()}},{key:"slidePlayerPause",value:function(e){if(E(e)){var t=e.querySelector(".gvideo-wrapper");t&&(e=t.getAttribute("data-index"))}var i=this.getSlidePlayerInstance(e);i&&i.playing&&i.pause()}},{key:"playSlideVideo",value:function(e){if(E(e)){var 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n=P(this.settings.svg,"next")?this.settings.svg.next:"",s=P(this.settings.svg,"prev")?this.settings.svg.prev:"",l=P(this.settings.svg,"close")?this.settings.svg.close:"",o=this.settings.lightboxHTML;o=y(o=(o=(o=o.replace(/{nextSVG}/g,n)).replace(/{prevSVG}/g,s)).replace(/{closeSVG}/g,l)),document.body.appendChild(o);var a=document.getElementById("glightbox-body");this.modal=a;var c=a.querySelector(".gclose");this.prevButton=a.querySelector(".gprev"),this.nextButton=a.querySelector(".gnext"),this.overlay=a.querySelector(".goverlay"),this.loader=a.querySelector(".gloader"),this.slidesContainer=document.getElementById("glightbox-slider"),this.bodyHiddenChildElms=i,this.events={},d(this.modal,"glightbox-"+this.settings.skin),this.settings.closeButton&&c&&(this.events.close=h("click",{onElement:c,withCallback:function(t,i){t.preventDefault(),e.close()}})),c&&!this.settings.closeButton&&c.parentNode.removeChild(c),this.nextButton&&(this.events.next=h("click",{onElement:this.nextButton,withCallback:function(t,i){t.preventDefault(),e.nextSlide()}})),this.prevButton&&(this.events.prev=h("click",{onElement:this.prevButton,withCallback:function(t,i){t.preventDefault(),e.prevSlide()}})),this.settings.closeOnOutsideClick&&(this.events.outClose=h("click",{onElement:a,withCallback:function(t,i){e.preventOutsideClick||u(document.body,"glightbox-mobile")||g(t.target,".ginner-container")||g(t.target,".gbtn")||u(t.target,"gnext")||u(t.target,"gprev")||e.close()}})),r(this.elements,(function(t,i){e.slidesContainer.appendChild(t.instance.create()),t.slideNode=e.slidesContainer.querySelectorAll(".gslide")[i]})),Q&&d(document.body,"glightbox-touch"),this.events.resize=h("resize",{onElement:window,withCallback:function(){e.resize()}}),this.built=!0}},{key:"resize",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:null;if((e=e||this.activeSlide)&&!u(e,"zoomed")){var t=x(),i=e.querySelector(".gvideo-wrapper"),n=e.querySelector(".gslide-image"),s=this.slideDescription,l=t.width,o=t.height;if(l<=768?d(document.body,"glightbox-mobile"):c(document.body,"glightbox-mobile"),i||n){var r=!1;if(s&&(u(s,"description-bottom")||u(s,"description-top"))&&!u(s,"gabsolute")&&(r=!0),n)if(l<=768)n.querySelector("img");else if(r){var a,h=s.offsetHeight,g=n.querySelector("img"),v=this.elements[this.index].node,f=null!==(a=v.getAttribute("data-height"))&&void 0!==a?a:"100vh";g.setAttribute("style","max-height: calc(".concat(f," - ").concat(h,"px)")),s.setAttribute("style","max-width: ".concat(g.offsetWidth,"px;"))}if(i){var p=P(this.settings.plyr.config,"ratio")?this.settings.plyr.config.ratio:"";if(!p){var m=i.clientWidth,y=i.clientHeight,b=m/y;p="".concat(m/b,":").concat(y/b)}var S=p.split(":"),w=this.settings.videosWidth,T=this.settings.videosWidth,C=(T=z(w)||-1!==w.indexOf("px")?parseInt(w):-1!==w.indexOf("vw")?l*parseInt(w)/100:-1!==w.indexOf("vh")?o*parseInt(w)/100:-1!==w.indexOf("%")?l*parseInt(w)/100:parseInt(i.clientWidth))/(parseInt(S[0])/parseInt(S[1]));if(C=Math.floor(C),r&&(o-=s.offsetHeight),T>l||C>o||o<C&&l>T){var k=i.offsetWidth,E=i.offsetHeight,A=o/E,L={width:k*A,height:E*A};i.parentNode.setAttribute("style","max-width: ".concat(L.width,"px")),r&&s.setAttribute("style","max-width: ".concat(L.width,"px;"))}else i.parentNode.style.maxWidth="".concat(w),r&&s.setAttribute("style","max-width: ".concat(w,";"))}}}}},{key:"reload",value:function(){this.init()}},{key:"updateNavigationClasses",value:function(){var e=this.loop();c(this.nextButton,"disabled"),c(this.prevButton,"disabled"),0==this.index&&this.elements.length-1==0?(d(this.prevButton,"disabled"),d(this.nextButton,"disabled")):0!==this.index||e?this.index!==this.elements.length-1||e||d(this.nextButton,"disabled"):d(this.prevButton,"disabled")}},{key:"loop",value:function(){var e=P(this.settings,"loopAtEnd")?this.settings.loopAtEnd:null;return e=P(this.settings,"loop")?this.settings.loop:e,e}},{key:"close",value:function(){var e=this;if(!this.lightboxOpen){if(this.events){for(var t in this.events)this.events.hasOwnProperty(t)&&this.events[t].destroy();this.events=null}return!1}if(this.closing)return!1;this.closing=!0,this.slidePlayerPause(this.activeSlide),this.fullElementsList&&(this.elements=this.fullElementsList),this.bodyHiddenChildElms.length&&r(this.bodyHiddenChildElms,(function(e){e.removeAttribute("aria-hidden")})),d(this.modal,"glightbox-closing"),v(this.overlay,"none"==this.settings.openEffect?"none":this.settings.cssEfects.fade.out),v(this.activeSlide,this.settings.cssEfects[this.settings.closeEffect].out,(function(){if(e.activeSlide=null,e.prevActiveSlideIndex=null,e.prevActiveSlide=null,e.built=!1,e.events){for(var t in e.events)e.events.hasOwnProperty(t)&&e.events[t].destroy();e.events=null}var i=document.body;c(ee,"glightbox-open"),c(i,"glightbox-open touching gdesc-open glightbox-touch glightbox-mobile gscrollbar-fixer"),e.modal.parentNode.removeChild(e.modal),e.trigger("close"),C(e.settings.onClose)&&e.settings.onClose();var n=document.querySelector(".gcss-styles");n&&n.parentNode.removeChild(n),e.lightboxOpen=!1,e.closing=null}))}},{key:"destroy",value:function(){this.close(),this.clearAllEvents(),this.baseEvents&&this.baseEvents.destroy()}},{key:"on",value:function(e,t){var i=arguments.length>2&&void 0!==arguments[2]&&arguments[2];if(!e||!C(t))throw new TypeError("Event name and callback must be defined");this.apiEvents.push({evt:e,once:i,callback:t})}},{key:"once",value:function(e,t){this.on(e,t,!0)}},{key:"trigger",value:function(e){var t=this,i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:null,n=[];r(this.apiEvents,(function(t,s){var l=t.evt,o=t.once,r=t.callback;l==e&&(r(i),o&&n.push(s))})),n.length&&r(n,(function(e){return t.apiEvents.splice(e,1)}))}},{key:"clearAllEvents",value:function(){this.apiEvents.splice(0,this.apiEvents.length)}},{key:"version",value:function(){return"3.3.0"}}]);return function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{},t=new ie(e);return t.init(),t}}));
|
0000cd/wolf-set
| 12,528 |
themes/bluf/static/css/APlayer.min.css
|
.aplayer{background:#fff;font-family:Arial,Helvetica,sans-serif;margin:5px;box-shadow:0 2px 2px 0 rgba(0,0,0,.07),0 1px 5px 0 rgba(0,0,0,.1);border-radius:2px;overflow:hidden;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;line-height:normal;position:relative}.aplayer *{box-sizing:content-box}.aplayer svg{width:100%;height:100%}.aplayer svg circle,.aplayer svg path{fill:#fff}.aplayer.aplayer-withlist .aplayer-info{border-bottom:1px solid #e9e9e9}.aplayer.aplayer-withlist .aplayer-list{display:block}.aplayer.aplayer-withlist .aplayer-icon-order,.aplayer.aplayer-withlist .aplayer-info .aplayer-controller .aplayer-time .aplayer-icon.aplayer-icon-menu{display:inline}.aplayer.aplayer-withlrc .aplayer-pic{height:90px;width:90px}.aplayer.aplayer-withlrc .aplayer-info{margin-left:90px;height:90px;padding:10px 7px 0}.aplayer.aplayer-withlrc .aplayer-lrc{display:block}.aplayer.aplayer-narrow{width:66px}.aplayer.aplayer-narrow .aplayer-info,.aplayer.aplayer-narrow .aplayer-list{display:none}.aplayer.aplayer-narrow .aplayer-body,.aplayer.aplayer-narrow .aplayer-pic{height:66px;width:66px}.aplayer.aplayer-fixed{position:fixed;bottom:0;left:0;right:0;margin:0;z-index:99;overflow:visible;max-width:400px;box-shadow:none}.aplayer.aplayer-fixed .aplayer-list{margin-bottom:65px;border:1px solid #eee;border-bottom:none}.aplayer.aplayer-fixed .aplayer-body{position:fixed;bottom:0;left:0;right:0;margin:0;z-index:99;background:#fff;padding-right:18px;transition:all .3s ease;max-width:400px}.aplayer.aplayer-fixed .aplayer-lrc{display:block;position:fixed;bottom:10px;left:0;right:0;margin:0;z-index:98;pointer-events:none;text-shadow:-1px -1px 0 #fff}.aplayer.aplayer-fixed .aplayer-lrc:after,.aplayer.aplayer-fixed .aplayer-lrc:before{display:none}.aplayer.aplayer-fixed .aplayer-info{-webkit-transform:scaleX(1);transform:scaleX(1);-webkit-transform-origin:0 0;transform-origin:0 0;transition:all .3s ease;border-bottom:none;border-top:1px solid #e9e9e9}.aplayer.aplayer-fixed .aplayer-info .aplayer-music{width:calc(100% - 105px)}.aplayer.aplayer-fixed .aplayer-miniswitcher{display:block}.aplayer.aplayer-fixed.aplayer-narrow .aplayer-info{display:block;-webkit-transform:scaleX(0);transform:scaleX(0)}.aplayer.aplayer-fixed.aplayer-narrow .aplayer-body{width:66px!important}.aplayer.aplayer-fixed.aplayer-narrow .aplayer-miniswitcher .aplayer-icon{-webkit-transform:rotateY(0);transform:rotateY(0)}.aplayer.aplayer-fixed .aplayer-icon-back,.aplayer.aplayer-fixed .aplayer-icon-forward,.aplayer.aplayer-fixed .aplayer-icon-lrc,.aplayer.aplayer-fixed .aplayer-icon-play{display:inline-block}.aplayer.aplayer-fixed .aplayer-icon-back,.aplayer.aplayer-fixed .aplayer-icon-forward,.aplayer.aplayer-fixed .aplayer-icon-menu,.aplayer.aplayer-fixed .aplayer-icon-play{position:absolute;bottom:27px;width:20px;height:20px}.aplayer.aplayer-fixed .aplayer-icon-back{right:75px}.aplayer.aplayer-fixed .aplayer-icon-play{right:50px}.aplayer.aplayer-fixed .aplayer-icon-forward{right:25px}.aplayer.aplayer-fixed .aplayer-icon-menu{right:0}.aplayer.aplayer-arrow .aplayer-icon-loop,.aplayer.aplayer-arrow .aplayer-icon-order,.aplayer.aplayer-mobile .aplayer-icon-volume-down{display:none}.aplayer.aplayer-loading .aplayer-info .aplayer-controller .aplayer-loading-icon{display:block}.aplayer.aplayer-loading .aplayer-info .aplayer-controller .aplayer-bar-wrap .aplayer-bar .aplayer-played .aplayer-thumb{-webkit-transform:scale(1);transform:scale(1)}.aplayer .aplayer-body{position:relative}.aplayer .aplayer-icon{width:15px;height:15px;border:none;background-color:transparent;outline:none;cursor:pointer;opacity:.8;vertical-align:middle;padding:0;font-size:12px;margin:0;display:inline-block}.aplayer .aplayer-icon path{transition:all .2s ease-in-out}.aplayer .aplayer-icon-back,.aplayer .aplayer-icon-forward,.aplayer .aplayer-icon-lrc,.aplayer .aplayer-icon-order,.aplayer .aplayer-icon-play{display:none}.aplayer .aplayer-icon-lrc-inactivity svg{opacity:.4}.aplayer .aplayer-icon-forward{-webkit-transform:rotate(180deg);transform:rotate(180deg)}.aplayer .aplayer-lrc-content{display:none}.aplayer .aplayer-pic{position:relative;float:left;height:66px;width:66px;background-size:cover;background-position:50%;transition:all .3s ease;cursor:pointer}.aplayer .aplayer-pic:hover .aplayer-button{opacity:1}.aplayer .aplayer-pic .aplayer-button{position:absolute;border-radius:50%;opacity:.8;text-shadow:0 1px 1px rgba(0,0,0,.2);box-shadow:0 1px 1px rgba(0,0,0,.2);background:rgba(0,0,0,.2);transition:all .1s ease}.aplayer .aplayer-pic .aplayer-button path{fill:#fff}.aplayer .aplayer-pic .aplayer-hide{display:none}.aplayer .aplayer-pic .aplayer-play{width:26px;height:26px;border:2px solid #fff;bottom:50%;right:50%;margin:0 -15px -15px 0}.aplayer .aplayer-pic .aplayer-play svg{position:absolute;top:3px;left:4px;height:20px;width:20px}.aplayer .aplayer-pic .aplayer-pause{width:16px;height:16px;border:2px solid #fff;bottom:4px;right:4px}.aplayer .aplayer-pic .aplayer-pause svg{position:absolute;top:2px;left:2px;height:12px;width:12px}.aplayer .aplayer-info{margin-left:66px;padding:14px 7px 0 10px;height:66px;box-sizing:border-box}.aplayer .aplayer-info .aplayer-music{overflow:hidden;white-space:nowrap;text-overflow:ellipsis;margin:0 0 13px 5px;-webkit-user-select:text;-moz-user-select:text;-ms-user-select:text;user-select:text;cursor:default;padding-bottom:2px;height:20px}.aplayer .aplayer-info .aplayer-music .aplayer-title{font-size:14px}.aplayer .aplayer-info .aplayer-music .aplayer-author{font-size:12px;color:#666}.aplayer .aplayer-info .aplayer-controller{position:relative;display:flex}.aplayer .aplayer-info .aplayer-controller .aplayer-bar-wrap{margin:0 0 0 5px;padding:4px 0;cursor:pointer!important;flex:1}.aplayer .aplayer-info .aplayer-controller .aplayer-bar-wrap:hover .aplayer-bar .aplayer-played .aplayer-thumb{-webkit-transform:scale(1);transform:scale(1)}.aplayer .aplayer-info .aplayer-controller .aplayer-bar-wrap .aplayer-bar{position:relative;height:2px;width:100%;background:#cdcdcd}.aplayer .aplayer-info .aplayer-controller .aplayer-bar-wrap .aplayer-bar .aplayer-loaded{position:absolute;left:0;top:0;bottom:0;background:#aaa;height:2px;transition:all .5s ease}.aplayer .aplayer-info .aplayer-controller .aplayer-bar-wrap .aplayer-bar .aplayer-played{position:absolute;left:0;top:0;bottom:0;height:2px}.aplayer .aplayer-info .aplayer-controller .aplayer-bar-wrap .aplayer-bar .aplayer-played .aplayer-thumb{position:absolute;top:0;right:5px;margin-top:-4px;margin-right:-10px;height:10px;width:10px;border-radius:50%;cursor:pointer;transition:all .3s ease-in-out;-webkit-transform:scale(0);transform:scale(0)}.aplayer .aplayer-info .aplayer-controller .aplayer-time{position:relative;right:0;bottom:4px;height:17px;color:#999;font-size:11px;padding-left:7px}.aplayer .aplayer-info .aplayer-controller .aplayer-time .aplayer-time-inner{vertical-align:middle}.aplayer .aplayer-info .aplayer-controller .aplayer-time .aplayer-icon{cursor:pointer;transition:all .2s ease}.aplayer .aplayer-info .aplayer-controller .aplayer-time .aplayer-icon path{fill:#666}.aplayer .aplayer-info .aplayer-controller .aplayer-time .aplayer-icon.aplayer-icon-loop{margin-right:2px}.aplayer .aplayer-info .aplayer-controller .aplayer-time .aplayer-icon:hover path{fill:#000}.aplayer .aplayer-info .aplayer-controller .aplayer-time .aplayer-icon.aplayer-icon-menu,.aplayer .aplayer-info .aplayer-controller .aplayer-time.aplayer-time-narrow .aplayer-icon-menu,.aplayer .aplayer-info .aplayer-controller .aplayer-time.aplayer-time-narrow .aplayer-icon-mode{display:none}.aplayer .aplayer-info .aplayer-controller .aplayer-volume-wrap{position:relative;display:inline-block;margin-left:3px;cursor:pointer!important}.aplayer .aplayer-info .aplayer-controller .aplayer-volume-wrap:hover .aplayer-volume-bar-wrap{height:40px}.aplayer .aplayer-info .aplayer-controller .aplayer-volume-wrap .aplayer-volume-bar-wrap{position:absolute;bottom:15px;right:-3px;width:25px;height:0;z-index:99;overflow:hidden;transition:all .2s ease-in-out}.aplayer .aplayer-info .aplayer-controller .aplayer-volume-wrap .aplayer-volume-bar-wrap.aplayer-volume-bar-wrap-active{height:40px}.aplayer .aplayer-info .aplayer-controller .aplayer-volume-wrap .aplayer-volume-bar-wrap .aplayer-volume-bar{position:absolute;bottom:0;right:10px;width:5px;height:35px;background:#aaa;border-radius:2.5px;overflow:hidden}.aplayer .aplayer-info .aplayer-controller .aplayer-volume-wrap .aplayer-volume-bar-wrap .aplayer-volume-bar .aplayer-volume{position:absolute;bottom:0;right:0;width:5px;transition:all .1s ease}.aplayer .aplayer-info .aplayer-controller .aplayer-loading-icon{display:none}.aplayer .aplayer-info .aplayer-controller .aplayer-loading-icon svg{position:absolute;-webkit-animation:rotate 1s linear infinite;animation:rotate 1s linear infinite}.aplayer .aplayer-lrc{display:none;position:relative;height:30px;text-align:center;overflow:hidden;margin:-10px 0 7px}.aplayer .aplayer-lrc:before{top:0;height:10%;background:linear-gradient(180deg,#fff 0,hsla(0,0%,100%,0));filter:progid:DXImageTransform.Microsoft.gradient(startColorstr="#ffffff",endColorstr="#00ffffff",GradientType=0)}.aplayer .aplayer-lrc:after,.aplayer .aplayer-lrc:before{position:absolute;z-index:1;display:block;overflow:hidden;width:100%;content:" "}.aplayer .aplayer-lrc:after{bottom:0;height:33%;background:linear-gradient(180deg,hsla(0,0%,100%,0) 0,hsla(0,0%,100%,.8));filter:progid:DXImageTransform.Microsoft.gradient(startColorstr="#00ffffff",endColorstr="#ccffffff",GradientType=0)}.aplayer .aplayer-lrc p{font-size:12px;color:#666;line-height:16px!important;height:16px!important;padding:0!important;margin:0!important;transition:all .5s ease-out;opacity:.4;overflow:hidden}.aplayer .aplayer-lrc p.aplayer-lrc-current{opacity:1;overflow:visible;height:auto!important;min-height:16px}.aplayer .aplayer-lrc.aplayer-lrc-hide{display:none}.aplayer .aplayer-lrc .aplayer-lrc-contents{width:100%;transition:all .5s ease-out;-webkit-user-select:text;-moz-user-select:text;-ms-user-select:text;user-select:text;cursor:default}.aplayer .aplayer-list{overflow:auto;transition:all .5s ease;will-change:height;display:none;overflow:hidden}.aplayer .aplayer-list.aplayer-list-hide{max-height:0!important}.aplayer .aplayer-list ol{list-style-type:none;margin:0;padding:0;overflow-y:auto}.aplayer .aplayer-list ol::-webkit-scrollbar{width:5px}.aplayer .aplayer-list ol::-webkit-scrollbar-thumb{border-radius:3px;background-color:#eee}.aplayer .aplayer-list ol::-webkit-scrollbar-thumb:hover{background-color:#ccc}.aplayer .aplayer-list ol li{position:relative;height:32px;line-height:32px;padding:0 15px;font-size:12px;border-top:1px solid #e9e9e9;cursor:pointer;transition:all .2s ease;overflow:hidden;margin:0}.aplayer .aplayer-list ol li:first-child{border-top:none}.aplayer .aplayer-list ol li:hover{background:#efefef}.aplayer .aplayer-list ol li.aplayer-list-light{background:#e9e9e9}.aplayer .aplayer-list ol li.aplayer-list-light .aplayer-list-cur{display:inline-block}.aplayer .aplayer-list ol li .aplayer-list-cur{display:none;width:3px;height:22px;position:absolute;left:0;top:5px;cursor:pointer}.aplayer .aplayer-list ol li .aplayer-list-index{color:#666;margin-right:12px;cursor:pointer}.aplayer .aplayer-list ol li .aplayer-list-author{color:#666;float:right;cursor:pointer}.aplayer .aplayer-notice{opacity:0;position:absolute;top:50%;left:50%;-webkit-transform:translate(-50%,-50%);transform:translate(-50%,-50%);font-size:12px;border-radius:4px;padding:5px 10px;transition:all .3s ease-in-out;overflow:hidden;color:#fff;pointer-events:none;background-color:#f4f4f5;color:#909399}.aplayer .aplayer-miniswitcher{display:none;position:absolute;top:0;right:0;bottom:0;height:100%;background:#e6e6e6;width:18px;border-radius:0 2px 2px 0}.aplayer .aplayer-miniswitcher .aplayer-icon{height:100%;width:100%;-webkit-transform:rotateY(180deg);transform:rotateY(180deg);transition:all .3s ease}.aplayer .aplayer-miniswitcher .aplayer-icon path{fill:#666}.aplayer .aplayer-miniswitcher .aplayer-icon:hover path{fill:#000}@-webkit-keyframes aplayer-roll{0%{left:0}to{left:-100%}}@keyframes aplayer-roll{0%{left:0}to{left:-100%}}@-webkit-keyframes rotate{0%{-webkit-transform:rotate(0);transform:rotate(0)}to{-webkit-transform:rotate(1turn);transform:rotate(1turn)}}@keyframes rotate{0%{-webkit-transform:rotate(0);transform:rotate(0)}to{-webkit-transform:rotate(1turn);transform:rotate(1turn)}}
/*# sourceMappingURL=APlayer.min.css.map*/
|
000haoji/deep-student
| 58,557 |
src/components/AnkiCardGeneration.tsx
|
import React, { useState, useRef, useEffect } from 'react';
import { invoke } from '@tauri-apps/api/core';
import { listen } from '@tauri-apps/api/event';
import {
AnkiCard,
AnkiGenerationOptions,
AnkiCardTemplate,
CustomAnkiTemplate,
CreateTemplateRequest,
FieldExtractionRule,
FieldType
} from '../types';
import { ANKI_CARD_TEMPLATES, getDefaultTemplate, getTemplatePrompt, getTemplateFields, templateManager } from '../data/ankiTemplates';
import TemplateManager from './TemplateManager';
import { useSystemSettings } from '../hooks/useSystemSettings';
import './UnifiedTemplateSelector.css';
import { IframePreview, renderCardPreview as renderTemplatePreview } from './SharedPreview';
import {
BookOpen, AlertTriangle, CheckCircle, RefreshCcw, X,
Upload, Lightbulb, FileText, Clock, Settings
} from 'lucide-react';
interface AnkiCardGenerationProps {
onTemplateSelectionRequest?: (callback: (template: any) => void) => void;
}
const AnkiCardGeneration: React.FC<AnkiCardGenerationProps> = ({ onTemplateSelectionRequest }) => {
const [documentContent, setDocumentContent] = useState('');
const [generatedCards, setGeneratedCards] = useState<AnkiCard[]>([]);
const [selectedCards, setSelectedCards] = useState<Set<number>>(new Set());
const [isGenerating, setIsGenerating] = useState(false);
const [error, setError] = useState<string | null>(null);
const [options, setOptions] = useState<AnkiGenerationOptions>({
deck_name: 'AI学习卡片',
note_type: 'Basic',
enable_images: false,
max_cards_per_mistake: 30,
max_tokens: 8192,
temperature: 0.3,
template_id: getDefaultTemplate().id,
segment_overlap_size: 200
});
const [selectedTemplate, setSelectedTemplate] = useState<AnkiCardTemplate>(getDefaultTemplate());
const [showTemplatePreview, setShowTemplatePreview] = useState(false);
const [currentDocumentId, setCurrentDocumentId] = useState<string | null>(null);
const [documentTasks, setDocumentTasks] = useState<any[]>([]);
const [selectedTaskId, setSelectedTaskId] = useState<string | null>(null);
const [isAnkiConnectAvailable, setIsAnkiConnectAvailable] = useState<boolean | null>(null);
const [ankiDeckNames, setAnkiDeckNames] = useState<string[]>([]);
const [ankiModelNames, setAnkiModelNames] = useState<string[]>([]);
const [isAddingToAnki, setIsAddingToAnki] = useState(false);
const [ankiConnectionError, setAnkiConnectionError] = useState<string | null>(null);
const [isExportingApkg, setIsExportingApkg] = useState(false);
const [selectedFiles, setSelectedFiles] = useState<File[]>([]);
const [isDragOver, setIsDragOver] = useState(false);
const [isProcessingFiles, setIsProcessingFiles] = useState(false);
const [allTemplates, setAllTemplates] = useState<CustomAnkiTemplate[]>([]);
const [showTemplateManager, setShowTemplateManager] = useState(false);
const [isLoadingTemplates, setIsLoadingTemplates] = useState(false);
const [customRequirements, setCustomRequirements] = useState('');
const [isAnkiConnectEnabled, setIsAnkiConnectEnabled] = useState(false);
const [systemPrompt, setSystemPrompt] = useState('你是一个专业的ANKI学习卡片制作助手。请根据提供的学习内容，生成高质量的ANKI学习卡片。\n\n要求：\n1. 卡片应该有助于记忆和理解\n2. 问题要简洁明确\n3. 答案要准确完整\n4. 适当添加相关标签\n5. 确保卡片的逻辑性和实用性');
const [showPromptConfig, setShowPromptConfig] = useState(false);
const fileInputRef = useRef<HTMLInputElement>(null);
const loadAllTemplates = async () => {
setIsLoadingTemplates(true);
try {
await templateManager.refresh();
setAllTemplates(templateManager.getAllTemplates());
} catch (error) {
console.error('加载模板失败:', error);
setError(`加载模板失败: ${error}`);
} finally {
setIsLoadingTemplates(false);
}
};
const updateToDefaultTemplate = () => {
try {
const defaultTemplate = templateManager.getDefaultTemplate();
if (defaultTemplate && defaultTemplate.id !== selectedTemplate.id) {
const ankiTemplate = templateManager.toAnkiCardTemplate(defaultTemplate);
setSelectedTemplate(ankiTemplate);
setOptions(prev => ({
...prev,
template_id: defaultTemplate.id,
note_type: defaultTemplate.note_type
}));
}
} catch (error) {
console.error('更新默认模板失败:', error);
}
};
const handleTemplateSelect = (template: CustomAnkiTemplate) => {
const ankiTemplate = templateManager.toAnkiCardTemplate(template);
setSelectedTemplate(ankiTemplate);
setOptions({
...options,
template_id: template.id,
note_type: template.note_type
});
};
const handleTemplateChange = (templateId: string) => {
const template = ANKI_CARD_TEMPLATES.find(t => t.id === templateId);
if (template) {
setSelectedTemplate(template);
setOptions({
...options,
template_id: templateId,
note_type: template.note_type
});
}
};
const renderClozeText = (text: string) => {
if (!text) return '';
return text.replace(/\{\{c(\d+)::([^}]+?)\}\}/g,
'<span class="cloze-highlight">$2</span>'
);
};
const getTaskCards = () => {
if (!selectedTaskId) return generatedCards;
const task = documentTasks.find(t => t.task_id === selectedTaskId);
return task?.cards || [];
};
const getCurrentDisplayCards = () => {
if (selectedTaskId) {
return getTaskCards();
}
return generatedCards;
};
const getCardGlobalIndex = (localIndex: number) => {
if (!selectedTaskId) return localIndex;
const taskCards = getTaskCards();
const targetCard = taskCards[localIndex];
if (!targetCard) return -1;
return generatedCards.findIndex(card =>
card.front === targetCard.front &&
card.back === targetCard.back
);
};
const handleDragOver = (e: React.DragEvent) => {
e.preventDefault();
setIsDragOver(true);
};
const handleDragLeave = (e: React.DragEvent) => {
e.preventDefault();
setIsDragOver(false);
};
const handleDrop = (e: React.DragEvent) => {
e.preventDefault();
setIsDragOver(false);
const files = Array.from(e.dataTransfer.files);
const supportedFiles = files.filter(file =>
file.type === 'application/pdf' ||
file.name.endsWith('.pdf') ||
file.name.endsWith('.docx') ||
file.name.endsWith('.txt') ||
file.name.endsWith('.md')
);
if (supportedFiles.length > 0) {
setSelectedFiles(prev => [...prev, ...supportedFiles]);
} else {
setError('请选择支持的文件格式（PDF、DOCX、TXT、MD）');
}
};
const processSelectedFile = async (file: File) => {
setIsProcessingFiles(true);
setError(null);
try {
const fileName = file.name.toLowerCase();
if (fileName.endsWith('.docx') || fileName.endsWith('.pdf')) {
const reader = new FileReader();
reader.onload = async (e) => {
try {
const dataUrl = e.target?.result as string;
// 从data URL中提取base64内容（移除 "data:application/pdf;base64," 等前缀）
const base64Content = dataUrl.split(',')[1];
const { invoke } = await import('@tauri-apps/api/core');
const extractedText = await invoke('parse_document_from_base64', {
fileName: file.name,
base64Content: base64Content
});
setDocumentContent(extractedText as string);
} catch (error) {
setError(`文档解析失败: ${error}`);
} finally {
setIsProcessingFiles(false);
}
};
reader.readAsDataURL(file);
} else {
const reader = new FileReader();
reader.onload = (e) => {
const content = e.target?.result as string;
setDocumentContent(content);
setIsProcessingFiles(false);
};
reader.readAsText(file, 'UTF-8');
}
} catch (error) {
setError(`文件处理失败: ${error}`);
setIsProcessingFiles(false);
}
};
const generateCards = async () => {
if (!documentContent) {
setError('请输入文档内容');
return;
}
setIsGenerating(true);
setError(null);
setCurrentDocumentId(null);
setDocumentTasks([]);
setGeneratedCards([]);
setSelectedCards(new Set());
try {
const templatePrompt = getTemplatePrompt(options.template_id || getDefaultTemplate().id);
const templateFields = getTemplateFields(options.template_id || getDefaultTemplate().id);
const currentTemplate = allTemplates.find(t => t.id === (options.template_id || getDefaultTemplate().id));
const fieldExtractionRules = currentTemplate?.field_extraction_rules || {};
await invoke('start_enhanced_document_processing', {
documentContent: documentContent,
originalDocumentName: `AI学习文档_${new Date().toISOString().slice(0, 10)}`,
options: {
...options,
max_output_tokens_override: options.max_tokens,
temperature_override: options.temperature,
template_id: selectedTemplate?.id || null,
custom_anki_prompt: templatePrompt,
template_fields: templateFields,
field_extraction_rules: fieldExtractionRules,
custom_requirements: customRequirements.trim() || null,
system_prompt: systemPrompt.trim() || null
}
});
} catch (err) {
setError(`生成失败: ${err}`);
setIsGenerating(false);
}
};
const handleAnkiStreamEvent = (received_payload: any) => {
let actual_payload = received_payload;
if (received_payload && typeof received_payload === 'object' && Object.prototype.hasOwnProperty.call(received_payload, 'payload')) {
actual_payload = received_payload.payload;
}
if (!actual_payload || !actual_payload.type) {
return;
}
switch (actual_payload.type) {
case 'DocumentProcessingStarted':
if (actual_payload.data && actual_payload.data.document_id) {
setCurrentDocumentId(actual_payload.data.document_id);
const initialTasks = Array.from({ length: actual_payload.data.total_segments || 0 }, (_, i) => ({
task_id: `temp_task_${actual_payload.data.document_id}_${i}`,
segment_index: i,
status: 'pending',
progress: 0,
cards: [],
content_preview: `片段 ${i + 1} (等待处理中...)`,
error_message: null,
}));
setDocumentTasks(initialTasks);
setGeneratedCards([]);
setSelectedCards(new Set());
}
break;
case 'TaskStatusUpdate':
if (actual_payload.data && actual_payload.data.task_id) {
setDocumentTasks(prevTasks => {
let taskUpdated = false;
const updatedTasks = prevTasks.map(t => {
if (t.task_id === actual_payload.data.task_id) {
taskUpdated = true;
return { ...t, status: actual_payload.data.status?.toLowerCase() || 'pending', error_message: actual_payload.data.message || t.error_message };
}
return t;
});
if (!taskUpdated && typeof actual_payload.data.segment_index === 'number') {
return prevTasks.map(t => {
if (t.segment_index === actual_payload.data.segment_index && t.task_id.startsWith('temp_task_')) {
return { ...t, task_id: actual_payload.data.task_id, status: actual_payload.data.status?.toLowerCase() || 'pending', error_message: actual_payload.data.message || t.error_message };
}
return t;
});
}
return updatedTasks;
});
}
break;
case 'NewCard':
case 'NewErrorCard':
if (actual_payload.data && actual_payload.data.task_id) {
const isError = actual_payload.type === 'NewErrorCard';
let newCardEntry = { ...actual_payload.data, is_error_card: isError };
const isDuplicateCard = (existingCard: AnkiCard, newCard: AnkiCard) => {
if (selectedTemplate.note_type === 'Cloze') {
const existingText = existingCard.text || existingCard.front || '';
const newText = newCard.text || newCard.front || '';
return existingText === newText && existingText.length > 0;
}
return existingCard.front === newCard.front && existingCard.back === newCard.back;
};
if (selectedTemplate.note_type === 'Cloze' && !newCardEntry.text && newCardEntry.front) {
newCardEntry = { ...newCardEntry, text: newCardEntry.front, front: '' };
}
setDocumentTasks(prev => {
let cardAddedToTask = false;
const newTasks = prev.map(task => {
if (task.task_id === newCardEntry.task_id) {
cardAddedToTask = true;
const isDuplicate = task.cards.some((existingCard: AnkiCard) => isDuplicateCard(existingCard, newCardEntry));
if (isDuplicate) return task;
return { ...task, cards: [...task.cards, newCardEntry] };
}
return task;
});
return newTasks;
});
setGeneratedCards(prev => {
const isDuplicate = prev.some(existingCard => isDuplicateCard(existingCard, newCardEntry));
if (isDuplicate) return prev;
return [...prev, newCardEntry];
});
}
break;
case 'TaskCompleted':
if (actual_payload.data && actual_payload.data.task_id) {
setDocumentTasks(prev =>
prev.map(task => {
if (task.task_id === actual_payload.data.task_id) {
return { ...task, status: (actual_payload.data.final_status || 'Completed').toLowerCase(), progress: 100 };
}
return task;
})
);
}
break;
case 'DocumentProcessingCompleted':
if (actual_payload.data && actual_payload.data.document_id) {
setIsGenerating(false);
if (selectedTemplate.note_type === 'Cloze') {
setGeneratedCards(prev => prev.map(card => (!card.text && card.front) ? { ...card, text: card.front, front: '' } : card));
setDocumentTasks(prev => prev.map(task => ({
...task,
cards: task.cards.map((card: any) => (!card.text && card.front) ? { ...card, text: card.front, front: '' } : card)
})));
}
}
break;
case 'TaskProcessingError':
if (actual_payload.data) {
const errorMsg = actual_payload.data.error_message || '处理过程中发生未知错误';
const taskId = actual_payload.data.task_id;
const detailedError = taskId ? `任务 ${taskId.substring(0, 8)}... 发生错误: ${errorMsg}` : `处理错误: ${errorMsg}`;
setError(prevError => prevError ? `${prevError}\n${detailedError}` : detailedError);
if (taskId) {
setDocumentTasks(prev => prev.map(task => task.task_id === taskId ? { ...task, status: 'failed', error_message: errorMsg } : task));
}
}
break;
default:
break;
}
};
const toggleCardSelection = (index: number) => {
const newSelected = new Set(selectedCards);
if (newSelected.has(index)) {
newSelected.delete(index);
} else {
newSelected.add(index);
}
setSelectedCards(newSelected);
};
const toggleSelectAll = () => {
const currentCards = getCurrentDisplayCards();
const currentGlobalIndices = currentCards.map((_: any, localIndex: number) => getCardGlobalIndex(localIndex));
const allCurrentSelected = currentGlobalIndices.every((globalIndex: number) => selectedCards.has(globalIndex));
const newSelected = new Set(selectedCards);
if (allCurrentSelected) {
currentGlobalIndices.forEach((globalIndex: number) => newSelected.delete(globalIndex));
} else {
currentGlobalIndices.forEach((globalIndex: number) => newSelected.add(globalIndex));
}
setSelectedCards(newSelected);
};
const editCard = (index: number, field: 'front' | 'back' | 'text', value: string) => {
const newCards = [...generatedCards];
newCards[index] = { ...newCards[index], [field]: value };
setGeneratedCards(newCards);
setDocumentTasks(prev =>
prev.map(task => ({
...task,
cards: task.cards.map((card: any) =>
card.front === generatedCards[index].front && card.back === generatedCards[index].back
? { ...card, [field]: value }
: card
)
}))
);
};
const deleteCard = (index: number) => {
const cardToDelete = generatedCards[index];
if (!cardToDelete) return;
const newCards = generatedCards.filter((_, i) => i !== index);
setGeneratedCards(newCards);
setDocumentTasks(prev =>
prev.map(task => ({
...task,
cards: task.cards.filter((card: any) =>
!(card.front === cardToDelete.front && card.back === cardToDelete.back)
)
}))
);
const newSelected = new Set<number>();
selectedCards.forEach(selectedIndex => {
if (selectedIndex < index) {
newSelected.add(selectedIndex);
} else if (selectedIndex > index) {
newSelected.add(selectedIndex - 1);
}
});
setSelectedCards(newSelected);
};
const checkAnkiConnectStatus = async () => {
try {
console.log('获取Anki牌组和模型列表...');
try {
const deckNames = await invoke('anki_get_deck_names') as string[];
const modelNames = await invoke('anki_get_model_names') as string[];
console.log('获取到牌组:', deckNames);
console.log('获取到模型:', modelNames);
setAnkiDeckNames(deckNames);
setAnkiModelNames(modelNames);
setIsAnkiConnectAvailable(true);
setAnkiConnectionError(null);
return true;
} catch (err) {
console.error('AnkiConnect连接失败:', err);
setIsAnkiConnectAvailable(false);
setAnkiConnectionError(err as string);
return false;
}
} catch (err) {
console.error('AnkiConnect连接失败:', err);
setIsAnkiConnectAvailable(false);
const errorMessage = err instanceof Error ? err.message :
(typeof err === 'object' ? JSON.stringify(err) : String(err));
setAnkiConnectionError(errorMessage);
setAnkiDeckNames([]);
setAnkiModelNames([]);
}
};
const handleAddToAnkiConnect = async () => {
if (selectedCards.size === 0) {
setError('请选择要添加的卡片');
return;
}
if (!options.deck_name.trim() || !options.note_type.trim()) {
setError('请输入牌组名称和笔记类型');
return;
}
setIsAddingToAnki(true);
setError(null);
setAnkiConnectionError(null);
try {
const selectedCardsList = Array.from(selectedCards).sort((a, b) => a - b).map(index => generatedCards[index]);
const noteIds = await invoke<(number | null)[]>('add_cards_to_anki_connect', {
selectedCards: selectedCardsList,
deckName: options.deck_name,
noteType: options.note_type
});
const successCount = noteIds.filter(id => id !== null).length;
const failCount = noteIds.length - successCount;
if (successCount > 0) {
alert(failCount > 0 ? `成功添加 ${successCount} 张卡片，${failCount} 张失败` : `成功添加 ${successCount} 张卡片到Anki！`);
setError(null);
} else {
setError('所有卡片添加失败，请检查卡片内容或Anki设置');
}
} catch (err) {
const errorMessage = err instanceof Error ? err.message :
(typeof err === 'object' ? JSON.stringify(err) : String(err));
setAnkiConnectionError(errorMessage);
setError(`添加失败: ${errorMessage}`);
} finally {
setIsAddingToAnki(false);
}
};
const handleExportByLevel = async (level: 'document' | 'task' | 'selection') => {
let cardsToExport: AnkiCard[] = [];
let exportDescription = '';
switch (level) {
case 'document':
cardsToExport = generatedCards;
exportDescription = `文档 ${currentDocumentId?.substring(0, 8)}`;
break;
case 'task':
cardsToExport = getTaskCards();
exportDescription = `任务 ${selectedTaskId?.substring(0, 8)}`;
break;
case 'selection':
cardsToExport = Array.from(selectedCards).sort((a, b) => a - b).map(index => generatedCards[index]);
exportDescription = '选中卡片';
break;
}
if (cardsToExport.length === 0 || !options.deck_name.trim() || !options.note_type.trim()) {
setError('没有可导出的卡片或未指定牌组/笔记类型');
return;
}
setIsExportingApkg(true);
setError(null);
try {
const result = await invoke<string>('export_cards_as_apkg_with_template', {
selectedCards: cardsToExport,
deckName: options.deck_name,
noteType: options.note_type,
templateId: selectedTemplate?.id || null
});
alert(`导出成功！\n${exportDescription}: ${cardsToExport.length} 张卡片\n${result}`);
setError(null);
} catch (err) {
setError(`导出失败: ${err}`);
} finally {
setIsExportingApkg(false);
}
};
const loadAnkiConnectSetting = async () => {
try {
const enabled = await invoke<string>('get_setting', { key: 'anki_connect_enabled' });
setIsAnkiConnectEnabled(enabled === 'true');
} catch (error) {
setIsAnkiConnectEnabled(false);
}
};
useEffect(() => {
loadAnkiConnectSetting();
templateManager.loadTemplates().then(() => {
setAllTemplates(templateManager.getAllTemplates());
updateToDefaultTemplate();
});
const unsubscribe = templateManager.subscribe(() => {
setAllTemplates(templateManager.getAllTemplates());
updateToDefaultTemplate();
});
let unlistenFunction: (() => void) | null = null;
listen('anki_generation_event', (event) => {
handleAnkiStreamEvent(event.payload);
}).then(unlisten => {
unlistenFunction = unlisten;
});
return () => {
unsubscribe();
if (unlistenFunction) {
unlistenFunction();
}
};
}, []);
useEffect(() => {
if (isAnkiConnectEnabled) {
const timer = setTimeout(() => checkAnkiConnectStatus(), 1000);
return () => clearTimeout(timer);
} else {
setIsAnkiConnectAvailable(null);
setAnkiConnectionError(null);
}
}, [isAnkiConnectEnabled]);
useEffect(() => {
const handleWindowFocus = () => loadAnkiConnectSetting();
const handleSettingsChange = () => loadAnkiConnectSetting();
window.addEventListener('focus', handleWindowFocus);
window.addEventListener('systemSettingsChanged', handleSettingsChange);
// 添加定期检查设置变化（作为备用机制）
const settingsCheckInterval = setInterval(() => {
loadAnkiConnectSetting();
}, 5000); // 每5秒检查一次设置（频率降低）
return () => {
window.removeEventListener('focus', handleWindowFocus);
window.removeEventListener('systemSettingsChanged', handleSettingsChange);
clearInterval(settingsCheckInterval);
};
}, []);
return (
<div style={{ width: '100%', height: '100%', overflow: 'auto', background: '#f8fafc' }}>
<div style={{ background: 'white', borderBottom: '1px solid #e5e7eb', padding: '24px 32px', position: 'relative' }}>
<div style={{ position: 'absolute', top: 0, left: 0, right: 0, height: '4px', background: 'linear-gradient(90deg, #667eea, #764ba2)' }}></div>
<div style={{ position: 'relative', zIndex: 1 }}>
<div style={{ display: 'flex', alignItems: 'center', justifyContent: 'space-between', marginBottom: '8px' }}>
<div style={{ display: 'flex', alignItems: 'center' }}>
<svg style={{ width: '32px', height: '32px', marginRight: '12px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24" strokeWidth={2}>
<rect width="20" height="14" x="2" y="5" rx="2" />
<line x1="2" x2="22" y1="10" y2="10" />
</svg>
<h1 style={{ fontSize: '28px', fontWeight: '700', margin: 0, color: '#1f2937' }}>ANKI制卡助手</h1>
</div>
<button
onClick={() => setShowPromptConfig(!showPromptConfig)}
style={{
display: 'flex',
alignItems: 'center',
gap: '8px',
padding: '8px 16px',
backgroundColor: showPromptConfig ? '#667eea' : 'transparent',
color: showPromptConfig ? 'white' : '#667eea',
border: '2px solid #667eea',
borderRadius: '8px',
cursor: 'pointer',
fontSize: '14px',
fontWeight: '500',
transition: 'all 0.2s ease'
}}
>
<Settings size={16} />
Prompt配置
</button>
</div>
<p style={{ fontSize: '16px', color: '#6b7280', margin: 0, lineHeight: '1.5' }}>
将学习资料智能转换为ANKI记忆卡片，提升记忆效率
</p>
</div>
</div>
{showPromptConfig && (
<div style={{
background: 'white',
borderBottom: '1px solid #e5e7eb',
padding: '24px 32px',
borderLeft: '4px solid #667eea'
}}>
<h3 style={{
margin: '0 0 16px 0',
fontSize: '18px',
fontWeight: '600',
color: '#1f2937',
display: 'flex',
alignItems: 'center',
gap: '8px'
}}>
<Settings size={20} />
系统Prompt配置
</h3>
<div style={{ marginBottom: '16px' }}>
<label style={{
display: 'block',
marginBottom: '8px',
fontSize: '14px',
fontWeight: '500',
color: '#374151'
}}>
自定义系统Prompt（留空使用默认设置）：
</label>
<textarea
value={systemPrompt}
onChange={(e) => setSystemPrompt(e.target.value)}
placeholder="在此输入自定义的系统prompt，这将覆盖默认的制卡指令..."
style={{
width: '100%',
minHeight: '120px',
padding: '12px',
border: '2px solid #e5e7eb',
borderRadius: '8px',
fontSize: '14px',
lineHeight: '1.5',
fontFamily: 'Monaco, Consolas, "Courier New", monospace',
resize: 'vertical',
outline: 'none',
transition: 'border-color 0.2s ease'
}}
onFocus={(e) => e.target.style.borderColor = '#667eea'}
onBlur={(e) => e.target.style.borderColor = '#e5e7eb'}
/>
<div style={{
marginTop: '8px',
fontSize: '12px',
color: '#6b7280',
display: 'flex',
alignItems: 'center',
gap: '4px'
}}>
<svg style={{ width: '14px', height: '14px', color: '#f59e0b' }} fill="currentColor" viewBox="0 0 20 20">
<path fillRule="evenodd" d="M8.257 3.099c.765-1.36 2.722-1.36 3.486 0l5.58 9.92c.75 1.334-.213 2.98-1.742 2.98H4.42c-1.53 0-2.493-1.646-1.743-2.98l5.58-9.92zM11 13a1 1 0 11-2 0 1 1 0 012 0zm-1-8a1 1 0 00-1 1v3a1 1 0 002 0V6a1 1 0 00-1-1z" clipRule="evenodd" />
</svg>
修改Prompt会影响所有生成的卡片质量和格式，请谨慎设置
</div>
</div>
<div style={{ display: 'flex', gap: '12px', alignItems: 'center' }}>
<button
onClick={() => {
setSystemPrompt('你是一个专业的ANKI学习卡片制作助手。请根据提供的学习内容，生成高质量的ANKI学习卡片。\n\n要求：\n1. 卡片应该有助于记忆和理解\n2. 问题要简洁明确\n3. 答案要准确完整\n4. 适当添加相关标签\n5. 确保卡片的逻辑性和实用性');
}}
style={{
padding: '8px 16px',
backgroundColor: '#f3f4f6',
color: '#374151',
border: '1px solid #d1d5db',
borderRadius: '6px',
cursor: 'pointer',
fontSize: '14px',
fontWeight: '500'
}}
>
恢复默认
</button>
<span style={{ fontSize: '12px', color: '#6b7280' }}>
当前字符数: {systemPrompt.length}
</span>
</div>
</div>
)}
<div className="anki-card-generation" style={{ padding: '24px', background: 'transparent' }}>
<div className="input-section">
<div className="form-group">
<label>文档上传：</label>
<div className={`upload-zone ${isDragOver ? 'drag-over' : ''} ${isProcessingFiles ? 'uploading' : ''}`} onDragOver={handleDragOver} onDragLeave={handleDragLeave} onDrop={handleDrop}>
<div className="upload-content">
<div className="upload-icon">
<svg style={{ width: '24px', height: '24px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M3 7v10a2 2 0 002 2h14a2 2 0 002-2V9a2 2 0 00-2-2h-6l-2-2H5a2 2 0 00-2 2z" />
</svg>
</div>
<div className="upload-text">{isProcessingFiles ? '处理中...' : '拖拽文件到此处或点击选择文件'}</div>
<div className="upload-hint">支持格式: PDF, DOCX, TXT, MD</div>
<input type="file" ref={fileInputRef} accept=".pdf,.docx,.txt,.md" onChange={(e) => setSelectedFiles(prev => [...prev, ...Array.from(e.target.files || [])])} style={{ display: 'none' }} id="anki-file-input" />
<label htmlFor="anki-file-input" className="btn btn-primary">选择文件</label>
</div>
{selectedFiles.length > 0 && (
<div className="selected-files">
<h4>选择的文件 ({selectedFiles.length})</h4>
<div className="file-list">
{selectedFiles.map((file, index) => (
<div key={index} className="file-item">
<span className="file-name">{file.name}</span>
<span className="file-size">{(file.size / 1024 / 1024).toFixed(2)} MB</span>
<button onClick={() => setSelectedFiles(prev => prev.filter((_, i) => i !== index))} className="btn-remove">
<svg style={{ width: '16px', height: '16px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M6 18L18 6M6 6l12 12" />
</svg>
</button>
</div>
))}
</div>
<div className="upload-actions">
<button onClick={() => { if (selectedFiles.length > 0) { processSelectedFile(selectedFiles[0]); setSelectedFiles([]); } }} disabled={isProcessingFiles || selectedFiles.length === 0} className="btn btn-success">{isProcessingFiles ? '处理中...' : '处理文件'}</button>
<button onClick={() => setSelectedFiles([])} disabled={isProcessingFiles} className="btn btn-secondary">清空</button>
</div>
</div>
)}
</div>
</div>
<div className="form-group">
<label>文档内容：</label>
<textarea value={documentContent} onChange={(e) => setDocumentContent(e.target.value)} placeholder="请输入或上传学习文档内容..." rows={8} className="form-control" />
</div>
<div className="form-group">
<label>制卡要求（可选）：</label>
<textarea value={customRequirements} onChange={(e) => setCustomRequirements(e.target.value)} placeholder="请描述您的特殊制卡要求，例如：重点关注概念定义、增加实例说明、突出重点公式、按难度分层等..." rows={4} className="form-control" style={{ fontSize: '14px', lineHeight: '1.5', border: '2px dashed #e2e8f0', borderRadius: '8px', padding: '12px', backgroundColor: '#f8fafc' }} />
<small className="form-help" style={{ color: '#64748b', fontSize: '12px', marginTop: '5px', display: 'flex', alignItems: 'center', gap: '4px' }}>
<svg style={{ width: '16px', height: '16px', color: '#fbbf24' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9.663 17h4.673M12 3v1m6.364 1.636l-.707.707M21 12h-1M4 12H3m3.343-5.657l-.707-.707m2.828 9.9a5 5 0 117.072 0l-.548.547A3.374 3.374 0 0014 18.469V19a2 2 0 11-4 0v-.531c0-.895-.356-1.754-.988-2.386l-.548-.547z" />
</svg>
提示：详细的要求有助于AI生成更符合您需求的卡片。例如："请重点制作概念定义类卡片，每个卡片包含实际应用场景"
</small>
</div>
<div className="options-section">
<h4>生成选项</h4>
<div className="template-section">
<h5>
<svg style={{ width: '20px', height: '20px', marginRight: '8px', color: '#667eea', display: 'inline-block' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M7 21a4 4 0 01-4-4V5a2 2 0 012-2h4a2 2 0 012 2v12a4 4 0 01-4 4zM21 5a2 2 0 00-2-2h-4a2 2 0 00-2 2v12a4 4 0 004 4h4a2 2 0 002-2V5z" />
</svg>
卡片模板
</h5>
<div className="unified-template-selector">
<div className="current-template-display">
<div className="current-template-card">
<div className="template-header">
<div className="template-info">
<h6 className="template-name">{selectedTemplate.name}</h6>
<p className="template-description">{selectedTemplate.description}</p>
</div>
<div className="template-actions">
<button type="button" onClick={() => setShowTemplatePreview(!showTemplatePreview)} className="btn btn-outline btn-sm">
{showTemplatePreview ? '隐藏预览' : (
<>
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M15 12a3 3 0 11-6 0 3 3 0 016 0z" />
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M2.458 12C3.732 7.943 7.523 5 12 5c4.478 0 8.268 2.943 9.542 7-1.274 4.057-5.064 7-9.542 7-4.477 0-8.268-2.943-9.542-7z" />
</svg>
预览
</>
)}
</button>
<button type="button" onClick={() => { if (onTemplateSelectionRequest) { onTemplateSelectionRequest((template: CustomAnkiTemplate) => handleTemplateSelect(template)); } else { setShowTemplateManager(true); loadAllTemplates(); } }} className="btn btn-primary btn-sm">
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M7 21a4 4 0 01-4-4V5a2 2 0 012-2h4a2 2 0 012 2v12a4 4 0 01-4 4zM21 5a2 2 0 00-2-2h-4a2 2 0 00-2 2v12a4 4 0 004 4h4a2 2 0 002-2V5z" />
</svg>
选择模板
</button>
</div>
</div>
<div className="template-quick-info">
<span className="field-count">
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z" />
</svg>
{selectedTemplate.fields.length} 个字段
</span>
<span className="note-type">
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" />
</svg>
{selectedTemplate.note_type}
</span>
</div>
</div>
</div>
{showTemplatePreview && (
<div className="template-preview-detail">
<h6>模板预览：{selectedTemplate.name}</h6>
<div className="template-info-detail">
<div className="template-description"><strong>描述：</strong>{selectedTemplate.description}</div>
<div className="template-fields-detail"><strong>包含字段：</strong><span className="field-list">{selectedTemplate.fields.map((field, index) => (<span key={field} className="field-tag">{field}{index < selectedTemplate.fields.length - 1 && ', '}</span>))}</span></div>
<div className="template-usage"><strong>适用场景：</strong>{selectedTemplate.id === 'minimal-card' && '适合快速记忆、概念复习'}{selectedTemplate.id === 'academic-card' && '适合学术学习、专业术语'}{selectedTemplate.id === 'code-card' && '适合编程学习、代码练习'}{selectedTemplate.id === 'cloze-card' && '适合主动回忆、关键词记忆'}{selectedTemplate.id === 'choice-card' && '适合理解检验、选择判断'}</div>
</div>
<div className="preview-container">
<div className="preview-card">
<div className="preview-label">正面</div>
<div className="preview-content"><IframePreview htmlContent={renderTemplatePreview(selectedTemplate.front_template, selectedTemplate)} cssContent={selectedTemplate.css_style} /></div>
</div>
<div className="preview-card">
<div className="preview-label">背面</div>
<div className="preview-content"><IframePreview htmlContent={renderTemplatePreview(selectedTemplate.back_template, selectedTemplate)} cssContent={selectedTemplate.css_style} /></div>
</div>
</div>
</div>
)}
</div>
</div>
<div className="form-row">
<div className="form-group">
<label>目标牌组：</label>
{ankiDeckNames.length > 0 ? (<select value={options.deck_name} onChange={(e) => setOptions({...options, deck_name: e.target.value})} className="form-control"><option value="">选择已有牌组或输入新牌组名</option>{ankiDeckNames.map(deckName => (<option key={deckName} value={deckName}>{deckName}</option>))}</select>) : (<input type="text" value={options.deck_name} onChange={(e) => setOptions({...options, deck_name: e.target.value})} className="form-control" placeholder="输入牌组名称（如果不存在将自动创建）" />)}
</div>
<div className="form-group">
<label>笔记类型：</label>
{ankiModelNames.length > 0 ? (<select value={options.note_type} onChange={(e) => setOptions({...options, note_type: e.target.value})} className="form-control"><option value="">选择笔记类型</option>{ankiModelNames.map(modelName => (<option key={modelName} value={modelName}>{modelName}</option>))}</select>) : (<input type="text" value={options.note_type} onChange={(e) => setOptions({...options, note_type: e.target.value})} className="form-control" placeholder="输入笔记类型（如：Basic, Cloze）" />)}
</div>
</div>
<div className="advanced-options">
<h5>AI生成参数</h5>
<div className="form-row">
<div className="form-group">
<label>最大令牌数：</label>
<input type="number" value={options.max_tokens || 4096} onChange={(e) => setOptions({...options, max_tokens: parseInt(e.target.value) || 4096})} className="form-control" min="512" max="8192" step="256" placeholder="4096" />
<small className="form-help">控制AI生成文本的长度（512-8192）</small>
</div>
<div className="form-group">
<label>创造性温度：</label>
<input type="number" value={options.temperature || 0.3} onChange={(e) => setOptions({...options, temperature: parseFloat(e.target.value) || 0.3})} className="form-control" min="0" max="1" step="0.1" placeholder="0.3" />
<small className="form-help">控制AI回答的创造性（0-1，数值越低越保守）</small>
</div>
<div className="form-group">
<label>每个主题最大卡片数：</label>
<input type="number" value={options.max_cards_per_mistake} onChange={(e) => setOptions({...options, max_cards_per_mistake: parseInt(e.target.value) || 5})} className="form-control" min="1" max="99" placeholder="5" />
<small className="form-help">每个知识点生成的卡片数量</small>
</div>
<div className="form-group">
<label>任务重叠区域大小：</label>
<input
type="number"
value={options.segment_overlap_size}
onChange={(e) => setOptions({...options, segment_overlap_size: parseInt(e.target.value) || 200})}
className="form-control"
min="0"
max="1000"
placeholder="200"
title="分段间重叠字符数，防止知识点在分段边界被切断，推荐设置200-400字符"
/>
<small className="form-help">重叠字符数（推荐200-400）</small>
</div>
</div>
</div>
</div>
<button onClick={generateCards} disabled={isGenerating || !documentContent} className="btn btn-primary">{isGenerating ? '正在生成...' : '生成ANKI卡片'}</button>
{isAnkiConnectEnabled && (
<div className="anki-status" style={{ marginTop: '20px', padding: '15px', backgroundColor: '#f8f9fa', borderRadius: '8px', border: '1px solid #e9ecef' }}>
<div className="status-indicator">
<span className="status-label">AnkiConnect状态：</span>
{isAnkiConnectAvailable === null ? (
<span className="status-checking" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<svg style={{ width: '16px', height: '16px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M21 21l-6-6m2-5a7 7 0 11-14 0 7 7 0 0114 0z" />
</svg>
检查中...
</span>
) : isAnkiConnectAvailable ? (
<span className="status-available" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<svg style={{ width: '16px', height: '16px', color: '#10b981' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M5 13l4 4L19 7" />
</svg>
已连接
</span>
) : (
<span className="status-unavailable" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<svg style={{ width: '16px', height: '16px', color: '#f59e0b' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 9v2m0 4h.01m-6.938 4h13.856c1.54 0 2.502-1.667 1.732-2.5L13.732 4c-.77-.833-1.964-.833-2.732 0L3.34 16.5c-.77.833.192 2.5 1.732 2.5z" />
</svg>
未连接
</span>
)}
<button onClick={checkAnkiConnectStatus} className="btn btn-sm btn-secondary" style={{ marginLeft: '10px' }} disabled={isAnkiConnectAvailable === null}>{isAnkiConnectAvailable === null ? '检查中...' : '重新检查'}</button>
</div>
{ankiConnectionError && !isAnkiConnectAvailable && (
<div className="connection-error" style={{ backgroundColor: '#fff3cd', border: '1px solid #ffeaa7', padding: '12px', borderRadius: '8px', marginTop: '12px', fontSize: '0.9em' }}>
<div style={{ color: '#856404', fontWeight: 'bold', marginBottom: '8px' }}>
<div style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<svg style={{ width: '16px', height: '16px', color: '#f59e0b' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 9v2m0 4h.01m-6.938 4h13.856c1.54 0 2.502-1.667 1.732-2.5L13.732 4c-.77-.833-1.964-.833-2.732 0L3.34 16.5c-.77.833.192 2.5 1.732 2.5z" />
</svg>
AnkiConnect 连接失败: {ankiConnectionError}
</div>
</div>
<div style={{ marginTop: '0.5rem', fontSize: '0.8rem', color: '#6c757d' }}>
如果只想导出 .apkg 文件手动导入，可以忽略此错误。
</div>
</div>
)}
</div>
)}
</div>
{error && (
<div className="error-message">
<span className="error-icon">
<svg style={{ width: '20px', height: '20px', color: '#f59e0b' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 9v2m0 4h.01m-6.938 4h13.856c1.54 0 2.502-1.667 1.732-2.5L13.732 4c-.77-.833-1.964-.833-2.732 0L3.34 16.5c-.77.833.192 2.5 1.732 2.5z" />
</svg>
</span>
<span className="error-text">{error}</span>
</div>
)}
{(isGenerating || isAddingToAnki || isExportingApkg) && (<div className="loading-indicator"><div className="loading-spinner"></div><span className="loading-text">{isGenerating && (<div className="generation-status"><div className="status-main">正在生成ANKI卡片...</div>{currentDocumentId && (<div className="status-detail">文档ID: {currentDocumentId.substring(0, 8)}...{documentTasks.length > 0 && ` | ${documentTasks.length} 个任务`}{generatedCards.length > 0 && ` | ${generatedCards.length} 张卡片已生成`}</div>)}</div>)}{isAddingToAnki && '正在添加到Anki...'}{isExportingApkg && '正在导出.apkg文件...'}</span></div>)}
{currentDocumentId && (
<div className="document-processing-status">
<h3 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<svg style={{ width: '24px', height: '24px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" />
</svg>
文档处理状态
</h3>
<div className="document-info">
<span>文档ID: {currentDocumentId.substring(0, 8)}...</span>
<span>任务数量: {documentTasks.length}</span>
{generatedCards.length > 0 && (<><span>总卡片: {generatedCards.length}</span>{generatedCards.filter((card: any) => card.is_error_card).length > 0 && (<span className="error-summary">错误: {generatedCards.filter((card: any) => card.is_error_card).length}</span>)}</>)}
{documentTasks.filter(t => t.status === 'completed').length === documentTasks.length && documentTasks.length > 0 && !isGenerating && (
<span className="completion-indicator" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<CheckCircle size={16} color="green" />
全部完成
</span>
)}
</div>
{documentTasks.length > 0 && (
<div className="tasks-list">
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<BookOpen size={20} />
任务列表
</h4>
{documentTasks.map(task => (
<div key={task.task_id} className={`task-item ${selectedTaskId === task.task_id ? 'selected' : ''}`} onClick={() => setSelectedTaskId(task.task_id)}>
<div className="task-header">
<span className="task-id">任务 {task.task_id.substring(0, 8)}</span>
<div className="task-status-info">
<span className={`task-status status-${task.status}`}>
{task.status === 'pending' && (
<span style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<Clock size={14} />
等待中
</span>
)}
{task.status === 'processing' && (
<span style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<RefreshCcw size={14} />
处理中
</span>
)}
{task.status === 'completed' && (
<span style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<CheckCircle size={14} color="green" />
已完成
</span>
)}
{task.status === 'failed' && (
<span style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<X size={14} color="red" />
失败
</span>
)}
{task.status === 'truncated' && (
<span style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<AlertTriangle size={14} color="orange" />
已截断
</span>
)}
</span>
{task.cards.some((card: any) => card.is_error_card) && (
<span className="error-indicator" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<AlertTriangle size={14} color="orange" />
{task.cards.filter((card: any) => card.is_error_card).length} 个错误
</span>
)}
</div>
</div>
{task.content_preview && (<div className="task-preview">{task.content_preview}</div>)}
{task.status === 'failed' && task.error_message && (<div className="task-error-message" style={{ color: 'red', fontSize: '0.9em', marginTop: '5px', whiteSpace: 'pre-wrap' }}>错误详情: {task.error_message}</div>)}
<div className="task-progress">
<div className="progress-bar"><div className="progress-fill" style={{ width: `${task.progress}%` }} /></div>
<span className="progress-text">{task.progress}% - {task.cards.length} 张卡片{task.cards.filter((card: any) => card.is_error_card).length > 0 && (<span className="error-count">({task.cards.filter((card: any) => card.is_error_card).length} 错误)</span>)}</span>
</div>
</div>
))}
</div>
)}
</div>
)}
{generatedCards.length > 0 && (
<div className="cards-preview">
<div className="cards-header">
<h3>{selectedTaskId ? `任务 ${selectedTaskId.substring(0, 8)} 的卡片 (${getTaskCards().length}张)` : `全部卡片 (${generatedCards.length}张)`}</h3>
<div className="card-controls">
{selectedTaskId && (<button onClick={() => setSelectedTaskId(null)} className="btn btn-outline btn-sm">显示全部卡片</button>)}
<button onClick={toggleSelectAll} className="btn btn-secondary">{selectedCards.size === getCurrentDisplayCards().length ? '取消全选' : '全选'}</button>
<span className="selected-count">已选择: {selectedCards.size}/{getCurrentDisplayCards().length}</span>
</div>
</div>
<div className="cards-list">
{getCurrentDisplayCards().map((card: any, localIndex: number) => {
const globalIndex = getCardGlobalIndex(localIndex);
return (
<div key={`${selectedTaskId || 'all'}-${localIndex}`} className={`card-item ${selectedCards.has(globalIndex) ? 'selected' : ''} ${(card as any).is_error_card ? 'error-card' : ''}`}>
<div className="card-header">
<input type="checkbox" checked={selectedCards.has(globalIndex)} onChange={() => toggleCardSelection(globalIndex)} />
<span className="card-number">
{(card as any).is_error_card ? (
<span style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<AlertTriangle size={16} color="orange" />
错误卡片
</span>
) : (
`卡片 ${selectedTaskId ? localIndex + 1 : globalIndex + 1}`
)}
</span>
<button onClick={() => deleteCard(globalIndex)} className="btn btn-danger btn-sm">删除</button>
</div>
{(card as any).is_error_card && (card as any).error_content && (<div className="error-content"><label>错误原因：</label><div className="error-text">{(card as any).error_content}</div></div>)}
<div className="card-content">
{selectedTemplate.note_type === 'Cloze' ? (
<>
<div className="card-field">
<label>填空题文本：</label>
<textarea value={card.text || card.front || ''} onChange={(e) => editCard(globalIndex, 'text', e.target.value)} rows={4} className="form-control" placeholder="包含填空标记的文本，如：定律公式是 F = {{c1::ma}}" />
<small className="form-help">使用{`{{c1::答案}}`}、{`{{c2::答案}}`}等格式标记填空部分</small>
</div>
<div className="card-field">
<label>预览效果：</label>
<div className="cloze-preview" dangerouslySetInnerHTML={{ __html: renderClozeText(card.text || card.front || '') }} />
</div>
</>
) : (
<>
<div className="card-field">
<label>正面（问题）：</label>
<textarea value={card.front} onChange={(e) => editCard(globalIndex, 'front', e.target.value)} rows={2} className="form-control" />
</div>
<div className="card-field">
<label>背面（答案）：</label>
<textarea value={card.back} onChange={(e) => editCard(globalIndex, 'back', e.target.value)} rows={3} className="form-control" />
</div>
</>
)}
<div className="card-field">
<label>标签：</label>
<div className="tags">{card.tags.map((tag: string, tagIndex: number) => (<span key={tagIndex} className="tag">{tag}</span>))}</div>
</div>
</div>
</div>
);
})}
</div>
<div className="output-actions">
<div className="export-options">
<h5 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Upload size={20} />
导出选项
</h5>
<div className="export-buttons">
{currentDocumentId && (<button className="btn btn-success btn-sm" disabled={generatedCards.length === 0 || isExportingApkg} onClick={() => handleExportByLevel('document')}>导出整个文档 ({generatedCards.length}张)</button>)}
{selectedTaskId && (<button className="btn btn-success btn-sm" disabled={getTaskCards().length === 0 || isExportingApkg} onClick={() => handleExportByLevel('task')}>导出当前任务 ({getTaskCards().length}张)</button>)}
<button className="btn btn-success btn-sm" disabled={selectedCards.size === 0 || isExportingApkg} onClick={() => handleExportByLevel('selection')}>导出选中卡片 ({selectedCards.size}张)</button>
</div>
</div>
{isAnkiConnectEnabled && (
<div className="anki-connect-actions">
<h5 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Settings size={20} />
AnkiConnect
</h5>
<button className="btn btn-info" disabled={selectedCards.size === 0 || isAddingToAnki || !isAnkiConnectAvailable} onClick={handleAddToAnkiConnect} title={!isAnkiConnectAvailable ? "请确保Anki桌面程序正在运行并启用了AnkiConnect插件" : ""}>{isAddingToAnki ? '添加中...' : `添加到Anki (${selectedCards.size}张)`}</button>
</div>
)}
</div>
</div>
)}
</div>
{showTemplateManager && (<TemplateManager onClose={() => setShowTemplateManager(false)} onSelectTemplate={(template) => { handleTemplateSelect(template); setShowTemplateManager(false); }} />)}
<style dangerouslySetInnerHTML={{ __html: `.cloze-highlight { background: #FFD700; color: #2c3e50; padding: 2px 8px; border-radius: 6px; font-weight: 600; box-shadow: 0 2px 4px rgba(0,0,0,0.2); } .cloze-preview { padding: 12px; background: #f8fafc; border-radius: 8px; border: 1px solid #e2e8f0; line-height: 1.6; font-size: 14px; }` }} />
</div>
);
};
export default AnkiCardGeneration;
|
0015/StickiNote
| 1,181,912 |
main/ui_resources/notes.c
|
#ifdef __has_include
#if __has_include("lvgl.h")
#ifndef LV_LVGL_H_INCLUDE_SIMPLE
#define LV_LVGL_H_INCLUDE_SIMPLE
#endif
#endif
#endif
#if defined(LV_LVGL_H_INCLUDE_SIMPLE)
#include "lvgl.h"
#else
#include "lvgl/lvgl.h"
#endif
#ifndef LV_ATTRIBUTE_MEM_ALIGN
#define LV_ATTRIBUTE_MEM_ALIGN
#endif
#ifndef LV_ATTRIBUTE_IMAGE_NOTES
#define LV_ATTRIBUTE_IMAGE_NOTES
#endif
const LV_ATTRIBUTE_MEM_ALIGN LV_ATTRIBUTE_LARGE_CONST LV_ATTRIBUTE_IMAGE_NOTES uint8_t notes_map[] = {
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};
const lv_image_dsc_t notes = {
.header.cf = LV_COLOR_FORMAT_RGB565A8,
.header.magic = LV_IMAGE_HEADER_MAGIC,
.header.w = 256,
.header.h = 256,
.data_size = 65536 * 3,
.data = notes_map,
};
|
000haoji/deep-student
| 1,644 |
src/components/ModernSelect.css
|
.modern-select {
position: relative;
font-size: 0.9rem;
user-select: none;
}
.modern-select.full-width {
width: 100%;
}
.select-trigger {
width: 100%;
display: flex;
align-items: center;
justify-content: space-between;
gap: 0.5rem;
padding: 0.75rem 1rem;
border: 2px solid #e2e8f0;
border-radius: 10px;
background: #f9fafb;
font-weight: 500;
color: #2d3748;
cursor: pointer;
transition: all 0.2s ease;
}
.select-trigger:hover {
border-color: #667eea;
}
.select-trigger:focus-visible {
outline: none;
border-color: #667eea;
box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.15);
}
.select-trigger .arrow {
font-size: 0.75rem;
color: #667eea;
transition: transform 0.2s ease;
}
.modern-select.open .arrow {
transform: rotate(180deg);
}
.options-list {
position: absolute;
top: calc(100% + 4px);
left: 0;
width: 100%;
max-height: 240px;
overflow-y: auto;
background: #ffffff;
border: 2px solid #e2e8f0;
border-radius: 12px;
box-shadow: 0 8px 24px rgba(0, 0, 0, 0.08);
z-index: 1000;
padding: 0.25rem 0;
animation: fadeInScale 0.15s ease;
}
@keyframes fadeInScale {
0% {
opacity: 0;
transform: scale(0.95);
}
100% {
opacity: 1;
transform: scale(1);
}
}
.options-list li {
padding: 0.625rem 1rem;
cursor: pointer;
transition: background 0.15s ease, color 0.15s ease;
white-space: nowrap;
}
.options-list li:hover {
background: #f0f4ff;
color: #4c51bf;
}
.options-list li.selected {
background: #667eea;
color: #ffffff;
}
.modern-select.disabled .select-trigger {
background: #edf2f7;
cursor: not-allowed;
opacity: 0.6;
}
|
0000cd/wolf-set
| 13,749 |
themes/bluf/static/css/glightbox.min.css
|
.glightbox-container{width:100%;height:100%;position:fixed;top:0;left:0;z-index:999999!important;overflow:hidden;-ms-touch-action:none;touch-action:none;-webkit-text-size-adjust:100%;-moz-text-size-adjust:100%;-ms-text-size-adjust:100%;text-size-adjust:100%;-webkit-backface-visibility:hidden;backface-visibility:hidden;outline:0}.glightbox-container.inactive{display:none}.glightbox-container .gcontainer{position:relative;width:100%;height:100%;z-index:9999;overflow:hidden}.glightbox-container .gslider{-webkit-transition:-webkit-transform .4s ease;transition:-webkit-transform .4s ease;transition:transform .4s ease;transition:transform .4s ease,-webkit-transform .4s ease;height:100%;left:0;top:0;width:100%;position:relative;overflow:hidden;display:-webkit-box!important;display:-ms-flexbox!important;display:flex!important;-webkit-box-pack:center;-ms-flex-pack:center;justify-content:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0)}.glightbox-container .gslide{width:100%;position:absolute;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;display:-webkit-box;display:-ms-flexbox;display:flex;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:center;-ms-flex-pack:center;justify-content:center;opacity:0}.glightbox-container .gslide.current{opacity:1;z-index:99999;position:relative}.glightbox-container .gslide.prev{opacity:1;z-index:9999}.glightbox-container .gslide-inner-content{width:100%}.glightbox-container .ginner-container{position:relative;width:100%;display:-webkit-box;display:-ms-flexbox;display:flex;-webkit-box-pack:center;-ms-flex-pack:center;justify-content:center;-webkit-box-orient:vertical;-webkit-box-direction:normal;-ms-flex-direction:column;flex-direction:column;max-width:100%;margin:auto;height:100vh}.glightbox-container .ginner-container.gvideo-container{width:100%}.glightbox-container .ginner-container.desc-bottom,.glightbox-container .ginner-container.desc-top{-webkit-box-orient:vertical;-webkit-box-direction:normal;-ms-flex-direction:column;flex-direction:column}.glightbox-container .ginner-container.desc-left,.glightbox-container .ginner-container.desc-right{max-width:100%!important}.gslide iframe,.gslide video{outline:0!important;border:none;min-height:165px;-webkit-overflow-scrolling:touch;-ms-touch-action:auto;touch-action:auto}.gslide:not(.current){pointer-events:none}.gslide-image{-webkit-box-align:center;-ms-flex-align:center;align-items:center}.gslide-image img{max-height:100vh;display:block;padding:0;float:none;outline:0;border:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;max-width:100vw;width:auto;height:auto;-o-object-fit:cover;object-fit:cover;-ms-touch-action:none;touch-action:none;margin:auto;min-width:200px}.desc-bottom .gslide-image img,.desc-top .gslide-image img{width:auto}.desc-left .gslide-image img,.desc-right .gslide-image img{width:auto;max-width:100%}.gslide-image img.zoomable{position:relative}.gslide-image img.dragging{cursor:-webkit-grabbing!important;cursor:grabbing!important;-webkit-transition:none;transition:none}.gslide-video{position:relative;max-width:100vh;width:100%!important}.gslide-video .plyr__poster-enabled.plyr--loading .plyr__poster{display:none}.gslide-video .gvideo-wrapper{width:100%;margin:auto}.gslide-video::before{content:'';position:absolute;width:100%;height:100%;background:rgba(255,0,0,.34);display:none}.gslide-video.playing::before{display:none}.gslide-video.fullscreen{max-width:100%!important;min-width:100%;height:75vh}.gslide-video.fullscreen video{max-width:100%!important;width:100%!important}.gslide-inline{background:#fff;text-align:left;max-height:calc(100vh - 40px);overflow:auto;max-width:100%;margin:auto}.gslide-inline .ginlined-content{padding:20px;width:100%}.gslide-inline .dragging{cursor:-webkit-grabbing!important;cursor:grabbing!important;-webkit-transition:none;transition:none}.ginlined-content{overflow:auto;display:block!important;opacity:1}.gslide-external{display:-webkit-box;display:-ms-flexbox;display:flex;width:100%;min-width:100%;background:#fff;padding:0;overflow:auto;max-height:75vh;height:100%}.gslide-media{display:-webkit-box;display:-ms-flexbox;display:flex;width:auto}.zoomed .gslide-media{-webkit-box-shadow:none!important;box-shadow:none!important}.desc-bottom .gslide-media,.desc-top .gslide-media{margin:0 auto;-webkit-box-orient:vertical;-webkit-box-direction:normal;-ms-flex-direction:column;flex-direction:column}.gslide-description{position:relative;-webkit-box-flex:1;-ms-flex:1 0 100%;flex:1 0 100%}.gslide-description.description-left,.gslide-description.description-right{max-width:100%}.gslide-description.description-bottom,.gslide-description.description-top{margin:0 auto;width:100%}.gslide-description p{margin-bottom:12px}.gslide-description p:last-child{margin-bottom:0}.zoomed .gslide-description{display:none}.glightbox-button-hidden{display:none}.glightbox-mobile .glightbox-container .gslide-description{height:auto!important;width:100%;position:absolute;bottom:0;padding:19px 11px;max-width:100vw!important;-webkit-box-ordinal-group:3!important;-ms-flex-order:2!important;order:2!important;max-height:78vh;overflow:auto!important;background:-webkit-gradient(linear,left top,left bottom,from(rgba(0,0,0,0)),to(rgba(0,0,0,.75)));background:linear-gradient(to bottom,rgba(0,0,0,0) 0,rgba(0,0,0,.75) 100%);-webkit-transition:opacity .3s linear;transition:opacity .3s linear;padding-bottom:50px}.glightbox-mobile .glightbox-container .gslide-title{color:#fff;font-size:1em}.glightbox-mobile .glightbox-container .gslide-desc{color:#a1a1a1}.glightbox-mobile .glightbox-container .gslide-desc a{color:#fff;font-weight:700}.glightbox-mobile .glightbox-container .gslide-desc *{color:inherit}.glightbox-mobile .glightbox-container .gslide-desc .desc-more{color:#fff;opacity:.4}.gdesc-open .gslide-media{-webkit-transition:opacity .5s ease;transition:opacity .5s ease;opacity:.4}.gdesc-open .gdesc-inner{padding-bottom:30px}.gdesc-closed .gslide-media{-webkit-transition:opacity .5s ease;transition:opacity .5s ease;opacity:1}.greset{-webkit-transition:all .3s ease;transition:all .3s ease}.gabsolute{position:absolute}.grelative{position:relative}.glightbox-desc{display:none!important}.glightbox-open{overflow:hidden}.gloader{height:25px;width:25px;-webkit-animation:lightboxLoader .8s infinite linear;animation:lightboxLoader .8s infinite linear;border:2px solid #fff;border-right-color:transparent;border-radius:50%;position:absolute;display:block;z-index:9999;left:0;right:0;margin:0 auto;top:47%}.goverlay{width:100%;height:calc(100vh + 1px);position:fixed;top:-1px;left:0;background:#000;will-change:opacity}.glightbox-mobile .goverlay{background:#000}.gclose,.gnext,.gprev{z-index:99999;cursor:pointer;width:26px;height:44px;border:none;display:-webkit-box;display:-ms-flexbox;display:flex;-webkit-box-pack:center;-ms-flex-pack:center;justify-content:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-orient:vertical;-webkit-box-direction:normal;-ms-flex-direction:column;flex-direction:column}.gclose svg,.gnext svg,.gprev svg{display:block;width:25px;height:auto;margin:0;padding:0}.gclose.disabled,.gnext.disabled,.gprev.disabled{opacity:.1}.gclose .garrow,.gnext .garrow,.gprev .garrow{stroke:#fff}.gbtn.focused{outline:2px solid #0f3d81}iframe.wait-autoplay{opacity:0}.glightbox-closing .gclose,.glightbox-closing .gnext,.glightbox-closing .gprev{opacity:0!important}.glightbox-clean .gslide-description{background:#fff}.glightbox-clean .gdesc-inner{padding:22px 20px}.glightbox-clean .gslide-title{font-size:1em;font-weight:400;font-family:arial;color:#000;margin-bottom:19px;line-height:1.4em}.glightbox-clean .gslide-desc{font-size:.86em;margin-bottom:0;font-family:arial;line-height:1.4em}.glightbox-clean .gslide-video{background:#000}.glightbox-clean .gclose,.glightbox-clean .gnext,.glightbox-clean .gprev{background-color:rgba(0,0,0,.75);border-radius:4px}.glightbox-clean .gclose path,.glightbox-clean .gnext path,.glightbox-clean .gprev path{fill:#fff}.glightbox-clean .gprev{position:absolute;top:-100%;left:30px;width:40px;height:50px}.glightbox-clean .gnext{position:absolute;top:-100%;right:30px;width:40px;height:50px}.glightbox-clean .gclose{width:35px;height:35px;top:15px;right:10px;position:absolute}.glightbox-clean .gclose svg{width:18px;height:auto}.glightbox-clean .gclose:hover{opacity:1}.gfadeIn{-webkit-animation:gfadeIn .5s ease;animation:gfadeIn .5s ease}.gfadeOut{-webkit-animation:gfadeOut .5s ease;animation:gfadeOut .5s ease}.gslideOutLeft{-webkit-animation:gslideOutLeft .3s ease;animation:gslideOutLeft .3s ease}.gslideInLeft{-webkit-animation:gslideInLeft .3s ease;animation:gslideInLeft .3s ease}.gslideOutRight{-webkit-animation:gslideOutRight .3s ease;animation:gslideOutRight .3s ease}.gslideInRight{-webkit-animation:gslideInRight .3s ease;animation:gslideInRight .3s ease}.gzoomIn{-webkit-animation:gzoomIn .5s ease;animation:gzoomIn .5s ease}.gzoomOut{-webkit-animation:gzoomOut .5s ease;animation:gzoomOut .5s ease}@-webkit-keyframes lightboxLoader{0%{-webkit-transform:rotate(0);transform:rotate(0)}100%{-webkit-transform:rotate(360deg);transform:rotate(360deg)}}@keyframes lightboxLoader{0%{-webkit-transform:rotate(0);transform:rotate(0)}100%{-webkit-transform:rotate(360deg);transform:rotate(360deg)}}@-webkit-keyframes gfadeIn{from{opacity:0}to{opacity:1}}@keyframes gfadeIn{from{opacity:0}to{opacity:1}}@-webkit-keyframes gfadeOut{from{opacity:1}to{opacity:0}}@keyframes gfadeOut{from{opacity:1}to{opacity:0}}@-webkit-keyframes gslideInLeft{from{opacity:0;-webkit-transform:translate3d(-60%,0,0);transform:translate3d(-60%,0,0)}to{visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0);opacity:1}}@keyframes gslideInLeft{from{opacity:0;-webkit-transform:translate3d(-60%,0,0);transform:translate3d(-60%,0,0)}to{visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0);opacity:1}}@-webkit-keyframes gslideOutLeft{from{opacity:1;visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0)}to{-webkit-transform:translate3d(-60%,0,0);transform:translate3d(-60%,0,0);opacity:0;visibility:hidden}}@keyframes gslideOutLeft{from{opacity:1;visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0)}to{-webkit-transform:translate3d(-60%,0,0);transform:translate3d(-60%,0,0);opacity:0;visibility:hidden}}@-webkit-keyframes gslideInRight{from{opacity:0;visibility:visible;-webkit-transform:translate3d(60%,0,0);transform:translate3d(60%,0,0)}to{-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0);opacity:1}}@keyframes gslideInRight{from{opacity:0;visibility:visible;-webkit-transform:translate3d(60%,0,0);transform:translate3d(60%,0,0)}to{-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0);opacity:1}}@-webkit-keyframes gslideOutRight{from{opacity:1;visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0)}to{-webkit-transform:translate3d(60%,0,0);transform:translate3d(60%,0,0);opacity:0}}@keyframes gslideOutRight{from{opacity:1;visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0)}to{-webkit-transform:translate3d(60%,0,0);transform:translate3d(60%,0,0);opacity:0}}@-webkit-keyframes gzoomIn{from{opacity:0;-webkit-transform:scale3d(.3,.3,.3);transform:scale3d(.3,.3,.3)}to{opacity:1}}@keyframes gzoomIn{from{opacity:0;-webkit-transform:scale3d(.3,.3,.3);transform:scale3d(.3,.3,.3)}to{opacity:1}}@-webkit-keyframes gzoomOut{from{opacity:1}50%{opacity:0;-webkit-transform:scale3d(.3,.3,.3);transform:scale3d(.3,.3,.3)}to{opacity:0}}@keyframes gzoomOut{from{opacity:1}50%{opacity:0;-webkit-transform:scale3d(.3,.3,.3);transform:scale3d(.3,.3,.3)}to{opacity:0}}@media (min-width:769px){.glightbox-container .ginner-container{width:auto;height:auto;-webkit-box-orient:horizontal;-webkit-box-direction:normal;-ms-flex-direction:row;flex-direction:row}.glightbox-container .ginner-container.desc-top .gslide-description{-webkit-box-ordinal-group:1;-ms-flex-order:0;order:0}.glightbox-container .ginner-container.desc-top .gslide-image,.glightbox-container .ginner-container.desc-top .gslide-image img{-webkit-box-ordinal-group:2;-ms-flex-order:1;order:1}.glightbox-container .ginner-container.desc-left .gslide-description{-webkit-box-ordinal-group:1;-ms-flex-order:0;order:0}.glightbox-container .ginner-container.desc-left .gslide-image{-webkit-box-ordinal-group:2;-ms-flex-order:1;order:1}.gslide-image img{max-height:97vh;max-width:100%}.gslide-image img.zoomable{cursor:-webkit-zoom-in;cursor:zoom-in}.zoomed .gslide-image img.zoomable{cursor:-webkit-grab;cursor:grab}.gslide-inline{max-height:95vh}.gslide-external{max-height:100vh}.gslide-description.description-left,.gslide-description.description-right{max-width:275px}.glightbox-open{height:auto}.goverlay{background:rgba(0,0,0,.92)}.glightbox-clean .gslide-media{-webkit-box-shadow:1px 2px 9px 0 rgba(0,0,0,.65);box-shadow:1px 2px 9px 0 rgba(0,0,0,.65)}.glightbox-clean .description-left .gdesc-inner,.glightbox-clean .description-right .gdesc-inner{position:absolute;height:100%;overflow-y:auto}.glightbox-clean .gclose,.glightbox-clean .gnext,.glightbox-clean .gprev{background-color:rgba(0,0,0,.32)}.glightbox-clean .gclose:hover,.glightbox-clean .gnext:hover,.glightbox-clean .gprev:hover{background-color:rgba(0,0,0,.7)}.glightbox-clean .gprev{top:45%}.glightbox-clean .gnext{top:45%}}@media (min-width:992px){.glightbox-clean .gclose{opacity:.7;right:20px}}@media screen and (max-height:420px){.goverlay{background:#000}}
|
0000cd/wolf-set
| 10,402 |
themes/bluf/assets/js/script.new.js
|
// Isotope
let buttonFilters = {};
// Update all buttons matching the filter
function updateButtons(filterValue, isAdd) {
// Select all buttons that match the filter value
const buttons = document.querySelectorAll(`.filter-btn[data-filter="${filterValue}"]`);
// Update class for all matching buttons
buttons.forEach(function (button) {
if (isAdd) {
button.classList.add('is-checked');
} else {
button.classList.remove('is-checked');
}
});
}
// Flatten object into a string of filters
function concatValues(obj) {
let value = '';
for (const prop in obj) {
value += obj[prop].join('');
}
return value;
}
// initialize Isotope
const grid = document.querySelector('.grid');
const iso = new Isotope(grid, {
itemSelector: '.grid-item',
masonry: {
columnWidth: 255,
fitWidth: true,
gutter: 16,
}
});
// // navbar menu
// document.addEventListener('click', function (event) {
// // 获取所有菜单
// const menuGroups = document.querySelectorAll('.filter-button-group'); // 监听.filter-button-group 按钮
// const isMenuToggle = event.target.matches('.menu-toggle');
// // 如果点击的是菜单触发按钮
// if (isMenuToggle) {
// const toggleId = event.target.id;
// const filterGroupId = 'filter-group-' + toggleId.split('-')[2];
// const filterGroup = document.getElementById(filterGroupId);
// // 如果当前菜单未展开，则关闭所有菜单，并展开当前点击的菜单
// if (!filterGroup.classList.contains('active')) {
// // 关闭所有菜单
// menuGroups.forEach(function (menu) {
// menu.classList.remove('active');
// });
// // 展开点击的菜单
// filterGroup.classList.add('active');
// } else {
// // 如果当前菜单已展开，再次点击则关闭
// filterGroup.classList.remove('active');
// }
// } else {
// // 如果点击的不是菜单触发按钮
// // 检查点击是否发生在已展开的菜单内部
// const isInsideMenu = Array.from(menuGroups).some(function (menu) {
// return menu.contains(event.target);
// });
// // 如果点击的不是菜单内部，关闭所有菜单
// if (!isInsideMenu) {
// menuGroups.forEach(function (menu) {
// menu.classList.remove('active');
// });
// }
// }
// });
document.addEventListener('click', function (event) {
// 获取所有菜单
const menuGroups = document.querySelectorAll('.filter-button-group');
// 检查ID是否包含menu-toggle
const isMenuToggle = event.target?.id?.includes('menu-toggle');
// 如果点击的是菜单触发按钮
if (isMenuToggle) {
const toggleId = event.target.id;
const filterGroupId = 'filter-group-' + toggleId.split('-')[2];
const filterGroup = document.getElementById(filterGroupId);
// 如果当前菜单未展开，则关闭所有菜单，并展开当前点击的菜单
if (!filterGroup.classList.contains('active')) {
// 关闭所有菜单
menuGroups.forEach(function (menu) {
menu.classList.remove('active');
});
// 展开点击的菜单
filterGroup.classList.add('active');
} else {
// 如果当前菜单已展开，再次点击则关闭
filterGroup.classList.remove('active');
}
} else {
// 如果点击的不是菜单触发按钮
// 检查点击是否发生在已展开的菜单内部
const isInsideMenu = Array.from(menuGroups).some(function (menu) {
return menu.contains(event.target);
});
// 如果点击的不是菜单内部，关闭所有菜单
if (!isInsideMenu) {
menuGroups.forEach(function (menu) {
menu.classList.remove('active');
});
}
}
});
// Handle lazy-loading images
const lazyImages = document.querySelectorAll('img[loading="lazy"]');
lazyImages.forEach((img) => {
img.addEventListener('load', () => {
iso.layout(); // Trigger re-layout after each lazy-loaded image loads
});
});
// // use imagesLoaded, trigger layout after each image loads
// imagesLoaded(grid).on('progress', function (instance, image) {
// iso.layout();
// });
// // Sync top-bar-inner width with grid width
// const topBarElement = document.querySelector('.top-bar-inner');
// if (grid && topBarElement) {
// const resizeObserver = new ResizeObserver((entries) => {
// for (let entry of entries) {
// const windowWidth = window.innerWidth;
// const minWidth = windowWidth * 0.80;
// const newWidth = Math.max(entry.contentRect.width, minWidth);
// topBarElement.style.width = newWidth + 'px';
// }
// });
// resizeObserver.observe(grid);
// } else {
// console.error('Grid or top-bar-inner element not found!');
// }
const topBarElement = document.querySelector('.top-bar-inner');
let shouldIgnoreResize = false;
// 添加按钮事件监听
document.querySelectorAll('.filter-btn').forEach(btn => {
btn.addEventListener('click', () => {
shouldIgnoreResize = true;
setTimeout(() => {
shouldIgnoreResize = false;
}, 1000); // 1秒后恢复监听
});
});
if (grid && topBarElement) {
const resizeObserver = new ResizeObserver((entries) => {
// 如果在忽略期间,直接返回
if (shouldIgnoreResize) {
// console.log(`[${new Date().toLocaleString()}] Resize ignored due to filter button click`);
return;
}
for (let entry of entries) {
const windowWidth = window.innerWidth;
const minWidth = windowWidth * 0.80;
const newWidth = Math.max(entry.contentRect.width, minWidth);
topBarElement.style.width = newWidth + 'px';
// console.log(
// `[${new Date().toLocaleString()}] Top bar width changed:\n`,
// `Window width: ${windowWidth}px\n`,
// `Min width: ${minWidth}px\n`,
// `Grid width: ${entry.contentRect.width}px\n`,
// `New width set to: ${newWidth}px\n`,
// `Reason: ${entry.contentRect.width >= minWidth ? 'Grid width larger than minimum' : 'Using minimum width'}`
// );
}
});
resizeObserver.observe(grid);
} else {
console.error('Grid or top-bar-inner element not found!');
}
// Use event delegation for all filter button groups
document.querySelectorAll('.filter-button-group').forEach(function (group) {
group.addEventListener('click', function (event) {
if (!event.target.matches('.filter-btn')) {
return; // Skip clicks that are not on buttons
}
const filterValue = event.target.getAttribute('data-filter');
const filterGroup = event.target.getAttribute('data-filter-group');
// Check if filter is already in the buttonFilters
const isFilterActive = buttonFilters[filterGroup]?.includes(filterValue);
// Toggle filter in buttonFilters
if (isFilterActive) {
buttonFilters[filterGroup] = buttonFilters[filterGroup].filter(f => f !== filterValue);
updateButtons(filterValue, false); // Update all buttons to remove 'is-checked'
} else {
buttonFilters[filterGroup] = buttonFilters[filterGroup] || [];
buttonFilters[filterGroup].push(filterValue);
updateButtons(filterValue, true); // Update all buttons to add 'is-checked'
}
// Combine filters
const filterString = concatValues(buttonFilters);
// Apply filter without causing layout to be called again
iso.arrange({ filter: filterString });
});
});
// Reset filters and update buttons
function resetFilters() {
// Clear buttonFilters object
buttonFilters = {};
// Remove 'is-checked' class from all filter buttons
document.querySelectorAll('.filter-btn.is-checked').forEach(function (button) {
button.classList.remove('is-checked');
});
// No need to manually hide the button here, it will be handled by showResetButton()
// Apply filter to show all items
iso.arrange({ filter: '*' });
// Ensure the reset button visibility is updated
showResetButton();
}
// Show or hide the reset button with animation
function showResetButton() {
const hasActiveFilters = Object.keys(buttonFilters).some(key => buttonFilters[key].length > 0);
const resetButton = document.getElementById('reset-filters');
if (hasActiveFilters) {
resetButton.style.display = 'block'; // Make sure the button is visible before adding 'show'
// Trigger a reflow to ensure the animation plays
(() => resetButton.offsetWidth)();
resetButton.classList.add('show');
} else {
resetButton.classList.remove('show');
// Add a transitionend event listener to hide the button after the animation
resetButton.addEventListener('transitionend', function hideButton() {
// Check if the button is still not part of the 'show' class before hiding it
if (!resetButton.classList.contains('show')) {
resetButton.style.display = 'none';
}
resetButton.removeEventListener('transitionend', hideButton);
});
}
}
// Event listener for the reset button
document.getElementById('reset-filters').addEventListener('click', function () {
resetFilters();
});
// Modify the existing click event on filter buttons to call showResetButton
document.querySelectorAll('.filter-button-group').forEach(function (group) {
group.addEventListener('click', function (event) {
// Existing code...
// After the existing filtering logic, add:
showResetButton();
});
});
// Call showResetButton after initializing to make sure button is in correct state
showResetButton();
// If there's other code that clears filters, make sure to call showResetButton() after that action
// Function to shake the reset button
function shakeResetButton() {
const resetButton = document.getElementById('reset-filters');
resetButton.classList.add('shake');
resetButton.addEventListener('animationend', function () {
resetButton.classList.remove('shake');
});
}
// Modify the existing arrangeComplete event for Isotope to check for zero results
iso.on('arrangeComplete', function (filteredItems) {
// Check if no items are filtered
if (filteredItems.length === 0) {
// Shake the reset button to notify the user
shakeResetButton();
}
});
|
0000cd/wolf-set
| 9,361 |
themes/bluf/assets/css/style.css
|
:root {
--primary-color: {{ .Site.Params.lightColor }};
--text-color: #020617;
--text-secondary: #52525b;
--bg-primary: #f3f4f6;
--bg-primary-top: #f3f4f6E6;
--cards-white: #fafafa;
--shadow-color: rgba(0, 0, 0, 0.1);
}
@media (prefers-color-scheme: dark) {
:root:not([data-theme="light"]) {
--primary-color: {{ .Site.Params.darkColor }};
--text-color: #f4f4f5;
--text-secondary: #d4d4d8;
--bg-primary: #18181b;
--bg-primary-top: #18181bE6;
--cards-white: #262626;
--shadow-color: rgba(248, 250, 252, 0.15);
}
}
[data-theme="dark"] {
--primary-color: {{ .Site.Params.darkColor }};
--text-color: #f4f4f5;
--text-secondary: #d4d4d8;
--bg-primary: #18181b;
--bg-primary-top: #18181bE6;
--cards-white: #262626;
--shadow-color: rgba(248, 250, 252, 0.15);
}
body {
margin: 0;
padding-top: 70px;
background-color: var(--bg-primary);
color: var(--text-color);
font-family: Palatino, Palatino Linotype, Palatino LT STD, "PingFang SC", "Hiragino Sans GB", "Heiti SC", "Microsoft YaHei", "WenQuanYi Micro Hei", sans-serif;
}
a {
color: var(--text-color);
text-decoration: none;
}
.grid {
margin: 0 auto;
padding: 20px 0 20px 0;
width: 100%;
height: 100%;
opacity: 0;
visibility: hidden;
transition: opacity 0.5s, visibility 0.5s;
}
.grid.show {
opacity: 1;
visibility: visible;
}
.grid a:visited {
color: var(--text-secondary);
}
/* 网格项样式 */
.grid-item {
width: 255px;
margin: 8px 0 8px 0;
background: var(--cards-white);
color: var(--text-color);
border-radius: 16px;
overflow: hidden;
transition: box-shadow 0.3s ease-in-out;
}
.grid-item:hover {
box-shadow: 0px 0px 18px var(--shadow-color);
}
/* 网格项头部样式 */
.grid-item-header {
display: flex;
justify-content: space-between;
align-items: center;
padding: 10px 13px 4px;
}
.grid-item-img {
max-width: 255px;
background: var(--cards-white);
opacity: 0;
transition: opacity 0.5s ease;
}
.grid-item-img.loaded {
opacity: 1;
}
.grid-item-title {
font-size: 1.25em;
margin: 0;
flex: 1;
}
.grid-item-color-mark {
width: 20px;
height: 20px;
border-radius: 50%;
background: var(--primary-color);
}
/* 网格项描述样式 */
.grid-item-description {
padding: 4px 13px 10px 13px;
font-size: 0.875em;
}
.grid-item-description p {
margin: 0;
}
/* 网格项中部样式 */
.grid-item-middle {
padding: 4px 14px 4px 12px;
display: flex;
justify-content: space-between;
align-items: center;
}
.grid-item-tags {
display: flex;
flex-wrap: wrap;
gap: 5px;
}
.grid-item-tag {
background: var(--bg-primary);
color: var(--text-secondary);
border-radius: 3px;
padding: 2px 5px;
font-size: 0.75em;
}
.grid-item-date {
color: var(--text-secondary);
font-size: 0.75em;
}
/* 网格项链接样式 */
.grid-item-links {
padding: 0 13px 10px;
display: flex;
justify-content: space-around;
align-items: center;
}
.grid-item-links a {
color: var(--text-color);
text-decoration: none;
padding: 5px;
font-size: 0.75em;
}
.grid-item-links a:hover {
text-decoration: underline;
}
/* 顶部栏样式 */
.top-bar {
margin: 0 auto;
position: fixed;
top: 0;
left: 0;
width: 100vw;
box-sizing: border-box;
background: var(--bg-primary-top);
color: var(--text-color);
padding: 10px 0;
z-index: 1000;
}
.top-bar-inner {
margin: 0 auto;
display: flex;
width: 90%;
justify-content: space-between;
}
.top-bar-logo {
height: 40px;
width: 40px;
vertical-align: middle;
margin-right: 10px;
}
.top-bar-title {
font-size: 1.5em;
margin: 0 100px 0 5px;
display: flex;
align-items: center;
white-space: nowrap;
font-family: Times New Roman, "PingFang SC", "Hiragino Sans GB", "Heiti SC", "Microsoft YaHei", "WenQuanYi Micro Hei", sans-serif;
}
.top-bar-nav {
display: flex;
align-items: center;
/* width: 100%; */
gap: 10px;
/* 确保各元素间距均匀 */
flex-wrap: nowrap;
}
.top-bar-nav a {
padding: 0 10px;
}
/* 选中状态样式 */
.is-checked {
background: var(--primary-color);
color: var(--cards-white);
}
/* 菜单容器样式 */
.menu-container {
position: relative;
display: inline-block;
padding: 10px;
margin: 5px 0;
flex-shrink: 0;
/* 不允许收缩 */
cursor: pointer;
}
.exlink:hover {
text-decoration: underline
}
.theme-toggle {
background-color: transparent;
font-size: 1em;
border: none;
cursor: pointer;
}
.hot-tags-container {
display: flex;
align-items: center;
gap: 10px;
overflow: hidden;
flex-shrink: 1;
margin-left: auto;
min-width: 0;
}
/* 导航按钮样式 */
.nav-button {
display: none;
position: absolute;
top: 100%;
left: 0;
background-color: var(--cards-white);
box-shadow: 0px 3px 6px var(--shadow-color);
border-radius: 4px;
padding: 10px;
z-index: 1001;
width: max-content;
}
.nav-button.active {
display: block;
}
.nav-button .filter-btn {
display: block;
margin-bottom: 5px;
}
.nav-button .filter-btn:last-child {
margin-bottom: 0;
}
/* 过滤按钮样式 */
button.filter-btn {
border: none;
border-radius: 4px;
cursor: pointer;
outline: none;
transition: background-color 0.3s, color 0.3s;
font-family: Palatino, Palatino Linotype, Palatino LT STD, "PingFang SC", "Hiragino Sans GB", "Heiti SC", "Microsoft YaHei", "WenQuanYi Micro Hei", sans-serif;
}
button.filter-btn:hover {
background-color: var(--text-secondary);
color: var(--cards-white);
}
button.filter-btn.is-checked {
background-color: var(--primary-color);
color: var(--cards-white);
}
.menu-toggle-btn {
background: var(--bg-primary-top);
color: var(--text-secondary);
}
/* 提高hot优先级 */
.hot-tag {
padding: 0 10px;
border-radius: 4px;
color: var(--text-color);
background-color: transparent;
text-decoration: none;
transition: all 0.3s ease;
white-space: nowrap;
flex-shrink: 0;
font-size: 1em;
}
.hot-tag:hover {
background-color: var(--cards-white);
}
/* 重置过滤按钮样式 */
#reset-filters {
position: fixed;
bottom: -100px;
left: 50%;
transform: translateX(-50%);
width: 50px;
height: 50px;
border-radius: 50%;
background-color: var(--primary-color);
color: var(--cards-white);
border: none;
cursor: pointer;
font-size: 24px;
line-height: 50px;
text-align: center;
box-shadow: 0 4px 8px var(--shadow-color);
transition: bottom 0.3s ease-in-out;
z-index: 1000;
display: none;
}
#reset-filters.show {
bottom: 30px;
display: block;
}
/* 重置过滤按钮抖动动画 */
@keyframes shake {
0%,
100% {
transform: translateX(-50%);
}
12.5%,
37.5%,
62.5%,
87.5% {
transform: translateX(calc(-50% - 3px));
}
25%,
50%,
75% {
transform: translateX(calc(-50% + 3px));
}
}
#reset-filters.shake {
animation: shake 0.8s ease-in-out both;
}
/* 适配移动端顶栏 */
@media screen and (max-width: 768px) {
body {
padding-top: 120px;
}
.menu-container {
display: flex;
align-items: center;
margin: 0;
position: relative;
}
.top-bar-inner {
flex-direction: column;
align-items: center;
}
.top-bar-title {
margin: 0;
}
.top-bar-nav {
margin: 0;
display: flex;
justify-content: left;
flex-wrap: nowrap;
overflow-x: auto;
}
.menu-toggle {
margin-right: 0;
}
.site-footer {
bottom: 15px;
}
.categories {
display: none;
}
.hot-tags-container {
display: none;
}
}
/* 文章 */
.post {
max-width: 800px;
padding: 20px;
line-height: 1.4;
margin-left: auto;
margin-right: auto;
}
.post a:hover {
text-decoration: underline;
}
.single-head {
margin: 0 auto;
display: flex;
justify-content: space-between;
align-items: center;
}
.post-footer {
padding: 20px;
text-align: center;
line-height: 1.5;
}
/* 头像问候 */
.greeting-widget {
position: fixed;
bottom: -100px;
left: 50%;
transform: translateX(-50%);
display: flex;
align-items: center;
background: var(--cards-white);
padding: 10px 20px;
border-radius: 50px;
box-shadow: 0 2px 10px var(--shadow-color);
transition: bottom 0.3s ease-out;
z-index: 1000;
gap: 10px;
}
.avatar {
width: 32px;
height: 32px;
border-radius: 50%;
flex-shrink: 0;
overflow: hidden;
}
.avatar img {
width: 100%;
height: 100%;
object-fit: cover;
}
.message {
color: var(--text-color);
}
.greeting-widget.show {
bottom: 20px;
}
/* 美化相册封面 */
#cover {
position: relative;
display: inline-block;
cursor: zoom-in;
}
.cover-line {
position: absolute;
bottom: 10px;
left: 50%;
transform: translateX(-50%);
width: 96px;
height: 4px;
border-radius: 4px;
background-color: var(--bg-primary-top);
}
.cover-img {
position: relative;
display: inline-block;
}
.cover-img {
transition: transform 1s ease;
}
#cover:hover .cover-img {
transform: scale(1.03);
}
|
000haoji/deep-student
| 8,404 |
src/components/EnhancedKnowledgeBaseManagement.css
|
/* 增强知识库管理样式 */
.knowledge-base-management {
padding: 20px;
max-width: 1400px;
margin: 0 auto;
background: #f8fafc;
min-height: 100vh;
}
/* 头部样式 */
.management-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 20px;
padding: 20px;
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
.management-header h2 {
margin: 0;
color: #1e293b;
font-size: 1.5rem;
font-weight: 600;
}
.header-actions {
display: flex;
gap: 10px;
}
/* 状态概览 */
.status-overview {
display: flex;
gap: 20px;
margin-bottom: 20px;
padding: 20px;
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
.status-item {
display: flex;
flex-direction: column;
gap: 5px;
}
.status-item .label {
font-size: 0.875rem;
color: #64748b;
font-weight: 500;
}
.status-item .value {
font-size: 1.25rem;
font-weight: 600;
color: #1e293b;
}
/* 主内容区域 */
.main-content {
display: grid;
grid-template-columns: 320px 1fr;
gap: 20px;
min-height: 600px;
}
/* 分库侧栏 */
.library-sidebar {
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
padding: 20px;
height: fit-content;
max-height: 800px;
overflow-y: auto;
}
.library-sidebar h3 {
margin: 0 0 15px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
}
.library-list {
display: flex;
flex-direction: column;
gap: 8px;
}
.library-item {
padding: 12px;
border: 2px solid #e2e8f0;
border-radius: 8px;
cursor: pointer;
transition: all 0.2s ease;
background: #f8fafc;
}
.library-item:hover {
border-color: #3b82f6;
background: #eff6ff;
}
.library-item.selected {
border-color: #3b82f6;
background: #dbeafe;
}
.library-item .library-info {
flex: 1;
}
.library-name {
font-weight: 600;
color: #1e293b;
margin-bottom: 4px;
}
.library-stats {
font-size: 0.875rem;
color: #64748b;
margin-bottom: 4px;
}
.library-description {
font-size: 0.75rem;
color: #64748b;
font-style: italic;
}
.library-actions {
display: flex;
gap: 5px;
margin-top: 8px;
}
.btn-icon {
background: none;
border: none;
padding: 4px;
border-radius: 4px;
cursor: pointer;
font-size: 0.875rem;
transition: background-color 0.2s ease;
}
.btn-icon:hover {
background-color: #e2e8f0;
}
/* 文档管理主区域 */
.documents-main {
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
padding: 20px;
overflow-y: auto;
}
.section-header h3 {
margin: 0 0 20px 0;
color: #1e293b;
font-size: 1.25rem;
font-weight: 600;
}
/* 文件上传区域 */
.upload-zone {
border: 2px dashed #cbd5e1;
border-radius: 12px;
padding: 30px;
margin-bottom: 30px;
text-align: center;
transition: all 0.3s ease;
background: #f8fafc;
}
.upload-zone.drag-over {
border-color: #3b82f6;
background: #eff6ff;
}
.upload-zone.uploading {
opacity: 0.7;
pointer-events: none;
}
.upload-content {
display: flex;
flex-direction: column;
align-items: center;
gap: 15px;
}
.upload-icon {
font-size: 3rem;
color: #64748b;
}
.upload-text {
font-size: 1.125rem;
font-weight: 500;
color: #334155;
}
.upload-hint {
font-size: 0.875rem;
color: #64748b;
}
/* 选中文件列表 */
.selected-files {
margin-top: 20px;
padding: 20px;
background: #f1f5f9;
border-radius: 8px;
}
.selected-files h4 {
margin: 0 0 15px 0;
color: #1e293b;
}
.file-list {
display: flex;
flex-direction: column;
gap: 8px;
margin-bottom: 15px;
}
.file-item {
display: flex;
justify-content: space-between;
align-items: center;
padding: 8px 12px;
background: white;
border-radius: 6px;
border: 1px solid #e2e8f0;
}
.file-name {
flex: 1;
font-weight: 500;
color: #1e293b;
}
.file-size {
font-size: 0.875rem;
color: #64748b;
margin-right: 10px;
}
.btn-remove {
background: #fee2e2;
color: #dc2626;
border: none;
border-radius: 4px;
width: 24px;
height: 24px;
cursor: pointer;
display: flex;
align-items: center;
justify-content: center;
font-size: 0.75rem;
}
.btn-remove:hover {
background: #fecaca;
}
.upload-actions {
display: flex;
gap: 10px;
}
/* 文档列表 */
.documents-section {
margin-top: 30px;
}
.documents-header h4 {
margin: 0 0 20px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
}
.loading-state {
text-align: center;
padding: 60px 20px;
color: #64748b;
font-size: 1.125rem;
}
.empty-state {
text-align: center;
padding: 60px 20px;
}
.empty-icon {
font-size: 4rem;
margin-bottom: 15px;
}
.empty-text {
font-size: 1.25rem;
font-weight: 500;
color: #334155;
margin-bottom: 8px;
}
.empty-hint {
color: #64748b;
font-size: 0.875rem;
}
.documents-grid {
display: grid;
grid-template-columns: repeat(auto-fill, minmax(300px, 1fr));
gap: 15px;
}
.document-card {
border: 1px solid #e2e8f0;
border-radius: 8px;
padding: 15px;
background: #f8fafc;
transition: all 0.2s ease;
}
.document-card:hover {
border-color: #3b82f6;
box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
}
.doc-header {
display: flex;
justify-content: space-between;
align-items: flex-start;
margin-bottom: 10px;
}
.doc-name {
font-weight: 600;
color: #1e293b;
flex: 1;
word-break: break-word;
}
.doc-actions {
display: flex;
gap: 5px;
}
.doc-info {
display: flex;
flex-direction: column;
gap: 6px;
}
.doc-stat {
display: flex;
justify-content: space-between;
font-size: 0.875rem;
}
.doc-stat .label {
color: #64748b;
}
.doc-stat .value {
color: #1e293b;
font-weight: 500;
}
/* 模态框样式 */
.modal-overlay {
position: fixed;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: rgba(0, 0, 0, 0.5);
display: flex;
align-items: center;
justify-content: center;
z-index: 1000;
}
.modal {
background: white;
border-radius: 12px;
box-shadow: 0 20px 40px rgba(0, 0, 0, 0.2);
max-width: 500px;
width: 90%;
max-height: 90vh;
overflow: hidden;
}
.modal-header {
display: flex;
justify-content: space-between;
align-items: center;
padding: 20px;
border-bottom: 1px solid #e2e8f0;
}
.modal-header h3 {
margin: 0;
color: #1e293b;
font-size: 1.25rem;
font-weight: 600;
}
.btn-close {
background: none;
border: none;
font-size: 1.25rem;
cursor: pointer;
color: #64748b;
padding: 5px;
border-radius: 4px;
}
.btn-close:hover {
background: #f1f5f9;
color: #1e293b;
}
.modal-body {
padding: 20px;
max-height: 400px;
overflow-y: auto;
}
.modal-footer {
display: flex;
justify-content: flex-end;
gap: 10px;
padding: 20px;
border-top: 1px solid #e2e8f0;
}
/* 表单样式 */
.form-group {
margin-bottom: 20px;
}
.form-group label {
display: block;
margin-bottom: 8px;
font-weight: 500;
color: #374151;
}
.form-input,
.form-textarea {
width: 100%;
padding: 10px 12px;
border: 1px solid #d1d5db;
border-radius: 6px;
font-size: 0.875rem;
transition: border-color 0.2s ease;
}
.form-input:focus,
.form-textarea:focus {
outline: none;
border-color: #3b82f6;
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
}
.form-textarea {
resize: vertical;
font-family: inherit;
}
/* 按钮样式 */
.btn {
padding: 8px 16px;
border: none;
border-radius: 6px;
font-size: 0.875rem;
font-weight: 500;
cursor: pointer;
transition: all 0.2s ease;
display: inline-flex;
align-items: center;
gap: 6px;
}
.btn:disabled {
opacity: 0.5;
cursor: not-allowed;
}
.btn-primary {
background: #3b82f6;
color: white;
}
.btn-primary:hover:not(:disabled) {
background: #2563eb;
}
.btn-secondary {
background: #64748b;
color: white;
}
.btn-secondary:hover:not(:disabled) {
background: #475569;
}
.btn-success {
background: #10b981;
color: white;
}
.btn-success:hover:not(:disabled) {
background: #059669;
}
/* 响应式设计 */
@media (max-width: 1024px) {
.main-content {
grid-template-columns: 1fr;
}
.library-sidebar {
max-height: 300px;
}
.status-overview {
flex-wrap: wrap;
gap: 15px;
}
}
@media (max-width: 768px) {
.knowledge-base-management {
padding: 10px;
}
.management-header {
flex-direction: column;
gap: 15px;
align-items: stretch;
}
.header-actions {
justify-content: center;
}
.documents-grid {
grid-template-columns: 1fr;
}
.modal {
width: 95%;
margin: 10px;
}
}
|
000haoji/deep-student
| 4,899 |
src/components/GraphVisualization.css
|
.graph-visualization-container {
display: flex;
flex-direction: column;
height: 100%;
padding: 20px;
background: #f8f9fa;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
}
.graph-controls {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 20px;
padding: 15px;
background: white;
border-radius: 8px;
box-shadow: 0 1px 4px rgba(0,0,0,0.1);
}
.control-group {
display: flex;
align-items: center;
gap: 10px;
}
.control-group label {
font-weight: 600;
color: #2c3e50;
}
.control-group select {
padding: 8px 12px;
border: 1px solid #bdc3c7;
border-radius: 6px;
background: white;
color: #2c3e50;
font-size: 14px;
}
.control-buttons {
display: flex;
gap: 10px;
}
.control-buttons button {
padding: 8px 16px;
border: none;
border-radius: 6px;
background: #3498db;
color: white;
font-size: 14px;
cursor: pointer;
transition: all 0.2s ease;
}
.control-buttons button:hover:not(:disabled) {
background: #2980b9;
transform: translateY(-1px);
}
.control-buttons button:disabled {
background: #bdc3c7;
cursor: not-allowed;
transform: none;
}
.error-message {
background: #fee;
border: 1px solid #fcc;
border-radius: 8px;
padding: 12px;
margin-bottom: 20px;
color: #c33;
font-weight: 500;
display: flex;
justify-content: space-between;
align-items: center;
}
.error-message button {
background: none;
border: none;
color: #c33;
font-size: 16px;
cursor: pointer;
padding: 0;
margin-left: 10px;
}
.graph-content {
display: flex;
gap: 20px;
flex: 1;
}
.graph-viz {
position: relative;
flex: 1;
background: white;
border-radius: 8px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
overflow: hidden;
}
.loading-overlay {
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: rgba(255, 255, 255, 0.9);
display: flex;
align-items: center;
justify-content: center;
z-index: 1000;
}
.loading-spinner {
padding: 20px;
background: white;
border-radius: 8px;
box-shadow: 0 2px 8px rgba(0,0,0,0.2);
color: #3498db;
font-weight: 600;
}
.node-details {
width: 300px;
background: white;
border-radius: 8px;
padding: 20px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
max-height: 500px;
overflow-y: auto;
}
.node-details h3 {
margin: 0 0 15px 0;
color: #2c3e50;
border-bottom: 2px solid #3498db;
padding-bottom: 8px;
}
.node-info {
margin-bottom: 15px;
font-size: 14px;
line-height: 1.6;
color: #34495e;
}
.node-info pre {
background: #f8f9fa;
padding: 10px;
border-radius: 4px;
font-size: 12px;
overflow-x: auto;
margin: 10px 0 0 0;
}
.node-actions {
display: flex;
gap: 10px;
}
.node-actions button {
flex: 1;
padding: 8px 12px;
border: none;
border-radius: 6px;
cursor: pointer;
font-size: 14px;
transition: all 0.2s ease;
}
.node-actions button:first-child {
background: #3498db;
color: white;
}
.node-actions button:first-child:hover {
background: #2980b9;
}
.node-actions button:last-child {
background: #95a5a6;
color: white;
}
.node-actions button:last-child:hover {
background: #7f8c8d;
}
.graph-legend {
width: 200px;
background: white;
border-radius: 8px;
padding: 20px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
height: fit-content;
}
.graph-legend h4 {
margin: 0 0 15px 0;
color: #2c3e50;
border-bottom: 2px solid #3498db;
padding-bottom: 8px;
}
.legend-items {
display: flex;
flex-direction: column;
gap: 12px;
}
.legend-item {
display: flex;
align-items: center;
gap: 10px;
font-size: 14px;
color: #34495e;
}
.legend-node {
width: 16px;
height: 16px;
border-radius: 50%;
border: 2px solid transparent;
}
.legend-node.problem-card {
background: #68CCE5;
border-color: #3498db;
}
.legend-node.tag {
background: #FFA500;
border-color: #e67e22;
}
.legend-edge {
width: 20px;
height: 3px;
border-radius: 2px;
}
.legend-edge.has-tag {
background: #3498db;
}
.legend-edge.parent-of {
background: #e74c3c;
}
.legend-edge.related {
background: #95a5a6;
}
.not-initialized {
display: flex;
align-items: center;
justify-content: center;
height: 300px;
background: white;
border-radius: 8px;
color: #7f8c8d;
font-size: 16px;
}
/* Neo4j visualization container styling */
#neo4j-viz {
border-radius: 8px;
}
/* Custom styling for Neo4j nodes and edges */
#neo4j-viz .vis-network {
border-radius: 8px;
}
/* Responsive design */
@media (max-width: 1200px) {
.graph-content {
flex-direction: column;
}
.node-details,
.graph-legend {
width: 100%;
}
.graph-viz {
height: 400px;
}
}
@media (max-width: 768px) {
.graph-controls {
flex-direction: column;
gap: 15px;
}
.control-buttons {
justify-content: center;
}
.graph-visualization-container {
padding: 10px;
}
}
|
000haoji/deep-student
| 4,684 |
src/components/ModernSidebar.tsx
|
import React from 'react';
import '../styles/modern-sidebar.css';
import {
FileText,
Layers,
Target,
BookOpen,
Brain,
Search,
CreditCard,
Palette,
Image,
BarChart3,
Package,
Settings,
FlaskConical,
ChevronLeft,
ChevronRight,
Network
} from 'lucide-react';
type CurrentView = 'analysis' | 'library' | 'settings' | 'mistake-detail' | 'batch' | 'review' | 'dashboard' | 'data-management' | 'unified-review' | 'create-review' | 'review-session' | 'anki-generation' | 'knowledge-base' | 'rag-query' | 'image-occlusion' | 'template-management' | 'gemini-adapter-test' | 'cogni-graph';
interface ModernSidebarProps {
currentView: CurrentView;
onViewChange: (view: CurrentView) => void;
sidebarCollapsed: boolean;
onToggleSidebar: () => void;
batchAnalysisEnabled: boolean;
geminiAdapterTestEnabled: boolean;
imageOcclusionEnabled: boolean;
startDragging: (e: React.MouseEvent) => void;
}
interface NavItem {
id: CurrentView;
label: string;
icon: React.ReactNode;
section: string;
visible?: boolean;
}
export const ModernSidebar: React.FC<ModernSidebarProps> = ({
currentView,
onViewChange,
sidebarCollapsed,
onToggleSidebar,
batchAnalysisEnabled,
geminiAdapterTestEnabled,
imageOcclusionEnabled,
startDragging
}) => {
const navItems: NavItem[] = [
// 分析工具
{ id: 'analysis', label: '分析', icon: <FileText size={20} />, section: '分析工具' },
{ id: 'batch', label: '批量分析', icon: <Layers size={20} />, section: '分析工具', visible: batchAnalysisEnabled },
{ id: 'unified-review', label: '统一回顾', icon: <Target size={20} />, section: '分析工具' },
// 知识管理
{ id: 'library', label: '错题库', icon: <BookOpen size={20} />, section: '知识管理' },
{ id: 'knowledge-base', label: '知识库', icon: <Brain size={20} />, section: '知识管理' },
{ id: 'rag-query', label: 'RAG查询', icon: <Search size={20} />, section: '知识管理' },
{ id: 'cogni-graph', label: '知识图谱', icon: <Network size={20} />, section: '知识管理' },
// ANKI工具
{ id: 'anki-generation', label: 'ANKI制卡', icon: <CreditCard size={20} />, section: 'ANKI工具' },
{ id: 'template-management', label: '模板管理', icon: <Palette size={20} />, section: 'ANKI工具' },
{ id: 'image-occlusion', label: '图片遮罩卡', icon: <Image size={20} />, section: 'ANKI工具', visible: imageOcclusionEnabled },
// 系统工具
{ id: 'dashboard', label: '数据统计', icon: <BarChart3 size={20} />, section: '系统工具' },
{ id: 'data-management', label: '数据管理', icon: <Package size={20} />, section: '系统工具' },
{ id: 'gemini-adapter-test', label: 'Gemini适配器测试', icon: <FlaskConical size={20} />, section: '系统工具', visible: geminiAdapterTestEnabled },
];
const sections = [...new Set(navItems.map(item => item.section))];
return (
<div className={`app-sidebar ${sidebarCollapsed ? 'collapsed' : ''}`}>
<div className="sidebar-header" onMouseDown={startDragging}>
<div className="app-logo">
{sidebarCollapsed ? (
<img src="/dslogo2.png" alt="Deep Student" className="logo-icon" />
) : (
<img src="/dslogo1.png" alt="Deep Student" className="logo-full" />
)}
</div>
</div>
<nav className="sidebar-nav">
{sections.map(section => {
const sectionItems = navItems.filter(item =>
item.section === section && (item.visible === undefined || item.visible)
);
if (sectionItems.length === 0) return null;
return (
<div key={section} className="nav-section">
<div className="nav-label">{!sidebarCollapsed && section}</div>
{sectionItems.map(item => (
<button
key={item.id}
className={`nav-item tooltip-test ${currentView === item.id ? 'active' : ''}`}
onClick={() => onViewChange(item.id)}
data-tooltip={sidebarCollapsed ? item.label : ''}
>
<span className="nav-icon">{item.icon}</span>
{!sidebarCollapsed && <span className="nav-text">{item.label}</span>}
</button>
))}
</div>
);
})}
</nav>
<div className="sidebar-footer">
<button
className={`nav-item tooltip-test ${currentView === 'settings' ? 'active' : ''}`}
onClick={() => onViewChange('settings')}
data-tooltip={sidebarCollapsed ? '设置' : ''}
>
<span className="nav-icon"><Settings size={20} /></span>
{!sidebarCollapsed && <span className="nav-text">设置</span>}
</button>
</div>
</div>
);
};
|
0000cd/wolf-set
| 1,736 |
themes/bluf/layouts/_default/single.html
|
<!DOCTYPE html>
<html lang="{{ .Site.LanguageCode }}">
<head>
{{ partial "head.html" . }}
<title>{{ .Title }} - {{ .Site.Title }}</title>
</head>
<body>
<div class="top-bar">
<div class="top-bar-inner" style="width: 80%;">
<div class="top-bar-title">
<a href="{{ .Site.BaseURL }}"><img class="top-bar-logo" src="/logo.webp" alt="Logo"></a>
<span class="top-bar-head">{{ .Site.Params.pagename }}</span>
</div>
<nav class="top-bar-nav">
<div class="menu-container">
<button class="theme-toggle" id="themeToggle" title="切换深浅配色">
深色模式
</button>
</div>
{{ with .Site.Data.navbar.external_links }}
<div class="menu-container">
{{ range . }}
<a href="{{ .url }}" target="_blank" class="menu-toggle exlink" rel="noopener" {{ if $.Site.Params.enableUmami
}}data-umami-event="NAV-{{ .name }}" {{ end }}>{{ .name }}</a>
{{ end }}
</div>
{{ end }}
</nav>
</div>
</div>
<article class="post">
<div class="single-head">
<h1>{{ .Title }}</h1>
<span><p>{{ .Date.Format "2006-01-02" }} | <a href="{{ .Site.BaseURL }}">↩</a></p></span>
</div>
<section>
{{ .Content }}
</section>
<footer class="post-footer">
{{ partial "cc.html" . }}
<a href="/">访问【首页】发现更多… </a>
</footer>
</article>
{{ partial "footer.html" . }}
</body>
</html>
|
0000cd/wolf-set
| 2,917 |
themes/bluf/layouts/_default/met.html
|
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<title>Meting Music</title>
<meta name="robots" content="noindex, nofollow">
<link rel="stylesheet" href="/css/APlayer.min.css">
<script src="/js/APlayer.min.js"></script>
<script src="/js/Meting.min.js"></script>
<style>
body {
background-color: #020202;
}
.aplayer {
margin: 0px;
}
.loading {
text-align: center;
padding: 10px;
}
.loading::after {
content: "";
display: inline-block;
width: 24px;
height: 24px;
border: 2px solid #f3f3f3;
border-top: 2px solid {{ .Site.Params.lightColor }};
border-radius: 50%;
animation: spin 1s linear infinite;
margin-left: 10px;
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
.hide {
display: none !important;
}
</style>
</head>
<body>
<div id="player-container">
<div id="loading" class="loading"></div>
</div>
<script>
const defaultConfig = {
server: 'netease',
type: 'album',
id: '137470856',
autoplay: 'true',
theme: '{{ .Site.Params.lightColor }}',
loop: 'all',
order: 'random',
preload: 'auto',
'list-max-height': '400px'
};
function createPlayer() {
const metingJs = document.createElement('meting-js');
const params = new URLSearchParams(window.location.search);
Object.keys(defaultConfig).forEach(key => {
metingJs.setAttribute(key, params.get(key) || defaultConfig[key]);
});
document.getElementById('player-container').appendChild(metingJs);
new MutationObserver((mutations, obs) => {
const aplayer = document.querySelector('.aplayer');
if (aplayer?.classList.contains('aplayer-withlist')) {
document.getElementById('loading').classList.add('hide');
obs.disconnect();
}
}).observe(document.getElementById('player-container'), {
childList: true,
subtree: true,
attributes: true,
attributeFilter: ['class']
});
}
window.addEventListener('load', createPlayer);
</script>
</body>
</html>
|
0000cd/wolf-set
| 2,132 |
themes/bluf/layouts/partials/getColorCategory.html
|
{{- $hex := . -}}
{{- if eq (substr $hex 0 1) "#" -}} {{/* 检查是否以 "#" 开头 */}}
{{- $hex = substr $hex 1 -}} {{/* 去掉 "#" */}}
{{- end -}}
{{/* 将 HEX 转换为 RGB */}}
{{- $r := printf "0x%s" (substr $hex 0 2) | int -}}
{{- $g := printf "0x%s" (substr $hex 2 2) | int -}}
{{- $b := printf "0x%s" (substr $hex 4 2) | int -}}
{{/* 将 RGB 归一化到 [0, 1] */}}
{{- $rf := div (float $r) 255 -}}
{{- $gf := div (float $g) 255 -}}
{{- $bf := div (float $b) 255 -}}
{{/* 模拟 max 和 min 函数 */}}
{{- $max := $rf -}}
{{- if gt $gf $max }} {{- $max = $gf -}} {{- end -}}
{{- if gt $bf $max }} {{- $max = $bf -}} {{- end -}}
{{- $min := $rf -}}
{{- if lt $gf $min }} {{- $min = $gf -}} {{- end -}}
{{- if lt $bf $min }} {{- $min = $bf -}} {{- end -}}
{{/* 计算 HSV 值 */}}
{{- $delta := sub $max $min -}}
{{- $hue := 0.0 -}}
{{- if gt $delta 0.0 -}}
{{- if eq $max $rf -}}
{{- $hue = mod (add (mul 60 (div (sub $gf $bf) $delta)) 360) 360 -}}
{{- else if eq $max $gf -}}
{{- $hue = add (mul 60 (div (sub $bf $rf) $delta)) 120 -}}
{{- else -}}
{{- $hue = add (mul 60 (div (sub $rf $gf) $delta)) 240 -}}
{{- end -}}
{{- end -}}
{{- $saturation := 0.0 -}}
{{- if gt $max 0.0 -}}
{{- $saturation = div $delta $max -}}
{{- end -}}
{{- $value := $max -}}
{{/* 优先判断灰色（包括黑和白） */}}
{{- $result := "unknown" -}}
{{- if le $saturation 0.2 -}}
{{- $result = "gray" -}}
{{- else -}}
{{/* 根据 Hue 值分类颜色 */}}
{{- if or (and (ge $hue 0) (lt $hue 15)) (and (ge $hue 345) (lt $hue 360)) -}}
{{- $result = "red" -}}
{{- else if and (ge $hue 15) (lt $hue 45) -}}
{{- $result = "orange" -}}
{{- else if and (ge $hue 45) (lt $hue 75) -}}
{{- $result = "yellow" -}}
{{- else if and (ge $hue 75) (lt $hue 165) -}}
{{- $result = "green" -}}
{{- else if and (ge $hue 165) (lt $hue 195) -}}
{{- $result = "cyan" -}}
{{- else if and (ge $hue 195) (lt $hue 255) -}}
{{- $result = "blue" -}}
{{- else if and (ge $hue 255) (lt $hue 315) -}}
{{- $result = "purple" -}}
{{- else if and (ge $hue 315) (lt $hue 345) -}}
{{- $result = "pink" -}}
{{- end -}}
{{- end -}}
{{/* 输出最终颜色分类 */}}
{{- $result -}}
|
000haoji/deep-student
| 37,889 |
src/components/KnowledgeBaseManagement.tsx
|
import React, { useState, useEffect, useCallback } from 'react';
import { TauriAPI } from '../utils/tauriApi';
import { useNotification } from '../hooks/useNotification';
import type {
RagDocument,
KnowledgeBaseStatusPayload,
RagProcessingEvent,
RagDocumentStatusEvent
} from '../types';
import { listen } from '@tauri-apps/api/event';
import './KnowledgeBaseManagement.css';
import {
BarChart3, FolderOpen, Target, RefreshCcw, Trash2, Upload,
FileText, CheckCircle, BookOpen, Sparkles, Rocket,
Calendar, Scale, Puzzle, Settings, File, Clock
} from 'lucide-react';
interface KnowledgeBaseManagementProps {
className?: string;
}
export const KnowledgeBaseManagement: React.FC<KnowledgeBaseManagementProps> = ({
className = ''
}) => {
const [documents, setDocuments] = useState<RagDocument[]>([]);
const [status, setStatus] = useState<KnowledgeBaseStatusPayload | null>(null);
const [loading, setLoading] = useState(false);
const [uploading, setUploading] = useState(false);
const [processingDocuments, setProcessingDocuments] = useState<Map<string, RagDocumentStatusEvent>>(new Map());
const [selectedFiles, setSelectedFiles] = useState<File[]>([]);
const { showSuccess, showError, showWarning } = useNotification();
// 拖拽状态
const [isDragOver, setIsDragOver] = useState(false);
// 加载知识库状态
const loadKnowledgeBaseStatus = useCallback(async () => {
try {
setLoading(true);
const [statusData, documentsData] = await Promise.all([
TauriAPI.ragGetKnowledgeBaseStatus(),
TauriAPI.ragGetAllDocuments()
]);
setStatus(statusData);
setDocuments(documentsData);
} catch (error) {
console.error('加载知识库状态失败:', error);
showError(`加载知识库状态失败: ${error}`);
} finally {
setLoading(false);
}
}, [showError]);
// 初始加载
useEffect(() => {
loadKnowledgeBaseStatus();
}, [loadKnowledgeBaseStatus]);
// 监听RAG处理事件
useEffect(() => {
const setupEventListeners = async () => {
try {
// 监听整体处理状态
const unlistenProcessing = await listen<RagProcessingEvent>('rag_processing_status', (event) => {
const data = event.payload;
if (data.status === 'completed') {
showSuccess(data.message);
loadKnowledgeBaseStatus(); // 重新加载状态
} else if (data.status === 'error') {
showError(`处理失败: ${data.message}`);
// 清空处理状态，让用户能够重试
setProcessingDocuments(new Map());
} else if (data.status === 'progress') {
// 可以显示整体进度信息
console.log(`整体处理进度: ${Math.round(data.progress * 100)}%`);
}
});
// 监听文档处理状态
const unlistenDocument = await listen<RagDocumentStatusEvent>('rag_document_status', (event) => {
const data = event.payload;
setProcessingDocuments(prev => {
const newMap = new Map(prev);
newMap.set(data.document_id, data);
return newMap;
});
if (data.status === 'Completed') {
showSuccess(`文档 "${data.file_name}" 处理完成，共生成 ${data.total_chunks} 个文本块`);
setTimeout(() => {
setProcessingDocuments(prev => {
const newMap = new Map(prev);
newMap.delete(data.document_id);
return newMap;
});
}, 3000);
} else if (data.status === 'Failed') {
const errorMsg = data.error_message || '未知错误';
showError(`文档 "${data.file_name}" 处理失败: ${errorMsg}`);
// 提供一些常见错误的解决建议
if (errorMsg.includes('Unsupported file format')) {
showWarning('请确保文件格式为 .txt, .md, .pdf 或 .docx');
} else if (errorMsg.includes('File not found')) {
showWarning('文件可能已被移动或删除，请重新选择文件');
} else if (errorMsg.includes('Permission denied')) {
showWarning('没有文件访问权限，请检查文件权限设置');
}
// 保持失败状态显示一段时间，然后清除
setTimeout(() => {
setProcessingDocuments(prev => {
const newMap = new Map(prev);
newMap.delete(data.document_id);
return newMap;
});
}, 8000);
}
});
return () => {
};
} catch (error) {
console.error('设置事件监听器失败:', error);
}
};
setupEventListeners();
}, [showSuccess, showError, loadKnowledgeBaseStatus]);
// 监听文件拖拽事件
useEffect(() => {
const setupFileDragListeners = async () => {
try {
// 尝试使用 Tauri v2 API
const { listen } = await import('@tauri-apps/api/event');
// 监听文件拖拽进入
const unlistenDragEnter = await listen('tauri://file-drop-hover', () => {
setIsDragOver(true);
console.log('文件拖拽进入');
});
// 监听文件拖拽离开
const unlistenDragLeave = await listen('tauri://file-drop-cancelled', () => {
setIsDragOver(false);
console.log('文件拖拽离开');
});
// 监听文件拖拽放下
const unlistenDrop = await listen<string[]>('tauri://file-drop', async (event) => {
setIsDragOver(false);
const filePaths = event.payload;
console.log('拖拽文件路径:', filePaths);
// 过滤支持的文件格式
const supportedExtensions = ['.txt', '.md', '.markdown', '.pdf', '.docx'];
const validFiles = filePaths.filter(path => {
const extension = path.toLowerCase().substring(path.lastIndexOf('.'));
return supportedExtensions.includes(extension);
});
if (validFiles.length === 0) {
showWarning('没有支持的文件格式。支持的格式：.txt, .md, .pdf, .docx');
return;
}
if (validFiles.length !== filePaths.length) {
showWarning(`已过滤不支持的文件，将上传 ${validFiles.length} 个支持的文件`);
}
try {
setUploading(true);
showSuccess(`开始处理 ${validFiles.length} 个文件...`);
await TauriAPI.ragAddDocuments(validFiles);
showSuccess(`成功拖拽上传 ${validFiles.length} 个文件到知识库！`);
// 重新加载知识库状态
await loadKnowledgeBaseStatus();
} catch (error) {
console.error('拖拽上传失败:', error);
let errorMessage = '拖拽上传失败';
if (typeof error === 'string') {
errorMessage = `拖拽上传失败: ${error}`;
} else if (error instanceof Error) {
errorMessage = `拖拽上传失败: ${error.message}`;
}
// 提供更有用的错误信息和建议
if (errorMessage.includes('系统找不到指定的文件') || errorMessage.includes('文件不存在')) {
errorMessage += '\n\n建议：\n• 确保文件未被移动或删除\n• 尝试使用"选择文件"按钮代替拖拽\n• 检查文件名是否包含特殊字符';
}
showError(errorMessage);
} finally {
setUploading(false);
}
});
console.log('文件拖拽监听器设置完成');
return () => {
// 清理拖拽监听器
};
} catch (error) {
console.error('设置文件拖拽监听器失败:', error);
showWarning('文件拖拽功能暂时不可用，请等待应用完全加载');
}
};
setupFileDragListeners();
}, [showSuccess, showError, showWarning, loadKnowledgeBaseStatus]);
// 处理文件选择
const handleFileSelect = (event: React.ChangeEvent<HTMLInputElement>) => {
const files = Array.from(event.target.files || []);
const supportedTypes = ['.txt', '.md', '.markdown', '.pdf', '.docx'];
const validFiles = files.filter(file => {
const extension = file.name.toLowerCase().substring(file.name.lastIndexOf('.'));
return supportedTypes.includes(extension);
});
if (validFiles.length !== files.length) {
showWarning(`只支持 ${supportedTypes.join(', ')} 格式的文件`);
}
setSelectedFiles(validFiles);
};
// 上传文档
const handleUploadDocuments = async () => {
if (selectedFiles.length === 0) {
showWarning('请先选择要上传的文件');
return;
}
try {
setUploading(true);
const documents: Array<{ file_name: string; base64_content: string }> = [];
// 读取文件内容，像Anki组件一样处理
for (const file of selectedFiles) {
try {
const content = await new Promise<string>((resolve, reject) => {
const reader = new FileReader();
reader.onload = (e) => {
const result = e.target?.result as string;
resolve(result);
};
reader.onerror = (e) => reject(e);
// 根据文件类型选择读取方式
if (file.type === 'text/plain' || file.name.endsWith('.txt') || file.name.endsWith('.md')) {
reader.readAsText(file);
} else {
// 对于PDF、DOCX等二进制文件，读取为ArrayBuffer然后转换为base64
reader.onload = (e) => {
const arrayBuffer = e.target?.result as ArrayBuffer;
const base64 = btoa(String.fromCharCode(...new Uint8Array(arrayBuffer)));
resolve(base64);
};
reader.readAsArrayBuffer(file);
}
});
documents.push({
file_name: file.name,
base64_content: content
});
} catch (fileError) {
console.error(`处理文件 ${file.name} 失败:`, fileError);
showError(`处理文件 ${file.name} 失败`);
}
}
if (documents.length === 0) {
showError('没有文件被成功处理');
return;
}
showSuccess(`开始处理 ${documents.length} 个文件...`);
await TauriAPI.ragAddDocumentsFromContent(documents);
showSuccess(`成功上传 ${documents.length} 个文件到知识库！`);
// 清空选择的文件
setSelectedFiles([]);
// 重新加载知识库状态
await loadKnowledgeBaseStatus();
} catch (error) {
console.error('上传文件失败:', error);
let errorMessage = '上传文件失败';
if (typeof error === 'string') {
errorMessage = `上传失败: ${error}`;
} else if (error instanceof Error) {
errorMessage = `上传失败: ${error.message}`;
} else if (error && typeof error === 'object' && 'message' in error) {
errorMessage = `上传失败: ${(error as any).message}`;
}
showError(errorMessage);
// 提供重试建议
showWarning('请检查文件格式是否正确');
} finally {
setUploading(false);
}
};
// 删除文档
const handleDeleteDocument = async (documentId: string, documentName: string) => {
if (!confirm(`确定要删除文档 "${documentName}" 吗？此操作不可撤销。`)) {
return;
}
try {
console.log('开始删除文档:', documentId, documentName);
await TauriAPI.ragDeleteDocument(documentId);
console.log('文档删除成功，开始刷新数据');
showSuccess(`文档 "${documentName}" 已删除`);
// 重新加载知识库状态和文档列表
await loadKnowledgeBaseStatus();
} catch (error) {
console.error('删除文档失败:', error);
showError(`删除文档失败: ${error}`);
}
};
// 清空知识库
const handleClearKnowledgeBase = async () => {
if (!confirm('确定要清空整个知识库吗？此操作将删除所有文档和向量数据，不可撤销。')) {
return;
}
try {
await TauriAPI.ragClearKnowledgeBase();
showSuccess('知识库已清空');
loadKnowledgeBaseStatus();
} catch (error) {
console.error('清空知识库失败:', error);
showError(`清空知识库失败: ${error}`);
}
};
// 格式化文件大小
const formatFileSize = (bytes?: number) => {
if (!bytes) return '未知';
if (bytes < 1024) return `${bytes} B`;
if (bytes < 1024 * 1024) return `${(bytes / 1024).toFixed(1)} KB`;
return `${(bytes / (1024 * 1024)).toFixed(1)} MB`;
};
// 格式化日期
const formatDate = (dateString: string) => {
return new Date(dateString).toLocaleString('zh-CN');
};
// 获取处理状态显示
const getProcessingStatusDisplay = (docId: string) => {
const processing = processingDocuments.get(docId);
if (!processing) return null;
const getStatusText = (status: string) => {
const statusMap: Record<string, string> = {
'Reading': '读取文件',
'Preprocessing': '预处理',
'Chunking': '文本分块',
'Embedding': '生成向量',
'Storing': '存储数据',
'Completed': '处理完成',
'Failed': '处理失败'
};
return statusMap[status] || status;
};
const getStatusClass = (status: string) => {
const classMap: Record<string, string> = {
'Pending': 'pending',
'Reading': 'reading',
'Preprocessing': 'reading',
'Chunking': 'reading',
'Embedding': 'reading',
'Storing': 'reading',
'Completed': 'completed',
'Failed': 'failed'
};
return classMap[status] || 'reading';
};
return (
<div className={`kb-processing-status ${getStatusClass(processing.status)}`}>
<div className="kb-processing-header">
<span className="kb-processing-title">
{getStatusText(processing.status)}
</span>
<span className="kb-processing-percentage">
{Math.round(processing.progress * 100)}%
</span>
</div>
{processing.status !== 'Completed' && processing.status !== 'Failed' && (
<div className="kb-processing-bar">
<div
className="kb-processing-progress"
style={{ width: `${processing.progress * 100}%` }}
/>
</div>
)}
{processing.chunks_processed > 0 && (
<div className="kb-processing-chunks">
<div className="kb-chunks-info" style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<BarChart3 size={16} />
已处理 {processing.chunks_processed} / {processing.total_chunks} 个文本块
</div>
{processing.total_chunks > 0 && (
<div className="kb-chunks-progress">
<div
className="kb-chunks-progress-bar"
style={{
width: `${(processing.chunks_processed / processing.total_chunks) * 100}%`
}}
/>
</div>
)}
</div>
)}
</div>
);
};
return (
<div className={`knowledge-base-container ${className} ${isDragOver ? 'drag-over' : ''}`}>
{isDragOver && (
<div className="kb-drag-overlay">
<div className="kb-drag-overlay-content">
<div className="kb-drag-icon" style={{ display: 'flex', justifyContent: 'center', marginBottom: '16px' }}>
<FolderOpen size={48} color="#667eea" />
</div>
<h2 className="kb-drag-title">松开鼠标上传文档</h2>
<p className="kb-drag-subtitle">
支持 .txt, .md, .pdf, .docx 格式的文档
</p>
</div>
</div>
)}
<div className="knowledge-base-content">
{/* 页面标题 */}
<div style={{
background: 'white',
borderBottom: '1px solid #e5e7eb',
padding: '24px 32px',
position: 'relative'
}}>
<div style={{
position: 'absolute',
top: 0,
left: 0,
right: 0,
height: '4px',
background: 'linear-gradient(90deg, #667eea, #764ba2)'
}}></div>
<div style={{ position: 'relative', zIndex: 1 }}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '8px' }}>
<svg xmlns="http://www.w3.org/2000/svg" width="32" height="32" viewBox="0 0 24 24" fill="none" stroke="#667eea" strokeWidth="2" strokeLinecap="round" strokeLinejoin="round" style={{ marginRight: '12px' }}>
<path d="M12 5a3 3 0 1 0-5.997.125 4 4 0 0 0-2.526 5.77 4 4 0 0 0 .556 6.588A4 4 0 1 0 12 18Z"/>
<path d="M12 5a3 3 0 1 1 5.997.125 4 4 0 0 1 2.526 5.77 4 4 0 0 1-.556 6.588A4 4 0 1 1 12 18Z"/>
<path d="M15 13a4.5 4.5 0 0 1-3-4 4.5 4.5 0 0 1-3 4"/>
<path d="M17.599 6.5a3 3 0 0 0 .399-1.375"/>
<path d="M6.003 5.125A3 3 0 0 0 6.401 6.5"/>
<path d="M3.477 10.896a4 4 0 0 1 .585-.396"/>
<path d="M19.938 10.5a4 4 0 0 1 .585.396"/>
<path d="M6 18a4 4 0 0 1-1.967-.516"/>
<path d="M19.967 17.484A4 4 0 0 1 18 18"/>
</svg>
<h1 style={{ fontSize: '28px', fontWeight: '700', margin: 0, color: '#1f2937' }}>RAG 知识库管理</h1>
</div>
<p style={{ fontSize: '16px', color: '#6b7280', margin: 0, lineHeight: '1.5' }}>
智能文档管理系统，为AI提供丰富的知识背景，让分析更加精准和深入
</p>
</div>
</div>
{/* 知识库状态 */}
<div className="kb-stats-grid">
<div className="kb-stat-card">
<div className="kb-stat-header">
<div className="kb-stat-icon blue">
<svg style={{ width: '24px', height: '24px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 6.253v13m0-13C10.832 5.477 9.246 5 7.5 5S4.168 5.477 3 6.253v13C4.168 18.477 5.754 18 7.5 18s3.332.477 4.5 1.253m0-13C13.168 5.477 14.754 5 16.5 5c1.746 0 3.332.477 4.5 1.253v13C19.832 18.477 18.246 18 16.5 18c-1.746 0-3.332.477-4.5 1.253" />
</svg>
</div>
<div>
<div className="kb-stat-label">Total Documents</div>
<div className="kb-stat-value">
{loading ? '...' : (status?.total_documents || 0)}
</div>
</div>
</div>
<div className="kb-stat-label">文档总数</div>
<div className="kb-stat-progress">
<div
className="kb-stat-progress-bar"
style={{width: loading ? '0%' : `${Math.min((status?.total_documents || 0) * 10, 100)}%`}}
/>
</div>
</div>
<div className="kb-stat-card">
<div className="kb-stat-header">
<div className="kb-stat-icon green">
<svg style={{ width: '24px', height: '24px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M8 7v8a2 2 0 002 2h6M8 7V5a2 2 0 012-2h4.586a1 1 0 01.707.293l4.414 4.414a1 1 0 01.293.707V15a2 2 0 01-2 2v0a2 2 0 01-2-2v-5a2 2 0 00-2-2H8z" />
</svg>
</div>
<div>
<div className="kb-stat-label">Text Chunks</div>
<div className="kb-stat-value">
{loading ? '...' : (status?.total_chunks || 0)}
</div>
</div>
</div>
<div className="kb-stat-label">文本块总数</div>
<div className="kb-stat-progress">
<div
className="kb-stat-progress-bar"
style={{width: loading ? '0%' : `${Math.min((status?.total_chunks || 0) * 2, 100)}%`}}
/>
</div>
</div>
<div className="kb-stat-card">
<div className="kb-stat-header">
<div className="kb-stat-icon purple">
<svg style={{ width: '24px', height: '24px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M4 7v10c0 2.21 3.582 4 8 4s8-1.79 8-4V7M4 7c0 2.21 3.582 4 8 4s8-1.79 8-4M4 7c0-2.21 3.582-4 8-4s8 1.79 8 4m0 5c0 2.21-3.582 4-8 4s-8-1.79-8-4" />
</svg>
</div>
<div>
<div className="kb-stat-label">Vector Store</div>
<div className="kb-stat-value" style={{fontSize: '1.5rem'}}>
{loading ? '...' : (status?.vector_store_type || 'SQLite')}
</div>
</div>
</div>
<div className="kb-stat-label">向量存储</div>
<div className="kb-stat-status">
<div className="kb-status-dot green"></div>
<span>运行中</span>
</div>
</div>
<div className="kb-stat-card">
<div className="kb-stat-header">
<div className="kb-stat-icon orange">
<svg style={{ width: '24px', height: '24px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9.663 17h4.673M12 3v1m6.364 1.636l-.707.707M21 12h-1M4 12H3m3.343-5.657l-.707-.707m2.828 9.9a5 5 0 117.072 0l-.548.547A3.374 3.374 0 0014 18.469V19a2 2 0 11-4 0v-.531c0-.895-.356-1.754-.988-2.386l-.548-.547z" />
</svg>
</div>
<div>
<div className="kb-stat-label">AI Model</div>
<div className="kb-stat-value" style={{fontSize: '1rem'}}>
{loading ? '...' : (status?.embedding_model_name || '未配置')}
</div>
</div>
</div>
<div className="kb-stat-label">嵌入模型</div>
<div className="kb-stat-status">
<div className={`kb-status-dot ${status?.embedding_model_name ? 'green' : 'red'}`}></div>
<span>{status?.embedding_model_name ? '已配置' : '待配置'}</span>
</div>
</div>
</div>
{/* 文件上传区域 */}
<div className="kb-upload-section">
<div className="kb-upload-header">
<div className="kb-upload-icon">
<svg style={{ width: '24px', height: '24px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M7 16a4 4 0 01-.88-7.903A5 5 0 1115.9 6L16 6a5 5 0 011 9.9M9 19l3 3m0 0l3-3m-3 3V10" />
</svg>
</div>
<div>
<div className="kb-upload-title">上传文档</div>
<div className="kb-upload-subtitle">支持多种格式，智能解析文档内容</div>
</div>
</div>
<div>
<div>
<label htmlFor="file-upload" style={{fontSize: '1.1rem', fontWeight: '600', color: '#2d3748', marginBottom: '1rem', display: 'flex', alignItems: 'center', gap: '8px'}}>
<svg style={{ width: '20px', height: '20px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M3 7v10a2 2 0 002 2h14a2 2 0 002-2V9a2 2 0 00-2-2h-6l-2-2H5a2 2 0 00-2 2z" />
</svg>
选择文档文件
</label>
<div style={{marginBottom: '1.5rem'}}>
<div style={{fontSize: '0.9rem', color: '#666', marginBottom: '0.75rem', display: 'flex', alignItems: 'center', gap: '8px'}}>
<Sparkles size={16} />
支持格式:
</div>
<div className="kb-format-tags">
<span className="kb-format-tag txt">
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" />
</svg>
.txt
</span>
<span className="kb-format-tag md">
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z" />
</svg>
.md
</span>
<span className="kb-format-tag pdf">
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 6.253v13m0-13C10.832 5.477 9.246 5 7.5 5S4.168 5.477 3 6.253v13C4.168 18.477 5.754 18 7.5 18s3.332.477 4.5 1.253m0-13C13.168 5.477 14.754 5 16.5 5c1.746 0 3.332.477 4.5 1.253v13C19.832 18.477 18.246 18 16.5 18c-1.746 0-3.332.477-4.5 1.253" />
</svg>
.pdf
</span>
<span className="kb-format-tag docx">
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" />
</svg>
.docx
</span>
</div>
</div>
<div style={{position: 'relative'}}>
<input
id="file-upload"
type="file"
multiple
accept=".txt,.md,.markdown,.pdf,.docx"
onChange={handleFileSelect}
style={{position: 'absolute', inset: '0', width: '100%', height: '100%', opacity: 0, cursor: 'pointer', zIndex: 10}}
/>
<div className="kb-upload-zone">
<div className="kb-upload-zone-icon" style={{ display: 'flex', justifyContent: 'center', marginBottom: '16px' }}>
<FolderOpen size={32} color="#667eea" />
</div>
<h3 className="kb-upload-zone-title">拖拽文件到窗口任意位置</h3>
<p className="kb-upload-zone-subtitle">支持 .txt、.md、.pdf、.docx 格式文档</p>
<div className="kb-upload-zone-button" style={{ display: 'flex', alignItems: 'center', gap: '8px', justifyContent: 'center' }}>
<Target size={16} />
推荐使用拖拽上传
</div>
</div>
</div>
</div>
{selectedFiles.length > 0 && (
<div className="kb-selected-files">
<div className="kb-selected-header">
<div className="kb-selected-icon" style={{ display: 'flex', alignItems: 'center' }}>
<CheckCircle size={20} color="green" />
</div>
<h3 className="kb-selected-title">
已选择 {selectedFiles.length} 个文件
</h3>
<div className="kb-selected-badge">
准备就绪
</div>
</div>
<div className="kb-file-list">
{selectedFiles.map((file, index) => (
<div key={index} className="kb-file-item">
<div className="kb-file-icon" style={{ display: 'flex', alignItems: 'center' }}>
<FileText size={20} color="#667eea" />
</div>
<div className="kb-file-info">
<div className="kb-file-name">{file.name}</div>
<div className="kb-file-meta">
<span className="kb-file-size">{formatFileSize(file.size)}</span>
<span className="kb-file-status">等待上传</span>
</div>
</div>
<div className="kb-file-check" style={{ display: 'flex', alignItems: 'center' }}>
<CheckCircle size={16} color="green" />
</div>
</div>
))}
</div>
</div>
)}
<div className="kb-action-buttons">
<button
onClick={handleUploadDocuments}
disabled={uploading || selectedFiles.length === 0}
className="kb-button primary"
>
{uploading ? (
<>
<div style={{
width: '20px',
height: '20px',
border: '2px solid transparent',
borderTop: '2px solid white',
borderRadius: '50%',
animation: 'spin 1s linear infinite'
}} />
<span>处理中...</span>
</>
) : (
<>
<Upload size={16} />
<span>处理文件 ({selectedFiles.length})</span>
</>
)}
</button>
<button
onClick={loadKnowledgeBaseStatus}
disabled={loading}
className="kb-button secondary"
>
<RefreshCcw size={16} />
<span>刷新状态</span>
</button>
</div>
</div>
</div>
{/* 文档列表 */}
<div className="kb-documents-section">
<div className="kb-documents-header">
<div className="kb-documents-title-group">
<div className="kb-documents-icon" style={{ display: 'flex', alignItems: 'center' }}>
<BookOpen size={24} color="#667eea" />
</div>
<div>
<div className="kb-documents-title">文档库</div>
<div className="kb-documents-subtitle">管理您的知识库文档</div>
</div>
</div>
<button
onClick={handleClearKnowledgeBase}
disabled={!documents.length || loading}
className="kb-button danger"
style={{ display: 'flex', alignItems: 'center', gap: '8px' }}
>
<Trash2 size={16} />
<span>清空知识库</span>
</button>
</div>
<div style={{
overflowX: 'auto',
overflowY: 'visible',
maxHeight: '70vh',
position: 'relative'
}}>
{loading ? (
<div className="kb-loading">
<div className="kb-loading-icon">
<div className="kb-loading-spinner"></div>
<div className="kb-loading-inner" style={{ display: 'flex', alignItems: 'center', justifyContent: 'center' }}>
<BookOpen size={24} color="#667eea" />
</div>
</div>
<h3 className="kb-loading-title">正在加载文档...</h3>
<p className="kb-loading-subtitle">请稍候，正在获取您的知识库内容</p>
<div className="kb-loading-dots">
<div className="kb-loading-dot"></div>
<div className="kb-loading-dot"></div>
<div className="kb-loading-dot"></div>
</div>
</div>
) : documents.length === 0 ? (
<div className="kb-empty">
<div className="kb-empty-icon">
<div className="kb-empty-circle" style={{ display: 'flex', alignItems: 'center', justifyContent: 'center' }}>
<BookOpen size={48} color="#667eea" />
</div>
</div>
<h3 className="kb-empty-title">
知识库等待您的第一份文档
</h3>
<p className="kb-empty-subtitle" style={{ display: 'flex', alignItems: 'center', gap: '8px', justifyContent: 'center' }}>
<Rocket size={16} />
上传一些文档开始使用RAG功能，让AI拥有丰富的知识背景，为您提供更加精准的分析结果
</p>
<div className="kb-empty-formats">
<div className="kb-format-tag pdf" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<File size={16} />
支持 PDF
</div>
<div className="kb-format-tag docx" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<File size={16} />
支持 Word
</div>
<div className="kb-format-tag md" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<File size={16} />
支持 Markdown
</div>
<div className="kb-format-tag txt" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<File size={16} />
支持 TXT
</div>
</div>
<div className="kb-empty-cta" style={{ display: 'flex', alignItems: 'center', gap: '8px', justifyContent: 'center' }}>
<Upload size={16} />
立即上传文档
</div>
</div>
) : (
<div className="kb-table-container">
<table className="kb-table">
<thead>
<tr>
<th>
<div style={{display: 'flex', alignItems: 'center', gap: '0.5rem'}}>
<FileText size={18} />
文档信息
</div>
</th>
<th>
<div style={{display: 'flex', alignItems: 'center', justifyContent: 'center', gap: '0.5rem'}}>
<Scale size={18} />
大小
</div>
</th>
<th>
<div style={{display: 'flex', alignItems: 'center', justifyContent: 'center', gap: '0.5rem'}}>
<Puzzle size={18} />
文本块
</div>
</th>
<th>
<div style={{display: 'flex', alignItems: 'center', justifyContent: 'center', gap: '0.5rem'}}>
<Clock size={18} />
上传时间
</div>
</th>
<th>
<div style={{display: 'flex', alignItems: 'center', justifyContent: 'center', gap: '0.5rem'}}>
<Settings size={18} />
操作
</div>
</th>
</tr>
</thead>
<tbody>
{documents.map((doc, index) => (
<tr key={doc.id}>
<td>
<div className="kb-doc-cell">
<div className="kb-doc-icon-wrapper">
<div className="kb-doc-icon" style={{ display: 'flex', alignItems: 'center', justifyContent: 'center' }}>
<FileText size={20} color="#667eea" />
</div>
<div className="kb-doc-number">{index + 1}</div>
</div>
<div className="kb-doc-info">
<div className="kb-doc-name">
{doc.file_name}
</div>
<div className="kb-doc-meta">
<span className="kb-doc-id">
ID: {doc.id.substring(0, 8)}...
</span>
<span className="kb-doc-status">
已处理
</span>
</div>
{processingDocuments.has(doc.id) && (
<div>
{getProcessingStatusDisplay(doc.id)}
</div>
)}
</div>
</div>
</td>
<td className="kb-cell-center">
<div className="kb-file-size-display">
{formatFileSize(doc.file_size)}
</div>
<div className="kb-file-size-label">
文件大小
</div>
</td>
<td className="kb-cell-center">
<div className="kb-chunks-badge">
<div className="kb-chunks-dot"></div>
{doc.total_chunks} 块
</div>
</td>
<td className="kb-cell-center">
<div className="kb-date-display">
{formatDate(doc.created_at)}
</div>
<div className="kb-date-label">
上传时间
</div>
</td>
<td className="kb-cell-center">
<button
onClick={() => handleDeleteDocument(doc.id, doc.file_name)}
className="kb-delete-button"
style={{ display: 'flex', alignItems: 'center', gap: '8px' }}
>
<div className="kb-delete-content">
<Trash2 size={16} />
<span>删除</span>
</div>
</button>
</td>
</tr>
))}
</tbody>
</table>
</div>
)}
</div>
</div>
</div>
</div>
);
};
export default KnowledgeBaseManagement;
|
000haoji/deep-student
| 9,811 |
src/components/TagManagement.tsx
|
import React, { useState, useEffect } from 'react';
import { invoke } from '@tauri-apps/api/core';
import {
Tag,
TagType,
CreateTagRequest,
TagHierarchy
} from '../types/cogni-graph';
import './TagManagement.css';
interface TagManagementProps {
isInitialized: boolean;
}
const TagManagement: React.FC<TagManagementProps> = ({ isInitialized }) => {
const [tags, setTags] = useState<Tag[]>([]);
const [tagHierarchy, setTagHierarchy] = useState<TagHierarchy[]>([]);
const [loading, setLoading] = useState(false);
const [error, setError] = useState<string | null>(null);
const [showCreateForm, setShowCreateForm] = useState(false);
const [selectedTagType, setSelectedTagType] = useState<TagType>('KnowledgeArea');
const [newTag, setNewTag] = useState<CreateTagRequest>({
name: '',
tag_type: 'Concept',
parent_id: undefined,
description: ''
});
useEffect(() => {
if (isInitialized) {
loadTags();
loadTagHierarchy();
}
}, [isInitialized]);
const loadTags = async () => {
try {
setLoading(true);
const allTags = await invoke<Tag[]>('get_tags_by_type', {
tagType: selectedTagType
});
setTags(allTags);
} catch (err) {
setError(`加载标签失败: ${err}`);
} finally {
setLoading(false);
}
};
const loadTagHierarchy = async () => {
try {
const hierarchy = await invoke<TagHierarchy[]>('get_tag_hierarchy', {
rootTagId: null
});
setTagHierarchy(hierarchy);
} catch (err) {
console.error('加载标签层次失败:', err);
}
};
const createTag = async () => {
if (!newTag.name.trim()) {
setError('标签名称不能为空');
return;
}
try {
setLoading(true);
setError(null);
const tagId = await invoke<string>('create_tag', {
request: {
...newTag,
description: newTag.description || undefined
}
});
// Reset form
setNewTag({
name: '',
tag_type: 'Concept',
parent_id: undefined,
description: ''
});
setShowCreateForm(false);
// Reload tags
await loadTags();
await loadTagHierarchy();
console.log('标签创建成功:', tagId);
} catch (err) {
setError(`创建标签失败: ${err}`);
} finally {
setLoading(false);
}
};
const initializeDefaultHierarchy = async () => {
try {
setLoading(true);
setError(null);
const result = await invoke<string>('initialize_default_tag_hierarchy');
// Reload data
await loadTags();
await loadTagHierarchy();
alert(`默认标签层次初始化成功: ${result}`);
} catch (err) {
setError(`初始化默认层次失败: ${err}`);
} finally {
setLoading(false);
}
};
const renderTagHierarchy = (hierarchies: TagHierarchy[], level: number = 0): JSX.Element[] => {
return hierarchies.map((hierarchy) => (
<div key={hierarchy.tag.id} className={`tag-node level-${level}`}>
<div className="tag-info">
<span className={`tag-type ${hierarchy.tag.tag_type.toLowerCase()}`}>
{hierarchy.tag.tag_type}
</span>
<span className="tag-name">{hierarchy.tag.name}</span>
<span className="tag-level">Level {hierarchy.tag.level}</span>
</div>
{hierarchy.tag.description && (
<div className="tag-description">{hierarchy.tag.description}</div>
)}
{hierarchy.children.length > 0 && (
<div className="tag-children">
{renderTagHierarchy(hierarchy.children, level + 1)}
</div>
)}
</div>
));
};
const getAvailableParents = (): Tag[] => {
return tags.filter(tag => {
// Can only be parent if it's a higher level type
const parentTypes: TagType[] = [];
switch (newTag.tag_type) {
case 'Topic':
parentTypes.push('KnowledgeArea');
break;
case 'Concept':
parentTypes.push('KnowledgeArea', 'Topic');
break;
case 'Method':
parentTypes.push('Topic', 'Concept');
break;
case 'Difficulty':
return []; // Difficulty tags usually standalone
default:
return [];
}
return parentTypes.includes(tag.tag_type);
});
};
if (!isInitialized) {
return (
<div className="tag-management-container">
<div className="not-initialized">
<p>图谱未初始化，请先完成Neo4j连接配置</p>
</div>
</div>
);
}
return (
<div className="tag-management-container">
<div className="tag-management-header">
<h3>标签管理</h3>
<div className="header-actions">
<button
onClick={() => setShowCreateForm(!showCreateForm)}
className="create-tag-btn"
disabled={loading}
>
➕ 创建标签
</button>
<button
onClick={initializeDefaultHierarchy}
className="init-hierarchy-btn"
disabled={loading}
>
🏗️ 初始化默认层次
</button>
</div>
</div>
{error && (
<div className="error-message">
{error}
<button onClick={() => setError(null)}>✕</button>
</div>
)}
{showCreateForm && (
<div className="create-tag-form">
<h4>创建新标签</h4>
<div className="form-group">
<label>标签名称:</label>
<input
type="text"
value={newTag.name}
onChange={(e) => setNewTag({ ...newTag, name: e.target.value })}
placeholder="输入标签名称"
/>
</div>
<div className="form-group">
<label>标签类型:</label>
<select
value={newTag.tag_type}
onChange={(e) => setNewTag({ ...newTag, tag_type: e.target.value as TagType })}
>
<option value="KnowledgeArea">知识领域</option>
<option value="Topic">主题</option>
<option value="Concept">概念</option>
<option value="Method">方法</option>
<option value="Difficulty">难度</option>
</select>
</div>
<div className="form-group">
<label>父标签 (可选):</label>
<select
value={newTag.parent_id || ''}
onChange={(e) => setNewTag({
...newTag,
parent_id: e.target.value || undefined
})}
>
<option value="">无父标签</option>
{getAvailableParents().map(tag => (
<option key={tag.id} value={tag.id}>
{tag.name} ({tag.tag_type})
</option>
))}
</select>
</div>
<div className="form-group">
<label>描述 (可选):</label>
<textarea
value={newTag.description}
onChange={(e) => setNewTag({ ...newTag, description: e.target.value })}
placeholder="输入标签描述"
rows={3}
/>
</div>
<div className="form-actions">
<button onClick={createTag} disabled={loading}>
✅ 创建
</button>
<button onClick={() => setShowCreateForm(false)} disabled={loading}>
❌ 取消
</button>
</div>
</div>
)}
<div className="tag-content">
<div className="tag-list-section">
<div className="section-header">
<h4>标签列表</h4>
<div className="filter-controls">
<label>筛选类型:</label>
<select
value={selectedTagType}
onChange={(e) => {
setSelectedTagType(e.target.value as TagType);
loadTags();
}}
>
<option value="KnowledgeArea">知识领域</option>
<option value="Topic">主题</option>
<option value="Concept">概念</option>
<option value="Method">方法</option>
<option value="Difficulty">难度</option>
</select>
</div>
</div>
{loading ? (
<div className="loading">加载中...</div>
) : (
<div className="tag-list">
{tags.map(tag => (
<div key={tag.id} className="tag-item">
<div className="tag-header">
<span className={`tag-type ${tag.tag_type.toLowerCase()}`}>
{tag.tag_type}
</span>
<span className="tag-name">{tag.name}</span>
<span className="tag-level">L{tag.level}</span>
</div>
{tag.description && (
<div className="tag-description">{tag.description}</div>
)}
<div className="tag-meta">
<span>创建时间: {new Date(tag.created_at).toLocaleDateString()}</span>
</div>
</div>
))}
{tags.length === 0 && (
<div className="no-tags">
暂无 {selectedTagType} 类型的标签
</div>
)}
</div>
)}
</div>
<div className="tag-hierarchy-section">
<h4>标签层次结构</h4>
{tagHierarchy.length > 0 ? (
<div className="hierarchy-tree">
{renderTagHierarchy(tagHierarchy)}
</div>
) : (
<div className="no-hierarchy">
暂无标签层次结构，请先创建标签或初始化默认层次
</div>
)}
</div>
</div>
</div>
);
};
export default TagManagement;
|
0000cd/wolf-set
| 1,667 |
themes/bluf/layouts/partials/head.html
|
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="author" content="{{ .Site.Params.author }}">
<meta name="template" content="bluf">
<meta name="theme-color" content="#0000cd">
<meta name="license" content="{{ .Site.Params.license }}">
<link rel="apple-touch-icon" sizes="180x180" href="/apple-touch-icon.png">
<link rel="icon" type="image/png" sizes="32x32" href="/favicon-32x32.png">
<link rel="icon" type="image/png" sizes="16x16" href="/favicon-16x16.png">
<link rel="manifest" href="/site.webmanifest">
{{/* {{ $style := resources.Get "css/style.css" }}
{{ $secureCSS := $style | resources.Minify | resources.Fingerprint }}
<link rel="stylesheet" href="{{ $secureCSS.RelPermalink }}" integrity="{{ $secureCSS.Data.Integrity }}"> */}}
{{ $style := resources.Get "css/style.css" | resources.ExecuteAsTemplate "css/style.css" . }}
{{ $secureCSS := $style | resources.Minify | resources.Fingerprint }}
<link rel="stylesheet" href="{{ $secureCSS.RelPermalink }}" integrity="{{ $secureCSS.Data.Integrity }}">
{{ if .Site.Params.enableUmami }}
<script defer src="{{ .Site.Params.UmamiLink }}" data-website-id="{{ .Site.Params.UmamiID }}"></script>
{{ end }}
<script>
(function() {
const savedTheme = localStorage.getItem('theme');
if (savedTheme) {
document.documentElement.setAttribute('data-theme', savedTheme);
} else {
const prefersDark = window.matchMedia('(prefers-color-scheme: dark)').matches;
if (prefersDark) {
document.documentElement.setAttribute('data-theme', 'dark');
}
}
})();
</script>
|
000haoji/deep-student
| 19,032 |
src/components/AnkiCardGeneration.css
|
.anki-card-generation {
padding: 20px;
max-width: 1400px;
margin: 0 auto;
background: #f8fafc;
min-height: 100vh;
}
/* 文档处理状态样式 */
.document-processing-status {
background: white;
padding: 20px;
border-radius: 12px;
margin-bottom: 20px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
border-left: 4px solid #3b82f6;
}
.document-info {
display: flex;
gap: 20px;
margin-bottom: 15px;
font-size: 0.875rem;
font-weight: 500;
color: #64748b;
}
.tasks-list {
margin-top: 15px;
}
.task-item {
background: white;
border: 1px solid #ddd;
border-radius: 6px;
padding: 12px;
margin-bottom: 8px;
cursor: pointer;
transition: all 0.2s ease;
}
.task-item:hover {
border-color: #2196f3;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.task-item.selected {
border-color: #2196f3;
background: #f3f8ff;
}
.task-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 8px;
}
.task-id {
font-weight: 600;
color: #333;
}
.task-status {
font-size: 0.75rem;
padding: 2px 6px;
border-radius: 3px;
font-weight: 500;
}
.status-pending { background: #fff3cd; color: #856404; }
.status-processing { background: #d1ecf1; color: #0c5460; }
.status-completed { background: #d4edda; color: #155724; }
.status-failed { background: #f8d7da; color: #721c24; }
.status-truncated { background: #ffeaa7; color: #8b6914; }
.task-status-info {
display: flex;
gap: 8px;
align-items: center;
}
.error-indicator {
background: #f8d7da;
color: #721c24;
font-size: 0.75rem;
padding: 2px 6px;
border-radius: 3px;
font-weight: 500;
}
.error-count {
color: #dc3545;
font-size: 0.75rem;
margin-left: 4px;
}
.error-summary {
background: #f8d7da;
color: #721c24;
padding: 2px 6px;
border-radius: 3px;
font-size: 0.75rem;
font-weight: 500;
}
.completion-indicator {
background: #d4edda;
color: #155724;
padding: 2px 6px;
border-radius: 3px;
font-size: 0.75rem;
font-weight: 500;
}
.generation-status {
text-align: left;
}
.status-main {
font-weight: 500;
margin-bottom: 4px;
}
.status-detail {
font-size: 0.75rem;
color: #64748b;
font-weight: 500;
}
.task-preview {
font-size: 0.875rem;
color: #64748b;
margin-bottom: 8px;
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
}
.task-progress {
display: flex;
align-items: center;
gap: 10px;
}
.progress-bar {
flex: 1;
height: 6px;
background: #e9ecef;
border-radius: 3px;
overflow: hidden;
}
.progress-fill {
height: 100%;
background: linear-gradient(90deg, #28a745, #20c997);
transition: width 0.3s ease;
}
.progress-text {
font-size: 0.75rem;
color: #64748b;
white-space: nowrap;
}
.anki-card-generation h2 {
color: #1e293b;
margin-bottom: 20px;
text-align: center;
font-size: 1.5rem;
font-weight: 600;
padding: 20px;
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
/* 输入区域样式 */
.input-section {
background: white;
padding: 20px;
border-radius: 12px;
margin-bottom: 20px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
.form-group {
margin-bottom: 15px;
}
.form-group label {
display: block;
margin-bottom: 8px;
font-weight: 500;
color: #374151;
}
.form-control {
width: 100%;
padding: 10px 12px;
border: 1px solid #d1d5db;
border-radius: 6px;
font-size: 0.875rem;
transition: border-color 0.2s ease;
}
.form-control:focus {
outline: none;
border-color: #3b82f6;
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
}
.form-row {
display: flex;
gap: 20px;
}
.form-row .form-group {
flex: 1;
}
/* 选项区域 */
.options-section {
border-top: 1px solid #e2e8f0;
padding-top: 20px;
margin-top: 20px;
}
.options-section h4 {
margin-bottom: 15px;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
}
/* 按钮样式 */
.btn {
padding: 8px 16px;
border: none;
border-radius: 6px;
cursor: pointer;
font-size: 0.875rem;
font-weight: 500;
text-decoration: none;
display: inline-flex;
align-items: center;
gap: 6px;
transition: all 0.2s ease;
}
.btn:disabled {
opacity: 0.5;
cursor: not-allowed;
}
.btn-primary {
background: #3b82f6;
color: white;
}
.btn-primary:hover:not(:disabled) {
background: #2563eb;
}
.btn-secondary {
background: #64748b;
color: white;
}
.btn-secondary:hover:not(:disabled) {
background: #475569;
}
.btn-outline {
background-color: transparent;
border: 1px solid #6c757d;
color: #6c757d;
}
.btn-outline:hover:not(:disabled) {
background-color: #6c757d;
color: white;
}
.btn-success {
background: #10b981;
color: white;
margin-right: 10px;
}
.btn-success:hover:not(:disabled) {
background: #059669;
}
.btn-info {
background-color: #17a2b8;
color: white;
}
.btn-info:hover:not(:disabled) {
background-color: #117a8b;
}
.btn-danger {
background-color: #dc3545;
color: white;
}
.btn-danger:hover:not(:disabled) {
background-color: #c82333;
}
.btn-sm {
padding: 4px 8px;
font-size: 0.75rem;
}
/* 错误信息 */
.error-message {
background-color: #f8d7da;
color: #721c24;
padding: 12px;
border-radius: 4px;
border: 1px solid #f5c6cb;
margin-bottom: 20px;
}
/* 卡片预览区域 */
.cards-preview {
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
padding: 20px;
}
.cards-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 1px solid #e2e8f0;
}
.cards-header h3 {
margin: 0;
color: #1e293b;
font-size: 1.25rem;
font-weight: 600;
}
.card-controls {
display: flex;
align-items: center;
gap: 15px;
}
.selected-count {
color: #64748b;
font-size: 0.875rem;
}
/* 卡片列表 */
.cards-list {
max-height: 600px;
overflow-y: auto;
margin-bottom: 20px;
}
.card-item {
border: 1px solid #e2e8f0;
border-radius: 8px;
margin-bottom: 15px;
transition: all 0.2s ease;
background: #f8fafc;
}
.card-item.selected {
border-color: #3b82f6;
box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
}
.card-item.error-card {
border-color: #dc3545;
background: #fff5f5;
}
.card-item.error-card .card-number {
color: #dc3545;
font-weight: 600;
}
.error-content {
background: #f8d7da;
border: 1px solid #f5c6cb;
border-radius: 4px;
padding: 10px;
margin: 10px 15px;
}
.error-content label {
color: #721c24;
font-weight: 600;
margin-bottom: 5px;
display: block;
}
.error-text {
color: #721c24;
font-size: 0.875rem;
}
.card-header {
display: flex;
align-items: center;
gap: 10px;
padding: 12px 15px;
background-color: #f1f5f9;
border-bottom: 1px solid #e2e8f0;
}
.card-number {
font-weight: 600;
color: #1e293b;
flex-grow: 1;
}
.card-content {
padding: 15px;
}
.card-field {
margin-bottom: 15px;
}
.card-field:last-child {
margin-bottom: 0;
}
.card-field label {
display: block;
margin-bottom: 8px;
font-weight: 500;
color: #374151;
font-size: 0.875rem;
}
/* 标签样式 */
.tags {
display: flex;
flex-wrap: wrap;
gap: 8px;
}
.tag {
background-color: #e2e8f0;
color: #1e293b;
padding: 4px 8px;
border-radius: 12px;
font-size: 0.75rem;
font-weight: 500;
}
/* 输出操作区域 - 增强版 */
.output-actions {
border-top: 1px solid #e2e8f0;
padding-top: 20px;
}
.export-options, .anki-connect-actions {
background: #f8fafc;
border: 1px solid #e2e8f0;
border-radius: 8px;
padding: 15px;
margin-bottom: 15px;
}
.export-options h5, .anki-connect-actions h5 {
margin: 0 0 10px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
}
.export-buttons {
display: flex;
gap: 8px;
flex-wrap: wrap;
}
.export-buttons .btn {
flex: 0 0 auto;
}
/* 响应式设计 */
@media (max-width: 1200px) {
.advanced-options .form-row {
flex-wrap: wrap;
}
.advanced-options .form-group {
min-width: 250px;
flex-basis: calc(50% - 10px);
}
}
@media (max-width: 768px) {
.anki-card-generation {
padding: 15px;
}
.form-row {
flex-direction: column;
}
.cards-header {
flex-direction: column;
align-items: flex-start;
gap: 10px;
}
.card-controls {
width: 100%;
justify-content: space-between;
}
.output-actions {
display: flex;
flex-direction: column;
gap: 10px;
}
.btn {
width: 100%;
}
}
/* 滚动条样式 */
.cards-list::-webkit-scrollbar {
width: 8px;
}
.cards-list::-webkit-scrollbar-track {
background: #f1f1f1;
border-radius: 4px;
}
.cards-list::-webkit-scrollbar-thumb {
background: #c1c1c1;
border-radius: 4px;
}
.cards-list::-webkit-scrollbar-thumb:hover {
background: #a8a8a8;
}
/* AnkiConnect状态样式 */
.anki-status {
margin-bottom: 15px;
padding: 15px;
background-color: #f8fafc;
border: 1px solid #e2e8f0;
border-radius: 8px;
}
.status-indicator {
display: flex;
align-items: center;
margin-bottom: 5px;
}
.status-label {
font-weight: 500;
color: #374151;
margin-right: 8px;
}
.status-checking {
color: #64748b;
font-style: italic;
}
.status-available {
color: #10b981;
font-weight: 600;
}
.status-unavailable {
color: #dc3545;
font-weight: 600;
}
.connection-error {
margin-top: 8px;
padding: 8px 12px;
background-color: #f8d7da;
color: #721c24;
border-radius: 4px;
font-size: 0.875rem;
border: 1px solid #f5c6cb;
}
/* 按钮增强样式 */
.btn:disabled {
opacity: 0.65;
cursor: not-allowed;
}
.btn-info:disabled {
background-color: #6c757d;
border-color: #6c757d;
}
.btn-info:disabled:hover {
background-color: #6c757d;
border-color: #6c757d;
}
/* 高级选项样式 */
.advanced-options {
margin-top: 20px;
padding: 15px;
background-color: #f8fafc;
border: 1px solid #e2e8f0;
border-radius: 8px;
}
.advanced-options h5 {
margin: 0 0 15px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
border-bottom: 1px solid #e2e8f0;
padding-bottom: 8px;
}
.form-help {
display: block;
color: #64748b;
font-size: 0.75rem;
margin-top: 4px;
line-height: 1.3;
word-wrap: break-word;
overflow-wrap: break-word;
max-width: 100%;
white-space: normal;
}
/* 增强form-row在高级选项中的显示 */
.advanced-options .form-row {
gap: 20px;
}
.advanced-options .form-group {
min-width: 200px;
flex: 1;
overflow: hidden; /* 防止内容溢出 */
}
.advanced-options .form-group .form-help {
word-break: break-word; /* 强制长词换行 */
hyphens: auto; /* 自动断字 */
}
/* 添加全局字体样式 */
.anki-card-generation {
font-family: inherit;
}
.anki-card-generation * {
font-family: inherit;
}
/* 数字输入框样式增强 */
.form-control[type="number"] {
text-align: right;
}
/* 文件上传区域样式 */
.upload-zone {
border: 2px dashed #cbd5e1;
border-radius: 12px;
padding: 20px;
margin-top: 10px;
text-align: center;
transition: all 0.3s ease;
background: #f8fafc;
}
.upload-zone.drag-over {
border-color: #3b82f6;
background: #eff6ff;
}
.upload-zone.uploading {
opacity: 0.7;
pointer-events: none;
}
.upload-content {
display: flex;
flex-direction: column;
align-items: center;
gap: 12px;
}
.upload-icon {
font-size: 2.5rem;
color: #64748b;
}
.upload-text {
font-size: 1rem;
font-weight: 500;
color: #334155;
}
.upload-hint {
font-size: 0.875rem;
color: #64748b;
}
/* 选中文件列表 */
.selected-files {
margin-top: 15px;
padding: 15px;
background: #f1f5f9;
border-radius: 8px;
}
.selected-files h4 {
margin: 0 0 12px 0;
color: #1e293b;
font-size: 1rem;
font-weight: 600;
}
.file-list {
display: flex;
flex-direction: column;
gap: 8px;
margin-bottom: 12px;
}
.file-item {
display: flex;
justify-content: space-between;
align-items: center;
padding: 8px 12px;
background: white;
border-radius: 6px;
border: 1px solid #e2e8f0;
}
.file-name {
flex: 1;
font-weight: 500;
color: #1e293b;
font-size: 0.875rem;
}
.file-size {
font-size: 0.75rem;
color: #64748b;
margin-right: 10px;
}
.btn-remove {
background: #fee2e2;
color: #dc2626;
border: none;
border-radius: 4px;
width: 20px;
height: 20px;
cursor: pointer;
display: flex;
align-items: center;
justify-content: center;
font-size: 0.75rem;
}
.btn-remove:hover {
background: #fecaca;
}
.upload-actions {
display: flex;
gap: 10px;
}
/* 增强的错误提示样式 */
.error-message {
display: flex;
align-items: center;
gap: 8px;
margin: 15px 0;
padding: 12px 16px;
background-color: #f8d7da;
color: #721c24;
border: 1px solid #f5c6cb;
border-radius: 6px;
font-size: 0.875rem;
line-height: 1.4;
}
.error-icon {
font-size: 1rem;
flex-shrink: 0;
}
.error-text {
flex: 1;
}
/* 加载状态指示器样式 */
.loading-indicator {
display: flex;
align-items: center;
gap: 12px;
margin: 15px 0;
padding: 12px 16px;
background-color: #e7f3ff;
color: #0066cc;
border: 1px solid #b3d9ff;
border-radius: 6px;
font-size: 0.875rem;
}
.loading-spinner {
width: 1rem;
height: 1rem;
border: 2px solid #b3d9ff;
border-top: 2px solid #0066cc;
border-radius: 50%;
animation: spin 1s linear infinite;
flex-shrink: 0;
}
.loading-text {
font-weight: 500;
}
/* 旋转动画 */
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
/* 改进现有错误消息样式以保持一致性 */
.connection-error {
margin-top: 8px;
padding: 8px 12px;
background-color: #fff3cd;
color: #856404;
border-radius: 4px;
font-size: 0.875rem;
border: 1px solid #ffeaa7;
}
/* 成功状态样式 */
.success-message {
display: flex;
align-items: center;
gap: 8px;
margin: 15px 0;
padding: 12px 16px;
background-color: #d4edda;
color: #155724;
border: 1px solid #c3e6cb;
border-radius: 6px;
font-size: 0.875rem;
line-height: 1.4;
}
.success-message .success-icon {
font-size: 1rem;
flex-shrink: 0;
}/* Template Selector Styles */
.template-section {
margin: 20px 0;
padding: 20px;
background: #f8fafc;
border: 1px solid #e2e8f0;
border-radius: 12px;
}
.template-section h5 {
margin: 0 0 16px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
display: flex;
align-items: center;
gap: 8px;
}
.template-selector {
display: flex;
flex-direction: column;
gap: 16px;
}
.template-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 16px;
margin-bottom: 16px;
}
.template-option {
background: white;
border: 2px solid #e2e8f0;
border-radius: 12px;
padding: 16px;
cursor: pointer;
transition: all 0.2s ease;
position: relative;
overflow: hidden;
}
.template-option:hover {
border-color: #3b82f6;
box-shadow: 0 4px 12px rgba(59, 130, 246, 0.15);
transform: translateY(-2px);
}
.template-option.selected {
border-color: #3b82f6;
background: linear-gradient(135deg, #eff6ff 0%, #dbeafe 100%);
box-shadow: 0 4px 16px rgba(59, 130, 246, 0.2);
}
.template-option.selected::before {
content: "✓";
position: absolute;
top: 12px;
right: 12px;
width: 24px;
height: 24px;
background: #3b82f6;
color: white;
border-radius: 50%;
display: flex;
align-items: center;
justify-content: center;
font-size: 14px;
font-weight: bold;
}
.template-preview {
margin-bottom: 12px;
min-height: 80px;
display: flex;
flex-direction: column;
gap: 8px;
overflow: visible;
}
.preview-front, .preview-back {
padding: 8px 12px;
border-radius: 6px;
font-size: 0.875rem;
line-height: 1.4;
}
.preview-front {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
font-weight: 500;
}
.preview-back {
background: linear-gradient(135deg, #11998e 0%, #38ef7d 100%);
color: white;
font-weight: 500;
}
.template-info {
text-align: left;
}
.template-name {
font-size: 1rem;
font-weight: 600;
color: #1e293b;
margin-bottom: 4px;
}
.template-desc {
font-size: 0.875rem;
color: #64748b;
line-height: 1.4;
margin-bottom: 8px;
}
.template-fields {
font-size: 0.75rem;
color: #3b82f6;
background: #eff6ff;
padding: 4px 8px;
border-radius: 4px;
font-weight: 500;
}
.template-actions {
display: flex;
justify-content: center;
margin-bottom: 16px;
}
.template-preview-detail {
background: white;
border: 1px solid #e2e8f0;
border-radius: 12px;
padding: 20px;
margin-top: 16px;
}
.template-preview-detail h6 {
margin: 0 0 16px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
text-align: center;
padding-bottom: 12px;
border-bottom: 2px solid #e2e8f0;
}
.template-info-detail {
background: #f8fafc;
padding: 16px;
border-radius: 8px;
margin-bottom: 20px;
font-size: 0.875rem;
line-height: 1.5;
}
.template-description,
.template-fields-detail,
.template-usage {
margin-bottom: 12px;
}
.template-description strong,
.template-fields-detail strong,
.template-usage strong {
color: #374151;
margin-right: 8px;
}
.field-list {
display: inline-flex;
flex-wrap: wrap;
gap: 4px;
margin-left: 8px;
}
.field-tag {
background: #dbeafe;
color: #1e40af;
padding: 2px 6px;
border-radius: 4px;
font-size: 0.75rem;
font-weight: 500;
}
.preview-container {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 20px;
margin-top: 20px;
}
.preview-card {
border: 1px solid #e2e8f0;
border-radius: 8px;
overflow: hidden;
background: white;
}
.preview-label {
background: #f1f5f9;
padding: 12px 16px;
font-weight: 600;
color: #374151;
font-size: 0.875rem;
text-transform: uppercase;
letter-spacing: 0.5px;
border-bottom: 1px solid #e2e8f0;
flex-shrink: 0;
}
.preview-content {
padding: 16px;
min-height: 120px;
font-size: 0.875rem;
line-height: 1.5;
word-wrap: break-word;
overflow: hidden;
display: flex;
flex-direction: column;
height: auto;
}
/* 确保模板预览区域的样式不被外部CSS干扰 */
.template-preview-detail .preview-content * {
box-sizing: border-box;
}
.template-preview-detail .preview-content .card {
margin: 0;
transform: scale(0.85);
transform-origin: top center;
width: 100%;
height: auto;
overflow: hidden;
}
/* 优化模板预览的显示效果 */
.template-preview-detail {
background: white;
border: 1px solid #e2e8f0;
border-radius: 12px;
padding: 20px;
margin-top: 16px;
overflow: hidden;
}
.preview-container {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 20px;
margin-top: 20px;
align-items: start;
}
.preview-card {
border: 1px solid #e2e8f0;
border-radius: 8px;
overflow: hidden;
background: white;
box-shadow: 0 2px 4px rgba(0,0,0,0.05);
height: auto;
min-height: 200px;
display: flex;
flex-direction: column;
}
/* Responsive template grid */
@media (max-width: 768px) {
.template-grid {
grid-template-columns: 1fr;
gap: 12px;
}
.preview-container {
grid-template-columns: 1fr;
gap: 16px;
}
.template-option {
padding: 14px;
}
.template-preview {
min-height: 70px;
overflow: visible;
}
.preview-front, .preview-back {
padding: 6px 10px;
font-size: 0.8rem;
}
.template-preview-detail .preview-content .card {
transform: scale(0.75);
overflow: hidden;
}
.preview-container {
grid-template-columns: 1fr;
}
}
|
000haoji/deep-student
| 1,224 |
src/components/DataStats.tsx
|
import { useState, useEffect } from 'react';
import { TauriAPI } from '../utils/tauriApi';
interface DataStatsProps {
className?: string;
}
export const DataStats: React.FC<DataStatsProps> = ({ className }) => {
const [mistakeCount, setMistakeCount] = useState(0);
const [loading, setLoading] = useState(true);
useEffect(() => {
const loadStats = async () => {
try {
const mistakes = await TauriAPI.getMistakes();
setMistakeCount(mistakes.length);
} catch (error) {
console.error('加载统计数据失败:', error);
} finally {
setLoading(false);
}
};
loadStats();
}, []);
if (loading) {
return <div className={className}>加载中...</div>;
}
return (
<div className={className}>
<div className="stat-item">
<span className="stat-label">错题总数:</span>
<span className="stat-value">{mistakeCount}</span>
</div>
<div className="stat-item">
<span className="stat-label">回顾分析:</span>
<span className="stat-value">0</span>
</div>
<div className="stat-item">
<span className="stat-label">存储大小:</span>
<span className="stat-value">计算中...</span>
</div>
</div>
);
};
|
000haoji/deep-student
| 38,208 |
src/components/DataImportExport.tsx
|
import React, { useState } from 'react';
import { TauriAPI } from '../utils/tauriApi';
import { DataStats } from './DataStats';
import { Upload, Download, BarChart3, AlertTriangle, Trash2, Lightbulb, FileText, Calendar, HardDrive, Settings } from 'lucide-react';
interface DataImportExportProps {
onClose?: () => void;
}
export const DataImportExport: React.FC<DataImportExportProps> = ({ onClose }) => {
const [isExporting, setIsExporting] = useState(false);
const [isImporting, setIsImporting] = useState(false);
const [importFile, setImportFile] = useState<File | null>(null);
const [exportFormat, setExportFormat] = useState<'json' | 'csv'>('json');
const [isExportingSettings, setIsExportingSettings] = useState(false);
const [isImportingSettings, setIsImportingSettings] = useState(false);
const [settingsImportFile, setSettingsImportFile] = useState<File | null>(null);
// 导出数据
const handleExport = async () => {
setIsExporting(true);
try {
console.log('开始导出完整数据...');
// 并行获取所有数据
const [
rawMistakes,
statistics,
apiConfigs,
modelAssignments,
subjectConfigs
] = await Promise.all([
TauriAPI.getMistakes(),
TauriAPI.getStatistics(),
TauriAPI.getApiConfigurations(),
TauriAPI.getModelAssignments(),
TauriAPI.getAllSubjectConfigs(false) // 包括禁用的配置
]);
// 新增：将图片文件转换为Base64包含在备份中
console.log('开始处理图片备份，错题数量:', rawMistakes.length);
const mistakesWithImages = await Promise.all(
rawMistakes.map(async (mistake) => {
try {
// 处理问题图片
const questionImageData = await Promise.all(
mistake.question_images.map(async (imagePath) => {
try {
const base64Data = await TauriAPI.getImageAsBase64(imagePath);
return {
path: imagePath,
data: base64Data
};
} catch (error) {
console.warn(`备份图片失败: ${imagePath}`, error);
return {
path: imagePath,
data: null
};
}
})
);
// 处理解析图片
const analysisImageData = await Promise.all(
mistake.analysis_images.map(async (imagePath) => {
try {
const base64Data = await TauriAPI.getImageAsBase64(imagePath);
return {
path: imagePath,
data: base64Data
};
} catch (error) {
console.warn(`备份解析图片失败: ${imagePath}`, error);
return {
path: imagePath,
data: null
};
}
})
);
return {
...mistake,
question_image_data: questionImageData,
analysis_image_data: analysisImageData
};
} catch (error) {
console.warn(`处理错题图片失败: ${mistake.id}`, error);
return mistake;
}
})
);
console.log('图片备份处理完成');
const mistakes = mistakesWithImages;
// 获取系统设置（尝试获取常见设置键）
const settingKeys = [
'theme', 'language', 'auto_save', 'default_subject',
'api_configs', 'model_assignments', 'model_adapter_options'
];
const settings: Record<string, any> = {};
for (const key of settingKeys) {
try {
const value = await TauriAPI.getSetting(key);
if (value !== null) {
settings[key] = value;
}
} catch (error) {
console.warn(`获取设置失败 ${key}:`, error);
}
}
const exportData = {
version: '2.0', // 升级版本号以支持完整数据
timestamp: new Date().toISOString(),
data: {
mistakes,
reviews: [], // 目前回顾数据存储在错题聊天记录中
settings: {
system_settings: settings,
api_configurations: apiConfigs,
model_assignments: modelAssignments,
subject_configurations: subjectConfigs
},
statistics
}
};
// 统计图片备份信息
const imageStats = mistakes.reduce((stats: any, mistake: any) => {
stats.totalQuestionImages += mistake.question_images?.length || 0;
stats.totalAnalysisImages += mistake.analysis_images?.length || 0;
stats.successfulQuestionImages += mistake.question_image_data?.filter((img: any) => img.data).length || 0;
stats.successfulAnalysisImages += mistake.analysis_image_data?.filter((img: any) => img.data).length || 0;
return stats;
}, {
totalQuestionImages: 0,
totalAnalysisImages: 0,
successfulQuestionImages: 0,
successfulAnalysisImages: 0
});
console.log('导出数据统计:', {
错题数量: mistakes.length,
系统设置: Object.keys(settings).length,
API配置: apiConfigs.length,
科目配置: subjectConfigs.length,
图片备份: {
问题图片总数: imageStats.totalQuestionImages,
解析图片总数: imageStats.totalAnalysisImages,
成功备份问题图片: imageStats.successfulQuestionImages,
成功备份解析图片: imageStats.successfulAnalysisImages,
图片备份成功率: imageStats.totalQuestionImages + imageStats.totalAnalysisImages > 0
? `${((imageStats.successfulQuestionImages + imageStats.successfulAnalysisImages) / (imageStats.totalQuestionImages + imageStats.totalAnalysisImages) * 100).toFixed(1)}%`
: '无图片'
}
});
if (exportFormat === 'json') {
// JSON格式导出
const dataStr = JSON.stringify(exportData, null, 2);
const dataBlob = new Blob([dataStr], { type: 'application/json' });
const link = document.createElement('a');
link.href = URL.createObjectURL(dataBlob);
link.download = `ai-mistake-manager-backup-${new Date().toISOString().split('T')[0]}.json`;
link.click();
URL.revokeObjectURL(link.href);
} else {
// CSV格式导出（仅错题数据）
const csvHeader = 'ID,科目,创建时间,问题描述,题目类型,标签,OCR文本\n';
const csvRows = mistakes.map(mistake => {
const row = [
mistake.id,
mistake.subject,
mistake.created_at,
`"${mistake.user_question.replace(/"/g, '""')}"`,
mistake.mistake_type,
`"${mistake.tags.join(', ')}"`,
`"${mistake.ocr_text.replace(/"/g, '""')}"`
];
return row.join(',');
}).join('\n');
const csvContent = csvHeader + csvRows;
const csvBlob = new Blob([csvContent], { type: 'text/csv;charset=utf-8;' });
const link = document.createElement('a');
link.href = URL.createObjectURL(csvBlob);
link.download = `ai-mistake-manager-mistakes-${new Date().toISOString().split('T')[0]}.csv`;
link.click();
URL.revokeObjectURL(link.href);
}
alert('数据导出成功！');
} catch (error) {
console.error('导出失败:', error);
alert('导出失败: ' + error);
} finally {
setIsExporting(false);
}
};
// 导出系统设置
const handleExportSettings = async () => {
setIsExportingSettings(true);
try {
console.log('开始导出系统设置...');
// 并行获取系统设置数据
const [
apiConfigs,
modelAssignments,
subjectConfigs
] = await Promise.all([
TauriAPI.getApiConfigurations(),
TauriAPI.getModelAssignments(),
TauriAPI.getAllSubjectConfigs(false) // 包括禁用的配置
]);
// 获取系统设置（尝试获取常见设置键）
const settingKeys = [
'theme', 'language', 'auto_save', 'default_subject',
'api_configs', 'model_assignments', 'model_adapter_options'
];
const systemSettings: Record<string, any> = {};
for (const key of settingKeys) {
try {
const value = await TauriAPI.getSetting(key);
if (value !== null) {
systemSettings[key] = value;
}
} catch (error) {
console.warn(`获取设置失败 ${key}:`, error);
}
}
const exportData = {
version: '2.0',
type: 'settings_only',
timestamp: new Date().toISOString(),
settings: {
system_settings: systemSettings,
api_configurations: apiConfigs,
model_assignments: modelAssignments,
subject_configurations: subjectConfigs
}
};
console.log('导出系统设置统计:', {
系统设置: Object.keys(systemSettings).length,
API配置: apiConfigs.length,
科目配置: subjectConfigs.length
});
const dataStr = JSON.stringify(exportData, null, 2);
const dataBlob = new Blob([dataStr], { type: 'application/json' });
const link = document.createElement('a');
link.href = URL.createObjectURL(dataBlob);
link.download = `ai-mistake-manager-settings-${new Date().toISOString().split('T')[0]}.json`;
link.click();
URL.revokeObjectURL(link.href);
alert('系统设置导出成功！');
} catch (error) {
console.error('系统设置导出失败:', error);
alert('系统设置导出失败: ' + error);
} finally {
setIsExportingSettings(false);
}
};
// 导入系统设置
const handleImportSettings = async () => {
if (!settingsImportFile) {
alert('请选择要导入的系统设置文件');
return;
}
setIsImportingSettings(true);
try {
const fileContent = await readFileAsText(settingsImportFile);
const importData = JSON.parse(fileContent);
if (!importData.settings || importData.type !== 'settings_only') {
throw new Error('无效的系统设置备份文件格式');
}
// 确认导入
const settingsInfo = {
系统设置: Object.keys(importData.settings.system_settings || {}).length,
API配置: (importData.settings.api_configurations || []).length,
模型分配: importData.settings.model_assignments ? 1 : 0,
科目配置: (importData.settings.subject_configurations || []).length
};
const confirmMessage = `
即将导入系统设置（备份版本: ${importData.version || '1.0'}）：
- 系统设置: ${settingsInfo.系统设置} 项
- API配置: ${settingsInfo.API配置} 个
- 模型分配: ${settingsInfo.模型分配 > 0 ? '包含' : '无'}
- 科目配置: ${settingsInfo.科目配置} 个
- 备份时间: ${new Date(importData.timestamp).toLocaleString('zh-CN')}
注意：导入将覆盖现有系统设置，是否继续？
`;
if (!confirm(confirmMessage.trim())) {
return;
}
console.log('开始导入系统设置...');
let importResults = {
settings: 0,
apiConfigs: 0,
modelAssignments: 0,
subjectConfigs: 0
};
// 导入系统设置
if (importData.settings.system_settings) {
for (const [key, value] of Object.entries(importData.settings.system_settings)) {
try {
await TauriAPI.saveSetting(key, String(value));
importResults.settings++;
} catch (error) {
console.warn(`导入设置失败 ${key}:`, error);
}
}
}
// 导入API配置
if (importData.settings.api_configurations) {
try {
await TauriAPI.saveApiConfigurations(importData.settings.api_configurations);
importResults.apiConfigs = importData.settings.api_configurations.length;
console.log('API配置导入成功');
} catch (error) {
console.warn('API配置导入失败:', error);
}
}
// 导入模型分配
if (importData.settings.model_assignments) {
try {
await TauriAPI.saveModelAssignments(importData.settings.model_assignments);
importResults.modelAssignments = 1;
console.log('模型分配导入成功');
} catch (error) {
console.warn('模型分配导入失败:', error);
}
}
// 导入科目配置
if (importData.settings.subject_configurations) {
console.log('科目配置导入功能需要后端API支持，暂时跳过');
}
const successMessage = `
系统设置导入完成！统计信息：
- 系统设置：${importResults.settings} 项
- API配置：${importResults.apiConfigs} 个
- 模型分配：${importResults.modelAssignments > 0 ? '已更新' : '无'}
页面将刷新以应用更改。
`;
alert(successMessage.trim());
window.location.reload();
} catch (error) {
console.error('系统设置导入失败:', error);
alert('系统设置导入失败: ' + error);
} finally {
setIsImportingSettings(false);
setSettingsImportFile(null);
}
};
// 导入数据
const handleImport = async () => {
if (!importFile) {
alert('请选择要导入的文件');
return;
}
setIsImporting(true);
try {
const fileContent = await readFileAsText(importFile);
if (importFile.name.endsWith('.json')) {
// JSON格式导入
const importData = JSON.parse(fileContent);
if (!importData.data || !importData.data.mistakes) {
throw new Error('无效的备份文件格式');
}
// 确认导入
const settingsInfo = importData.data.settings ? {
系统设置: Object.keys(importData.data.settings.system_settings || {}).length,
API配置: (importData.data.settings.api_configurations || []).length,
模型分配: importData.data.settings.model_assignments ? 1 : 0,
科目配置: (importData.data.settings.subject_configurations || []).length
} : {};
// 统计图片备份信息
const imageBackupStats = importData.data.mistakes.reduce((stats: any, mistake: any) => {
if (mistake.question_image_data) {
stats.totalQuestionImages += mistake.question_image_data.length;
stats.backedUpQuestionImages += mistake.question_image_data.filter((img: any) => img.data).length;
}
if (mistake.analysis_image_data) {
stats.totalAnalysisImages += mistake.analysis_image_data.length;
stats.backedUpAnalysisImages += mistake.analysis_image_data.filter((img: any) => img.data).length;
}
return stats;
}, {
totalQuestionImages: 0,
totalAnalysisImages: 0,
backedUpQuestionImages: 0,
backedUpAnalysisImages: 0
});
const totalImages = imageBackupStats.totalQuestionImages + imageBackupStats.totalAnalysisImages;
const backedUpImages = imageBackupStats.backedUpQuestionImages + imageBackupStats.backedUpAnalysisImages;
const confirmMessage = `
即将导入数据（备份版本: ${importData.version || '1.0'}）：
- 错题数量: ${importData.data.mistakes.length}
- 系统设置: ${settingsInfo.系统设置 || 0} 项
- API配置: ${settingsInfo.API配置 || 0} 个
- 模型分配: ${(settingsInfo.模型分配 || 0) > 0 ? '包含' : '无'}
- 科目配置: ${settingsInfo.科目配置 || 0} 个
- 图片备份: ${totalImages > 0 ? `${backedUpImages}/${totalImages} (${(backedUpImages/totalImages*100).toFixed(1)}%)` : '无图片'}
- 备份时间: ${new Date(importData.timestamp).toLocaleString('zh-CN')}
注意：导入将覆盖现有数据，是否继续？
`;
if (!confirm(confirmMessage.trim())) {
return;
}
console.log('开始导入完整数据...');
let importResults = {
mistakes: 0,
settings: 0,
apiConfigs: 0,
modelAssignments: 0,
subjectConfigs: 0
};
// 1. 预处理：恢复图片文件
console.log('开始恢复图片文件...');
const mistakesToImport = [];
for (const mistake of importData.data.mistakes) {
try {
const processedMistake = { ...mistake };
// 🎯 处理问题图片
if (mistake.question_image_data && mistake.question_image_data.length > 0) {
const newQuestionImages = [];
for (const imageInfo of mistake.question_image_data) {
if (imageInfo.data) {
try {
// 从备份的Base64数据恢复图片文件
const newPath = await TauriAPI.saveImageFromBase64(imageInfo.data, imageInfo.path);
newQuestionImages.push(newPath);
console.log(`恢复问题图片成功: ${imageInfo.path} -> ${newPath}`);
} catch (error) {
console.warn(`恢复问题图片失败: ${imageInfo.path}`, error);
// 如果恢复失败，使用原路径（可能不存在）
newQuestionImages.push(imageInfo.path);
}
} else {
// 没有备份数据，使用原路径
newQuestionImages.push(imageInfo.path);
}
}
processedMistake.question_images = newQuestionImages;
}
// 🎯 处理解析图片
if (mistake.analysis_image_data && mistake.analysis_image_data.length > 0) {
const newAnalysisImages = [];
for (const imageInfo of mistake.analysis_image_data) {
if (imageInfo.data) {
try {
const newPath = await TauriAPI.saveImageFromBase64(imageInfo.data, imageInfo.path);
newAnalysisImages.push(newPath);
console.log(`恢复解析图片成功: ${imageInfo.path} -> ${newPath}`);
} catch (error) {
console.warn(`恢复解析图片失败: ${imageInfo.path}`, error);
newAnalysisImages.push(imageInfo.path);
}
} else {
newAnalysisImages.push(imageInfo.path);
}
}
processedMistake.analysis_images = newAnalysisImages;
}
// 清理临时的图片数据字段，避免传递到后端
delete processedMistake.question_image_data;
delete processedMistake.analysis_image_data;
mistakesToImport.push(processedMistake);
} catch (error) {
console.warn(`处理错题失败: ${mistake.id}`, error);
mistakesToImport.push(mistake);
}
}
console.log('图片恢复完成，开始导入错题数据...');
// 2. 导入错题数据 - 使用批量操作
if (mistakesToImport.length > 0) {
try {
await TauriAPI.batchSaveMistakes(mistakesToImport);
importResults.mistakes = mistakesToImport.length;
console.log(`批量导入 ${mistakesToImport.length} 道错题成功`);
} catch (error) {
console.error('批量导入失败，尝试逐个导入:', error);
// 如果批量操作失败，回退到逐个保存
let successCount = 0;
for (const mistake of mistakesToImport) {
try {
await TauriAPI.updateMistake(mistake);
successCount++;
} catch (error) {
console.warn('导入错题失败:', mistake.id, error);
}
}
importResults.mistakes = successCount;
console.log(`逐个导入完成，成功: ${successCount}/${mistakesToImport.length}`);
}
}
// 2. 导入设置数据
if (importData.data.settings) {
// 导入系统设置
if (importData.data.settings.system_settings) {
for (const [key, value] of Object.entries(importData.data.settings.system_settings)) {
try {
await TauriAPI.saveSetting(key, String(value));
importResults.settings++;
} catch (error) {
console.warn(`导入设置失败 ${key}:`, error);
}
}
}
// 导入API配置
if (importData.data.settings.api_configurations) {
try {
await TauriAPI.saveApiConfigurations(importData.data.settings.api_configurations);
importResults.apiConfigs = importData.data.settings.api_configurations.length;
console.log('API配置导入成功');
} catch (error) {
console.warn('API配置导入失败:', error);
}
}
// 导入模型分配
if (importData.data.settings.model_assignments) {
try {
await TauriAPI.saveModelAssignments(importData.data.settings.model_assignments);
importResults.modelAssignments = 1;
console.log('模型分配导入成功');
} catch (error) {
console.warn('模型分配导入失败:', error);
}
}
// 导入科目配置（如果支持）
if (importData.data.settings.subject_configurations) {
// 注意：科目配置导入需要逐个处理，因为可能涉及创建或更新
for (const config of importData.data.settings.subject_configurations) {
try {
// 这里可能需要检查是创建还是更新
// 为简化，我们尝试更新，如果失败则跳过
console.log('科目配置导入功能需要后端API支持，暂时跳过');
} catch (error) {
console.warn('科目配置导入失败:', error);
}
}
}
}
const successMessage = `
导入完成！统计信息：
- 错题：${importResults.mistakes} 条
- 系统设置：${importResults.settings} 项
- API配置：${importResults.apiConfigs} 个
- 模型分配：${importResults.modelAssignments > 0 ? '已更新' : '无'}
页面将刷新以应用更改。
`;
alert(successMessage.trim());
window.location.reload();
} else if (importFile.name.endsWith('.csv')) {
// CSV格式导入（仅错题数据）
const lines = fileContent.split('\n');
const header = lines[0];
if (!header.includes('ID') || !header.includes('科目')) {
throw new Error('CSV文件格式不正确');
}
const mistakes = [];
for (let i = 1; i < lines.length; i++) {
const line = lines[i].trim();
if (!line) continue;
const values = parseCSVLine(line);
if (values.length >= 7) {
mistakes.push({
id: values[0],
subject: values[1],
created_at: values[2],
updated_at: values[2], // 使用创建时间作为更新时间
user_question: values[3],
mistake_type: values[4],
tags: values[5].split(', ').filter((tag: string) => tag.trim()),
ocr_text: values[6],
question_images: [],
analysis_images: [],
status: 'completed',
chat_history: []
});
}
}
if (mistakes.length === 0) {
throw new Error('CSV文件中没有有效的错题数据');
}
if (!confirm(`即将导入 ${mistakes.length} 道错题，是否继续？`)) {
return;
}
// 使用批量保存错题
try {
await TauriAPI.batchSaveMistakes(mistakes);
alert(`成功批量导入 ${mistakes.length} 道错题！`);
} catch (error) {
console.error('批量导入失败，尝试逐个导入:', error);
// 如果批量操作失败，回退到逐个保存
let successCount = 0;
for (const mistake of mistakes) {
try {
await TauriAPI.updateMistake(mistake);
successCount++;
} catch (error) {
console.warn('导入错题失败:', mistake.id, error);
}
}
alert(`成功导入 ${successCount} 道错题（使用逐个导入）！`);
}
} else {
throw new Error('不支持的文件格式，请选择 .json 或 .csv 文件');
}
} catch (error) {
console.error('导入失败:', error);
alert('导入失败: ' + error);
} finally {
setIsImporting(false);
setImportFile(null);
}
};
// 清空所有数据 - 三层验证防误触
const handleClearAllData = async () => {
// 第一层验证：基本确认
const confirmMessage = `
⚠️ 危险操作警告 ⚠️
您即将删除所有数据，包括：
- 所有错题记录
- 所有回顾分析
- 所有设置配置
此操作不可恢复！请确认您已经备份了重要数据。
确定要继续吗？
`;
if (!confirm(confirmMessage.trim())) {
return;
}
// 第二层验证：等待3秒冷静期
const waitMessage = `
正在进入数据清空流程...
请等待 3 秒冷静期，然后会进入最终确认。
如果您改变主意，请关闭此对话框。
`;
if (!confirm(waitMessage.trim())) {
return;
}
// 显示倒计时
for (let i = 3; i >= 1; i--) {
await new Promise(resolve => setTimeout(resolve, 1000));
if (!confirm(`${i} 秒后进入最终确认...\n\n点击"取消"可随时停止操作`)) {
return;
}
}
// 第三层验证：输入确认文本
const currentTime = new Date().toLocaleTimeString('zh-CN');
const finalConfirm = prompt(`
🔐 最终安全验证
当前时间: ${currentTime}
请输入以下确认文本来完成数据清空：
"我确认删除所有数据${currentTime.slice(-5)}"
注意：必须完全匹配，包括时间后缀
`);
const expectedText = `我确认删除所有数据${currentTime.slice(-5)}`;
if (finalConfirm !== expectedText) {
alert('确认文本不正确或已超时，操作已取消\n\n为了安全，请重新开始整个验证流程');
return;
}
try {
// 获取所有错题ID并批量删除
const allMistakes = await TauriAPI.getMistakes();
const mistakeIds = allMistakes.map(mistake => mistake.id);
if (mistakeIds.length === 0) {
alert('✅ 数据库已经是空的！');
return;
}
try {
await TauriAPI.batchDeleteMistakes(mistakeIds);
alert(`✅ 已批量清空 ${mistakeIds.length} 道错题！页面将刷新。`);
} catch (error) {
console.error('批量删除失败，尝试逐个删除:', error);
// 如果批量删除失败，回退到逐个删除
let deletedCount = 0;
for (const mistake of allMistakes) {
try {
await TauriAPI.deleteMistake(mistake.id);
deletedCount++;
} catch (error) {
console.warn('删除错题失败:', mistake.id, error);
}
}
alert(`✅ 已清空 ${deletedCount} 道错题（使用逐个删除）！页面将刷新。`);
}
window.location.reload();
} catch (error) {
console.error('清空数据失败:', error);
alert('清空数据失败: ' + error);
}
};
// 读取文件内容
const readFileAsText = (file: File): Promise<string> => {
return new Promise((resolve, reject) => {
const reader = new FileReader();
reader.onload = (e) => resolve(e.target?.result as string);
reader.onerror = (e) => reject(e);
reader.readAsText(file, 'utf-8');
});
};
// 解析CSV行
const parseCSVLine = (line: string): string[] => {
const result = [];
let current = '';
let inQuotes = false;
for (let i = 0; i < line.length; i++) {
const char = line[i];
if (char === '"') {
if (inQuotes && line[i + 1] === '"') {
current += '"';
i++; // 跳过下一个引号
} else {
inQuotes = !inQuotes;
}
} else if (char === ',' && !inQuotes) {
result.push(current);
current = '';
} else {
current += char;
}
}
result.push(current);
return result;
};
return (
<div style={{
width: '100%',
height: '100%',
overflow: 'auto',
background: '#f8fafc'
}}>
{/* 头部区域 - 统一白色样式 */}
<div style={{
background: 'white',
borderBottom: '1px solid #e5e7eb',
padding: '24px 32px',
position: 'relative'
}}>
<div style={{
position: 'absolute',
top: 0,
left: 0,
right: 0,
height: '4px',
background: 'linear-gradient(90deg, #667eea, #764ba2)'
}}></div>
<div style={{ position: 'relative', zIndex: 1 }}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '8px' }}>
<svg style={{ width: '32px', height: '32px', marginRight: '12px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24" strokeWidth={2}>
<path d="M11 21.73a2 2 0 0 0 2 0l7-4A2 2 0 0 0 21 16V8a2 2 0 0 0-1-1.73l-7-4a2 2 0 0 0-2 0l-7 4A2 2 0 0 0 3 8v8a2 2 0 0 0 1 1.73z" />
<path d="M12 22V12" />
<polyline points="3.29 7 12 12 20.71 7" />
<path d="m7.5 4.27 9 5.15" />
</svg>
<h1 style={{ fontSize: '28px', fontWeight: '700', margin: 0, color: '#1f2937' }}>数据管理</h1>
</div>
<p style={{ fontSize: '16px', color: '#6b7280', margin: 0, lineHeight: '1.5' }}>
备份和恢复您的学习数据，确保数据安全和迁移便利
</p>
</div>
</div>
<div className="data-import-export" style={{ padding: '24px', background: 'transparent' }}>
{/* 数据导出 */}
<div className="section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Upload size={20} />
数据导出
</h4>
<p>将您的错题数据导出为备份文件</p>
<div className="export-options">
<div className="format-selector">
<label>导出格式:</label>
<select
value={exportFormat}
onChange={(e) => setExportFormat(e.target.value as 'json' | 'csv')}
>
<option value="json">JSON (完整备份)</option>
<option value="csv">CSV (仅错题数据)</option>
</select>
</div>
<div className="format-description">
{exportFormat === 'json' ? (
<p style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Lightbulb size={16} />
JSON格式包含完整数据，可用于完整恢复
</p>
) : (
<p style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Lightbulb size={16} />
CSV格式仅包含错题基本信息，适合在Excel中查看
</p>
)}
</div>
</div>
<button
onClick={handleExport}
disabled={isExporting}
className="export-button"
style={{ display: 'flex', alignItems: 'center', gap: '8px' }}
>
{isExporting ? '导出中...' : (
<>
<Download size={16} />
导出数据
</>
)}
</button>
</div>
{/* 数据导入 */}
<div className="section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Download size={20} />
数据导入
</h4>
<p>从备份文件恢复您的错题数据</p>
<div className="import-options">
<div className="file-selector">
<input
type="file"
accept=".json,.csv"
onChange={(e) => setImportFile(e.target.files?.[0] || null)}
id="import-file"
/>
<label htmlFor="import-file" className="file-label">
{importFile ? importFile.name : '选择备份文件 (.json 或 .csv)'}
</label>
</div>
{importFile && (
<div className="file-info">
<p style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<FileText size={16} />
文件: {importFile.name}
</p>
<p style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<HardDrive size={16} />
大小: {(importFile.size / 1024).toFixed(2)} KB
</p>
<p style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Calendar size={16} />
修改时间: {new Date(importFile.lastModified).toLocaleString('zh-CN')}
</p>
</div>
)}
</div>
<button
onClick={handleImport}
disabled={isImporting || !importFile}
className="import-button"
style={{ display: 'flex', alignItems: 'center', gap: '8px' }}
>
{isImporting ? '导入中...' : (
<>
<Upload size={16} />
导入数据
</>
)}
</button>
</div>
{/* 系统设置导出/导入 */}
<div className="section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px', marginBottom: '1rem' }}>
<Settings size={20} />
系统设置管理
</h4>
<p style={{ marginBottom: '1.5rem' }}>单独导出或恢复API、科目、系统配置等设置，不影响错题数据</p>
<div style={{ display: 'grid', gridTemplateColumns: '1fr 1fr', gap: '1rem' }}>
{/* 设置导出 */}
<div style={{
border: '1px solid #e5e7eb',
borderRadius: '6px',
padding: '1rem'
}}>
<h5 style={{ margin: '0 0 0.5rem 0', fontSize: '14px', fontWeight: '600' }}>导出系统设置</h5>
<p style={{ margin: '0 0 1rem 0', fontSize: '13px', color: '#6b7280' }}>
包含API配置、科目设置、模型分配等
</p>
<button
onClick={handleExportSettings}
disabled={isExportingSettings}
style={{
display: 'flex',
alignItems: 'center',
gap: '6px',
padding: '8px 16px',
backgroundColor: '#3b82f6',
color: 'white',
border: 'none',
borderRadius: '4px',
fontSize: '14px',
cursor: isExportingSettings ? 'not-allowed' : 'pointer',
opacity: isExportingSettings ? 0.6 : 1
}}
>
{isExportingSettings ? '导出中...' : (
<>
<Download size={14} />
导出设置
</>
)}
</button>
</div>
{/* 设置导入 */}
<div style={{
border: '1px solid #e5e7eb',
borderRadius: '6px',
padding: '1rem'
}}>
<h5 style={{ margin: '0 0 0.5rem 0', fontSize: '14px', fontWeight: '600' }}>恢复系统设置</h5>
<p style={{ margin: '0 0 1rem 0', fontSize: '13px', color: '#6b7280' }}>
从设置备份文件恢复配置
</p>
<div style={{ marginBottom: '0.75rem' }}>
<input
type="file"
accept=".json"
onChange={(e) => setSettingsImportFile(e.target.files?.[0] || null)}
id="settings-import-file"
style={{ display: 'none' }}
/>
<label
htmlFor="settings-import-file"
style={{
display: 'inline-block',
padding: '6px 12px',
backgroundColor: '#f3f4f6',
border: '1px solid #d1d5db',
borderRadius: '4px',
fontSize: '13px',
cursor: 'pointer',
width: '100%',
textAlign: 'center',
boxSizing: 'border-box'
}}
>
{settingsImportFile ? settingsImportFile.name : '选择设置文件'}
</label>
</div>
<button
onClick={handleImportSettings}
disabled={isImportingSettings || !settingsImportFile}
style={{
display: 'flex',
alignItems: 'center',
gap: '6px',
padding: '8px 16px',
backgroundColor: '#10b981',
color: 'white',
border: 'none',
borderRadius: '4px',
fontSize: '14px',
cursor: (isImportingSettings || !settingsImportFile) ? 'not-allowed' : 'pointer',
opacity: (isImportingSettings || !settingsImportFile) ? 0.6 : 1
}}
>
{isImportingSettings ? '恢复中...' : (
<>
<Upload size={14} />
恢复设置
</>
)}
</button>
</div>
</div>
<div style={{
marginTop: '1rem',
padding: '0.75rem',
backgroundColor: '#f8fafc',
borderRadius: '4px',
fontSize: '13px',
color: '#6b7280'
}}>
<div style={{ display: 'flex', alignItems: 'center', gap: '6px', marginBottom: '4px' }}>
<Lightbulb size={14} />
<strong>提示：</strong>
</div>
<ul style={{ margin: 0, paddingLeft: '1.2rem' }}>
<li>系统设置备份独立于错题数据，可安全操作</li>
<li>包含API密钥等敏感信息，请妥善保管备份文件</li>
<li>恢复设置会覆盖当前配置，操作前请确认</li>
</ul>
</div>
</div>
{/* 数据统计 */}
<div className="section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<BarChart3 size={20} />
当前数据统计
</h4>
<DataStats className="data-stats" />
</div>
{/* 危险操作 */}
<div className="section danger-section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<AlertTriangle size={20} color="#dc3545" />
危险操作
</h4>
<p>以下操作将永久删除数据，请谨慎操作</p>
<button
onClick={handleClearAllData}
className="danger-button"
style={{ display: 'flex', alignItems: 'center', gap: '8px' }}
>
<Trash2 size={16} />
清空所有数据
</button>
</div>
{/* 使用提示 */}
<div className="section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Lightbulb size={20} />
使用提示
</h4>
<ul style={{ margin: 0, paddingLeft: '1.2rem' }}>
<li>建议定期导出数据进行备份</li>
<li>JSON格式可完整恢复所有数据</li>
<li>CSV格式适合数据分析和查看</li>
<li>导入前请确保文件格式正确</li>
</ul>
</div>
</div>
</div>
);
};
|
000haoji/deep-student
| 6,505 |
src/components/UnifiedAnalysisView.css
|
/* UnifiedAnalysisView 组件样式 */
.unified-analysis-loading {
display: flex;
justify-content: center;
align-items: center;
min-height: 400px;
}
.loading-spinner {
font-size: 1.1rem;
color: #6c757d;
}
.unified-analysis-error {
display: flex;
flex-direction: column;
justify-content: center;
align-items: center;
min-height: 400px;
padding: 2rem;
}
.error-message {
font-size: 1.2rem;
color: #dc3545;
margin-bottom: 1rem;
}
.error-details {
font-size: 0.9rem;
color: #6c757d;
text-align: center;
}
/* 图片预览容器 */
.image-preview-container {
margin-bottom: 1rem;
padding: 1rem;
border: 2px dashed #e5e7eb;
border-radius: 8px;
background-color: #f9fafb;
}
.image-preview-header {
margin-bottom: 0.75rem;
font-size: 0.9rem;
font-weight: 600;
color: #374151;
}
.image-preview-grid {
display: flex;
flex-wrap: wrap;
gap: 0.75rem;
}
.image-preview-item {
position: relative;
width: 120px;
height: 120px;
border-radius: 8px;
overflow: hidden;
border: 2px solid #e5e7eb;
background-color: white;
}
.image-preview-item img {
width: 100%;
height: 100%;
object-fit: cover;
}
.image-preview-info {
position: absolute;
bottom: 0;
left: 0;
right: 0;
background: linear-gradient(to top, rgba(0,0,0,0.8), transparent);
padding: 0.5rem;
display: flex;
justify-content: space-between;
align-items: center;
}
.image-name {
font-size: 0.75rem;
color: white;
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
flex: 1;
margin-right: 0.5rem;
}
.remove-image-btn {
background: rgba(220, 53, 69, 0.8);
color: white;
border: none;
border-radius: 50%;
width: 20px;
height: 20px;
display: flex;
align-items: center;
justify-content: center;
font-size: 0.75rem;
cursor: pointer;
transition: background-color 0.2s;
}
.remove-image-btn:hover {
background: rgba(220, 53, 69, 1);
}
/* 输入行样式 */
.input-row {
display: flex;
align-items: center;
gap: 0.5rem;
}
.input-row input[type="text"] {
flex: 1;
padding: 0.75rem;
border: 2px solid #e5e7eb;
border-radius: 0.5rem;
font-size: 0.9rem;
transition: border-color 0.2s;
}
.input-row input[type="text"]:focus {
outline: none;
border-color: #3b82f6;
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
}
.input-row input[type="text"]:disabled {
background-color: #f3f4f6;
color: #6b7280;
cursor: not-allowed;
}
/* 图片上传按钮 */
.image-upload-btn {
display: flex;
align-items: center;
justify-content: center;
width: 40px;
height: 40px;
background-color: #f3f4f6;
border: 2px solid #d1d5db;
border-radius: 0.5rem;
cursor: pointer;
transition: all 0.2s;
font-size: 1.2rem;
}
.image-upload-btn:hover {
background-color: #e5e7eb;
border-color: #9ca3af;
}
.image-upload-btn:active {
transform: scale(0.95);
}
/* 发送按钮 */
.send-button {
display: flex;
align-items: center;
justify-content: center;
width: 40px;
height: 40px;
background-color: #3b82f6;
color: white;
border: none;
border-radius: 0.5rem;
cursor: pointer;
transition: all 0.2s;
font-size: 1.2rem;
}
.send-button:hover:not(:disabled) {
background-color: #2563eb;
}
.send-button:disabled {
background-color: #9ca3af;
cursor: not-allowed;
}
.send-button:active:not(:disabled) {
transform: scale(0.95);
}
/* 保存按钮行 */
.save-buttons-row {
margin-top: 0.75rem;
padding-top: 0.75rem;
border-top: 1px solid #e5e7eb;
display: flex;
flex-wrap: wrap;
gap: 0.5rem;
}
.save-button-inline {
padding: 0.5rem 1rem;
background-color: #10b981;
color: white;
border: none;
border-radius: 0.375rem;
cursor: pointer;
font-size: 0.875rem;
font-weight: 500;
transition: background-color 0.2s;
}
.save-button-inline:hover:not(:disabled) {
background-color: #059669;
}
.save-button-inline:disabled {
background-color: #9ca3af;
cursor: not-allowed;
opacity: 0.5;
}
/* 保存按钮组 */
.save-buttons-group {
display: flex;
flex-wrap: wrap;
gap: 0.5rem;
}
.save-button-primary {
padding: 0.75rem 1rem;
background-color: #10b981;
color: white;
border: none;
border-radius: 0.375rem;
cursor: pointer;
font-size: 0.875rem;
font-weight: 600;
transition: all 0.2s;
}
.save-button-primary:hover:not(:disabled) {
background-color: #059669;
transform: translateY(-1px);
}
.save-button-primary:disabled {
background-color: #9ca3af;
cursor: not-allowed;
opacity: 0.5;
}
.save-button-secondary {
padding: 0.75rem 1rem;
background-color: #6b7280;
color: white;
border: none;
border-radius: 0.375rem;
cursor: pointer;
font-size: 0.875rem;
transition: all 0.2s;
}
.save-button-secondary:hover:not(:disabled) {
background-color: #4b5563;
transform: translateY(-1px);
}
.save-button-secondary:disabled {
background-color: #9ca3af;
cursor: not-allowed;
opacity: 0.5;
}
/* 多模态内容渲染样式 */
.content-text-part {
margin-bottom: 0.5rem;
}
.content-image-part {
margin: 0.5rem 0;
}
.content-image-part img {
max-width: 100%;
max-height: 300px;
display: block;
border-radius: 8px;
border: 1px solid #e5e7eb;
box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
}
.content-unknown {
padding: 1rem;
background-color: #fef3c7;
border: 1px solid #f59e0b;
border-radius: 0.5rem;
color: #92400e;
font-style: italic;
}
/* 聊天全屏模式 */
.chat-fullscreen .chat-container {
position: fixed;
top: 0;
left: 0;
right: 0;
bottom: 0;
z-index: 9999;
background: white;
display: flex;
flex-direction: column;
}
.chat-fullscreen .chat-history {
flex: 1;
overflow-y: auto;
}
/* 响应式设计 */
@media (max-width: 768px) {
.image-preview-grid {
justify-content: center;
}
.image-preview-item {
width: 100px;
height: 100px;
}
.input-row {
flex-wrap: wrap;
}
.input-row input[type="text"] {
min-width: 200px;
}
.save-buttons-group {
width: 100%;
}
.save-button-primary,
.save-button-secondary {
flex: 1;
min-width: 120px;
}
}
/* 动画效果 */
@keyframes fadeIn {
from {
opacity: 0;
transform: translateY(10px);
}
to {
opacity: 1;
transform: translateY(0);
}
}
.image-preview-item {
animation: fadeIn 0.3s ease-out;
}
.content-image-part img {
animation: fadeIn 0.5s ease-out;
}
/* 悬停效果 */
.image-preview-item:hover {
transform: scale(1.05);
transition: transform 0.2s;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.15);
}
.content-image-part img:hover {
transform: scale(1.02);
transition: transform 0.2s;
cursor: pointer;
}
|
000haoji/deep-student
| 6,130 |
src/components/ImageViewer.tsx
|
import { useState, useEffect } from 'react';
interface ImageViewerProps {
images: string[];
currentIndex: number;
isOpen: boolean;
onClose: () => void;
onNext?: () => void;
onPrev?: () => void;
}
export const ImageViewer: React.FC<ImageViewerProps> = ({
images,
currentIndex,
isOpen,
onClose,
onNext,
onPrev
}) => {
const [scale, setScale] = useState(1);
const [rotation, setRotation] = useState(0);
const [position, setPosition] = useState({ x: 0, y: 0 });
const [isDragging, setIsDragging] = useState(false);
const [dragStart, setDragStart] = useState({ x: 0, y: 0 });
// 重置状态当图片改变时
useEffect(() => {
setScale(1);
setRotation(0);
setPosition({ x: 0, y: 0 });
}, [currentIndex]);
// 键盘事件处理
useEffect(() => {
if (!isOpen) return;
const handleKeyDown = (e: KeyboardEvent) => {
switch (e.key) {
case 'Escape':
onClose();
break;
case 'ArrowLeft':
onPrev?.();
break;
case 'ArrowRight':
onNext?.();
break;
case '+':
case '=':
setScale(prev => Math.min(prev * 1.2, 5));
break;
case '-':
setScale(prev => Math.max(prev / 1.2, 0.1));
break;
case 'r':
case 'R':
setRotation(prev => (prev + 90) % 360);
break;
case '0':
setScale(1);
setRotation(0);
setPosition({ x: 0, y: 0 });
break;
}
};
document.addEventListener('keydown', handleKeyDown);
return () => document.removeEventListener('keydown', handleKeyDown);
}, [isOpen, onClose, onNext, onPrev]);
const handleMouseDown = (e: React.MouseEvent) => {
setIsDragging(true);
setDragStart({
x: e.clientX - position.x,
y: e.clientY - position.y
});
};
const handleMouseMove = (e: React.MouseEvent) => {
if (!isDragging) return;
setPosition({
x: e.clientX - dragStart.x,
y: e.clientY - dragStart.y
});
};
const handleMouseUp = () => {
setIsDragging(false);
};
const handleWheel = (e: React.WheelEvent) => {
e.preventDefault();
const delta = e.deltaY > 0 ? 0.9 : 1.1;
setScale(prev => Math.max(0.1, Math.min(5, prev * delta)));
};
if (!isOpen || images.length === 0) return null;
const currentImage = images[currentIndex];
return (
<div className="image-viewer-overlay" onClick={onClose}>
<div className="image-viewer-container" onClick={(e) => e.stopPropagation()}>
{/* 工具栏 */}
<div className="image-viewer-toolbar">
<div className="toolbar-left">
<span className="image-counter">
{currentIndex + 1} / {images.length}
</span>
</div>
<div className="toolbar-center">
<button
onClick={() => setScale(prev => Math.max(prev / 1.2, 0.1))}
className="toolbar-button"
title="缩小 (-)"
>
🔍-
</button>
<span className="scale-indicator">{Math.round(scale * 100)}%</span>
<button
onClick={() => setScale(prev => Math.min(prev * 1.2, 5))}
className="toolbar-button"
title="放大 (+)"
>
🔍+
</button>
<button
onClick={() => setRotation(prev => (prev + 90) % 360)}
className="toolbar-button"
title="旋转 (R)"
>
🔄
</button>
<button
onClick={() => {
setScale(1);
setRotation(0);
setPosition({ x: 0, y: 0 });
}}
className="toolbar-button"
title="重置 (0)"
>
🏠
</button>
</div>
<div className="toolbar-right">
<button onClick={onClose} className="close-button" title="关闭 (Esc)">
✕
</button>
</div>
</div>
{/* 图片容器 */}
<div
className="image-viewer-content"
onMouseDown={handleMouseDown}
onMouseMove={handleMouseMove}
onMouseUp={handleMouseUp}
onMouseLeave={handleMouseUp}
onWheel={handleWheel}
>
<img
src={currentImage}
alt={`图片 ${currentIndex + 1}`}
className="viewer-image"
style={{
transform: `translate(${position.x}px, ${position.y}px) scale(${scale}) rotate(${rotation}deg)`,
cursor: isDragging ? 'grabbing' : 'grab'
}}
draggable={false}
/>
</div>
{/* 导航按钮 */}
{images.length > 1 && (
<>
<button
onClick={onPrev}
className="nav-button nav-prev"
disabled={currentIndex === 0}
title="上一张 (←)"
>
‹
</button>
<button
onClick={onNext}
className="nav-button nav-next"
disabled={currentIndex === images.length - 1}
title="下一张 (→)"
>
›
</button>
</>
)}
{/* 缩略图栏 */}
{images.length > 1 && (
<div className="image-viewer-thumbnails">
{images.map((image, index) => (
<div
key={index}
className={`thumbnail ${index === currentIndex ? 'active' : ''}`}
onClick={() => {
// 这里需要父组件提供切换图片的方法
}}
>
<img src={image} alt={`缩略图 ${index + 1}`} />
</div>
))}
</div>
)}
{/* 快捷键提示 */}
<div className="keyboard-hints">
<div className="hint">ESC: 关闭</div>
<div className="hint">←→: 切换</div>
<div className="hint">+/-: 缩放</div>
<div className="hint">R: 旋转</div>
<div className="hint">0: 重置</div>
</div>
</div>
</div>
);
};
|
000haoji/deep-student
| 93,037 |
src/components/UniversalAppChatHost.tsx
|
import { useState, useEffect, useCallback, useRef } from 'react';
import { MessageWithThinking } from '../chat-core';
import { ImageViewer } from './ImageViewer';
import {
ChatMessage,
AnalysisResponse,
ContinueChatResponse
} from '../types/index';
// 移除不再使用的streamHandler import
import { TauriAPI } from '../utils/tauriApi';
import { useSubject } from '../contexts/SubjectContext';
import { getCurrentWindow } from '@tauri-apps/api/window';
import '../App.css';
import '../chat-core/styles/index.css';
import ModernSelect from './ModernSelect';
// UniversalAppChatHost Props接口定义
export type HostedChatMode =
| 'NEW_MISTAKE_ANALYSIS' // 对应原 App.tsx 的 'analysis' 视图，从零开始创建新错题分析
| 'EXISTING_MISTAKE_DETAIL' // 错题库详情：加载已有错题，进行追问
| 'EXISTING_BATCH_TASK_DETAIL'// 批量分析任务详情：加载已有分析，进行追问
| 'REVIEW_SESSION_DETAIL'; // 回顾分析会话详情：启动或继续回顾分析
// API 函数提供者接口，由父组件根据场景实现
export interface HostedChatApiProvider {
// 阶段一：获取用于流交互的ID及初始数据 (如OCR结果)
// 对于 NEW_MISTAKE_ANALYSIS: 调用原 App.tsx 中的 TauriAPI.analyzeStepByStep
// 对于其他模式: 可能直接返回传入的业务ID作为流ID，或调用特定API获取会话详情
initiateAndGetStreamId: (params: {
businessId?: string; // 外部业务ID (mistakeId, batchId, reviewSessionId)
subject?: string;
questionImages?: File[];
userQuestion?: string;
enableChainOfThought: boolean;
enableRag: boolean;
ragTopK: number;
}) => Promise<{
streamIdForEvents: string; // 后端用于流事件的ID (temp_id)
ocrResultData?: any; // OCR及初步分类结果
initialMessages?: ChatMessage[];// 可能由此阶段返回的初始消息
}>;
// 阶段二：使用阶段一获取的 streamIdForEvents，正式启动AI回答的流
startMainStreaming: (params: {
streamIdForEvents: string;
enableChainOfThought: boolean;
enableRag: boolean;
ragTopK: number;
}) => Promise<void>;
// 用于追问
continueUserChat: (params: {
streamIdForEvents: string; // 当前流ID
businessId: string; // 外部业务ID
fullChatHistory: ChatMessage[];// 包含新用户消息的完整历史
enableChainOfThought: boolean;
enableRag: boolean;
ragTopK: number;
}) => Promise<void>;
// (可选) 获取指定业务ID的完整聊天记录和相关数据
loadExistingSessionData?: (params: { businessId: string }) => Promise<{
chatHistory: ChatMessage[];
thinkingContent?: Map<number, string>;
ocrResultData?: any;
// ... other relevant data like subject, userQuestion for display
}>;
}
export interface UniversalAppChatHostProps {
mode: HostedChatMode;
// 外部传入的、代表当前业务实体的唯一ID (如 mistake.id, batchTask.id, reviewSession.id)
// 这个ID将传递给 apiProvider 中的函数。
businessSessionId: string;
// 预加载的初始数据 (通常用于 EXISTING_* 和 REVIEW_SESSION_DETAIL 模式)
// 如果未提供，组件可能会尝试通过 apiProvider.loadExistingSessionData 获取
preloadedData?: {
subject?: string;
userQuestion?: string; // 作为标题或问题描述
questionImages?: File[]; // 或图片URL列表
questionImageUrls?: string[];
ocrText?: string;
tags?: string[];
chatHistory?: ChatMessage[];
thinkingContent?: Map<number, string>;
status?: string; // 新增：允许传入会话状态
mistake_summary?: string | null; // 错题总结内容
user_error_analysis?: string | null; // 用户错误分析内容
// 添加原始错题对象引用，用于更新操作
originalMistake?: any; // 完整的原始错题对象
// ... 其他特定于该业务实体的数据
};
// 后端交互配置
serviceConfig: {
apiProvider: HostedChatApiProvider;
// 事件名生成函数，'id' 参数是 initiateAndGetStreamId 返回的 streamIdForEvents
streamEventNames: {
initialStream: (id: string) => { data: string; reasoning: string; ragSources?: string };
continuationStream: (id: string) => { data: string; reasoning: string; ragSources?: string };
};
defaultEnableChainOfThought: boolean;
defaultEnableRag: boolean;
defaultRagTopK: number;
defaultSelectedLibraries?: string[];
};
// 当内部核心状态（聊天记录、思维链、OCR结果）更新时回调
onCoreStateUpdate?: (data: {
chatHistory: ChatMessage[];
thinkingContent: Map<number, string>;
ocrResult?: any;
isAnalyzing?: boolean; // 当前分析状态
isChatting?: boolean; // 当前追问状态
}) => void;
// 当用户在组件内部触发保存操作时回调
onSaveRequest: (data: {
businessSessionId: string;
chatHistory: ChatMessage[];
thinkingContent: Map<number, string>;
ocrResult?: any; // OCR结果
temp_id?: string; // 直接传递的temp_id
// 总结内容 - 新增
summaryContent?: string;
// 原始输入数据，如 subject, userQuestion, questionImages，也应包含，因为保存时可能需要
originalInputs: { subject: string; userQuestion: string; questionImages: File[]; /*...*/ }
}) => Promise<void>;
onExitRequest?: () => void; // 如果组件有退出/返回按钮
}
// 真实API调用
const analyzeNewMistake = TauriAPI.analyzeNewMistake;
const continueChat = async (request: any): Promise<ContinueChatResponse> => {
return TauriAPI.continueChat(request);
};
function UniversalAppChatHost(props: UniversalAppChatHostProps) {
// 调试日志：检查接收到的props数据
console.log('🔍 UniversalAppChatHost 接收到的 props:', {
mode: props.mode,
businessSessionId: props.businessSessionId,
preloadedDataExists: !!props.preloadedData,
preloadedChatHistoryLength: props.preloadedData?.chatHistory?.length || 0,
preloadedChatHistoryData: props.preloadedData?.chatHistory,
preloadedOcrText: props.preloadedData?.ocrText?.substring(0, 100) + '...',
questionImageUrls: props.preloadedData?.questionImageUrls?.length || 0
});
console.log('🔍 [streamId] 组件模式和业务ID:', { mode: props.mode, businessSessionId: props.businessSessionId });
const [isChatFullscreen, setIsChatFullscreen] = useState(false);
// 使用全局科目状态
const { currentSubject, setCurrentSubject, getEnabledSubjects, loading: isLoadingSubjects } = useSubject();
// 分析相关状态 - 从props或全局状态获取初始值，但优先使用全局状态
const subject = currentSubject || props.preloadedData?.subject || '未选择科目';
const availableSubjects = getEnabledSubjects();
// 调试：监听科目变化
useEffect(() => {
console.log('📚 [UniversalAppChatHost] 科目状态变化:', {
currentSubject,
computedSubject: subject,
preloadedSubject: props.preloadedData?.subject,
mode: props.mode
});
}, [currentSubject, subject, props.preloadedData?.subject, props.mode]);
const [userQuestion, setUserQuestion] = useState(props.preloadedData?.userQuestion || '');
const [questionImages, setQuestionImages] = useState<File[]>(props.preloadedData?.questionImages || []);
const [questionImageUrls, setQuestionImageUrls] = useState<string[]>(props.preloadedData?.questionImageUrls || []);
const [imageViewerOpen, setImageViewerOpen] = useState(false);
const [currentImageIndex, setCurrentImageIndex] = useState(0);
const [isAnalyzing, setIsAnalyzing] = useState(false);
const [analysisResult, setAnalysisResult] = useState<AnalysisResponse | null>(
// 🎯 修复：为已存在的详情页面创建虚拟的analysisResult，确保输入框显示
props.mode !== 'NEW_MISTAKE_ANALYSIS' && props.preloadedData?.ocrText ? {
temp_id: props.businessSessionId,
initial_data: {
ocr_text: props.preloadedData.ocrText,
tags: props.preloadedData.tags || [],
mistake_type: '已加载的分析',
first_answer: typeof props.preloadedData.chatHistory?.[0]?.content === 'string'
? props.preloadedData.chatHistory[0].content
: '[多模态内容]'
}
} : null
);
// 过滤掉总结相关的消息，避免在页面刷新时显示
const filterSummaryMessages = (messages: ChatMessage[]) => {
console.log('🔍 [过滤器] 输入消息数量:', messages.length);
console.log('🔍 [过滤器] 原始消息列表:', messages.map((msg, i) => ({
index: i,
role: msg.role,
contentPreview: typeof msg.content === 'string' ? msg.content.substring(0, 100) + '...' : '[非文本内容]',
contentLength: typeof msg.content === 'string' ? msg.content.length : 0
})));
const filtered = messages.filter(msg => {
// 过滤掉总结请求消息
if (msg.role === 'user' && typeof msg.content === 'string' && msg.content.includes('[SUMMARY_REQUEST]')) {
console.log('🚫 [过滤] 移除总结请求消息:', msg.content.substring(0, 50) + '...');
return false;
}
// 过滤掉总结响应消息（通过内容特征识别）
if (msg.role === 'assistant' && typeof msg.content === 'string' &&
(msg.content.includes('核心知识点') && msg.content.includes('错误分析') && msg.content.includes('学习建议'))) {
console.log('🚫 [过滤] 移除总结响应消息:', msg.content.substring(0, 50) + '...');
return false;
}
return true;
});
console.log('✅ [过滤器] 过滤后消息数量:', filtered.length);
console.log('✅ [过滤器] 过滤后消息列表:', filtered.map((msg, i) => ({
index: i,
role: msg.role,
contentPreview: typeof msg.content === 'string' ? msg.content.substring(0, 100) + '...' : '[非文本内容]'
})));
return filtered;
};
const [chatHistory, setChatHistory] = useState<ChatMessage[]>(
filterSummaryMessages(props.preloadedData?.chatHistory || [])
);
// 调试日志：检查chatHistory初始化状态
console.log('🔍 UniversalAppChatHost chatHistory 初始化:', {
mode: props.mode,
businessSessionId: props.businessSessionId,
chatHistoryLength: chatHistory.length,
chatHistoryData: chatHistory,
preloadedDataChatHistory: props.preloadedData?.chatHistory,
preloadedDataChatHistoryLength: props.preloadedData?.chatHistory?.length || 0,
initialInputAllowed: props.mode !== 'NEW_MISTAKE_ANALYSIS' && props.preloadedData?.chatHistory && props.preloadedData.chatHistory.length > 0
});
const [currentMessage, setCurrentMessage] = useState('');
const [isChatting, setIsChatting] = useState(false);
const [streamingMessageIndex, setStreamingMessageIndex] = useState<number | null>(null);
const [isInputAllowed, setIsInputAllowed] = useState(
// 对于非NEW_MISTAKE_ANALYSIS模式，初始允许输入（等待流式处理完成后可以对话）
props.mode !== 'NEW_MISTAKE_ANALYSIS'
);
const [useStreamMode] = useState(true); // 固定启用流式模式
// 新增状态：用于立即显示OCR结果 - 从props获取初始值
const [ocrResult, setOcrResult] = useState<{
ocr_text: string;
tags: string[];
mistake_type: string;
} | null>(props.preloadedData?.ocrText ? {
ocr_text: props.preloadedData.ocrText,
tags: props.preloadedData.tags || [],
mistake_type: '已加载的分析'
} : null);
const [isOcrComplete, setIsOcrComplete] = useState(() => {
// 对于错题详情页面，如果有聊天记录，直接认为OCR已完成
// 🎯 修复：即使OCR结果为空，只要有聊天记录就应该显示聊天界面
const result = props.mode === 'EXISTING_MISTAKE_DETAIL' ?
!!(props.preloadedData?.chatHistory?.length) || !!props.preloadedData?.ocrText :
!!props.preloadedData?.ocrText;
console.log('🔍 [OCR状态] isOcrComplete 初始化:', {
mode: props.mode,
result,
hasOcrText: !!props.preloadedData?.ocrText,
chatHistoryLength: props.preloadedData?.chatHistory?.length || 0,
ocrText: props.preloadedData?.ocrText?.substring(0, 50) + '...',
logic: props.mode === 'EXISTING_MISTAKE_DETAIL' ?
`chatHistory(${props.preloadedData?.chatHistory?.length || 0}) || ocrText(${!!props.preloadedData?.ocrText})` :
`ocrText(${!!props.preloadedData?.ocrText})`
});
return result;
});
const [isOcrInProgress, setIsOcrInProgress] = useState(false); // 新增：OCR进行状态
const [enableChainOfThought] = useState(props.serviceConfig.defaultEnableChainOfThought);
const [thinkingContent, setThinkingContent] = useState<Map<number, string>>(props.preloadedData?.thinkingContent || new Map()); // 存储每条消息的思维链内容
// 总结流式内容状态 - 从数据库加载已有总结内容
const getInitialSummaryContent = () => {
if (props.mode === 'EXISTING_MISTAKE_DETAIL' && props.preloadedData) {
// 合并 mistake_summary 和 user_error_analysis 为显示内容
const mistakeSummary = props.preloadedData.mistake_summary;
const userErrorAnalysis = props.preloadedData.user_error_analysis;
console.log('📄 [总结加载] 检查数据库总结内容:', {
hasMistakeSummary: !!mistakeSummary,
hasUserErrorAnalysis: !!userErrorAnalysis,
mistakeSummaryLength: mistakeSummary?.length || 0,
userErrorAnalysisLength: userErrorAnalysis?.length || 0
});
if (mistakeSummary || userErrorAnalysis) {
let combined = '';
// 🎯 修复：保持原始格式，不添加硬编码标题
if (mistakeSummary) {
combined += mistakeSummary;
if (userErrorAnalysis) {
combined += '\n\n'; // 只在两部分都存在时添加分隔
}
}
if (userErrorAnalysis) {
combined += userErrorAnalysis;
}
console.log('📄 [总结加载] 合并后的总结内容:', {
combinedLength: combined.length,
combinedPreview: combined.substring(0, 200) + '...'
});
return combined.trim();
}
}
return '';
};
const [summaryStreamContent, setSummaryStreamContent] = useState(getInitialSummaryContent());
const [summaryStreamComplete, setSummaryStreamComplete] = useState(getInitialSummaryContent() !== '');
const [isGeneratingSummary, setIsGeneratingSummary] = useState(false);
// 使用useRef来确保事件处理器能访问到最新的isGeneratingSummary状态
const isGeneratingSummaryRef = useRef(isGeneratingSummary);
useEffect(() => {
isGeneratingSummaryRef.current = isGeneratingSummary;
console.log('🔄 [状态同步] isGeneratingSummary更新为:', isGeneratingSummary);
}, [isGeneratingSummary]);
// 当前流ID状态 - 用于API调用
const [currentStreamId, setCurrentStreamId] = useState<string | null>(null);
// 初始化streamId - 对于非NEW_MISTAKE_ANALYSIS模式，使用businessSessionId作为streamId
useEffect(() => {
if (props.mode !== 'NEW_MISTAKE_ANALYSIS' && !currentStreamId && props.businessSessionId) {
console.log('🔧 [初始化] 设置非新分析模式的streamId:', props.businessSessionId);
setCurrentStreamId(props.businessSessionId);
}
}, [props.mode, props.businessSessionId, currentStreamId]);
// RAG相关状态 - 从props获取初始值
const [enableRag, setEnableRag] = useState(props.serviceConfig.defaultEnableRag);
const [ragTopK, setRagTopK] = useState(props.serviceConfig.defaultRagTopK);
// 状态更新回调 - 使用useRef避免过度调用
const lastStateRef = useRef<string>('');
const updateTimeoutRef = useRef<number | null>(null);
useEffect(() => {
// 在总结生成期间，暂停状态更新回调以避免不必要的重渲染
if (isGeneratingSummary) {
console.log('📝 [状态更新] 总结生成中，暂停状态更新回调');
return;
}
// 创建状态指纹，只在真正有变化时才调用回调
const stateFingerprint = JSON.stringify({
chatHistoryLength: chatHistory.length,
thinkingContentSize: thinkingContent.size,
hasOcrResult: !!ocrResult,
isAnalyzing,
isChatting
});
if (lastStateRef.current !== stateFingerprint) {
lastStateRef.current = stateFingerprint;
// 恢复状态更新回调，但增加防抖机制
if (updateTimeoutRef.current) {
clearTimeout(updateTimeoutRef.current);
}
updateTimeoutRef.current = window.setTimeout(() => {
props.onCoreStateUpdate?.({
chatHistory,
thinkingContent,
ocrResult,
isAnalyzing,
isChatting
});
updateTimeoutRef.current = null;
}, 500); // 500ms防抖
}
}, [chatHistory, thinkingContent, ocrResult, isAnalyzing, isChatting, isGeneratingSummary]);
// 科目现在由全局状态管理，不再需要本地加载
// 监听preloadedData的变化，特别是chatHistory的实时更新
useEffect(() => {
// 🎯 关键修复：防止在流式处理期间或刚完成后错误同步状态
// 1. 仅当流式渲染未在进行时，才考虑从props同步chatHistory
if (streamingMessageIndex !== null) {
console.log('⚠️ [同步跳过] 正在流式渲染，暂不更新chatHistory');
return;
}
// 2. 如果正在分析或对话中，也跳过同步
if (isAnalyzing || isChatting) {
console.log('⚠️ [同步跳过] 正在分析或对话中，暂不更新chatHistory');
return;
}
// 3. 对于回顾分析模式，如果当前已有内容且preloaded为空，说明是流式处理完成后的状态，不应该同步
if (props.mode === 'REVIEW_SESSION_DETAIL' &&
chatHistory.length > 0 &&
(!props.preloadedData?.chatHistory || props.preloadedData.chatHistory.length === 0)) {
console.log('⚠️ [同步跳过] 回顾分析模式，保护已生成的内容');
return;
}
if (props.preloadedData?.chatHistory) {
const filteredPreloadedHistory = filterSummaryMessages(props.preloadedData.chatHistory);
// 使用JSON字符串比较来检测preloadedData和当前state是否有实质性差异
// 这比比较长度或时间戳更可靠
const preloadedHistoryStr = JSON.stringify(filteredPreloadedHistory);
const currentHistoryStr = JSON.stringify(chatHistory);
if (preloadedHistoryStr !== currentHistoryStr) {
console.log('🔄 [状态同步] 检测到 preloadedData.chatHistory 与内部状态不一致，检查是否需要同步。');
console.log(' - Preloaded 长度:', filteredPreloadedHistory.length);
console.log(' - 当前 State 长度:', chatHistory.length);
console.log(' - 模式:', props.mode);
console.log(' - 分析状态:', { isAnalyzing, isChatting });
console.log(' - 流式状态:', { streamingMessageIndex });
// 🎯 修复：智能同步逻辑，防止覆盖用户的追问对话
let shouldSync = false;
if (props.mode === 'EXISTING_MISTAKE_DETAIL') {
// 🎯 时间窗口保护：如果刚刚完成流式传输，给3秒保护时间
const now = Date.now();
const lastCompletionTime = eventListenersRef.current.lastStreamCompletionTime || 0;
const timeSinceCompletion = now - lastCompletionTime;
if (timeSinceCompletion < 3000) { // 3秒保护窗口
shouldSync = false;
console.log('🛡️ [状态同步] 流式完成后的保护窗口期，拒绝同步', {
timeSinceCompletion,
lastCompletionTime
});
} else if (chatHistory.length === 0) {
// 完全空的聊天记录，这是真正的初始加载
shouldSync = true;
console.log('🔄 [状态同步] 检测到初始加载，执行同步');
} else if (chatHistory.length < filteredPreloadedHistory.length) {
// 当前状态记录数少于预加载数据，可能是页面重新加载后需要恢复
shouldSync = true;
console.log('🔄 [状态同步] 检测到数据缺失，执行恢复同步');
} else {
// 🎯 关键：检查是否有用户追问的新消息
const currentUserMessages = chatHistory.filter(msg => msg.role === 'user').length;
const preloadedUserMessages = filteredPreloadedHistory.filter(msg => msg.role === 'user').length;
if (currentUserMessages > preloadedUserMessages) {
// 当前有更多用户消息，说明有新的追问，绝对不要同步
shouldSync = false;
console.log('🛡️ [状态同步] 检测到新的用户追问，保护追问对话，拒绝同步', {
currentUserMessages,
preloadedUserMessages,
currentTotal: chatHistory.length,
preloadedTotal: filteredPreloadedHistory.length
});
} else if (!isAnalyzing && !isChatting && streamingMessageIndex === null) {
// 没有新的用户消息，但仍有差异，且不在活动状态
shouldSync = false;
console.log('🛡️ [状态同步] 检测到其他内容差异，保护现有内容，暂不同步');
} else {
// 其他情况（如正在分析/聊天），保持不变
shouldSync = false;
console.log('🛡️ [状态同步] 检测到活动状态，暂不同步');
}
}
} else if (props.mode === 'REVIEW_SESSION_DETAIL') {
// 回顾分析：只有在初始加载时才同步
shouldSync = chatHistory.length === 0;
console.log(`🔄 [状态同步] 回顾分析模式：${shouldSync ? '执行' : '跳过'}同步`);
} else {
// 其他模式：按原逻辑，只有初始加载时同步
shouldSync = chatHistory.length === 0;
console.log(`🔄 [状态同步] 默认模式：${shouldSync ? '执行' : '跳过'}同步`);
}
if (shouldSync) {
setChatHistory(filteredPreloadedHistory);
console.log('✅ [状态同步] 已执行同步');
} else {
console.log('🛡️ [状态同步] 保护现有内容，跳过同步');
}
}
}
}, [props.preloadedData?.chatHistory, streamingMessageIndex, isAnalyzing, isChatting, props.mode]); // 🎯 移除chatHistory.length依赖，避免循环更新
// 🎯 新增：监听preloadedData的变化，同步总结状态 - 修复切换错题时总结状态持久化问题
useEffect(() => {
// 当切换到不同错题时，重新初始化总结状态
const newSummaryContent = getInitialSummaryContent();
const currentSummaryStr = summaryStreamContent;
// 只有当总结内容发生实质性变化时才更新
if (newSummaryContent !== currentSummaryStr) {
console.log('🔄 [总结同步] 检测到错题数据变化，更新总结状态');
console.log(' - 新总结内容长度:', newSummaryContent.length);
console.log(' - 当前总结内容长度:', currentSummaryStr.length);
console.log(' - 错题ID:', props.businessSessionId);
setSummaryStreamContent(newSummaryContent);
setSummaryStreamComplete(newSummaryContent !== '');
// 如果没有新的总结内容，确保生成状态被重置
if (newSummaryContent === '') {
setIsGeneratingSummary(false);
console.log('🔄 [总结同步] 重置生成状态，因为新错题无总结内容');
}
}
}, [props.preloadedData?.mistake_summary, props.preloadedData?.user_error_analysis, props.businessSessionId]);
// 🎯 新增：监听preloadedData的变化，同步图片URL - 修复切换错题时图片不显示问题
useEffect(() => {
console.log('🔄 [图片同步] preloadedData变化检测:', {
hasQuestionImageUrls: !!props.preloadedData?.questionImageUrls,
newImageUrlsLength: props.preloadedData?.questionImageUrls?.length || 0,
currentImageUrlsLength: questionImageUrls.length,
businessSessionId: props.businessSessionId,
newImageUrls: props.preloadedData?.questionImageUrls
});
if (props.preloadedData?.questionImageUrls && props.preloadedData.questionImageUrls.length > 0) {
const newImageUrls = props.preloadedData.questionImageUrls;
// 只有当图片URLs发生变化时才更新
if (JSON.stringify(newImageUrls) !== JSON.stringify(questionImageUrls)) {
console.log('🔄 [图片同步] 检测到图片数据变化，更新图片URLs');
console.log(' - 新图片数量:', newImageUrls.length);
console.log(' - 新图片URLs预览:', newImageUrls.map((url, i) => `${i+1}: ${url.substring(0, 50)}...`));
console.log(' - 当前图片数量:', questionImageUrls.length);
console.log(' - 错题ID:', props.businessSessionId);
setQuestionImageUrls(newImageUrls);
}
} else if (questionImageUrls.length > 0) {
// 如果新的错题没有图片，清空当前图片
console.log('🔄 [图片同步] 新错题无图片，清空图片URLs');
setQuestionImageUrls([]);
}
}, [props.preloadedData?.questionImageUrls, props.businessSessionId]);
// 🎯 新增：监听businessSessionId变化，重置关键状态 - 修复切换错题时状态混乱问题
// 这是保证组件在切换不同错题时能够完全重置的核心逻辑
useEffect(() => {
console.log('🔄 [会话重置] businessSessionId 变化，重置所有内部状态:', {
newId: props.businessSessionId,
mode: props.mode,
});
// 强制重置所有从 preloadedData 派生的状态
const { preloadedData } = props;
// 1. 重置聊天记录和思维链
const initialChatHistory = filterSummaryMessages(preloadedData?.chatHistory || []);
setChatHistory(initialChatHistory);
// 🎯 修复：正确恢复思维链数据
if (preloadedData?.thinkingContent && preloadedData.thinkingContent instanceof Map) {
console.log('🧠 [状态重置] 恢复思维链数据，条目数:', preloadedData.thinkingContent.size);
setThinkingContent(new Map(preloadedData.thinkingContent));
} else if (preloadedData?.chatHistory) {
// 🎯 修复：从聊天历史中恢复思维链数据
const recoveredThinkingContent = new Map<number, string>();
preloadedData.chatHistory.forEach((message, index) => {
if (message.role === 'assistant' && message.thinking_content) {
console.log(`🧠 [状态重置] 从聊天历史恢复思维链，索引${index}:`, message.thinking_content.substring(0, 50) + '...');
recoveredThinkingContent.set(index, message.thinking_content);
}
});
setThinkingContent(recoveredThinkingContent);
console.log('🧠 [状态重置] 从聊天历史恢复的思维链条目数:', recoveredThinkingContent.size);
} else {
console.log('🧠 [状态重置] 无思维链数据，初始化为空Map');
setThinkingContent(new Map());
}
// 2. 重置基础信息
// 科目现在由全局状态管理，不再需要本地设置
setUserQuestion(preloadedData?.userQuestion || '');
// 3. 重置图片
setQuestionImageUrls(preloadedData?.questionImageUrls || []);
setQuestionImages(preloadedData?.questionImages || []);
// 4. 重置OCR和分析结果
if (preloadedData?.ocrText) {
setOcrResult({
ocr_text: preloadedData.ocrText,
tags: preloadedData.tags || [],
mistake_type: '已加载的分析'
});
setIsOcrComplete(true);
// 为错题详情页面创建虚拟的analysisResult，确保输入框可用
setAnalysisResult({
temp_id: props.businessSessionId,
initial_data: {
ocr_text: preloadedData.ocrText,
tags: preloadedData.tags || [],
mistake_type: '已加载的分析',
first_answer: typeof preloadedData.chatHistory?.[0]?.content === 'string'
? preloadedData.chatHistory[0].content
: '[多模态内容]'
}
});
} else {
// 🎯 修复：即使OCR结果为空，如果有聊天记录也要设置为完成状态
if (props.mode === 'EXISTING_MISTAKE_DETAIL' && preloadedData?.chatHistory?.length) {
setOcrResult({
ocr_text: '',
tags: preloadedData.tags || [],
mistake_type: '已保存的错题'
});
setIsOcrComplete(true);
setAnalysisResult({
temp_id: props.businessSessionId,
initial_data: {
ocr_text: '',
tags: preloadedData.tags || [],
mistake_type: '已保存的错题',
first_answer: typeof preloadedData.chatHistory?.[0]?.content === 'string'
? preloadedData.chatHistory[0].content
: '[多模态内容]'
}
});
console.log('🔧 [OCR修复] OCR结果为空但有聊天记录，设置为完成状态以显示聊天界面');
} else {
setOcrResult(null);
setIsOcrComplete(false);
setAnalysisResult(null);
}
}
// 5. 重置总结状态
const newSummaryContent = getInitialSummaryContent();
setSummaryStreamContent(newSummaryContent);
setSummaryStreamComplete(newSummaryContent !== '');
setIsGeneratingSummary(false);
// 6. 重置流式处理和交互状态
setIsAnalyzing(false);
setIsChatting(false);
setStreamingMessageIndex(null);
setIsInputAllowed(props.mode !== 'NEW_MISTAKE_ANALYSIS'); // 允许非新分析模式初始输入
// 7. 重置流ID和自动启动标记
setCurrentStreamId(props.businessSessionId);
autoStartExecutedRef.current = false;
setAutoStartTriggered(false);
console.log('✅ [会话重置] 所有状态已根据新的 businessSessionId 重置完毕。');
}, [props.businessSessionId, props.preloadedData]); // 依赖项为 businessSessionId 和 preloadedData
// 自动启动分析逻辑 - 对于REVIEW_SESSION_DETAIL模式且聊天历史为空的情况
const [autoStartTriggered, setAutoStartTriggered] = useState(false);
// 处理聊天全屏切换 - 简化为直接状态切换
const handleChatFullscreenToggle = () => {
setIsChatFullscreen(!isChatFullscreen);
};
// 处理图片上传
const handleImageUpload = (e: React.ChangeEvent<HTMLInputElement>) => {
const files = Array.from(e.target.files || []);
const remainingSlots = 9 - questionImages.length;
const filesToAdd = files.slice(0, remainingSlots);
if (filesToAdd.length > 0) {
setQuestionImages(prev => [...prev, ...filesToAdd]);
// URL管理由useEffect自动处理，不需要在这里手动创建
}
// 清空input
e.target.value = '';
};
// 删除图片
const removeImage = (index: number) => {
// 只需要更新questionImages状态，URL管理由useEffect自动处理
setQuestionImages(prev => prev.filter((_, i) => i !== index));
};
// 打开图片查看器
const openImageViewer = (index: number) => {
setCurrentImageIndex(index);
setImageViewerOpen(true);
};
// 优化的文件上传点击处理器
const handleFileUploadClick = useCallback(() => {
const fileInput = document.querySelector('.file-input') as HTMLInputElement;
if (fileInput) {
fileInput.click();
}
}, []);
// 保留聊天相关的键盘快捷键
useEffect(() => {
const handleKeyDown = (e: KeyboardEvent) => {
// ESC键退出全屏
if (e.key === 'Escape' && isChatFullscreen) {
setIsChatFullscreen(false);
}
};
document.addEventListener('keydown', handleKeyDown);
return () => document.removeEventListener('keydown', handleKeyDown);
}, [isChatFullscreen]);
// Tauri文件拖拽事件监听
useEffect(() => {
if (props.mode !== 'NEW_MISTAKE_ANALYSIS') {
return; // 只在新分析模式下启用拖拽
}
let unlisten: (() => void) | undefined;
const setupDragDropListener = async () => {
try {
const appWindow = getCurrentWindow();
console.log('🎯 设置Tauri文件拖拽监听器');
unlisten = await appWindow.onFileDropEvent(async (event) => {
console.log('🎯 Tauri拖拽事件:', event);
if (event.payload.type === 'drop' && event.payload.paths) {
console.log('🎯 文件拖拽路径:', event.payload.paths);
// 过滤图片文件
const imageFiles = event.payload.paths.filter((path: string) => {
const ext = path.toLowerCase().split('.').pop();
return ['jpg', 'jpeg', 'png', 'gif', 'bmp', 'webp'].includes(ext || '');
});
console.log('🎯 过滤后的图片文件:', imageFiles);
if (imageFiles.length > 0) {
console.log('🎯 处理拖拽的图片文件:', imageFiles);
// 由于Tauri的文件系统API在当前配置下不可用，
// 我们暂时记录文件路径，提示用户使用文件选择器
alert(`检测到 ${imageFiles.length} 个图片文件，但拖拽功能需要额外配置。请使用"选择文件"按钮上传图片。`);
// 可以在这里添加将文件路径转换为File对象的逻辑
// 但需要先在Tauri配置中启用文件系统权限
}
} else if (event.payload.type === 'enter') {
console.log('🎯 文件进入拖拽区域');
// 可以在这里添加悬停效果
const uploadArea = document.getElementById('uploadArea');
if (uploadArea) {
uploadArea.classList.add('active');
}
} else if (event.payload.type === 'leave') {
console.log('🎯 文件离开拖拽区域');
// 移除悬停效果
const uploadArea = document.getElementById('uploadArea');
if (uploadArea) {
uploadArea.classList.remove('active');
}
}
});
} catch (error) {
console.error('🎯 设置拖拽监听器失败:', error);
}
};
setupDragDropListener();
return () => {
if (unlisten) {
unlisten();
console.log('🎯 清理Tauri文件拖拽监听器');
}
};
}, [props.mode, questionImages.length]);
// 管理题目图片URL的生命周期
useEffect(() => {
// 清理旧的URLs（避免在第一次渲染时清理不存在的URLs）
if (questionImageUrls.length > 0) {
questionImageUrls.forEach(url => {
try {
URL.revokeObjectURL(url);
} catch (error) {
console.warn('清理URL时出错:', error);
}
});
}
// 创建新的URLs
const newUrls = questionImages.map(file => {
try {
return URL.createObjectURL(file);
} catch (error) {
console.error('创建图片URL失败:', error);
return '';
}
}).filter(url => url !== '');
setQuestionImageUrls(newUrls);
// 清理函数
return () => {
newUrls.forEach(url => {
try {
URL.revokeObjectURL(url);
} catch (error) {
console.warn('清理URL时出错:', error);
}
});
};
}, [questionImages]); // 仅依赖questionImages，避免questionImageUrls导致循环
// 清理timeout防止内存泄漏
useEffect(() => {
return () => {
if (updateTimeoutRef.current) {
clearTimeout(updateTimeoutRef.current);
}
};
}, []);
// 开始分析 - 使用useCallback确保函数引用稳定
const handleAnalyze = useCallback(async () => {
// 对于非NEW_MISTAKE_ANALYSIS模式，可能不需要验证输入
if (props.mode === 'NEW_MISTAKE_ANALYSIS') {
if (!userQuestion.trim()) {
alert('请输入问题描述');
return;
}
if (questionImages.length === 0) {
alert('请上传至少一张题目图片');
return;
}
}
try {
if (useStreamMode) {
console.log('🚀 开始分步骤分析...');
// 设置初始状态：开始OCR
setIsOcrInProgress(true);
setIsAnalyzing(false); // OCR阶段还不是分析阶段
setStreamingMessageIndex(null);
setOcrResult(null);
setIsOcrComplete(false);
setAnalysisResult(null);
setChatHistory([]);
// 第一步：通过props的apiProvider获取流ID和初始数据
console.log('📝 第一步：OCR和获取流ID...');
const stepResult = await props.serviceConfig.apiProvider.initiateAndGetStreamId({
businessId: props.businessSessionId,
subject,
questionImages,
userQuestion,
enableChainOfThought,
enableRag,
ragTopK
});
// 关键修复：先完成异步操作，拿到所有数据后再统一更新状态，避免竞态条件
console.log('✅ 第一步完成，获得流ID:', stepResult.streamIdForEvents);
// OCR完成，开始AI分析阶段
setIsOcrInProgress(false);
setIsAnalyzing(true);
setCurrentStreamId(stepResult.streamIdForEvents);
// 🎯 重要：重置总结状态，避免显示上一个分析的总结内容
setSummaryStreamContent('');
setSummaryStreamComplete(false);
setIsGeneratingSummary(false);
console.log('🔄 [新分析] 总结状态已重置');
// 处理OCR结果（如果有）
if (stepResult.ocrResultData) {
setOcrResult(stepResult.ocrResultData);
setIsOcrComplete(true);
console.log('✅ OCR分析完成:', stepResult.ocrResultData);
} else if (props.mode === 'REVIEW_SESSION_DETAIL') {
// 关键修复：对于回顾分析模式，即使没有OCR数据也要创建虚拟结果以启用聊天界面
const virtualOcrResult = {
ocr_text: props.preloadedData?.ocrText || '统一回顾分析',
tags: props.preloadedData?.tags || ['回顾分析'],
mistake_type: '统一回顾分析'
};
setOcrResult(virtualOcrResult);
setIsOcrComplete(true);
console.log('✅ 回顾分析虚拟OCR结果已创建，启用聊天界面');
}
// 处理初始消息（如果有）
if (stepResult.initialMessages && stepResult.initialMessages.length > 0) {
setChatHistory(stepResult.initialMessages);
}
// 创建临时的分析结果对象
const tempAnalysisResult: AnalysisResponse = {
temp_id: stepResult.streamIdForEvents,
initial_data: {
ocr_text: stepResult.ocrResultData?.ocr_text || (props.mode === 'REVIEW_SESSION_DETAIL' ? '统一回顾分析' : ''),
tags: stepResult.ocrResultData?.tags || (props.mode === 'REVIEW_SESSION_DETAIL' ? ['回顾分析'] : []),
mistake_type: stepResult.ocrResultData?.mistake_type || (props.mode === 'REVIEW_SESSION_DETAIL' ? '统一回顾分析' : ''),
first_answer: '', // 暂时为空，等待流式填充
},
};
setAnalysisResult(tempAnalysisResult);
// 第二步：开始流式AI解答
console.log('🤖 第二步：开始流式AI解答...');
// 如果没有预设的初始消息，创建一个空的助手消息等待流式填充
if (!stepResult.initialMessages || stepResult.initialMessages.length === 0) {
const initialMessage: ChatMessage = {
role: 'assistant',
content: '',
timestamp: new Date().toISOString(),
};
console.log('🔧 [初始化] 创建空的助手消息等待流式填充');
setChatHistory([initialMessage]);
setStreamingMessageIndex(0);
} else {
console.log('🔧 [初始化] 使用预设消息，消息数量:', stepResult.initialMessages.length);
setChatHistory(stepResult.initialMessages);
// 如果有预设消息，准备流式更新最后一条助手消息
const lastIndex = stepResult.initialMessages.length - 1;
if (stepResult.initialMessages[lastIndex]?.role === 'assistant') {
console.log('🔧 [初始化] 设置streamingMessageIndex为:', lastIndex);
setStreamingMessageIndex(lastIndex);
} else {
// 如果最后一条不是助手消息，添加一条空的助手消息
const newMessage: ChatMessage = {
role: 'assistant',
content: '',
timestamp: new Date().toISOString(),
};
console.log('🔧 [初始化] 最后一条不是助手消息，添加新的助手消息');
setChatHistory([...stepResult.initialMessages, newMessage]);
setStreamingMessageIndex(stepResult.initialMessages.length);
}
}
// 启动流式解答
console.log(`🚀 启动流式解答，streamId: ${stepResult.streamIdForEvents}, enable_chain_of_thought: ${enableChainOfThought}, enable_rag: ${enableRag}`);
await props.serviceConfig.apiProvider.startMainStreaming({
streamIdForEvents: stepResult.streamIdForEvents,
enableChainOfThought,
enableRag,
ragTopK
});
// 注意：事件监听逻辑将被移到下面的useEffect中
} else {
// 使用传统非流式分析
console.log('📊 使用传统分析模式...');
// 传统分析模式暂不支持
throw new Error('传统分析模式暂不支持，请使用流式模式');
}
} catch (error) {
console.error('❌ 分析失败:', error);
alert('分析失败: ' + error);
setStreamingMessageIndex(null);
setOcrResult(null);
setIsOcrComplete(false);
setIsOcrInProgress(false);
setIsAnalyzing(false);
} finally {
// setIsAnalyzing(false); // isAnalyzing状态由事件监听器在流结束后设置
}
}, [
props.mode,
userQuestion,
questionImages,
useStreamMode,
subject,
enableChainOfThought,
enableRag,
ragTopK,
props.serviceConfig.apiProvider,
props.businessSessionId
]);
// 自动启动分析逻辑 - 🎯 修复：使用稳定的函数引用避免重复启动
const autoStartExecutedRef = useRef(false);
const handleAnalyzeRef = useRef(handleAnalyze);
handleAnalyzeRef.current = handleAnalyze; // 保持引用最新
useEffect(() => {
// 调试日志：检查自动启动条件
console.log('🔍 检查自动启动条件:', {
mode: props.mode,
status: props.preloadedData?.status,
autoStartTriggered,
autoStartExecutedRef: autoStartExecutedRef.current,
chatHistoryLength: chatHistory.length,
isAnalyzing,
isChatting
});
if (props.mode === 'REVIEW_SESSION_DETAIL' &&
props.preloadedData?.status === 'pending' &&
!autoStartTriggered &&
!autoStartExecutedRef.current &&
!isAnalyzing && // 🎯 新增：确保不在分析中
!isChatting && // 🎯 新增：确保不在对话中
chatHistory.length === 0) { // 🎯 新增：确保聊天记录为空（初始状态）
console.log('🚀 自动启动回顾分析流式处理 (条件满足)...');
setAutoStartTriggered(true);
autoStartExecutedRef.current = true;
// 🎯 使用 ref 调用函数，避免依赖不稳定的函数引用
console.log('🎯 执行自动启动handleAnalyze');
handleAnalyzeRef.current().catch(error => {
console.error('❌ 自动启动分析失败:', error);
setAutoStartTriggered(false); // 重置状态允许重试
autoStartExecutedRef.current = false; // 重置执行标记
});
} else if (autoStartExecutedRef.current && chatHistory.length > 0) {
// 🎯 新增：如果已经执行过自动启动且有聊天记录，说明流式处理已完成
console.log('✅ 自动启动的流式处理已完成，聊天记录长度:', chatHistory.length);
}
}, [
props.mode,
props.preloadedData?.status,
autoStartTriggered,
isAnalyzing, // 🎯 新增依赖：确保状态变化时重新检查
isChatting, // 🎯 新增依赖：确保状态变化时重新检查
chatHistory.length // 🎯 新增依赖：聊天记录变化时重新检查
// 🚨 移除 handleAnalyze 依赖！这是导致重复启动的根本原因
// handleAnalyze 函数因为依赖项变化会不断重新创建，导致这个 useEffect 重复触发
]);
// 使用useRef来保持事件监听器的稳定性
const eventListenersRef = useRef<{
unlistenContent?: () => void;
unlistenThinking?: () => void;
unlistenRag?: () => void;
currentStreamId?: string;
lastEventType?: 'initial' | 'continuation';
lastEventId?: string; // 🎯 新增：用于防止重复事件处理
isActivelyStreaming?: boolean; // 🎯 新增：用于保护正在进行的流式传输
lastStreamCompletionTime?: number; // 🎯 新增：记录上次流式完成时间，用于保护窗口
streamTimeoutId?: number; // 🎯 新增：流式超时定时器ID
}>({});
// 稳定的事件处理函数
const handleStreamEvent = useCallback((event: any, isThinking: boolean = false) => {
const currentIsGeneratingSummary = isGeneratingSummaryRef.current;
console.log(`💬 [Stable] 收到${isThinking ? '思维链' : '主内容'}流:`, event.payload);
console.log(`🔍 [Stable] 当前isGeneratingSummary状态 (ref):`, currentIsGeneratingSummary);
console.log(`🔍 [Stable] 事件类型: ${event.payload.is_complete ? '完成信号' : '流式内容'}`);
console.log(`🔍 [事件处理详情] 处理状态:`, {
isThinking,
streamingMessageIndex,
chatHistoryLength: chatHistory.length,
targetIndex: streamingMessageIndex ?? (chatHistory.length > 0 ? chatHistory.length - 1 : 0),
eventContentLength: event.payload.content?.length || 0,
isComplete: event.payload.is_complete || false,
mode: props.mode
});
if (isThinking) {
// 🎯 修复：改进思维链索引计算逻辑
let targetIndex;
// 🎯 关键修复：在追问场景中，优先验证streamingMessageIndex的有效性
if (streamingMessageIndex !== null && streamingMessageIndex >= 0 && streamingMessageIndex < chatHistory.length) {
// 🎯 进一步验证：确保目标索引对应的是assistant消息
const targetMessage = chatHistory[streamingMessageIndex];
if (targetMessage && targetMessage.role === 'assistant') {
targetIndex = streamingMessageIndex;
console.log(`🧠 [思维链] 使用已验证的streamingMessageIndex: ${targetIndex}, 对应消息角色: ${targetMessage.role}`);
} else {
console.warn(`🧠 [思维链] streamingMessageIndex(${streamingMessageIndex})对应的消息不是assistant或不存在，寻找替代索引`);
targetIndex = null; // 强制进入查找逻辑
}
} else {
console.log(`🧠 [思维链] streamingMessageIndex无效或为null: ${streamingMessageIndex}, 聊天历史长度: ${chatHistory.length}`);
targetIndex = null; // 强制进入查找逻辑
}
// 如果streamingMessageIndex无效，则查找最后一条assistant消息
if (targetIndex === null) {
console.log('🧠 [思维链] 开始查找最后一条assistant消息...');
let lastAssistantIndex = -1;
for (let i = chatHistory.length - 1; i >= 0; i--) {
console.log(`🧠 [思维链] 检查索引${i}: 角色=${chatHistory[i]?.role}, 内容长度=${chatHistory[i]?.content?.length || 0}`);
if (chatHistory[i]?.role === 'assistant') {
lastAssistantIndex = i;
console.log(`🧠 [思维链] 找到最后一条assistant消息，索引: ${lastAssistantIndex}`);
break;
}
}
if (lastAssistantIndex >= 0) {
targetIndex = lastAssistantIndex;
console.log(`🧠 [思维链] 使用找到的assistant消息索引: ${targetIndex}`);
} else {
// 兜底：如果没找到assistant消息，使用末尾索引，但要确保不越界
targetIndex = Math.max(0, Math.min(chatHistory.length - 1, chatHistory.length - 1));
console.warn(`🧠 [思维链] 未找到assistant消息，使用兜底索引: ${targetIndex}`);
}
}
// 🎯 新增：最终验证目标索引的合理性
if (targetIndex < 0 || targetIndex >= chatHistory.length) {
console.error(`🧠 [思维链] 最终计算的索引${targetIndex}超出范围[0, ${chatHistory.length-1}]，丢弃此思维链事件`);
return;
}
const finalTargetMessage = chatHistory[targetIndex];
console.log(`🧠 [思维链] 最终使用索引: ${targetIndex}, 对应消息:`, {
role: finalTargetMessage?.role,
contentLength: finalTargetMessage?.content?.length || 0,
messageExists: !!finalTargetMessage,
isAssistant: finalTargetMessage?.role === 'assistant'
});
// 🎯 安全检查：如果目标消息不是assistant，记录警告但仍然处理
if (finalTargetMessage?.role !== 'assistant') {
console.warn(`🧠 [思维链] 警告：索引${targetIndex}对应的消息角色是'${finalTargetMessage?.role}'，不是'assistant'`);
}
setThinkingContent(prev => {
const newMap = new Map(prev);
// 🎯 修复：根据事件类型决定是追加还是替换
if (event.payload.is_complete) {
// 如果是完成事件，使用完整内容
if (event.payload.content) {
console.log(`🧠 [思维链完成] 索引${targetIndex}设置完整内容，长度: ${event.payload.content.length}`);
newMap.set(targetIndex, event.payload.content);
}
} else {
// 如果是流式事件，追加内容
const currentContent = newMap.get(targetIndex) || '';
const newContent = currentContent + (event.payload.content || '');
console.log(`🧠 [思维链流式] 索引${targetIndex}追加内容，从${currentContent.length}到${newContent.length}`);
newMap.set(targetIndex, newContent);
}
console.log(`🧠 [思维链状态] 当前思维链映射:`, Array.from(newMap.entries()).map(([idx, content]) => `${idx}: ${content.length}字符`));
return newMap;
});
return;
}
// 处理主内容
if (event.payload.is_complete) {
console.log('🎉 [Stable] 流式完成');
// 检查是否为总结生成完成
if (currentIsGeneratingSummary) {
console.log('📝 [Stable] 总结生成完成');
if (event.payload.content) {
setSummaryStreamContent(event.payload.content);
// 🎯 新增：保存总结内容到数据库
handleSaveSummaryToDatabase(event.payload.content);
}
setSummaryStreamComplete(true);
setIsGeneratingSummary(false);
console.log('📝 [Stable] 总结状态重置完成');
return;
}
// 普通聊天完成处理 - 🎯 新策略：优先保护已累积的内容
console.log('🎉 [完成处理] 流式传输完成:', {
targetIndex: streamingMessageIndex ?? (chatHistory.length - 1),
hasCompletionContent: !!event.payload.content,
completionContentLength: event.payload.content?.length || 0,
completionContentPreview: event.payload.content?.substring(0, 100) || '[无内容]'
});
// 🎯 关键策略：完成事件主要用于标记流式结束，内容保护优先
setChatHistory(prev => {
const newHistory = [...prev];
const targetIndex = streamingMessageIndex ?? newHistory.length - 1;
if (newHistory[targetIndex]) {
const currentContent = newHistory[targetIndex].content as string || '';
let finalContent = currentContent; // 默认保持当前内容
// 只有在特定条件下才使用完成事件的内容
if (event.payload.content) {
// 策略1：如果当前内容为空，使用完成事件内容
if (currentContent.length === 0) {
finalContent = event.payload.content;
console.log('🔧 [完成处理] 当前内容为空，使用完成事件内容');
}
// 策略2：如果完成事件内容明显更完整（超过当前内容1.5倍），才考虑使用
else if (event.payload.content.length > currentContent.length * 1.5) {
finalContent = event.payload.content;
console.log('🔧 [完成处理] 完成事件内容更完整，使用完成事件内容');
}
// 策略3：默认保持当前累积内容
else {
console.log('🔧 [完成处理] 保护当前累积内容，忽略完成事件内容');
}
} else {
console.log('🔧 [完成处理] 完成事件无内容，保持当前累积内容');
}
console.log('🔧 [完成处理] 最终选择:', {
currentLength: currentContent.length,
completionLength: event.payload.content?.length || 0,
finalLength: finalContent.length,
strategy: finalContent === currentContent ? 'KEEP_CURRENT' : 'USE_COMPLETION'
});
newHistory[targetIndex] = { ...newHistory[targetIndex], content: finalContent };
} else {
console.warn('🚨 [完成处理] 目标索引不存在:', targetIndex);
}
return newHistory;
});
setIsAnalyzing(false);
setIsChatting(false);
setIsInputAllowed(true);
setStreamingMessageIndex(null);
// 🎯 记录流式完成时间，用于状态同步保护
eventListenersRef.current.lastStreamCompletionTime = Date.now();
// 🎯 清理流式超时定时器
if (eventListenersRef.current.streamTimeoutId) {
clearTimeout(eventListenersRef.current.streamTimeoutId);
eventListenersRef.current.streamTimeoutId = undefined;
console.log('🧹 [流式完成] 清理超时定时器');
}
} else if (event.payload.content) {
// 流式更新
if (currentIsGeneratingSummary) {
console.log(`📝 [Stable] 总结流式更新: "${event.payload.content.substring(0, 50)}..."`);
setSummaryStreamContent(prev => prev + event.payload.content);
return;
}
// 普通聊天流式更新
console.log(`💬 [Stable] 普通聊天流式更新:`, {
streamingMessageIndex,
eventContent: event.payload.content.substring(0, 50) + '...',
eventContentLength: event.payload.content.length
});
// 🎯 流式事件到达，清理超时定时器（避免误报）
if (eventListenersRef.current.streamTimeoutId) {
clearTimeout(eventListenersRef.current.streamTimeoutId);
eventListenersRef.current.streamTimeoutId = undefined;
console.log('🧹 [流式到达] 清理超时定时器');
}
setChatHistory(prev => {
const newHistory = [...prev];
const targetIndex = streamingMessageIndex ?? newHistory.length - 1;
console.log(`💬 [Stable] 更新目标索引: ${targetIndex}, 历史长度: ${newHistory.length}`);
if (newHistory[targetIndex]) {
const currentContent = newHistory[targetIndex].content as string || '';
newHistory[targetIndex] = {
...newHistory[targetIndex],
content: currentContent + event.payload.content
};
console.log(`💬 [Stable] 更新成功，新内容长度: ${newHistory[targetIndex].content.length}`);
} else {
console.warn(`💬 [Stable] 目标索引 ${targetIndex} 不存在于历史记录中`);
}
return newHistory;
});
}
}, [streamingMessageIndex, chatHistory.length]);
// 🎯 新增：保存总结内容到数据库的函数
const handleSaveSummaryToDatabase = useCallback(async (summaryContent: string) => {
try {
// 只有在错题详情模式下才保存总结内容
if (props.mode !== 'EXISTING_MISTAKE_DETAIL') {
console.log('📝 [总结保存] 非错题详情模式，跳过保存');
return;
}
// 确保有 businessSessionId（即错题ID）
if (!props.businessSessionId) {
console.error('❌ [总结保存] 缺少错题ID，无法保存');
return;
}
console.log('💾 [总结保存] 开始保存总结内容到数据库...');
console.log('📄 [总结保存] 总结内容长度:', summaryContent.length);
console.log('🆔 [总结保存] 错题ID:', props.businessSessionId);
// 🎯 修复：解析总结内容，保持原始格式
const parseSummaryContent = (content: string) => {
console.log('📄 [总结解析] 原始内容长度:', content.length);
console.log('📄 [总结解析] 原始内容预览:', content.substring(0, 200) + '...');
// 🎯 策略1：如果内容较短或者没有明显的分段标识，保存到第一个字段
const lines = content.split('\n');
const hasNumberedSections = lines.some(line => /^\s*\d+\.\s*(核心知识点|错误分析|学习建议)/.test(line));
const hasMarkdownSections = lines.some(line => /^#+\s*(核心知识点|错误分析|学习建议)/.test(line));
if (!hasNumberedSections && !hasMarkdownSections) {
console.log('📄 [总结解析] 无明确分段，保存到mistake_summary');
return {
mistakeSummary: content.trim(),
userErrorAnalysis: null,
};
}
// 🎯 策略2：尝试分段，但保持更完整的内容
let mistakeSummary = '';
let userErrorAnalysis = '';
let currentSection = '';
for (const line of lines) {
const trimmedLine = line.trim();
// 检测章节标题
if (/^\s*\d+\.\s*核心知识点|^#+\s*核心知识点|题目解析|正确解法/.test(trimmedLine)) {
currentSection = 'mistake_summary';
} else if (/^\s*\d+\.\s*错误分析|^#+\s*错误分析|^\s*\d+\.\s*学习建议|^#+\s*学习建议|薄弱环节/.test(trimmedLine)) {
currentSection = 'user_error_analysis';
}
if (currentSection === 'mistake_summary') {
mistakeSummary += line + '\n';
} else if (currentSection === 'user_error_analysis') {
userErrorAnalysis += line + '\n';
} else if (!currentSection) {
// 如果还没有检测到分段，先放到第一个字段
mistakeSummary += line + '\n';
}
}
// 🎯 策略3：如果分段后某个字段为空，将所有内容保存到第一个字段
if (!mistakeSummary.trim() && !userErrorAnalysis.trim()) {
console.log('📄 [总结解析] 分段失败，保存完整内容到mistake_summary');
return {
mistakeSummary: content.trim(),
userErrorAnalysis: null,
};
}
console.log('📄 [总结解析] 分段结果:', {
mistakeSummaryLength: mistakeSummary.trim().length,
userErrorAnalysisLength: userErrorAnalysis.trim().length
});
return {
mistakeSummary: mistakeSummary.trim() || null,
userErrorAnalysis: userErrorAnalysis.trim() || null,
};
};
// 解析总结内容，分离 mistake_summary 和 user_error_analysis
const { mistakeSummary, userErrorAnalysis } = parseSummaryContent(summaryContent);
// 使用原始错题对象作为基础，只更新总结字段
const originalMistake = props.preloadedData?.originalMistake;
if (!originalMistake) {
console.error('❌ [总结保存] 缺少原始错题对象，无法更新');
return;
}
const mistakeUpdate = {
...originalMistake,
// 更新总结字段
mistake_summary: mistakeSummary,
user_error_analysis: userErrorAnalysis,
status: "completed", // 🎯 修复：设置状态为已完成
updated_at: new Date().toISOString(),
};
// 调用后端 API 更新错题记录
const response = await TauriAPI.updateMistake(mistakeUpdate);
console.log('✅ [总结保存] 总结内容已成功保存到数据库');
console.log('📊 [总结保存] 更新后的错题数据:', response);
// 🎯 通过回调通知父组件更新 selectedMistake 状态
if (props.onSaveRequest) {
console.log('📢 [总结保存] 通知父组件更新错题状态...');
await props.onSaveRequest({
businessSessionId: props.businessSessionId,
chatHistory,
thinkingContent,
summaryContent, // 传递总结内容
originalInputs: {
subject: props.preloadedData?.subject || '',
userQuestion: props.preloadedData?.userQuestion || '',
questionImages: []
}
});
console.log('✅ [总结保存] 父组件状态更新完成');
}
} catch (error) {
console.error('❌ [总结保存] 保存总结内容失败:', error);
}
}, [props.mode, props.businessSessionId, props.preloadedData, chatHistory, thinkingContent, props.onSaveRequest]);
// 设置事件监听器（仅在streamId变化时）
useEffect(() => {
if (!currentStreamId) {
return;
}
// 检查是否需要重新设置监听器（考虑总结生成状态变化）
const listenerKey = `${currentStreamId}_${isGeneratingSummary ? 'summary' : 'normal'}`;
if (eventListenersRef.current.currentStreamId === listenerKey) {
console.log('🎧 [Stable] 监听器已存在且状态匹配，跳过重复设置:', {
listenerKey,
isGeneratingSummary
});
return;
}
// 🎯 错题详情和回顾分析页面保护：如果正在流式传输，不要重设监听器
if ((props.mode === 'EXISTING_MISTAKE_DETAIL' || props.mode === 'REVIEW_SESSION_DETAIL') &&
eventListenersRef.current.isActivelyStreaming) {
console.log('🛡️ [流式传输保护] 正在流式传输，跳过监听器重设:', {
mode: props.mode,
currentStreamId,
isActivelyStreaming: eventListenersRef.current.isActivelyStreaming,
streamingMessageIndex,
isChatting
});
return;
}
console.log('🎧 [Stable] 需要重新设置监听器:', {
oldListenerKey: eventListenersRef.current.currentStreamId,
newListenerKey: listenerKey,
currentStreamId,
isGeneratingSummary,
chatHistoryLength: chatHistory.length
});
const setupListeners = async () => {
// 清理旧的监听器
eventListenersRef.current.unlistenContent?.();
eventListenersRef.current.unlistenThinking?.();
eventListenersRef.current.unlistenRag?.();
const { listen } = await import('@tauri-apps/api/event');
// 🎯 重要修复：使用稳定的判断逻辑避免事件名称混乱
let shouldUseContinuation = false;
if (props.mode === 'NEW_MISTAKE_ANALYSIS') {
// 错题分析：基于聊天历史长度判断
const isInitialStream = chatHistory.length <= 1;
shouldUseContinuation = !isInitialStream || isGeneratingSummary;
console.log('🎯 [事件类型判断] 错题分析模式:', {
chatHistoryLength: chatHistory.length,
isInitialStream,
isGeneratingSummary,
shouldUseContinuation,
mode: props.mode
});
} else if (props.mode === 'REVIEW_SESSION_DETAIL') {
// 🎯 回顾分析：使用更精确的判断条件
// 如果是总结生成，总是使用continuation流
if (isGeneratingSummary) {
shouldUseContinuation = true;
} else {
// 🎯 修复：基于更可靠的条件判断事件类型
const hasUserMessages = chatHistory.filter(msg => msg.role === 'user').length > 0;
const hasAssistantContent = chatHistory.some(msg =>
msg.role === 'assistant' &&
typeof msg.content === 'string' &&
msg.content.trim().length > 0
);
// 🎯 关键修复：对于回顾分析，只有当确实需要追问时才使用continuation流
// 当有用户消息时，说明是追问场景，应该使用 review_chat_stream_*
// 当只有助手内容但没有用户消息时，说明是初始分析完成，仍应使用 review_analysis_stream_*
shouldUseContinuation = hasUserMessages;
console.log('🎯 [事件类型判断] 回顾分析模式（修复版）:', {
hasUserMessages,
hasAssistantContent,
shouldUseContinuation,
chatHistoryLength: chatHistory.length,
autoStartExecutedRef: autoStartExecutedRef.current,
eventType: shouldUseContinuation ? 'review_chat_stream' : 'review_analysis_stream'
});
}
} else if (props.mode === 'EXISTING_MISTAKE_DETAIL') {
// 🎯 错题详情页面修复：使用更稳定的判断逻辑，避免监听器频繁重设
if (isGeneratingSummary) {
// 总结生成总是使用continuation流
shouldUseContinuation = true;
} else {
// 🎯 关键修复：使用预加载数据来判断是否为初始加载
// 如果有预加载的聊天记录，说明这是已存在的错题，应该使用continuation流
const hasPreloadedChat = props.preloadedData?.chatHistory && props.preloadedData.chatHistory.length > 0;
// 或者当前聊天记录已经有用户消息（追问场景）
const hasUserMessages = chatHistory.filter(msg => msg.role === 'user').length > 0;
// 错题详情页面几乎总是使用continuation流，因为：
// 1. 如果有预加载聊天记录，说明已有对话历史
// 2. 如果用户发起追问，也应该使用continuation流
shouldUseContinuation = hasPreloadedChat || hasUserMessages || chatHistory.length > 1;
console.log('🎯 [事件类型判断] 错题详情模式（修复版）:', {
hasPreloadedChat,
hasUserMessages,
chatHistoryLength: chatHistory.length,
isGeneratingSummary,
shouldUseContinuation,
mode: props.mode
});
}
} else {
// 其他模式（EXISTING_BATCH_TASK_DETAIL等）：基于聊天历史长度判断
const isInitialStream = chatHistory.length <= 1;
shouldUseContinuation = !isInitialStream || isGeneratingSummary;
console.log('🎯 [事件类型判断] 其他模式:', {
chatHistoryLength: chatHistory.length,
isInitialStream,
isGeneratingSummary,
shouldUseContinuation,
mode: props.mode
});
}
const eventNames = shouldUseContinuation
? props.serviceConfig.streamEventNames.continuationStream(currentStreamId)
: props.serviceConfig.streamEventNames.initialStream(currentStreamId);
console.log('🎧 [Stable] 设置新的事件监听器:', {
streamId: currentStreamId,
chatHistoryLength: chatHistory.length,
shouldUseContinuation,
isGeneratingSummary,
eventNames,
mode: props.mode,
status: props.preloadedData?.status,
eventType: shouldUseContinuation ? 'CONTINUATION' : 'INITIAL',
autoStartExecuted: autoStartExecutedRef.current,
isAnalyzing,
isChatting
});
// 设置主内容监听器
console.log('🎧 [Stable] 正在设置主内容监听器，事件名:', eventNames.data);
console.log('🎧 [Stable] 监听器设置时的状态:', {
currentStreamId,
isGeneratingSummary: isGeneratingSummaryRef.current,
mode: props.mode,
chatHistoryLength: chatHistory.length,
shouldUseContinuation,
eventType: shouldUseContinuation ? 'CONTINUATION' : 'INITIAL'
});
eventListenersRef.current.unlistenContent = await listen(eventNames.data, (event: any) => {
console.log('🎧 [Stable] 主内容监听器收到事件:', {
eventName: eventNames.data,
isGeneratingSummary: isGeneratingSummaryRef.current,
payload: event.payload,
payloadContentLength: event.payload?.content?.length || 0,
isComplete: event.payload?.is_complete || false,
timestamp: new Date().toISOString(),
// 🎯 新增：追踪重复接收
listenerKey: eventListenersRef.current.currentStreamId,
mode: props.mode,
// 🎯 新增：当前聊天状态
currentChatHistoryLength: chatHistory.length,
currentStreamingIndex: streamingMessageIndex,
isChatting,
isAnalyzing
});
// 🎯 新增：防止重复处理相同事件
const eventId = `${eventNames.data}_${event.payload?.content?.substring(0, 10) || 'empty'}_${event.payload?.is_complete}`;
if (eventListenersRef.current.lastEventId === eventId) {
console.warn('🚨 [Stable] 检测到重复事件，跳过处理:', eventId);
return;
}
eventListenersRef.current.lastEventId = eventId;
// 🎯 错题详情和回顾分析页面：标记流式传输状态
if (props.mode === 'EXISTING_MISTAKE_DETAIL' || props.mode === 'REVIEW_SESSION_DETAIL') {
if (!event.payload?.is_complete) {
eventListenersRef.current.isActivelyStreaming = true;
} else {
eventListenersRef.current.isActivelyStreaming = false;
}
}
// 🎯 新增：验证事件处理条件
console.log('🎯 [事件处理] 准备处理事件，当前状态:', {
hasValidStreamingIndex: streamingMessageIndex !== null,
chatHistoryLength: chatHistory.length,
targetIndex: streamingMessageIndex ?? (chatHistory.length - 1),
isActivelyStreaming: eventListenersRef.current.isActivelyStreaming
});
handleStreamEvent(event, false);
});
// 设置思维链监听器
if (enableChainOfThought) {
eventListenersRef.current.unlistenThinking = await listen(eventNames.reasoning, (event: any) => {
handleStreamEvent(event, true);
});
}
// 🎯 修复：重新添加被遗漏的RAG来源事件监听器
if (enableRag && eventNames.ragSources) {
console.log('🎧 [Stable] 正在设置RAG来源监听器，事件名:', eventNames.ragSources);
eventListenersRef.current.unlistenRag = await listen(eventNames.ragSources, (event: any) => {
console.log(`📚 [Stable] 收到RAG来源信息:`, event.payload);
if (event.payload && event.payload.sources) {
setChatHistory(prev => {
const newHistory = [...prev];
const targetIndex = streamingMessageIndex ?? newHistory.length - 1;
if (newHistory[targetIndex]) {
newHistory[targetIndex] = {
...newHistory[targetIndex],
rag_sources: event.payload.sources
};
console.log(`✅ [Stable] RAG来源信息已更新到消息索引: ${targetIndex}`);
} else {
console.warn(`⚠️ [Stable] RAG事件：找不到目标消息索引: ${targetIndex}`);
}
return newHistory;
});
}
});
}
eventListenersRef.current.currentStreamId = listenerKey;
// eventListenersRef.current.lastEventType = isInitialStream ? 'initial' : 'continuation'; // 临时简化
};
setupListeners();
return () => {
console.log('🧹 [Stable] 清理事件监听器:', { streamId: currentStreamId });
eventListenersRef.current.unlistenContent?.();
eventListenersRef.current.unlistenThinking?.();
eventListenersRef.current.unlistenRag?.();
eventListenersRef.current.currentStreamId = undefined;
// 🎯 清理流式超时定时器
if (eventListenersRef.current.streamTimeoutId) {
clearTimeout(eventListenersRef.current.streamTimeoutId);
eventListenersRef.current.streamTimeoutId = undefined;
console.log('🧹 [监听器清理] 清理超时定时器');
}
};
}, [
currentStreamId,
isGeneratingSummary,
// 🎯 修复：错题详情页面不再依赖chatHistory.length，但回顾分析页面需要依赖以确保事件名称切换
// NEW_MISTAKE_ANALYSIS和REVIEW_SESSION_DETAIL需要基于chatHistory.length判断事件类型
...(props.mode === 'NEW_MISTAKE_ANALYSIS' || props.mode === 'EXISTING_BATCH_TASK_DETAIL' || props.mode === 'REVIEW_SESSION_DETAIL'
? [chatHistory.length]
: [])
]); // 🎯 REVIEW_SESSION_DETAIL重新加入chatHistory.length依赖，确保初次分析->追问时监听器重设
// 处理总结生成请求 - 使用聊天API但添加特殊标识区分总结内容
const handleGenerateSummary = useCallback(async (summaryPrompt: string) => {
console.log('🔍 [总结生成] 检查streamId状态:', {
currentStreamId,
mode: props.mode,
businessSessionId: props.businessSessionId
});
if (!currentStreamId) {
console.error('❌ 无法生成总结：缺少streamId');
return;
}
// 重置总结状态
console.log('📝 [总结生成] 开始重置状态');
setSummaryStreamContent('');
setSummaryStreamComplete(false);
setIsGeneratingSummary(true);
console.log('📝 [总结生成] 状态重置完成，isGeneratingSummary=true');
// 在总结提示词中添加特殊标识
const specialSummaryPrompt = `[SUMMARY_REQUEST] ${summaryPrompt}`;
// 创建总结请求消息（仅用于内部处理，不显示在聊天记录中）
const summaryRequestMessage: ChatMessage = {
role: 'user',
content: specialSummaryPrompt,
timestamp: new Date().toISOString(),
};
try {
console.log('📝 开始流式生成总结（带特殊标识）...');
// 调用后端API - 使用临时的聊天历史，不保存总结请求到正式记录
console.log(`📡 准备调用 continueUserChat 生成总结，使用的 streamId: ${currentStreamId}`);
console.log('🚫 [总结请求] 使用临时聊天历史，不会保存到数据库');
// 创建临时聊天历史用于总结生成，但不影响实际的聊天记录
const tempChatHistory = [...chatHistory, summaryRequestMessage];
console.log('📡 [总结生成] 当前事件监听器状态:', {
currentStreamId,
chatHistoryLength: chatHistory.length,
tempChatHistoryLength: tempChatHistory.length,
currentEventType: eventListenersRef.current.lastEventType,
isGeneratingSummary: isGeneratingSummaryRef.current,
mode: props.mode,
businessSessionId: props.businessSessionId,
expectedEventName: `continue_chat_stream_${currentStreamId}`
});
await props.serviceConfig.apiProvider.continueUserChat({
streamIdForEvents: currentStreamId,
businessId: props.businessSessionId,
fullChatHistory: tempChatHistory, // 使用临时历史，包含总结请求
enableChainOfThought: false, // 总结不需要思维链
enableRag: false, // 总结不需要RAG
ragTopK: 0
});
} catch (error) {
console.error('❌ 总结生成失败:', error);
alert('总结生成失败: ' + error);
setIsGeneratingSummary(false);
setSummaryStreamComplete(true);
}
}, [currentStreamId, props.serviceConfig.apiProvider, props.businessSessionId, chatHistory]);
// 发送聊天消息 - 完全重写，修复所有流式问题
const handleSendMessage = async () => {
if (!currentMessage.trim() || !currentStreamId) return;
const userMessage: ChatMessage = {
role: 'user',
content: currentMessage,
timestamp: new Date().toISOString(),
};
const newChatHistory = [...chatHistory, userMessage];
setChatHistory(newChatHistory);
setCurrentMessage('');
setIsChatting(true);
try {
if (useStreamMode) {
// 流式对话 - 全新改进版本
console.log('💬 开始流式对话...');
// 创建空的助手消息等待流式填充
const assistantMessage: ChatMessage = {
role: 'assistant',
content: '',
timestamp: new Date().toISOString(),
};
const streamingHistory = [...newChatHistory, assistantMessage];
const newStreamingIndex = streamingHistory.length - 1;
// 🎯 关键修复：先更新聊天历史，再设置streamingMessageIndex
setChatHistory(streamingHistory);
// 🎯 延迟设置streamingMessageIndex，确保聊天历史已经更新
setTimeout(() => {
console.log(`🎯 [追问修复] 设置streamingMessageIndex: ${newStreamingIndex}, 聊天历史长度: ${streamingHistory.length}`);
console.log(`🎯 [追问修复] 目标消息验证:`, {
targetMessage: streamingHistory[newStreamingIndex],
role: streamingHistory[newStreamingIndex]?.role,
isAssistant: streamingHistory[newStreamingIndex]?.role === 'assistant'
});
setStreamingMessageIndex(newStreamingIndex);
}, 10); // 短暂延迟，让状态更新完成
// 调用后端API
console.log(`📡 准备调用 continueUserChat，使用的 streamId: ${currentStreamId}`);
console.log(`📡 [追问调试] 当前状态:`, {
newStreamingIndex: newStreamingIndex,
chatHistoryLength: newChatHistory.length,
fullHistoryLength: streamingHistory.length,
currentStreamId,
businessId: props.businessSessionId,
// 🎯 新增：追问时的关键状态
autoStartExecuted: autoStartExecutedRef.current,
currentEventListenerKey: eventListenersRef.current.currentStreamId,
expectedEventName: `review_chat_stream_${currentStreamId}`,
mode: props.mode
});
// 🎯 新增：确保在发送请求前监听器已正确设置
console.log(`🎧 [追问前检查] 监听器状态:`, {
hasContentListener: !!eventListenersRef.current.unlistenContent,
currentListenerKey: eventListenersRef.current.currentStreamId,
expectedListenerKey: `${currentStreamId}_${isGeneratingSummary ? 'summary' : 'normal'}`
});
await props.serviceConfig.apiProvider.continueUserChat({
streamIdForEvents: currentStreamId,
businessId: props.businessSessionId,
fullChatHistory: newChatHistory,
enableChainOfThought,
enableRag,
ragTopK
});
console.log(`✅ [追问调试] continueUserChat 调用完成`);
// 🎯 新增：设置超时机制，防止流式事件缺失导致永久等待
const streamTimeoutId = setTimeout(() => {
if (isChatting && streamingMessageIndex !== null) {
console.warn('⚠️ [流式超时] 10秒内未收到流式事件，强制清理状态');
setIsChatting(false);
setStreamingMessageIndex(null);
setIsInputAllowed(true);
}
}, 10000); // 10秒超时
// 将超时ID存储到ref中，以便在事件处理中清理
eventListenersRef.current.streamTimeoutId = streamTimeoutId;
} else {
// 传统非流式对话暂不支持
throw new Error('传统对话模式暂不支持，请使用流式模式');
}
} catch (error) {
console.error('❌ 对话失败:', error);
alert('对话失败: ' + error);
setStreamingMessageIndex(null);
setIsChatting(false);
setIsInputAllowed(true);
// 🎯 清理流式超时定时器
if (eventListenersRef.current.streamTimeoutId) {
clearTimeout(eventListenersRef.current.streamTimeoutId);
eventListenersRef.current.streamTimeoutId = undefined;
console.log('🧹 [错误处理] 清理超时定时器');
}
} finally {
// isChatting 状态由事件监听器在流结束后设置，或者在错误/超时时手动设置
}
};
// 保存到错题库
const handleSaveToLibrary = async () => {
try {
// 🎯 修复：正确处理思维链数据的保存
const chatHistoryWithThinking = chatHistory.map((message, index) => {
// 如果是assistant消息且有思维链，则添加thinking_content字段
if (message.role === 'assistant' && thinkingContent.has(index)) {
const thinkingText = thinkingContent.get(index);
console.log(`💾 [保存] 为索引${index}的assistant消息添加思维链，长度:`, thinkingText?.length || 0);
return {
...message,
thinking_content: thinkingText
};
}
return message;
});
console.log('💾 [保存] 处理后的聊天历史，包含思维链的消息数:',
chatHistoryWithThinking.filter(msg => msg.thinking_content).length);
console.log('💾 准备保存数据:', {
businessSessionId: props.businessSessionId,
chatHistoryLength: chatHistoryWithThinking.length,
thinkingContentSize: thinkingContent.size,
ocrResult: ocrResult,
temp_id: analysisResult?.temp_id || currentStreamId,
originalInputs: { subject, userQuestion, questionImagesCount: questionImages.length }
});
// 确保传递正确的temp_id
const temp_id = analysisResult?.temp_id || currentStreamId;
console.log('💾 UniversalAppChatHost传递的temp_id:', temp_id);
await props.onSaveRequest({
businessSessionId: props.businessSessionId,
chatHistory: chatHistoryWithThinking,
thinkingContent,
ocrResult: ocrResult || (analysisResult ? {
ocr_text: analysisResult.initial_data.ocr_text,
tags: analysisResult.initial_data.tags,
mistake_type: analysisResult.initial_data.mistake_type,
temp_id: temp_id === null ? undefined : temp_id
} : null),
temp_id: temp_id === null ? undefined : temp_id,
// 传递总结内容
summaryContent: summaryStreamContent && summaryStreamComplete ? summaryStreamContent : undefined,
originalInputs: {
subject,
userQuestion,
questionImages
}
});
// 只在NEW_MISTAKE_ANALYSIS模式下重置状态
if (props.mode === 'NEW_MISTAKE_ANALYSIS') {
handleReset();
}
} catch (error) {
console.error('保存失败:', error);
alert('保存失败: ' + error);
}
};
// 重置分析
const handleReset = () => {
// 清理timeout
if (updateTimeoutRef.current) {
clearTimeout(updateTimeoutRef.current);
updateTimeoutRef.current = null;
}
setAnalysisResult(null);
setChatHistory([]);
setCurrentMessage('');
setStreamingMessageIndex(null);
setOcrResult(null);
setIsOcrComplete(false);
setIsOcrInProgress(false);
setIsAnalyzing(false);
setUserQuestion('');
setQuestionImages([]);
// 🎯 重要：重置总结状态
setSummaryStreamContent('');
setSummaryStreamComplete(false);
setIsGeneratingSummary(false);
console.log('🔄 [重置分析] 总结状态已重置');
setThinkingContent(new Map());
setIsInputAllowed(false);
};
// 分库接口类型
interface SubLibrary {
id: string;
name: string;
description?: string;
created_at: string;
updated_at: string;
document_count: number;
chunk_count: number;
}
// 分库选择相关状态
const [subLibraries, setSubLibraries] = useState<SubLibrary[]>([]);
const [selectedLibraries, setSelectedLibraries] = useState<string[]>([]);
const [showLibrarySelector, setShowLibrarySelector] = useState(false);
const librarySelectorRef = useRef<HTMLDivElement>(null);
// 加载分库列表
const loadSubLibraries = useCallback(async () => {
try {
const libraries = await TauriAPI.getRagSubLibraries();
setSubLibraries(libraries);
console.log('🎯 加载分库列表完成，数量:', libraries.length);
} catch (error) {
console.error('加载分库列表失败:', error);
}
}, []); // 移除selectedLibraries.length依赖，避免循环触发
// 切换分库选择
const toggleLibrarySelection = (libraryId: string) => {
console.log('🎯 切换知识库选择:', libraryId);
setSelectedLibraries(prev => {
const newSelection = prev.includes(libraryId)
? prev.filter(id => id !== libraryId)
: [...prev, libraryId];
console.log('🎯 知识库选择更新:', prev, '->', newSelection);
return newSelection;
});
};
// 全选/取消全选分库
const toggleAllLibraries = () => {
if (selectedLibraries.length === subLibraries.length) {
// 当前全选状态，执行取消全选
setSelectedLibraries([]);
} else {
// 当前非全选状态，执行全选
setSelectedLibraries(subLibraries.map(lib => lib.id));
}
};
// 处理点击外部关闭分库选择器
useEffect(() => {
const handleClickOutside = (event: MouseEvent) => {
if (librarySelectorRef.current && !librarySelectorRef.current.contains(event.target as Node)) {
setShowLibrarySelector(false);
}
};
if (showLibrarySelector) {
document.addEventListener('mousedown', handleClickOutside);
}
return () => {
document.removeEventListener('mousedown', handleClickOutside);
};
}, [showLibrarySelector]);
// 组件挂载时加载分库列表
useEffect(() => {
if (enableRag) {
loadSubLibraries();
}
}, [enableRag, loadSubLibraries]);
// 初始化默认选中的分库 - 只在首次加载分库时执行
useEffect(() => {
if (subLibraries.length > 0 && selectedLibraries.length === 0) {
// 优先使用props中指定的默认分库
if (props.serviceConfig.defaultSelectedLibraries && props.serviceConfig.defaultSelectedLibraries.length > 0) {
console.log('🎯 使用props指定的默认分库');
setSelectedLibraries(props.serviceConfig.defaultSelectedLibraries);
} else {
// 否则默认选择所有分库（仅在初始化时）
console.log('🎯 初始化时默认选择所有分库');
setSelectedLibraries(subLibraries.map(lib => lib.id));
}
}
}, [subLibraries.length]); // 只在分库列表变化时触发，不依赖selectedLibraries
// 处理props传入的默认选中分库（用于组件重新加载的情况）
useEffect(() => {
if (props.serviceConfig.defaultSelectedLibraries && props.serviceConfig.defaultSelectedLibraries.length > 0) {
console.log('🎯 检测到props中的默认分库设置');
setSelectedLibraries(props.serviceConfig.defaultSelectedLibraries);
}
}, [props.serviceConfig.defaultSelectedLibraries]);
// 渲染分析界面 - 左右分栏布局
const renderAnalysisView = () => (
<div className="analysis-layout">
{/* 左侧上传栏 */}
<div className="left-panel">
<div className="cherry-app">
<div className="app-header">
<div className="app-title">
<img src="/dslogo1.png" alt="DeepStudent 深度学者" className="app-logo" />
</div>
<p className="app-subtitle">
{props.mode === 'NEW_MISTAKE_ANALYSIS' ? '上传多张题目图片获取AI增强解析' : '查看历史分析并进行深度追问'}
</p>
</div>
{/* 科目显示 - 只读 */}
<div className="readonly-subject-display">
<span className="subject-badge">{subject || '未选择科目'}</span>
</div>
{/* 图片上传区域 - 完全按照HTML模板 */}
{props.mode === 'NEW_MISTAKE_ANALYSIS' ? (
<div
className={`upload-card ${questionImages.length > 0 ? 'has-files' : ''}`}
id="uploadArea"
onClick={handleFileUploadClick}
>
<div className="upload-icon">
<svg width="22" height="22" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
<path d="M18 15V18H6V15H4V18C4 19.1 4.9 20 6 20H18C19.1 20 20 19.1 20 18V15H18Z" fill="currentColor"/>
<path d="M12 5L7 10H10V14H14V10H17L12 5Z" fill="currentColor"/>
</svg>
</div>
<p className="upload-text">
{questionImages.length > 0 ? '已添加题目图片' : '拖放题目图片到此处'}
</p>
<p className="upload-hint">
{questionImages.length > 0 ? '可继续添加或拖放更多图片' : '或点击选择文件 (最多9张JPG/PNG)'}
</p>
{questionImages.length > 0 && (
<div className="counter-badge">{questionImages.length}/9</div>
)}
<input
type="file"
multiple
accept="image/*"
onChange={handleImageUpload}
className="file-input"
id="fileInput"
/>
</div>
) : (
// 错题详情模式：显示现有图片
<div className="upload-card readonly-mode">
<div className="upload-icon">
<svg width="22" height="22" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
<path d="M18 15V18H6V15H4V18C4 19.1 4.9 20 6 20H18C19.1 20 20 19.1 20 18V15H18Z" fill="currentColor"/>
<path d="M12 5L7 10H10V14H14V10H17L12 5Z" fill="currentColor"/>
</svg>
</div>
<p className="upload-text">题目图片</p>
<p className="upload-hint">点击下方图片查看大图</p>
</div>
)}
{/* 图片预览列表 */}
<div className="preview-list" id="previewList">
{(() => {
const imagesToDisplay = props.mode === 'NEW_MISTAKE_ANALYSIS'
? questionImageUrls
: (questionImageUrls.length > 0 ? questionImageUrls : (props.preloadedData?.questionImageUrls || []));
return imagesToDisplay.map((url, index) => (
<div key={index} className="preview-item">
<img
src={url}
alt={`题目图片 ${index + 1}`}
className="preview-image"
onClick={() => openImageViewer(index)}
/>
{props.mode === 'NEW_MISTAKE_ANALYSIS' && (
<div
className="preview-remove"
onClick={(e) => {
e.stopPropagation();
removeImage(index);
}}
>
<svg viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
<path d="M18 6L6 18" stroke="white" strokeWidth="2" strokeLinecap="round"/>
<path d="M6 6L18 18" stroke="white" strokeWidth="2" strokeLinecap="round"/>
</svg>
</div>
)}
</div>
));
})()}
</div>
{/* 问题描述输入 */}
<div className="input-container">
<label className="input-label">问题描述 (可选)</label>
{props.mode === 'NEW_MISTAKE_ANALYSIS' ? (
<textarea
className="cherry-textarea"
value={userQuestion}
onChange={(e) => setUserQuestion(e.target.value)}
placeholder="例如：我需要这道微积分题的详细解题步骤..."
/>
) : (
<div className="cherry-textarea readonly">
{userQuestion || props.preloadedData?.userQuestion || '无问题描述'}
</div>
)}
</div>
{/* RAG开关 - 按照HTML模板 */}
{props.mode === 'NEW_MISTAKE_ANALYSIS' && (
<>
<div className="rag-controls-container">
<div className="rag-toggle" id="ragToggle" onClick={() => setEnableRag(!enableRag)}>
<input
type="checkbox"
id="ragCheckbox"
checked={enableRag}
readOnly
/>
<span className="rag-switch">
<span className="rag-slider"></span>
</span>
<span className="rag-label">启用RAG知识库增强</span>
</div>
{/* 分库选择下拉框 */}
{enableRag && (
<div className="rag-library-selector" ref={librarySelectorRef}>
<div
className="library-selector-trigger"
onClick={() => setShowLibrarySelector(!showLibrarySelector)}
>
<span className="library-selector-label">
知识库范围 ({selectedLibraries.length}/{subLibraries.length})
</span>
<span className="library-selector-arrow">
{showLibrarySelector ? '▲' : '▼'}
</span>
</div>
{showLibrarySelector && (
<div className="library-selector-dropdown">
<div className="library-selector-header">
<button
className="library-selector-action"
onClick={(e) => {
e.preventDefault();
e.stopPropagation();
toggleAllLibraries();
}}
>
{selectedLibraries.length === subLibraries.length ? '取消全选' : '全选'}
</button>
</div>
<div className="library-selector-list">
{subLibraries.length > 0 ? (
subLibraries.map(library => (
<div
key={library.id}
className={`library-selector-item ${selectedLibraries.includes(library.id) ? 'selected' : ''}`}
onClick={(e) => {
// 如果点击的是checkbox或其容器，不处理外层点击
if ((e.target as HTMLElement).closest('.library-checkbox')) {
console.log('🎯 点击了checkbox区域，跳过外层处理');
return;
}
console.log('🎯 点击了知识库项目外层区域:', library.id);
e.preventDefault();
e.stopPropagation();
toggleLibrarySelection(library.id);
}}
>
<div className="library-checkbox" onClick={(e) => e.stopPropagation()}>
<input
type="checkbox"
checked={selectedLibraries.includes(library.id)}
onChange={(e) => {
console.log('🎯 checkbox onChange事件:', library.id);
e.preventDefault();
e.stopPropagation();
toggleLibrarySelection(library.id);
}}
/>
</div>
<div className="library-info">
<div className="library-name">{library.name}</div>
<div className="library-stats">
📄 {library.document_count} | 📝 {library.chunk_count}
</div>
</div>
</div>
))
) : (
<div className="library-selector-empty">
<div style={{ padding: '20px', textAlign: 'center', color: 'var(--cherry-text-secondary)', fontSize: '13px' }}>
暂无可用的知识库分库
</div>
</div>
)}
</div>
</div>
)}
</div>
)}
</div>
<div className="rag-hint">
{enableRag
? `连接RAG知识库获取更精准的解析 (已选择 ${selectedLibraries.length} 个分库)`
: '连接RAG知识库获取更精准的解析'
}
</div>
</>
)}
{/* 主要操作按钮 */}
{props.mode === 'NEW_MISTAKE_ANALYSIS' ? (
<button
onClick={handleAnalyze}
disabled={isOcrInProgress || isAnalyzing}
className="analyze-btn"
>
<svg className="btn-icon" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
<path d="M20 7H4V5H20V7Z" fill="#111"/>
<path d="M20 11H4V9H20V11Z" fill="#111"/>
<path d="M4 15H20V13H4V15Z" fill="#111"/>
<path d="M4 19H20V17H4V19Z" fill="#111"/>
</svg>
{isOcrInProgress ? 'OCR进行中...' : isAnalyzing ? '深度分析中...' : '开始深度分析'}
</button>
) : (
<button
onClick={props.onExitRequest}
className="analyze-btn back-mode"
>
← 返回列表
</button>
)}
{/* 次要操作按钮 */}
{analysisResult && props.mode === 'NEW_MISTAKE_ANALYSIS' && (
<div className="secondary-buttons">
<button onClick={handleSaveToLibrary} className="save-btn-secondary">
💾 保存到错题库
</button>
<button onClick={handleReset} className="reset-btn-secondary">
🔄 重新分析
</button>
</div>
)}
</div>
</div>
{/* 右侧结果栏 */}
<div className="right-panel">
{!ocrResult && !analysisResult && props.mode === 'NEW_MISTAKE_ANALYSIS' ? (
<div className="empty-result">
<div className="empty-icon">
<img src="/dslogo2.png" alt="Deep Student" className="empty-logo" />
</div>
<h3>等待分析</h3>
<p>请在左侧上传题目图片并点击"开始分析"</p>
</div>
) : (
<div className="analysis-result">
<div className="result-header">
<h3>📊 分析结果</h3>
{isAnalyzing && (
<div className="analyzing-indicator">
<span className="spinner">⏳</span>
<span>分析中...</span>
</div>
)}
</div>
{/* OCR结果区域 - 立即显示 */}
{ocrResult && (
<div className="result-info">
<div className="info-item">
<strong>题目类型:</strong>
<span className="info-value">{ocrResult.mistake_type}</span>
</div>
<div className="info-item">
<strong>标签:</strong>
<div className="tags">
{ocrResult.tags.map((tag, index) => (
<span key={index} className="tag">{tag}</span>
))}
</div>
</div>
<div className="info-item">
<strong>OCR文本:</strong>
<div className="ocr-text">{ocrResult.ocr_text}</div>
</div>
</div>
)}
{/* AI解答区域 */}
{isOcrComplete && (
<div className={`chat-container ${isChatFullscreen ? 'chat-fullscreen' : ''}`}>
<div className="chat-history">
{chatHistory.map((message, index) => {
const isStreaming = streamingMessageIndex === index;
const thinking = thinkingContent.get(index);
// 检查是否为最后一条AI消息
const isLastAssistantMessage = message.role === 'assistant' &&
index === chatHistory.length - 1 &&
chatHistory.slice(index + 1).every(m => m.role !== 'assistant');
// 调试：总结框显示条件和聊天历史
if (message.role === 'assistant') {
console.log(`🎯 [总结框] 检查消息 ${index}:`, {
isLastAssistantMessage,
messageRole: message.role,
messageIndex: index,
chatHistoryLength: chatHistory.length,
isLastIndex: index === chatHistory.length - 1,
messageContent: typeof message.content === 'string' ? message.content.substring(0, 50) + '...' : '[多媒体内容]',
mode: props.mode,
summaryStreamContent: summaryStreamContent.substring(0, 50) + '...',
summaryStreamComplete
});
}
return (
<MessageWithThinking
key={index}
content={message.content}
thinkingContent={thinking}
isStreaming={isStreaming}
role={message.role as 'user' | 'assistant'}
timestamp={message.timestamp}
ragSources={message.rag_sources}
showSummaryBox={isLastAssistantMessage && props.mode !== 'REVIEW_SESSION_DETAIL'}
chatHistory={chatHistory}
subject={props.preloadedData?.subject}
mistakeId={props.mode === 'EXISTING_MISTAKE_DETAIL' ? props.businessSessionId :
props.mode === 'NEW_MISTAKE_ANALYSIS' ? 'new_analysis' : undefined}
reviewSessionId={props.mode === 'REVIEW_SESSION_DETAIL' ? props.businessSessionId : undefined}
onGenerateSummary={(prompt) => handleGenerateSummary(prompt)}
currentStreamId={currentStreamId ?? undefined}
isGenerating={isGeneratingSummary}
summaryStreamContent={summaryStreamContent}
summaryStreamComplete={summaryStreamComplete}
/>
);
})}
{isAnalyzing && chatHistory.length === 0 && (
<div className="message assistant">
<div className="message-content typing">
<span className="typing-indicator">
<span></span>
<span></span>
<span></span>
</span>
AI正在思考中...
</div>
</div>
)}
{isChatting && streamingMessageIndex === null && (
<div className="message assistant">
<div className="message-content typing">
<span className="typing-indicator">
<span></span>
<span></span>
<span></span>
</span>
正在思考中...
</div>
</div>
)}
</div>
{/* 在OCR开始后就显示输入框，但在分析过程中禁用发送功能 */}
{(analysisResult || isAnalyzing || isOcrInProgress) && (
<div className="chat-input">
<input
type="text"
value={currentMessage}
onChange={(e) => setCurrentMessage(e.target.value)}
placeholder={isOcrInProgress ? "OCR中，请等待..." : isAnalyzing ? "分析中，请等待..." : "继续提问..."}
onKeyDown={(e) => e.key === 'Enter' && !isOcrInProgress && !isAnalyzing && handleSendMessage()}
disabled={isChatting || isOcrInProgress || isAnalyzing}
/>
<button
onClick={handleSendMessage}
disabled={isChatting || !currentMessage.trim() || isOcrInProgress || isAnalyzing}
className="send-button"
>
{isChatting ? '⏳' : (isOcrInProgress || isAnalyzing) ? '⏸️' : '📤'}
</button>
<button
className="chat-fullscreen-toggle"
onClick={handleChatFullscreenToggle}
title={isChatFullscreen ? '退出全屏' : '全屏模式'}
>
{isChatFullscreen ? '🔲' : '📱'}
</button>
</div>
)}
</div>
)}
</div>
)}
</div>
</div>
);
return (
<>
{/* 始终渲染分析界面 */}
{renderAnalysisView()}
{/* 图片查看器 */}
<ImageViewer
images={questionImageUrls}
currentIndex={currentImageIndex}
isOpen={imageViewerOpen}
onClose={() => setImageViewerOpen(false)}
onNext={() => setCurrentImageIndex(prev => (prev + 1) % questionImageUrls.length)}
onPrev={() => setCurrentImageIndex(prev => (prev - 1 + questionImageUrls.length) % questionImageUrls.length)}
/>
</>
);
}
export default UniversalAppChatHost;
|
000haoji/deep-student
| 6,153 |
src/hooks/useSystemSettings.ts
|
/**
* Custom hook for managing system settings
* Extracted from Settings component to reduce complexity
*/
import { useState, useEffect, useCallback } from 'react';
import { invoke as tauriInvoke } from '@tauri-apps/api/core';
// 系统设置接口
export interface SystemSettings {
autoSave: boolean;
theme: string;
language: string;
enableNotifications: boolean;
maxChatHistory: number;
debugMode: boolean;
enableAnkiConnect: boolean;
}
// 检查是否在Tauri环境中
const isTauri = typeof window !== 'undefined' && window.__TAURI_INTERNALS__;
const invoke = isTauri ? tauriInvoke : null;
// 默认设置
const DEFAULT_SETTINGS: SystemSettings = {
autoSave: true,
theme: 'light',
language: 'zh-CN',
enableNotifications: true,
maxChatHistory: 100,
debugMode: false,
enableAnkiConnect: true
};
export const useSystemSettings = () => {
const [settings, setSettings] = useState<SystemSettings>(DEFAULT_SETTINGS);
const [loading, setLoading] = useState(true);
const [saving, setSaving] = useState(false);
// 加载系统设置
const loadSettings = useCallback(async () => {
setLoading(true);
try {
if (invoke) {
const settingsPromises = Object.keys(DEFAULT_SETTINGS).map(async (key) => {
try {
const value = await invoke('get_setting', { key }) as string;
return { key, value };
} catch {
return { key, value: String(DEFAULT_SETTINGS[key as keyof SystemSettings]) };
}
});
const settingsResults = await Promise.all(settingsPromises);
const loadedSettings: SystemSettings = { ...DEFAULT_SETTINGS };
for (const { key, value } of settingsResults) {
const settingKey = key as keyof SystemSettings;
// 类型转换
switch (settingKey) {
case 'autoSave':
case 'enableNotifications':
case 'debugMode':
loadedSettings[settingKey] = value === 'true';
break;
case 'maxChatHistory':
loadedSettings[settingKey] = parseInt(value, 10) || DEFAULT_SETTINGS[settingKey];
break;
default:
(loadedSettings as any)[settingKey] = value;
}
}
setSettings(loadedSettings);
}
} catch (error) {
console.error('加载系统设置失败:', error);
setSettings(DEFAULT_SETTINGS);
} finally {
setLoading(false);
}
}, []);
// 保存单个设置
const saveSetting = useCallback(async (key: keyof SystemSettings, value: any) => {
setSaving(true);
try {
if (invoke) {
await invoke('save_setting', { key, value: String(value) });
setSettings(prev => ({ ...prev, [key]: value }));
return true;
}
return false;
} catch (error) {
console.error(`保存设置 ${key} 失败:`, error);
return false;
} finally {
setSaving(false);
}
}, []);
// 保存所有设置
const saveAllSettings = useCallback(async (newSettings: SystemSettings) => {
setSaving(true);
try {
if (invoke) {
const savePromises = Object.entries(newSettings).map(([key, value]) =>
invoke('save_setting', { key, value: String(value) })
);
await Promise.all(savePromises);
setSettings(newSettings);
return true;
}
return false;
} catch (error) {
console.error('保存系统设置失败:', error);
return false;
} finally {
setSaving(false);
}
}, []);
// 重置设置为默认值
const resetSettings = useCallback(async () => {
return await saveAllSettings(DEFAULT_SETTINGS);
}, [saveAllSettings]);
// 更新设置（本地状态，不保存）
const updateSetting = useCallback(<K extends keyof SystemSettings>(
key: K,
value: SystemSettings[K]
) => {
setSettings(prev => ({ ...prev, [key]: value }));
}, []);
// 批量更新设置（本地状态，不保存）
const updateSettings = useCallback((updates: Partial<SystemSettings>) => {
setSettings(prev => ({ ...prev, ...updates }));
}, []);
// 应用主题
const applyTheme = useCallback(async (theme: string) => {
const success = await saveSetting('theme', theme);
if (success) {
// 应用主题到DOM
document.documentElement.setAttribute('data-theme', theme);
document.body.className = theme === 'dark' ? 'dark-theme' : 'light-theme';
}
return success;
}, [saveSetting]);
// 验证设置
const validateSettings = useCallback((settingsToValidate: Partial<SystemSettings>) => {
const errors: string[] = [];
if (settingsToValidate.maxChatHistory !== undefined) {
if (settingsToValidate.maxChatHistory < 10 || settingsToValidate.maxChatHistory > 1000) {
errors.push('最大聊天历史记录数量必须在10-1000之间');
}
}
if (settingsToValidate.theme !== undefined) {
if (!['light', 'dark', 'auto'].includes(settingsToValidate.theme)) {
errors.push('主题必须是light、dark或auto');
}
}
if (settingsToValidate.language !== undefined) {
if (!['zh-CN', 'en-US'].includes(settingsToValidate.language)) {
errors.push('语言必须是zh-CN或en-US');
}
}
return errors;
}, []);
// 获取设置摘要（用于显示）
const getSettingsSummary = useCallback(() => {
return {
configuredItems: Object.keys(settings).length,
autoSaveEnabled: settings.autoSave,
currentTheme: settings.theme,
debugModeEnabled: settings.debugMode,
maxHistorySize: settings.maxChatHistory
};
}, [settings]);
// 初始化时加载设置
useEffect(() => {
loadSettings();
}, [loadSettings]);
// 应用主题到DOM
useEffect(() => {
if (!loading) {
document.documentElement.setAttribute('data-theme', settings.theme);
document.body.className = settings.theme === 'dark' ? 'dark-theme' : 'light-theme';
}
}, [settings.theme, loading]);
return {
// 状态
settings,
loading,
saving,
// 方法
loadSettings,
saveSetting,
saveAllSettings,
resetSettings,
updateSetting,
updateSettings,
applyTheme,
validateSettings,
getSettingsSummary,
// 便利属性
isAutoSaveEnabled: settings.autoSave,
isDarkTheme: settings.theme === 'dark',
isDebugMode: settings.debugMode
};
};
|
000haoji/deep-student
| 5,277 |
src/hooks/useNotification.ts
|
/**
* Custom hook for managing notifications and messages
* Extracted from various components to reduce complexity
*/
import { useState, useCallback, useRef, useEffect } from 'react';
export interface NotificationMessage {
id: string;
type: 'success' | 'error' | 'warning' | 'info';
title?: string;
text: string;
duration?: number;
persistent?: boolean;
}
export const useNotification = () => {
const [notifications, setNotifications] = useState<NotificationMessage[]>([]);
const timeoutRefs = useRef<Map<string, any>>(new Map());
// 显示通知
const showNotification = useCallback((
type: NotificationMessage['type'],
text: string,
options?: {
title?: string;
duration?: number;
persistent?: boolean;
}
) => {
const id = `notification-${Date.now()}-${Math.random().toString(36).substr(2, 9)}`;
const duration = options?.duration ?? (type === 'error' ? 5000 : 3000);
const notification: NotificationMessage = {
id,
type,
text,
title: options?.title,
duration,
persistent: options?.persistent || false
};
setNotifications(prev => [...prev, notification]);
// 自动删除（除非是持久化通知）
if (!notification.persistent && duration > 0) {
const timeoutId = setTimeout(() => {
removeNotification(id);
}, duration);
timeoutRefs.current.set(id, timeoutId);
}
return id;
}, []);
// 删除通知
const removeNotification = useCallback((id: string) => {
setNotifications(prev => prev.filter(n => n.id !== id));
// 清除定时器
const timeoutId = timeoutRefs.current.get(id);
if (timeoutId) {
clearTimeout(timeoutId);
timeoutRefs.current.delete(id);
}
}, []);
// 清除所有通知
const clearAllNotifications = useCallback(() => {
// 清除所有定时器
timeoutRefs.current.forEach(timeoutId => clearTimeout(timeoutId));
timeoutRefs.current.clear();
setNotifications([]);
}, []);
// 便利方法
const showSuccess = useCallback((text: string, options?: Omit<Parameters<typeof showNotification>[2], 'title'> & { title?: string }) => {
return showNotification('success', text, options);
}, [showNotification]);
const showError = useCallback((text: string, options?: Omit<Parameters<typeof showNotification>[2], 'title'> & { title?: string }) => {
return showNotification('error', text, options);
}, [showNotification]);
const showWarning = useCallback((text: string, options?: Omit<Parameters<typeof showNotification>[2], 'title'> & { title?: string }) => {
return showNotification('warning', text, options);
}, [showNotification]);
const showInfo = useCallback((text: string, options?: Omit<Parameters<typeof showNotification>[2], 'title'> & { title?: string }) => {
return showNotification('info', text, options);
}, [showNotification]);
// 显示加载通知
const showLoading = useCallback((text: string, options?: { title?: string }) => {
return showNotification('info', text, {
...options,
persistent: true,
duration: 0
});
}, [showNotification]);
// 更新现有通知
const updateNotification = useCallback((id: string, updates: Partial<Omit<NotificationMessage, 'id'>>) => {
setNotifications(prev => prev.map(notification =>
notification.id === id
? { ...notification, ...updates }
: notification
));
}, []);
// 检查是否有特定类型的通知
const hasNotificationType = useCallback((type: NotificationMessage['type']) => {
return notifications.some(n => n.type === type);
}, [notifications]);
// 获取特定类型的通知数量
const getNotificationCount = useCallback((type?: NotificationMessage['type']) => {
if (type) {
return notifications.filter(n => n.type === type).length;
}
return notifications.length;
}, [notifications]);
// 批量操作的便利方法
const showBatchResult = useCallback((
results: { success: number; failed: number; total: number },
operation: string
) => {
if (results.failed === 0) {
showSuccess(`${operation}成功完成，处理了 ${results.success} 项`);
} else if (results.success === 0) {
showError(`${operation}失败，${results.failed} 项处理失败`);
} else {
showWarning(
`${operation}部分完成：${results.success} 项成功，${results.failed} 项失败`
);
}
}, [showSuccess, showError, showWarning]);
// 显示操作确认
const showOperationProgress = useCallback((operation: string, current: number, total: number) => {
const id = `progress-${operation}`;
updateNotification(id, {
type: 'info',
text: `${operation}中... (${current}/${total})`,
persistent: true
});
return id;
}, [updateNotification]);
// 清理函数
useEffect(() => {
return () => {
// 组件卸载时清理所有定时器
timeoutRefs.current.forEach(timeoutId => clearTimeout(timeoutId));
timeoutRefs.current.clear();
};
}, []);
return {
// 状态
notifications,
hasNotifications: notifications.length > 0,
// 基础方法
showNotification,
removeNotification,
clearAllNotifications,
updateNotification,
// 便利方法
showSuccess,
showError,
showWarning,
showInfo,
showLoading,
// 查询方法
hasNotificationType,
getNotificationCount,
// 特殊用途方法
showBatchResult,
showOperationProgress
};
};
|
000haoji/deep-student
| 7,273 |
src/hooks/useApiConfig.ts
|
/**
* Custom hook for managing API configurations
* Extracted from Settings component to reduce complexity
*/
import { useState, useEffect, useCallback } from 'react';
import { invoke as tauriInvoke } from '@tauri-apps/api/core';
// API配置接口
export interface ApiConfig {
id: string;
name: string;
apiKey: string;
baseUrl: string;
model: string;
isMultimodal: boolean;
isReasoning: boolean;
enabled: boolean;
modelAdapter: string;
}
// 模型分配接口
export interface ModelAssignments {
model1_config_id: string | null;
model2_config_id: string | null;
review_analysis_model_config_id: string | null;
anki_card_model_config_id: string | null;
embedding_model_config_id: string | null;
reranker_model_config_id: string | null;
summary_model_config_id: string | null;
}
// 检查是否在Tauri环境中
const isTauri = typeof window !== 'undefined' && window.__TAURI_INTERNALS__;
const invoke = isTauri ? tauriInvoke : null;
export const useApiConfig = () => {
const [apiConfigs, setApiConfigs] = useState<ApiConfig[]>([]);
const [modelAssignments, setModelAssignments] = useState<ModelAssignments>({
model1_config_id: null,
model2_config_id: null,
review_analysis_model_config_id: null,
anki_card_model_config_id: null,
embedding_model_config_id: null,
reranker_model_config_id: null,
summary_model_config_id: null,
});
const [loading, setLoading] = useState(true);
const [saving, setSaving] = useState(false);
const [testingApi, setTestingApi] = useState<string | null>(null);
// 加载API配置
const loadApiConfigs = useCallback(async () => {
setLoading(true);
try {
if (invoke) {
const [configs, assignments] = await Promise.all([
invoke('get_api_configurations').catch(() => []) as Promise<ApiConfig[]>,
invoke('get_model_assignments').catch(() => ({
model1_config_id: null,
model2_config_id: null,
review_analysis_model_config_id: null,
anki_card_model_config_id: null,
embedding_model_config_id: null,
reranker_model_config_id: null,
summary_model_config_id: null,
})) as Promise<ModelAssignments>
]);
setApiConfigs(configs || []);
setModelAssignments(assignments || {
model1_config_id: null,
model2_config_id: null,
review_analysis_model_config_id: null,
anki_card_model_config_id: null,
embedding_model_config_id: null,
reranker_model_config_id: null,
summary_model_config_id: null,
});
}
} catch (error) {
console.error('加载API配置失败:', error);
} finally {
setLoading(false);
}
}, []);
// 保存API配置
const saveApiConfigs = useCallback(async (configs: ApiConfig[]) => {
setSaving(true);
try {
if (invoke) {
await invoke('save_api_configurations', { configs });
setApiConfigs(configs);
return true;
}
return false;
} catch (error) {
console.error('保存API配置失败:', error);
return false;
} finally {
setSaving(false);
}
}, []);
// 保存模型分配
const saveModelAssignments = useCallback(async (assignments: ModelAssignments) => {
setSaving(true);
try {
if (invoke) {
await invoke('save_model_assignments', { assignments });
setModelAssignments(assignments);
return true;
}
return false;
} catch (error) {
console.error('保存模型分配失败:', error);
return false;
} finally {
setSaving(false);
}
}, []);
// 测试API连接
const testApiConnection = useCallback(async (config: ApiConfig) => {
setTestingApi(config.id);
try {
if (invoke) {
const result = await invoke('test_api_connection', {
apiKey: config.apiKey,
baseUrl: config.baseUrl
}) as boolean;
return result;
}
return false;
} catch (error) {
console.error('API连接测试失败:', error);
return false;
} finally {
setTestingApi(null);
}
}, []);
// 添加API配置
const addApiConfig = useCallback((config: Omit<ApiConfig, 'id'>) => {
const newConfig: ApiConfig = {
...config,
id: Date.now().toString()
};
const updatedConfigs = [...apiConfigs, newConfig];
setApiConfigs(updatedConfigs);
return newConfig;
}, [apiConfigs]);
// 更新API配置
const updateApiConfig = useCallback((id: string, updates: Partial<ApiConfig>) => {
const updatedConfigs = apiConfigs.map(config =>
config.id === id ? { ...config, ...updates } : config
);
setApiConfigs(updatedConfigs);
return updatedConfigs.find(c => c.id === id);
}, [apiConfigs]);
// 删除API配置
const deleteApiConfig = useCallback((id: string) => {
const updatedConfigs = apiConfigs.filter(config => config.id !== id);
setApiConfigs(updatedConfigs);
// 如果删除的配置被分配给模型，清除分配
const updatedAssignments = { ...modelAssignments };
if (modelAssignments.model1_config_id === id) {
updatedAssignments.model1_config_id = null;
}
if (modelAssignments.model2_config_id === id) {
updatedAssignments.model2_config_id = null;
}
if (updatedAssignments.model1_config_id !== modelAssignments.model1_config_id ||
updatedAssignments.model2_config_id !== modelAssignments.model2_config_id) {
setModelAssignments(updatedAssignments);
}
return updatedConfigs;
}, [apiConfigs, modelAssignments]);
// 获取多模态配置（用于模型1）
const getMultimodalConfigs = useCallback(() => {
return apiConfigs.filter(config => config.isMultimodal && config.enabled);
}, [apiConfigs]);
// 获取所有启用的配置（用于模型2）
const getEnabledConfigs = useCallback(() => {
return apiConfigs.filter(config => config.enabled);
}, [apiConfigs]);
// 获取配置按ID
const getConfigById = useCallback((id: string | null) => {
if (!id) return null;
return apiConfigs.find(config => config.id === id) || null;
}, [apiConfigs]);
// 验证模型分配
const validateModelAssignments = useCallback(() => {
const errors: string[] = [];
if (modelAssignments.model1_config_id) {
const model1Config = getConfigById(modelAssignments.model1_config_id);
if (!model1Config) {
errors.push('模型1配置不存在');
} else if (!model1Config.isMultimodal) {
errors.push('模型1必须是多模态配置');
} else if (!model1Config.enabled) {
errors.push('模型1配置未启用');
}
}
if (modelAssignments.model2_config_id) {
const model2Config = getConfigById(modelAssignments.model2_config_id);
if (!model2Config) {
errors.push('模型2配置不存在');
} else if (!model2Config.enabled) {
errors.push('模型2配置未启用');
}
}
return errors;
}, [modelAssignments, getConfigById]);
// 初始化时加载配置
useEffect(() => {
loadApiConfigs();
}, [loadApiConfigs]);
return {
// 状态
apiConfigs,
modelAssignments,
loading,
saving,
testingApi,
// 方法
loadApiConfigs,
saveApiConfigs,
saveModelAssignments,
testApiConnection,
addApiConfig,
updateApiConfig,
deleteApiConfig,
// 便利方法
getMultimodalConfigs,
getEnabledConfigs,
getConfigById,
validateModelAssignments
};
};
|
000haoji/deep-student
| 1,715 |
src/types/neovis.d.ts
|
declare module 'neovis.js' {
export interface Neo4jConfig {
serverUrl: string;
serverUser: string;
serverPassword: string;
serverDatabase?: string;
driverConfig?: {
encrypted?: string;
trust?: string;
};
}
export interface NeovisConfig {
containerId: string;
neo4j: Neo4jConfig;
labels?: {
[key: string]: {
label?: string;
value?: string;
color?: string;
size?: string;
community?: string;
caption?: string | string[];
title_properties?: string[];
font?: {
color?: string;
size?: number;
face?: string;
};
};
};
relationships?: {
[key: string]: {
thickness?: string;
color?: string;
caption?: boolean | string;
};
};
initialCypher?: string;
consoleDebug?: boolean;
visConfig?: any;
}
export interface NeovisNode {
id: string;
labels: string[];
properties: Record<string, any>;
}
export interface NeovisRelationship {
id: string;
type: string;
startNode: string;
endNode: string;
properties: Record<string, any>;
}
export class NeoVis {
constructor(config: NeovisConfig);
render(): void;
reload(): void;
clearNetwork(): void;
stabilize(): void;
renderWithCypher(cypher: string): void;
registerOnEvent(event: string, callback: (event: any) => void): void;
_addNode(nodeId: string, node: NeovisNode): void;
_addRelationship(relationshipId: string, relationship: NeovisRelationship): void;
// 网络实例（可选，有些版本可能暴露）
_network?: any;
_nodes?: any;
_edges?: any;
}
export default NeoVis;
}
|
000haoji/deep-student
| 3,357 |
src/types/cogni-graph.ts
|
export interface ProblemCard {
id: string;
content_problem: string;
content_insight: string;
status: 'unsolved' | 'solved';
embedding?: number[];
created_at: string;
last_accessed_at: string;
access_count: number;
source_excalidraw_path?: string;
}
export interface Tag {
id: string;
name: string;
tag_type: TagType;
level: number;
description?: string;
created_at: string;
}
export type TagType =
| 'KnowledgeArea'
| 'Topic'
| 'Concept'
| 'Method'
| 'Difficulty';
export type RelationshipType =
| 'HAS_TAG'
| 'IS_VARIATION_OF'
| 'USES_GENERAL_METHOD'
| 'CONTRASTS_WITH'
| 'PARENT_OF'
| 'CHILD_OF'
| 'RELATED_TO'
| 'PREREQUISITE_OF';
export interface Relationship {
from_id: string;
to_id: string;
relationship_type: RelationshipType;
}
export interface SearchRequest {
query: string;
limit?: number;
libraries?: string[];
}
export interface SearchResult {
card: ProblemCard;
score: number;
matched_by: string[];
}
export interface RecommendationRequest {
card_id: string;
limit?: number;
}
export interface Recommendation {
card: ProblemCard;
relationship_type: RelationshipType;
confidence: number;
reasoning: string;
}
export interface CreateCardRequest {
content_problem: string;
content_insight: string;
tags: string[];
source_excalidraw_path?: string;
}
export interface CreateTagRequest {
name: string;
tag_type: TagType;
parent_id?: string;
description?: string;
}
export interface TagHierarchy {
tag: Tag;
children: TagHierarchy[];
parent?: Tag;
}
export interface GraphNode {
id: string;
label: string;
type: 'ProblemCard' | 'Tag';
properties: Record<string, any>;
}
export interface GraphEdge {
id: string;
from: string;
to: string;
type: RelationshipType;
properties?: Record<string, any>;
}
export interface GraphData {
nodes: GraphNode[];
edges: GraphEdge[];
}
export interface Neo4jConfig {
uri: string;
username: string;
password: string;
database?: string;
}
export interface GraphConfig {
neo4j: Neo4jConfig;
vector_dimensions: number;
similarity_threshold: number;
max_search_results: number;
recommendation_limit: number;
}
// Tauri API types
export interface KnowledgeGraphAPI {
initializeKnowledgeGraph: (config: GraphConfig) => Promise<string>;
createProblemCard: (request: CreateCardRequest) => Promise<string>;
getProblemCard: (cardId: string) => Promise<ProblemCard | null>;
searchKnowledgeGraph: (request: SearchRequest) => Promise<SearchResult[]>;
getAiRecommendations: (request: RecommendationRequest) => Promise<Recommendation[]>;
searchSimilarCards: (cardId: string, limit?: number) => Promise<SearchResult[]>;
getCardsByTag: (tagName: string, limit?: number) => Promise<ProblemCard[]>;
getAllTags: () => Promise<Tag[]>;
getGraphConfig: () => Promise<GraphConfig>;
updateGraphConfig: (config: GraphConfig) => Promise<string>;
testNeo4jConnection: (config: GraphConfig) => Promise<string>;
processHandwrittenInput: (imageData: string) => Promise<CreateCardRequest>;
// Tag management APIs
createTag: (request: CreateTagRequest) => Promise<string>;
getTagHierarchy: (rootTagId?: string) => Promise<TagHierarchy[]>;
getTagsByType: (tagType: TagType) => Promise<Tag[]>;
initializeDefaultTagHierarchy: () => Promise<string>;
}
|
000haoji/deep-student
| 24,458 |
src/types/index.ts
|
/**
* Unified Type Definitions
*
* Consolidates all TypeScript interfaces and types used throughout the application
* to improve maintainability and consistency.
*/
// ============================================================================
// Core Data Models (matching backend Rust structs)
// ============================================================================
export interface RagSourceInfo {
document_id: string;
file_name: string;
chunk_text: string;
score: number;
chunk_index: number;
}
// 多模态内容块类型
export type ChatMessageContentPart =
| { type: 'text'; text: string }
| { type: 'image_url'; image_url: { url: string; detail?: 'low' | 'high' | 'auto' } };
// 追问时上传的图片文件基本信息
export interface UploadedImageInfo {
id: string; // 临时客户端ID
name: string;
type: string; // MIME type
base64_data: string; // 图片的Base64编码
file?: File; // 原始File对象，可选
}
// 用于编辑错题时的表单数据结构
export interface MistakeEditForm {
user_question: string;
tags: string; // 逗号分隔的字符串
mistake_type: string;
}
export interface ChatMessage {
id?: string; // 消息的唯一ID，前端生成或后端返回
role: 'user' | 'assistant' | 'system';
content: string | ChatMessageContentPart[]; // 支持旧的字符串格式和新的多模态数组格式
timestamp: string;
thinking_content?: string;
rag_sources?: RagSourceInfo[];
// 🎯 修复BUG-05：新增图片字段支持多模态对话
image_paths?: string[]; // 用户消息中包含的图片路径
image_base64?: string[]; // 备用：base64编码的图片数据
}
export interface MistakeItem {
id: string;
subject: string;
created_at: string;
question_images: string[]; // 后端返回的本地文件路径
analysis_images: string[]; // 后端返回的本地文件路径
user_question: string;
ocr_text: string;
tags: string[];
mistake_type: string;
status: string; // "analyzing", "completed", "error", "summary_required"
updated_at: string;
chat_history: ChatMessage[];
// 前端生成的用于显示的图片URLs（从question_images转换而来）
question_image_urls?: string[];
// 新增字段：错题总结相关
mistake_summary?: string | null; // 错题简要解析：题目要点、正确解法、关键知识点
user_error_analysis?: string | null; // 用户错误分析：错误原因、思维误区、薄弱点总结
}
export interface SubjectConfig {
id: string;
subject_name: string;
display_name: string;
description: string;
is_enabled: boolean;
prompts: SubjectPrompts;
mistake_types: string[];
default_tags: string[];
created_at: string;
updated_at: string;
}
export interface SubjectPrompts {
analysis_prompt: string;
review_prompt: string;
chat_prompt: string;
ocr_prompt: string;
classification_prompt: string;
consolidated_review_prompt: string;
anki_generation_prompt: string;
}
// ============================================================================
// API Request/Response Types
// ============================================================================
export interface AnalysisRequest {
subject: string;
question_image_files: string[]; // Base64编码的图片字符串
analysis_image_files: string[]; // Base64编码的图片字符串
user_question: string;
enable_chain_of_thought?: boolean;
}
export interface AnalysisResponse {
temp_id: string;
initial_data: InitialAnalysisData;
}
export interface InitialAnalysisData {
ocr_text: string;
tags: string[];
mistake_type: string;
first_answer: string;
}
export interface ContinueChatRequest {
temp_id: string;
chat_history: ChatMessage[];
enable_chain_of_thought?: boolean;
}
export interface ContinueChatResponse {
new_assistant_message: string;
}
export interface SaveMistakeRequest {
temp_id: string;
final_chat_history: ChatMessage[];
}
export interface SaveMistakeResponse {
success: boolean;
final_mistake_item?: MistakeItem;
}
// ============================================================================
// API Configuration Types
// ============================================================================
export interface ApiConfig {
id: string;
name: string;
apiKey: string;
baseUrl: string;
model: string;
isMultimodal: boolean;
isReasoning: boolean;
enabled: boolean;
modelAdapter: string;
}
export interface ModelAssignments {
model1_config_id: string | null;
model2_config_id: string | null;
review_analysis_model_config_id: string | null;
anki_card_model_config_id: string | null;
embedding_model_config_id: string | null;
reranker_model_config_id: string | null;
}
export type ModelAdapter = 'openai' | 'anthropic' | 'google' | 'custom';
// ============================================================================
// System Settings Types
// ============================================================================
export interface SystemSettings {
autoSave: boolean;
theme: 'light' | 'dark' | 'auto';
language: string;
enableNotifications: boolean;
maxChatHistory: number;
debugMode: boolean;
enableAnkiConnect: boolean;
}
// ============================================================================
// UI Component Types
// ============================================================================
export interface NotificationMessage {
id: string;
type: 'success' | 'error' | 'warning' | 'info';
title?: string;
text: string;
duration?: number;
persistent?: boolean;
}
export interface StreamChunk {
content: string;
is_complete: boolean;
chunk_id: string;
}
export interface StreamMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp: string;
}
export interface StreamOptions {
enableChainOfThought?: boolean;
onChunk?: (chunk: string) => void;
onThinking?: (thinking: string) => void;
onComplete?: (fullResponse: string, thinkingContent?: string) => void;
onError?: (error: string) => void;
onProgress?: (progress: { content: string; thinking?: string }) => void;
}
export interface StreamRequest {
type: 'analysis' | 'chat' | 'continue_chat';
tempId?: string;
mistakeId?: number;
imageData?: string;
userInput?: string;
chatHistory?: StreamMessage[];
enableChainOfThought?: boolean;
}
// ============================================================================
// Batch Analysis Types
// ============================================================================
export interface BatchTask {
id: string; // 唯一ID (前端生成, e.g., UUID)
subject: string; // 科目
questionImages: File[]; // 题目图片文件列表
questionImageUrls?: string[]; // 题目图片预览URL (前端生成)
analysisImages: File[]; // 解析辅助图片文件列表 (可选)
analysisImageUrls?: string[]; // 解析辅助图片预览URL (前端生成, 可选)
userQuestion: string; // 用户问题描述
// 用于持久化存储的Base64数据 (仅在序列化时使用)
questionImagesBase64?: Array<{
base64: string;
name: string;
type: string;
size: number;
}>;
analysisImagesBase64?: Array<{
base64: string;
name: string;
type: string;
size: number;
}>;
status: 'pending' | // 待处理
'ocr_processing' | // OCR识别与初步分析中
'awaiting_stream_start' | // 等待AI解答流开始
'streaming_answer' | // AI解答流式处理中
'completed' | // 处理完成
'error_ocr' | // OCR或初步分析阶段错误
'error_stream' | // AI解答流阶段错误
'saving'; // 保存到错题库中 (可选状态)
temp_id: string | null; // 后端分析会话ID (来自 analyzeStepByStep)
ocr_result: { // OCR及初步分类结果 (来自 analyzeStepByStep)
ocr_text: string;
tags: string[];
mistake_type: string;
} | null;
chatHistory: ChatMessage[]; // 该任务的完整聊天记录 (包括AI的回答和用户的追问)
thinkingContent: Map<number, string>; // 思维链内容 (key为chatHistory中的消息索引)
// 用于流式处理的临时状态 (在BatchTask对象内部管理，而非全局)
currentFullContentForStream: string;
currentThinkingContentForStream: string;
errorDetails?: string; // 详细错误信息
progress?: number; // 0-100, 用于流式处理时的进度显示 (可选)
}
// ============================================================================
// Batch Operations Types
// ============================================================================
export interface BatchOperationResult {
success: boolean;
processed_count: number;
message: string;
}
export interface BatchDeleteRequest {
mistake_ids: string[];
}
export interface BatchUpdateStatusRequest {
updates: Record<string, string>; // mistake_id -> new_status
}
export interface BatchUpdateTagsRequest {
updates: Record<string, string[]>; // mistake_id -> new_tags
}
export interface BatchCleanupRequest {
archive_days?: number;
}
export interface BatchCleanupResult {
orphaned_messages_cleaned: number;
mistakes_archived: number;
message: string;
}
export interface BatchExportRequest {
mistake_ids: string[];
}
// ============================================================================
// Database Query Types
// ============================================================================
export interface OptimizedGetMistakesRequest {
subject_filter?: string;
type_filter?: string;
tags_filter?: string[];
limit?: number;
offset?: number;
}
export interface FullTextSearchRequest {
search_term: string;
subject_filter?: string;
limit?: number;
}
export interface DateRangeRequest {
start_date: string; // RFC3339 format
end_date: string; // RFC3339 format
subject_filter?: string;
}
// ============================================================================
// Statistics Types
// ============================================================================
export interface Statistics {
total_mistakes: number;
total_reviews: number;
subject_stats: Record<string, number>;
type_stats: Record<string, number>;
tag_stats: Record<string, number>;
recent_mistakes: any[];
}
// ============================================================================
// File Management Types
// ============================================================================
export interface ImageFile {
file: File;
preview: string;
id: string;
}
export interface FileUploadResult {
success: boolean;
path?: string;
error?: string;
}
// ============================================================================
// Component Props Types
// ============================================================================
export interface BaseComponentProps {
className?: string;
children?: React.ReactNode;
}
export interface ModalProps extends BaseComponentProps {
isOpen: boolean;
onClose: () => void;
title?: string;
}
export interface FormProps extends BaseComponentProps {
onSubmit: (data: any) => void | Promise<void>;
loading?: boolean;
disabled?: boolean;
}
export interface ListProps<T> extends BaseComponentProps {
items: T[];
renderItem: (item: T, index: number) => React.ReactNode;
loading?: boolean;
empty?: React.ReactNode;
}
export interface PaginationProps {
currentPage: number;
totalPages: number;
onPageChange: (page: number) => void;
pageSize?: number;
total?: number;
}
// ============================================================================
// Error Handling Types
// ============================================================================
export interface AppError {
type: 'validation' | 'network' | 'server' | 'unknown';
message: string;
details?: any;
code?: string;
}
export type AsyncResult<T> = {
data?: T;
error?: AppError;
loading: boolean;
};
// ============================================================================
// Hook Return Types
// ============================================================================
export interface UseApiConfigReturn {
apiConfigs: ApiConfig[];
modelAssignments: ModelAssignments;
loading: boolean;
saving: boolean;
testingApi: string | null;
loadApiConfigs: () => Promise<void>;
saveApiConfigs: (configs: ApiConfig[]) => Promise<boolean>;
saveModelAssignments: (assignments: ModelAssignments) => Promise<boolean>;
testApiConnection: (config: ApiConfig) => Promise<boolean>;
addApiConfig: (config: Omit<ApiConfig, 'id'>) => ApiConfig;
updateApiConfig: (id: string, updates: Partial<ApiConfig>) => ApiConfig | undefined;
deleteApiConfig: (id: string) => ApiConfig[];
getMultimodalConfigs: () => ApiConfig[];
getEnabledConfigs: () => ApiConfig[];
getConfigById: (id: string | null) => ApiConfig | null;
validateModelAssignments: () => string[];
}
export interface UseSystemSettingsReturn {
settings: SystemSettings;
loading: boolean;
saving: boolean;
loadSettings: () => Promise<void>;
saveSetting: <K extends keyof SystemSettings>(key: K, value: SystemSettings[K]) => Promise<boolean>;
saveAllSettings: (newSettings: SystemSettings) => Promise<boolean>;
resetSettings: () => Promise<boolean>;
updateSetting: <K extends keyof SystemSettings>(key: K, value: SystemSettings[K]) => void;
updateSettings: (updates: Partial<SystemSettings>) => void;
applyTheme: (theme: string) => Promise<boolean>;
validateSettings: (settingsToValidate: Partial<SystemSettings>) => string[];
getSettingsSummary: () => any;
isAutoSaveEnabled: boolean;
isDarkTheme: boolean;
isDebugMode: boolean;
}
export interface UseNotificationReturn {
notifications: NotificationMessage[];
hasNotifications: boolean;
showNotification: (type: NotificationMessage['type'], text: string, options?: any) => string;
removeNotification: (id: string) => void;
clearAllNotifications: () => void;
updateNotification: (id: string, updates: Partial<Omit<NotificationMessage, 'id'>>) => void;
showSuccess: (text: string, options?: any) => string;
showError: (text: string, options?: any) => string;
showWarning: (text: string, options?: any) => string;
showInfo: (text: string, options?: any) => string;
showLoading: (text: string, options?: any) => string;
hasNotificationType: (type: NotificationMessage['type']) => boolean;
getNotificationCount: (type?: NotificationMessage['type']) => number;
showBatchResult: (results: { success: number; failed: number; total: number }, operation: string) => void;
showOperationProgress: (operation: string, current: number, total: number) => string;
}
// ============================================================================
// Utility Types
// ============================================================================
export type DeepPartial<T> = {
[P in keyof T]?: T[P] extends object ? DeepPartial<T[P]> : T[P];
};
export type RequiredKeys<T, K extends keyof T> = T & Required<Pick<T, K>>;
export type OptionalKeys<T, K extends keyof T> = Omit<T, K> & Partial<Pick<T, K>>;
export type KeyOf<T> = keyof T;
export type ValueOf<T> = T[keyof T];
// ============================================================================
// Event Types
// ============================================================================
export interface CustomEvent<T = any> {
type: string;
payload: T;
timestamp: number;
}
export type EventHandler<T = any> = (event: CustomEvent<T>) => void;
// ============================================================================
// Theme Types
// ============================================================================
export interface ThemeColors {
primary: string;
secondary: string;
accent: string;
background: string;
surface: string;
text: string;
textSecondary: string;
border: string;
error: string;
warning: string;
success: string;
info: string;
}
export interface Theme {
name: string;
colors: ThemeColors;
spacing: {
xs: string;
sm: string;
md: string;
lg: string;
xl: string;
};
typography: {
fontFamily: string;
fontSize: {
xs: string;
sm: string;
md: string;
lg: string;
xl: string;
};
};
borderRadius: string;
shadows: {
sm: string;
md: string;
lg: string;
};
}
// ============================================================================
// Review Analysis Types (new feature)
// ============================================================================
export interface ReviewSessionTask {
id: string; // 回顾分析会话的唯一ID (前端生成或后端返回后设置)
name: string; // 用户为该回顾任务设定的名称 (e.g., "期中数学复习 - 函数部分")
creationDate: string; // 创建日期 (ISO 8601)
subject: string; // 所属科目
mistakeIds: string[]; // 参与此次回顾分析的原始错题ID列表
userConsolidatedInput: string; // 前端整合的包含多个错题信息和用户引导问题的长文本
userOverallPrompt: string; // 用户针对此次回顾的总体性问题或分析指引
status: 'pending' | // 待处理（刚创建，未开始分析）
'processing_setup' | // 后端正在设置会话
'awaiting_stream_start' | // 等待AI解答流开始
'streaming_answer' | // AI解答流式处理中
'completed' | // 处理完成
'error_setup' | // 后端设置阶段错误
'error_stream'; // AI解答流阶段错误
review_session_id: string | null; // 后端分析会话ID (用于流式通信)
// 存储针对整合后输入的单一AI分析结果
chatHistory: ChatMessage[]; // 本次回顾分析的完整聊天记录 (用户总体问题 + AI统一回答 + 后续追问)
thinkingContent: Map<number, string>; // 本次回顾分析的思维链内容 (key为chatHistory中的消息索引)
// 用于流式处理的临时状态
currentFullContentForStream: string;
currentThinkingContentForStream: string;
errorDetails?: string; // 详细错误信息
}
// 回顾分析相关的API请求/响应类型
export interface StartConsolidatedReviewAnalysisRequest {
subject: string;
consolidatedInput: string;
overallPrompt: string;
enableChainOfThought: boolean;
mistakeIds: string[]; // 参与回顾分析的错题ID列表
}
export interface StartConsolidatedReviewAnalysisResponse {
review_session_id: string;
}
export interface TriggerConsolidatedReviewStreamRequest {
reviewSessionId: string;
enableChainOfThought: boolean;
}
export interface ContinueConsolidatedReviewStreamRequest {
reviewSessionId: string;
chatHistory: ChatMessage[];
enableChainOfThought: boolean;
}
// 数据整合引擎使用的类型
export interface MistakeConsolidationData {
mistakeId: string;
ocr_text: string;
user_question: string;
chat_history: ChatMessage[];
}
export interface ConsolidatedMistakeData {
selectedMistakes: MistakeConsolidationData[];
consolidatedText: string;
userOverallPrompt: string;
}
// ============================================================================
// Mistake Summary Generation Types
// ============================================================================
export interface GenerateMistakeSummaryRequest {
mistake_id: string;
force_regenerate?: boolean; // 是否强制重新生成总结
}
export interface GenerateMistakeSummaryResponse {
success: boolean;
mistake_summary?: string | null;
user_error_analysis?: string | null;
error_message?: string | null;
}
// ============================================================================
// ANKI Card Generation Types
// ============================================================================
export interface AnkiCard {
front: string;
back: string;
text?: string; // 填空题使用的字段
tags: string[];
images: string[];
}
// ANKI卡片模板定义
export interface AnkiCardTemplate {
id: string;
name: string;
description: string;
preview_front: string;
preview_back: string;
front_template: string;
back_template: string;
css_style: string;
note_type: string; // 对应的Anki笔记类型
generation_prompt: string; // 每个模板专门的生成prompt
fields: string[]; // 模板包含的字段列表
}
// 自定义ANKI模板系统类型定义
export type FieldType = 'Text' | 'Array' | 'Number' | 'Boolean';
export interface FieldExtractionRule {
field_type: FieldType;
is_required: boolean;
default_value?: string;
validation_pattern?: string; // 正则表达式
description: string;
}
export interface CustomAnkiTemplate {
id: string;
name: string;
description: string;
author?: string;
version: string;
preview_front: string;
preview_back: string;
note_type: string;
fields: string[];
generation_prompt: string;
front_template: string;
back_template: string;
css_style: string;
field_extraction_rules: Record<string, FieldExtractionRule>;
created_at: string;
updated_at: string;
is_active: boolean;
is_built_in: boolean;
}
export interface CreateTemplateRequest {
name: string;
description: string;
author?: string;
preview_front: string;
preview_back: string;
note_type: string;
fields: string[];
generation_prompt: string;
front_template: string;
back_template: string;
css_style: string;
field_extraction_rules: Record<string, FieldExtractionRule>;
}
export interface UpdateTemplateRequest {
name?: string;
description?: string;
author?: string;
preview_front?: string;
preview_back?: string;
note_type?: string;
fields?: string[];
generation_prompt?: string;
front_template?: string;
back_template?: string;
css_style?: string;
field_extraction_rules?: Record<string, FieldExtractionRule>;
is_active?: boolean;
}
export interface TemplateImportRequest {
template_data: string; // JSON格式的模板数据
overwrite_existing: boolean;
}
export interface TemplateExportResponse {
template_data: string; // JSON格式的模板数据
filename: string;
}
export interface AnkiGenerationOptions {
deck_name: string;
note_type: string;
enable_images: boolean;
max_cards_per_mistake: number;
max_tokens?: number;
temperature?: number;
template_id?: string; // 选择的模板ID
custom_anki_prompt?: string; // 模板专用的生成prompt
template_fields?: string[]; // 模板包含的字段列表
field_extraction_rules?: Record<string, FieldExtractionRule>; // 字段提取规则用于动态解析
custom_requirements?: string; // 用户自定义制卡要求
segment_overlap_size?: number; // 任务间重叠区域大小（字符数）
system_prompt?: string; // 用户自定义系统 prompt
}
export interface AnkiDocumentGenerationRequest {
document_content: string;
subject_name: string;
options?: AnkiGenerationOptions;
}
export interface AnkiDocumentGenerationResponse {
success: boolean;
cards: AnkiCard[];
error_message?: string;
}
export interface AnkiCardGenerationResponse {
success: boolean;
cards: AnkiCard[];
error_message?: string;
}
export interface AnkiExportResponse {
success: boolean;
file_path?: string;
card_count: number;
error_message?: string;
}
export interface AnkiConnectResult {
success: boolean;
result?: any;
error?: string;
}
// ============================================================================
// RAG Knowledge Base Types
// ============================================================================
export interface DocumentChunk {
id: string;
document_id: string;
chunk_index: number;
text: string;
metadata: Record<string, string>;
}
export interface RetrievedChunk {
chunk: DocumentChunk;
score: number;
}
export interface RagQueryOptions {
top_k: number;
enable_reranking?: boolean;
}
export interface RagQueryResponse {
retrieved_chunks: RetrievedChunk[];
query_vector_time_ms: number;
search_time_ms: number;
reranking_time_ms?: number;
total_time_ms: number;
}
export interface KnowledgeBaseStatusPayload {
total_documents: number;
total_chunks: number;
embedding_model_name?: string;
vector_store_type: string;
}
export interface DocumentUploadRequest {
file_paths: string[];
chunk_size?: number;
chunk_overlap?: number;
enable_preprocessing?: boolean;
}
export interface DocumentProcessingStatus {
document_id: string;
file_name: string;
status: DocumentProcessingStage;
progress: number;
error_message?: string;
chunks_processed: number;
total_chunks: number;
}
export type DocumentProcessingStage =
| 'Pending'
| 'Reading'
| 'Preprocessing'
| 'Chunking'
| 'Embedding'
| 'Storing'
| 'Completed'
| 'Failed';
export interface RagSettings {
knowledge_base_path: string;
default_embedding_model_id?: string;
default_reranker_model_id?: string;
default_top_k: number;
enable_rag_by_default: boolean;
}
export interface RagEnhancedAnalysisRequest {
temp_id: string;
enable_chain_of_thought: boolean;
enable_rag?: boolean;
rag_options?: RagQueryOptions;
}
export interface RagEnhancedChatRequest {
temp_id: string;
chat_history: ChatMessage[];
enable_chain_of_thought?: boolean;
enable_rag?: boolean;
rag_options?: RagQueryOptions;
}
// RAG文档信息
export interface RagDocument {
id: string;
file_name: string;
file_path?: string;
file_size?: number;
total_chunks: number;
created_at: string;
updated_at: string;
}
// RAG处理事件
export interface RagProcessingEvent {
id: string;
status: string;
progress: number;
message: string;
timestamp: string;
}
export interface RagDocumentStatusEvent {
document_id: string;
file_name: string;
status: DocumentProcessingStage;
progress: number;
error_message?: string;
chunks_processed: number;
total_chunks: number;
}
// ============================================================================
// Export all types for easy importing
// ============================================================================
// 所有类型都已经在上面定义并导出，无需重复导出
|
000haoji/deep-student
| 2,365 |
src/utils/streamHandler.ts
|
import { listen } from '@tauri-apps/api/event';
export interface StreamChunk {
content: string;
is_complete: boolean;
chunk_id: string;
}
export class StreamHandler {
private listeners: Map<string, (chunk: StreamChunk) => void> = new Map();
private unlistenFunctions: Map<string, () => void> = new Map();
// 开始监听流式事件
async startListening(eventName: string, onChunk: (chunk: StreamChunk) => void): Promise<void> {
// 如果已经在监听这个事件，先停止
if (this.unlistenFunctions.has(eventName)) {
this.stopListening(eventName);
}
this.listeners.set(eventName, onChunk);
try {
const unlisten = await listen<StreamChunk>(eventName, (event) => {
const chunk = event.payload;
// 详细的控制台调试输出
console.group(`🔄 流式数据 [${eventName}]`);
console.log('📦 数据块ID:', chunk.chunk_id);
console.log('📝 内容长度:', chunk.content.length);
console.log('✅ 是否完成:', chunk.is_complete);
if (chunk.content.length > 0) {
console.log('📄 内容预览:', chunk.content.length > 100 ?
chunk.content.substring(0, 100) + '...' : chunk.content);
}
console.groupEnd();
// 如果内容不为空，显示实时内容
if (chunk.content.length > 0) {
console.log(`💬 实时输出: ${chunk.content}`);
}
// 调用回调函数处理数据块
onChunk(chunk);
// 如果流完成，自动停止监听
if (chunk.is_complete) {
console.log(`🎉 流式输出完成 [${eventName}]`);
this.stopListening(eventName);
}
});
this.unlistenFunctions.set(eventName, unlisten);
console.log(`🎧 开始监听流式事件: ${eventName}`);
} catch (error) {
console.error(`❌ 监听流式事件失败 [${eventName}]:`, error);
throw error;
}
}
// 停止监听流式事件
stopListening(eventName: string): void {
const unlisten = this.unlistenFunctions.get(eventName);
if (unlisten) {
unlisten();
this.unlistenFunctions.delete(eventName);
this.listeners.delete(eventName);
console.log(`停止监听流式事件: ${eventName}`);
}
}
// 停止所有监听
stopAllListening(): void {
for (const eventName of this.unlistenFunctions.keys()) {
this.stopListening(eventName);
}
}
// 检查是否正在监听某个事件
isListening(eventName: string): boolean {
return this.unlistenFunctions.has(eventName);
}
}
// 创建全局实例
export const streamHandler = new StreamHandler();
|
000haoji/deep-student
| 1,983 |
src/utils/chatMessageConverter.ts
|
/**
* Chat Message Converter
*
* Utilities for converting between different chat message formats.
* Single responsibility: Message format conversion.
*/
export interface ChatMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp?: string;
}
export interface TauriChatMessage {
role: string;
content: string;
thinking_content?: string;
timestamp?: string;
}
/**
* Convert Tauri chat history to standard ChatMessage format
*/
export function convertFromTauriFormat(tauriHistory: TauriChatMessage[]): ChatMessage[] {
return tauriHistory.map((msg, index) => ({
id: `msg-${Date.now()}-${index}`,
role: msg.role as 'user' | 'assistant' | 'system',
content: msg.content,
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
}));
}
/**
* Convert ChatMessage format to Tauri backend format
*/
export function convertToTauriFormat(messages: ChatMessage[]): TauriChatMessage[] {
return messages.map(msg => ({
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
}));
}
/**
* Create a new chat message
*/
export function createChatMessage(
role: 'user' | 'assistant' | 'system',
content: string,
thinking_content?: string
): ChatMessage {
return {
id: `msg-${Date.now()}-${Math.random().toString(36).substr(2, 9)}`,
role,
content,
thinking_content,
timestamp: new Date().toISOString()
};
}
/**
* Merge thinking content into a chat message
*/
export function addThinkingToMessage(message: ChatMessage, thinking: string): ChatMessage {
return {
...message,
thinking_content: (message.thinking_content || '') + thinking
};
}
/**
* Update message content
*/
export function updateMessageContent(message: ChatMessage, content: string): ChatMessage {
return {
...message,
content
};
}
|
000haoji/deep-student
| 5,384 |
src/utils/simplifiedApiAdapter.ts
|
/**
* Simplified API Adapter
*
* Replaces the complex aiSdkAdapter.ts with a simpler implementation
* that leverages the unified stream handler.
*/
import { invoke } from '@tauri-apps/api/core';
import { unifiedStreamHandler, StreamRequest, StreamOptions, StreamMessage as _StreamMessage } from './unifiedStreamHandler';
export interface ChatMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp?: string;
}
export interface AnalysisRequest {
imageData?: string;
userInput?: string;
chatHistory?: ChatMessage[];
enableChainOfThought?: boolean;
}
/**
* Simplified API calls that use the unified stream handler
*/
export const simplifiedApi = {
/**
* Analyze step by step with streaming
*/
async analyzeStepByStep(
imageData: string,
userInput: string,
options: StreamOptions & { enableChainOfThought?: boolean } = {}
): Promise<string> {
const request: StreamRequest = {
type: 'analysis',
imageData,
userInput,
enableChainOfThought: options.enableChainOfThought !== false
};
return unifiedStreamHandler.startStream(request, options);
},
/**
* Start chat with streaming
*/
async startChat(
chatHistory: ChatMessage[] = [],
options: StreamOptions & { enableChainOfThought?: boolean } = {}
): Promise<string> {
const request: StreamRequest = {
type: 'chat',
chatHistory: chatHistory.map(msg => ({
id: msg.id,
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
})),
enableChainOfThought: options.enableChainOfThought !== false
};
return unifiedStreamHandler.startStream(request, options);
},
/**
* Continue chat with streaming
*/
async continueChat(
tempId: string,
chatHistory: ChatMessage[] = [],
options: StreamOptions & { enableChainOfThought?: boolean } = {}
): Promise<string> {
const request: StreamRequest = {
type: 'continue_chat',
tempId,
chatHistory: chatHistory.map(msg => ({
id: msg.id,
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
})),
enableChainOfThought: options.enableChainOfThought !== false
};
return unifiedStreamHandler.startStream(request, options);
},
/**
* Stop a specific stream
*/
stopStream(streamId: string): void {
unifiedStreamHandler.stopStream(streamId);
},
/**
* Stop all streams
*/
stopAllStreams(): void {
unifiedStreamHandler.stopAllStreams();
},
/**
* Get current progress for a stream
*/
getStreamProgress(streamId: string): { content: string; thinking: string } | null {
return unifiedStreamHandler.getProgress(streamId);
},
/**
* Check if a stream is active
*/
isStreamActive(streamId: string): boolean {
return unifiedStreamHandler.isStreamActive(streamId);
}
};
/**
* Non-streaming utility functions for direct backend calls
*/
export const directApi = {
async getMistakeChatHistory(mistakeId: number): Promise<ChatMessage[]> {
const result = await invoke('get_mistake_chat_history', { mistakeId });
return this.convertChatHistory(result as any[]);
},
async getAllMistakes(): Promise<any[]> {
return invoke('get_all_mistakes');
},
async saveMistake(mistake: any): Promise<number> {
return invoke('save_mistake', { mistake });
},
async deleteMistake(mistakeId: number): Promise<void> {
return invoke('delete_mistake', { mistakeId });
},
async updateMistake(mistakeId: number, updates: any): Promise<void> {
return invoke('update_mistake', { mistakeId, updates });
},
async getApiConfigurations(): Promise<any> {
return invoke('get_api_configurations');
},
async saveApiConfigurations(configs: any): Promise<void> {
return invoke('save_api_configurations', { configs });
},
/**
* Convert backend chat history to frontend format
*/
convertChatHistory(backendHistory: any[]): ChatMessage[] {
return backendHistory.map((msg, index) => ({
id: msg.id || `msg-${index}`,
role: msg.role as 'user' | 'assistant',
content: msg.content || '',
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
}));
},
/**
* Convert frontend messages to backend format
*/
convertToBackendFormat(messages: ChatMessage[]): any[] {
return messages.map(msg => ({
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
}));
}
};
/**
* Combined API object that includes both streaming and direct calls
*/
export const api = {
...simplifiedApi,
...directApi
};
// Export individual functions for backward compatibility
export const {
analyzeStepByStep,
startChat,
continueChat,
stopStream,
stopAllStreams,
getStreamProgress,
isStreamActive
} = simplifiedApi;
export const {
getMistakeChatHistory,
getAllMistakes,
saveMistake,
deleteMistake,
updateMistake,
getApiConfigurations,
saveApiConfigurations,
convertChatHistory,
convertToBackendFormat
} = directApi;
|
000haoji/deep-student
| 11,423 |
src/utils/debugLogger.ts
|
/**
* 调试日志记录模块
* 用于追踪RAG内容显示、聊天记录保存、聊天记录串号等关键问题
*/
import { invoke } from '@tauri-apps/api/core';
export type LogLevel = 'DEBUG' | 'INFO' | 'WARN' | 'ERROR' | 'TRACE';
export interface LogEntry {
timestamp: string;
level: LogLevel;
module: string;
operation: string;
data: any;
context?: {
userId?: string;
sessionId?: string;
mistakeId?: string;
streamId?: string;
businessId?: string;
};
stackTrace?: string;
}
export interface ChatRecordDebugInfo {
action: 'LOAD' | 'SAVE' | 'DISPLAY' | 'MISMATCH';
mistakeId: string;
expectedChatHistory?: any[];
actualChatHistory?: any[];
ragSources?: any[];
thinkingContent?: Map<number, string>;
streamingState?: any;
}
export interface RAGDebugInfo {
action: 'QUERY' | 'RESPONSE' | 'DISPLAY' | 'MISSING';
query?: string;
sources?: any[];
displayedSources?: any[];
expectedCount?: number;
actualCount?: number;
ragEnabled?: boolean;
ragTopK?: number;
}
class DebugLogger {
private logQueue: LogEntry[] = [];
private flushInterval: number | null = null;
private maxQueueSize = 100;
constructor() {
this.startAutoFlush();
this.setupErrorHandlers();
}
/**
* 记录聊天记录相关的调试信息
*/
async logChatRecord(
level: LogLevel,
operation: string,
debugInfo: ChatRecordDebugInfo,
additionalData?: any
) {
const logEntry: LogEntry = {
timestamp: new Date().toISOString(),
level,
module: 'CHAT_RECORD',
operation,
data: {
debugInfo,
additionalData,
// 添加详细的聊天记录比较信息
chatHistoryComparison: debugInfo.action === 'MISMATCH' ? {
expectedLength: debugInfo.expectedChatHistory?.length || 0,
actualLength: debugInfo.actualChatHistory?.length || 0,
firstMismatchIndex: this.findFirstMismatch(
debugInfo.expectedChatHistory || [],
debugInfo.actualChatHistory || []
)
} : undefined
},
context: {
mistakeId: debugInfo.mistakeId,
sessionId: this.getCurrentSessionId(),
businessId: debugInfo.mistakeId
},
stackTrace: level === 'ERROR' ? new Error().stack : undefined
};
await this.addLog(logEntry);
// 立即输出严重问题
if (level === 'ERROR' || debugInfo.action === 'MISMATCH') {
console.error('🚨 [CHAT_RECORD_CRITICAL]', logEntry);
await this.flushLogs();
}
}
/**
* 记录RAG相关的调试信息
*/
async logRAG(
level: LogLevel,
operation: string,
debugInfo: RAGDebugInfo,
additionalData?: any
) {
const logEntry: LogEntry = {
timestamp: new Date().toISOString(),
level,
module: 'RAG',
operation,
data: {
debugInfo,
additionalData,
// 添加RAG状态检查
ragStateCheck: {
ragEnabled: debugInfo.ragEnabled,
expectedSources: debugInfo.expectedCount || 0,
actualSources: debugInfo.actualCount || 0,
missingSourcesCount: (debugInfo.expectedCount || 0) - (debugInfo.actualCount || 0)
}
},
context: {
sessionId: this.getCurrentSessionId()
},
stackTrace: level === 'ERROR' ? new Error().stack : undefined
};
await this.addLog(logEntry);
// 立即输出RAG问题
if (level === 'ERROR' || debugInfo.action === 'MISSING') {
console.error('🚨 [RAG_CRITICAL]', logEntry);
await this.flushLogs();
}
}
/**
* 记录通用调试信息
*/
async log(
level: LogLevel,
module: string,
operation: string,
data: any,
context?: any
) {
const logEntry: LogEntry = {
timestamp: new Date().toISOString(),
level,
module,
operation,
data,
context: {
...context,
sessionId: this.getCurrentSessionId()
},
stackTrace: level === 'ERROR' ? new Error().stack : undefined
};
await this.addLog(logEntry);
if (level === 'ERROR') {
console.error(`🚨 [${module}_ERROR]`, logEntry);
await this.flushLogs();
}
}
/**
* 记录组件状态变化
*/
async logStateChange(
component: string,
operation: string,
oldState: any,
newState: any,
trigger?: string
) {
const logEntry: LogEntry = {
timestamp: new Date().toISOString(),
level: 'TRACE',
module: 'STATE_CHANGE',
operation: `${component}.${operation}`,
data: {
component,
oldState: this.sanitizeState(oldState),
newState: this.sanitizeState(newState),
stateDiff: this.calculateStateDiff(oldState, newState),
trigger
},
context: {
sessionId: this.getCurrentSessionId()
}
};
await this.addLog(logEntry);
}
/**
* 记录流式处理相关信息
*/
async logStreaming(
operation: string,
streamId: string,
eventType: string,
payload: any,
additionalInfo?: any
) {
const logEntry: LogEntry = {
timestamp: new Date().toISOString(),
level: 'DEBUG',
module: 'STREAMING',
operation,
data: {
streamId,
eventType,
payload: this.sanitizePayload(payload),
additionalInfo,
payloadSize: JSON.stringify(payload).length
},
context: {
streamId,
sessionId: this.getCurrentSessionId()
}
};
await this.addLog(logEntry);
}
/**
* 记录API调用信息
*/
async logApiCall(
operation: string,
method: string,
url: string,
request: any,
response?: any,
error?: any,
duration?: number
) {
const level: LogLevel = error ? 'ERROR' : 'INFO';
const logEntry: LogEntry = {
timestamp: new Date().toISOString(),
level,
module: 'API',
operation,
data: {
method,
url,
request: this.sanitizeRequest(request),
response: this.sanitizeResponse(response),
error: error ? {
message: error.message,
code: error.code,
stack: error.stack
} : undefined,
duration: duration ? `${duration}ms` : undefined
},
context: {
sessionId: this.getCurrentSessionId()
},
stackTrace: error ? new Error().stack : undefined
};
await this.addLog(logEntry);
if (error) {
console.error('🚨 [API_ERROR]', logEntry);
await this.flushLogs();
}
}
private async addLog(logEntry: LogEntry) {
this.logQueue.push(logEntry);
// 队列满了就立即刷新
if (this.logQueue.length >= this.maxQueueSize) {
await this.flushLogs();
}
}
private async flushLogs() {
if (this.logQueue.length === 0) return;
const logsToFlush = [...this.logQueue];
this.logQueue = [];
try {
// 调用后端写入日志文件
await invoke('write_debug_logs', { logs: logsToFlush });
} catch (error) {
console.error('Failed to write debug logs:', error);
// 如果后端写入失败，至少在浏览器控制台输出
console.group('📋 Debug Logs (Backend Write Failed)');
logsToFlush.forEach(log => {
const prefix = `[${log.timestamp}] [${log.level}] [${log.module}]`;
switch (log.level) {
case 'ERROR':
console.error(prefix, log);
break;
case 'WARN':
console.warn(prefix, log);
break;
case 'DEBUG':
case 'TRACE':
console.debug(prefix, log);
break;
default:
console.log(prefix, log);
}
});
console.groupEnd();
}
}
private startAutoFlush() {
// 每5秒自动刷新一次日志
this.flushInterval = window.setInterval(() => {
this.flushLogs();
}, 5000);
}
private setupErrorHandlers() {
// 捕获未处理的错误
window.addEventListener('error', (event) => {
this.log('ERROR', 'GLOBAL', 'UNHANDLED_ERROR', {
message: event.message,
filename: event.filename,
lineno: event.lineno,
colno: event.colno,
error: event.error
});
});
// 捕获Promise拒绝
window.addEventListener('unhandledrejection', (event) => {
this.log('ERROR', 'GLOBAL', 'UNHANDLED_REJECTION', {
reason: event.reason,
promise: event.promise
});
});
}
private findFirstMismatch(expected: any[], actual: any[]): number {
const minLength = Math.min(expected.length, actual.length);
for (let i = 0; i < minLength; i++) {
if (JSON.stringify(expected[i]) !== JSON.stringify(actual[i])) {
return i;
}
}
return expected.length !== actual.length ? minLength : -1;
}
private calculateStateDiff(oldState: any, newState: any) {
if (typeof oldState !== 'object' || typeof newState !== 'object') {
return { changed: oldState !== newState };
}
const changes: any = {};
const allKeys = new Set([...Object.keys(oldState || {}), ...Object.keys(newState || {})]);
for (const key of allKeys) {
if (oldState?.[key] !== newState?.[key]) {
changes[key] = {
from: oldState?.[key],
to: newState?.[key]
};
}
}
return changes;
}
private sanitizeState(state: any) {
if (!state) return state;
// 避免记录过大的状态对象
const sanitized = { ...state };
// 限制聊天历史长度
if (sanitized.chatHistory && Array.isArray(sanitized.chatHistory)) {
if (sanitized.chatHistory.length > 10) {
sanitized.chatHistory = [
...sanitized.chatHistory.slice(0, 5),
{ _truncated: `... ${sanitized.chatHistory.length - 10} items ...` },
...sanitized.chatHistory.slice(-5)
];
}
}
// 限制思维链内容
if (sanitized.thinkingContent instanceof Map) {
sanitized.thinkingContent = Object.fromEntries(sanitized.thinkingContent);
}
return sanitized;
}
private sanitizePayload(payload: any) {
if (!payload) return payload;
// 限制payload大小
const str = JSON.stringify(payload);
if (str.length > 1000) {
return {
_truncated: true,
_originalSize: str.length,
_preview: str.substring(0, 500) + '...'
};
}
return payload;
}
private sanitizeRequest(request: any) {
if (!request) return request;
const sanitized = { ...request };
// 移除敏感信息
if (sanitized.password) sanitized.password = '[REDACTED]';
if (sanitized.apiKey) sanitized.apiKey = '[REDACTED]';
if (sanitized.token) sanitized.token = '[REDACTED]';
return sanitized;
}
private sanitizeResponse(response: any) {
return this.sanitizePayload(response);
}
private getCurrentSessionId(): string {
// 获取当前会话ID，可以从localStorage或其他地方获取
return localStorage.getItem('debug-session-id') ||
`session-${Date.now()}-${Math.random().toString(36).substr(2, 9)}`;
}
/**
* 清理资源
*/
destroy() {
if (this.flushInterval) {
clearInterval(this.flushInterval);
this.flushInterval = null;
}
this.flushLogs();
}
}
// 导出单例实例
export const debugLogger = new DebugLogger();
// 便捷方法
export const logChatRecord = debugLogger.logChatRecord.bind(debugLogger);
export const logRAG = debugLogger.logRAG.bind(debugLogger);
export const logStateChange = debugLogger.logStateChange.bind(debugLogger);
export const logStreaming = debugLogger.logStreaming.bind(debugLogger);
export const logApiCall = debugLogger.logApiCall.bind(debugLogger);
export const log = debugLogger.log.bind(debugLogger);
// 确保页面卸载时清理日志
window.addEventListener('beforeunload', () => {
debugLogger.destroy();
});
|
000haoji/deep-student
| 3,037 |
src/utils/aiSdkAdapter.ts
|
/**
* AI SDK Adapter for Tauri Backend
*
* Simplified adapter focused on AI SDK integration.
* Uses separated modules for stream handling and API communication.
*/
import { createAnalysisStream, createChatStream } from './tauriStreamAdapter';
import { tauriApiClient } from './tauriApiClient';
import { convertToTauriFormat, type ChatMessage } from './chatMessageConverter';
export interface AnalysisRequest {
imageData?: string;
userInput?: string;
chatHistory?: ChatMessage[];
enableChainOfThought?: boolean;
}
/**
* Custom fetch implementation for AI SDK compatibility
* Routes requests to appropriate stream handlers
*/
export async function createTauriStreamingFetch(
url: string,
options: RequestInit & { body?: string }
): Promise<Response> {
const requestData = JSON.parse(options.body as string);
if (url.includes('/api/analysis')) {
const { imageData, userInput, enableChainOfThought = true } = requestData;
return createAnalysisStream(imageData, userInput, enableChainOfThought);
}
if (url.includes('/api/chat') || url.includes('/api/continue-chat')) {
const { tempId, chatHistory, enableChainOfThought = true } = requestData;
const tauriHistory = convertToTauriFormat(chatHistory || []);
return createChatStream(tempId, tauriHistory, enableChainOfThought);
}
throw new Error(`Unsupported endpoint: ${url}`);
}
/**
* Create a custom fetch function for AI SDK
*/
export function createAISdkFetch() {
return async (input: RequestInfo | URL, init?: RequestInit) => {
const url = typeof input === 'string' ? input : input.toString();
const options = { ...init, body: init?.body as string };
if (url.startsWith('/api/')) {
return createTauriStreamingFetch(url, options);
}
return fetch(input, init);
};
}
/**
* Simplified API adapter using the dedicated client
*/
export const tauriApiAdapter = {
async analyzeStepByStep(imageData: string, userInput: string, enableChainOfThought = true) {
const base64Data = imageData.startsWith('data:') ? imageData : `data:image/jpeg;base64,${imageData}`;
return tauriApiClient.analyzeStepByStep({
subject: "数学",
question_image_files: [base64Data],
analysis_image_files: [],
user_question: userInput,
enable_chain_of_thought: enableChainOfThought
});
},
async getChatHistory(tempId: string) {
console.log('getChatHistory called for tempId:', tempId);
return [];
},
async startStreamingAnswer(tempId: string, enableChainOfThought = true) {
return tauriApiClient.startStreamingAnswer(tempId, enableChainOfThought);
},
async continueChatStream(tempId: string, chatHistory: any[], enableChainOfThought = true) {
return tauriApiClient.continueChatStream(tempId, chatHistory, enableChainOfThought);
},
async getMistakeChatHistory(mistakeId: number) {
return tauriApiClient.getMistakeChatHistory(mistakeId);
},
async getAllMistakes() {
return tauriApiClient.getAllMistakes();
}
};
|
000haoji/deep-student
| 41,446 |
src/utils/tauriApi.ts
|
// Tauri API调用模块 - 真实的后端API调用
import { invoke } from '@tauri-apps/api/core';
import { MistakeItem, ChatMessage, RagSourceInfo } from '../types';
// 重新导出类型以保持兼容性
export type { MistakeItem, ChatMessage, RagSourceInfo };
// 回顾分析相关类型 - 复用错题分析结构
export interface ReviewAnalysisItem {
id: string;
name: string;
subject: string;
created_at: string;
updated_at: string;
mistake_ids: string[];
consolidated_input: string;
user_question: string;
status: string;
tags: string[];
analysis_type: string;
chat_history: ChatMessage[];
}
export interface AnalysisRequest {
subject: string;
question_image_files: string[]; // Base64编码的图片字符串
analysis_image_files: string[]; // Base64编码的图片字符串
user_question: string;
}
export interface AnalysisResponse {
temp_id: string;
initial_data: {
ocr_text: string;
tags: string[];
mistake_type: string;
first_answer: string;
};
}
export interface ContinueChatRequest {
temp_id: string;
chat_history: ChatMessage[];
}
export interface ContinueChatResponse {
new_assistant_message: string;
}
export interface SaveMistakeRequest {
temp_id: string;
final_chat_history: ChatMessage[];
}
export interface SaveMistakeResponse {
success: boolean;
final_mistake_item?: MistakeItem;
}
// 工具函数：将File对象转换为Base64字符串
export const fileToBase64 = (file: File): Promise<string> => {
return new Promise((resolve, reject) => {
const reader = new FileReader();
reader.readAsDataURL(file);
reader.onload = () => {
const result = reader.result as string;
// 移除 "data:image/jpeg;base64," 前缀，只保留Base64数据
const base64Data = result.split(',')[1];
resolve(base64Data);
};
reader.onerror = error => reject(error);
});
};
// 工具函数：批量转换文件为Base64
export const filesToBase64 = async (files: File[]): Promise<string[]> => {
const promises = files.map(file => fileToBase64(file));
return Promise.all(promises);
};
// Tauri API调用类
export class TauriAPI {
// 错题分析相关API
static async analyzeNewMistake(request: {
subject: string;
question_image_files: File[];
analysis_image_files: File[];
user_question: string;
}): Promise<AnalysisResponse> {
try {
// 转换图片文件为Base64
const questionImageBase64 = await filesToBase64(request.question_image_files);
const analysisImageBase64 = await filesToBase64(request.analysis_image_files);
// 根据后端AnalysisRequest结构，需要传递request对象
const analysisRequest = {
subject: request.subject,
question_image_files: questionImageBase64,
analysis_image_files: analysisImageBase64,
user_question: request.user_question,
};
const response = await invoke<AnalysisResponse>('analyze_new_mistake', {
request: analysisRequest,
});
return response;
} catch (error) {
console.error('分析新错题失败:', error);
throw new Error(`分析失败: ${error}`);
}
}
// 分析新错题 - 流式版本
static async analyzeNewMistakeStream(request: {
subject: string;
question_image_files: File[];
analysis_image_files: File[];
user_question: string;
}): Promise<AnalysisResponse> {
try {
// 转换图片文件为Base64
const questionImageBase64 = await filesToBase64(request.question_image_files);
const analysisImageBase64 = await filesToBase64(request.analysis_image_files);
// 根据后端AnalysisRequest结构，需要传递request对象
const analysisRequest = {
subject: request.subject,
question_image_files: questionImageBase64,
analysis_image_files: analysisImageBase64,
user_question: request.user_question,
};
const response = await invoke<AnalysisResponse>('analyze_new_mistake_stream', {
request: analysisRequest,
});
return response;
} catch (error) {
console.error('流式分析新错题失败:', error);
throw new Error(`流式分析失败: ${error}`);
}
}
// 分步骤分析：先OCR，再流式AI解答
static async analyzeStepByStep(request: {
subject: string;
question_image_files: File[];
analysis_image_files: File[];
user_question: string;
enable_chain_of_thought?: boolean;
}): Promise<{
temp_id: string;
ocr_result: {
ocr_text: string;
tags: string[];
mistake_type: string;
};
}> {
try {
// 转换图片文件为Base64
const questionImageBase64 = await filesToBase64(request.question_image_files);
const analysisImageBase64 = await filesToBase64(request.analysis_image_files);
// 调用后端的分步骤分析命令
const analysisRequest = {
subject: request.subject,
question_image_files: questionImageBase64,
analysis_image_files: analysisImageBase64,
user_question: request.user_question,
enable_chain_of_thought: request.enable_chain_of_thought || false,
};
const response = await invoke<{
temp_id: string;
ocr_result: {
ocr_text: string;
tags: string[];
mistake_type: string;
};
}>('analyze_step_by_step', {
request: analysisRequest,
});
return response;
} catch (error) {
console.error('分步骤分析失败:', error);
// 更好的错误处理
if (error && typeof error === 'object') {
const errorMessage = (error as any).message || JSON.stringify(error);
throw new Error(`分步骤分析失败: ${errorMessage}`);
} else {
throw new Error(`分步骤分析失败: ${String(error)}`);
}
}
}
// 开始流式AI解答（在OCR完成后调用）
static async startStreamingAnswer(tempId: string, enableChainOfThought: boolean = false): Promise<void> {
try {
await invoke('start_streaming_answer', {
request: {
temp_id: tempId,
enable_chain_of_thought: enableChainOfThought,
},
});
} catch (error) {
console.error('开始流式解答失败:', error);
throw new Error(`开始流式解答失败: ${error}`);
}
}
static async continueChat(request: ContinueChatRequest): Promise<ContinueChatResponse> {
try {
const response = await invoke<ContinueChatResponse>('continue_chat', {
request: request,
});
return response;
} catch (error) {
console.error('继续对话失败:', error);
throw new Error(`对话失败: ${error}`);
}
}
// 继续对话 - 流式版本
static async continueChatStream(request: {
temp_id: string;
chat_history: ChatMessage[];
enable_chain_of_thought?: boolean;
}): Promise<ContinueChatResponse> {
try {
const response = await invoke<ContinueChatResponse>('continue_chat_stream', {
request: {
temp_id: request.temp_id,
chat_history: request.chat_history,
enable_chain_of_thought: request.enable_chain_of_thought || false,
},
});
return response;
} catch (error) {
console.error('流式继续对话失败:', error);
throw new Error(`流式对话失败: ${error}`);
}
}
static async saveMistakeFromAnalysis(request: SaveMistakeRequest): Promise<SaveMistakeResponse> {
try {
const response = await invoke<SaveMistakeResponse>('save_mistake_from_analysis', {
request: request,
});
return response;
} catch (error) {
console.error('保存错题失败:', error);
let errorMessage = '未知错误';
if (error && typeof error === 'object') {
if ('message' in error) {
errorMessage = (error as any).message;
} else {
errorMessage = JSON.stringify(error);
}
} else if (typeof error === 'string') {
errorMessage = error;
}
throw new Error(`保存失败: ${errorMessage}`);
}
}
// 错题库管理API
static async getMistakes(filter?: {
subject?: string;
mistake_type?: string;
tags?: string[];
}): Promise<MistakeItem[]> {
try {
const response = await invoke<MistakeItem[]>('get_mistakes', {
subject: filter?.subject || null,
mistake_type: filter?.mistake_type || null,
tags: filter?.tags || null,
});
return response;
} catch (error) {
console.error('获取错题列表失败:', error);
throw new Error(`获取错题列表失败: ${error}`);
}
}
// 回顾分析列表API（复用错题分析的列表模式）
static async getReviewAnalyses(filter?: {
subject?: string;
status?: string;
}): Promise<ReviewAnalysisItem[]> {
try {
const response = await invoke<ReviewAnalysisItem[]>('get_review_analyses', {
subject: filter?.subject || null,
status: filter?.status || null,
});
return response;
} catch (error) {
console.error('获取回顾分析列表失败:', error);
throw new Error(`获取回顾分析列表失败: ${error}`);
}
}
static async getMistakeDetails(id: string): Promise<MistakeItem | null> {
try {
const response = await invoke<MistakeItem | null>('get_mistake_details', { id });
return response;
} catch (error) {
console.error('获取错题详情失败:', error);
throw new Error(`获取错题详情失败: ${error}`);
}
}
static async updateMistake(mistake: MistakeItem): Promise<MistakeItem> {
try {
const response = await invoke<MistakeItem>('update_mistake', { mistake });
return response;
} catch (error) {
console.error('更新错题失败:', error);
throw new Error(`更新错题失败: ${error}`);
}
}
static async deleteMistake(id: string): Promise<boolean> {
try {
const response = await invoke<boolean>('delete_mistake', { id });
return response;
} catch (error) {
console.error('删除错题失败:', error);
throw new Error(`删除错题失败: ${error}`);
}
}
static async getMistakeQuestionImages(mistakeId: string): Promise<string[]> {
try {
const mistake = await this.getMistakeDetails(mistakeId);
if (!mistake) {
return [];
}
const images: string[] = [];
for (const imagePath of mistake.question_images) {
try {
const base64 = await this.getImageAsBase64(imagePath);
images.push(base64);
} catch (error) {
console.warn(`获取题目图片失败: ${imagePath}`, error);
}
}
return images;
} catch (error) {
console.error('获取错题题目图片失败:', error);
throw new Error(`获取错题题目图片失败: ${error}`);
}
}
static async getMistakeAnalysisImages(mistakeId: string): Promise<string[]> {
try {
const mistake = await this.getMistakeDetails(mistakeId);
if (!mistake) {
return [];
}
const images: string[] = [];
for (const imagePath of mistake.analysis_images) {
try {
const base64 = await this.getImageAsBase64(imagePath);
images.push(base64);
} catch (error) {
console.warn(`获取解析图片失败: ${imagePath}`, error);
}
}
return images;
} catch (error) {
console.error('获取错题解析图片失败:', error);
throw new Error(`获取错题解析图片失败: ${error}`);
}
}
static async continueMistakeChat(mistakeId: string, chatHistory: ChatMessage[]): Promise<ContinueChatResponse> {
try {
const response = await invoke<ContinueChatResponse>('continue_mistake_chat', {
mistakeId: mistakeId,
chatHistory: chatHistory,
});
return response;
} catch (error) {
console.error('在错题详情页继续对话失败:', error);
throw new Error(`对话失败: ${error}`);
}
}
// 继续错题对话 - 流式版本
static async continueMistakeChatStream(request: {
mistakeId: string;
chatHistory: ChatMessage[];
enableChainOfThought?: boolean;
}): Promise<void> {
try {
await invoke('continue_mistake_chat_stream', {
mistakeId: request.mistakeId,
chatHistory: request.chatHistory,
enableChainOfThought: request.enableChainOfThought || false,
});
} catch (error) {
console.error('流式错题对话失败:', error);
throw new Error(`流式对话失败: ${error}`);
}
}
// 回顾分析API (流式版本)
static async analyzeReviewSession(subject: string, mistakeIds: string[]): Promise<AnalysisResponse> {
try {
const response = await invoke<AnalysisResponse>('analyze_review_session_stream', {
subject,
mistake_ids: mistakeIds,
});
return response;
} catch (error) {
console.error('回顾分析失败:', error);
throw new Error(`回顾分析失败: ${error}`);
}
}
// 配置管理API
static async saveSetting(key: string, value: string): Promise<void> {
try {
await invoke<void>('save_setting', { key, value });
} catch (error) {
console.error('保存设置失败:', error);
throw new Error(`保存设置失败: ${error}`);
}
}
static async getSetting(key: string): Promise<string | null> {
try {
const response = await invoke<string | null>('get_setting', { key });
return response;
} catch (error) {
console.error('获取设置失败:', error);
throw new Error(`获取设置失败: ${error}`);
}
}
static async testApiConnection(apiKey: string, apiBase: string, model?: string): Promise<boolean> {
try {
const response = await invoke<boolean>('test_api_connection', {
api_key: apiKey,
api_base: apiBase,
model: model || null,
});
return response;
} catch (error) {
console.error('测试API连接失败:', error);
throw new Error(`测试API连接失败: ${error}`);
}
}
// 统计信息API
static async getStatistics(): Promise<any> {
try {
const response = await invoke<any>('get_statistics');
return response;
} catch (error) {
console.error('获取统计信息失败:', error);
throw new Error(`获取统计信息失败: ${error}`);
}
}
// 支持的科目API
static async getSupportedSubjects(): Promise<string[]> {
try {
const response = await invoke<string[]>('get_supported_subjects');
return response;
} catch (error) {
console.error('获取支持的科目失败:', error);
throw new Error(`获取支持的科目失败: ${error}`);
}
}
// 文件管理API
static async getImageAsBase64(relativePath: string): Promise<string> {
try {
const response = await invoke<string>('get_image_as_base64', { relativePath: relativePath });
return response;
} catch (error) {
console.error('获取图片Base64失败:', error);
throw new Error(`获取图片失败: ${error}`);
}
}
static async saveImageFromBase64(base64Data: string, originalPath: string): Promise<string> {
try {
// 从原路径中提取文件名或生成新的文件名
const pathParts = originalPath.split('/');
const fileName = pathParts[pathParts.length - 1];
const response = await invoke<string>('save_image_from_base64_path', {
base64Data: base64Data,
fileName: fileName
});
return response;
} catch (error) {
console.error('保存图片Base64失败:', error);
throw new Error(`保存图片失败: ${error}`);
}
}
static async cleanupOrphanedImages(): Promise<string[]> {
try {
const response = await invoke<string[]>('cleanup_orphaned_images');
return response;
} catch (error) {
console.error('清理孤立图片失败:', error);
throw new Error(`清理孤立图片失败: ${error}`);
}
}
// API配置管理API
static async getApiConfigurations(): Promise<any[]> {
try {
const response = await invoke<any[]>('get_api_configurations');
return response;
} catch (error) {
console.error('获取API配置失败:', error);
throw new Error(`获取API配置失败: ${error}`);
}
}
static async saveApiConfigurations(configs: any[]): Promise<void> {
try {
await invoke<void>('save_api_configurations', { configs });
} catch (error) {
console.error('保存API配置失败:', error);
throw new Error(`保存API配置失败: ${error}`);
}
}
static async getModelAssignments(): Promise<any> {
try {
const response = await invoke<any>('get_model_assignments');
return response;
} catch (error) {
console.error('获取模型分配失败:', error);
throw new Error(`获取模型分配失败: ${error}`);
}
}
static async saveModelAssignments(assignments: any): Promise<void> {
try {
await invoke<void>('save_model_assignments', { assignments });
} catch (error) {
console.error('保存模型分配失败:', error);
throw new Error(`保存模型分配失败: ${error}`);
}
}
// 科目配置管理API
static async getAllSubjectConfigs(enabledOnly: boolean = false): Promise<any[]> {
try {
const response = await invoke<any[]>('get_all_subject_configs', { enabled_only: enabledOnly });
return response;
} catch (error) {
console.error('获取科目配置列表失败:', error);
throw new Error(`获取科目配置列表失败: ${error}`);
}
}
static async getSubjectConfigById(id: string): Promise<any | null> {
try {
const response = await invoke<any | null>('get_subject_config_by_id', { id });
return response;
} catch (error) {
console.error('获取科目配置失败:', error);
throw new Error(`获取科目配置失败: ${error}`);
}
}
static async getSubjectConfigByName(subjectName: string): Promise<any | null> {
try {
const response = await invoke<any | null>('get_subject_config_by_name', { subject_name: subjectName });
return response;
} catch (error) {
console.error('获取科目配置失败:', error);
throw new Error(`获取科目配置失败: ${error}`);
}
}
static async createSubjectConfig(request: {
subject_name: string;
display_name: string;
description?: string;
prompts?: any;
mistake_types?: string[];
default_tags?: string[];
}): Promise<any> {
try {
const response = await invoke<any>('create_subject_config', { request });
return response;
} catch (error) {
console.error('创建科目配置失败:', error);
throw new Error(`创建科目配置失败: ${error}`);
}
}
static async updateSubjectConfig(request: {
id: string;
display_name?: string;
description?: string;
is_enabled?: boolean;
prompts?: any;
mistake_types?: string[];
default_tags?: string[];
}): Promise<any> {
try {
const response = await invoke<any>('update_subject_config', { request });
return response;
} catch (error) {
console.error('更新科目配置失败:', error);
throw new Error(`更新科目配置失败: ${error}`);
}
}
static async deleteSubjectConfig(id: string): Promise<boolean> {
try {
const response = await invoke<boolean>('delete_subject_config', { id });
return response;
} catch (error) {
console.error('删除科目配置失败:', error);
throw new Error(`删除科目配置失败: ${error}`);
}
}
static async initializeDefaultSubjectConfigs(): Promise<void> {
try {
await invoke<void>('initialize_default_subject_configs');
} catch (error) {
console.error('初始化默认科目配置失败:', error);
throw new Error(`初始化默认科目配置失败: ${error}`);
}
}
// 流式回顾分析API
static async analyzeReviewSessionStream(subject: string, mistakeIds: string[]): Promise<{ review_id: string }> {
try {
const response = await invoke<{ review_id: string }>('analyze_review_session_stream', {
subject,
mistake_ids: mistakeIds
});
return response;
} catch (error) {
console.error('流式回顾分析失败:', error);
throw new Error(`流式回顾分析失败: ${error}`);
}
}
// 批量操作API
static async batchSaveMistakes(mistakes: MistakeItem[]): Promise<void> {
try {
await invoke<void>('batch_save_mistakes', { mistakes });
} catch (error) {
console.error('批量保存错题失败:', error);
throw new Error(`批量保存错题失败: ${error}`);
}
}
static async batchDeleteMistakes(ids: string[]): Promise<void> {
try {
await invoke<void>('batch_delete_mistakes', { ids });
} catch (error) {
console.error('批量删除错题失败:', error);
throw new Error(`批量删除错题失败: ${error}`);
}
}
// ============================================================================
// 回顾分析功能API
// ============================================================================
// 开始统一回顾分析 - 第一步：创建会话并缓存数据
static async startConsolidatedReviewAnalysis(request: {
subject: string;
consolidatedInput: string;
overallPrompt: string;
enableChainOfThought: boolean;
mistakeIds: string[]; // 🔧 修复：添加错题ID列表参数
}): Promise<{ review_session_id: string }> {
try {
const response = await invoke<{ review_session_id: string }>('start_consolidated_review_analysis', {
request: {
subject: request.subject,
consolidated_input: request.consolidatedInput,
overall_prompt: request.overallPrompt,
enable_chain_of_thought: request.enableChainOfThought,
mistake_ids: request.mistakeIds, // 🔧 修复：传递错题ID列表
}
});
return response;
} catch (error) {
console.error('开始统一回顾分析失败:', error);
throw new Error(`开始统一回顾分析失败: ${error}`);
}
}
// 触发统一回顾分析流式处理 - 第二步：开始AI分析
static async triggerConsolidatedReviewStream(request: {
review_session_id: string;
enable_chain_of_thought: boolean;
enable_rag?: boolean;
rag_options?: { top_k: number };
}): Promise<void> {
try {
await invoke<void>('trigger_consolidated_review_stream', {
request: {
review_session_id: request.review_session_id,
enable_chain_of_thought: request.enable_chain_of_thought,
enable_rag: request.enable_rag,
rag_options: request.rag_options
}
});
} catch (error) {
console.error('触发统一回顾分析流式处理失败 (raw):', error);
let errorMessage = '未知错误';
if (error && typeof error === 'object') {
errorMessage = (error as any).message || JSON.stringify(error);
} else if (typeof error === 'string') {
errorMessage = error;
}
throw new Error(`触发统一回顾分析流式处理失败: ${errorMessage}`);
}
}
// 继续统一回顾分析对话
static async continueConsolidatedReviewStream(request: {
review_session_id: string;
chat_history: ChatMessage[];
enable_chain_of_thought: boolean;
enable_rag?: boolean;
rag_options?: { top_k: number };
}): Promise<void> {
try {
await invoke<void>('continue_consolidated_review_stream', {
request: {
review_session_id: request.review_session_id,
chat_history: request.chat_history,
enable_chain_of_thought: request.enable_chain_of_thought,
enable_rag: request.enable_rag,
rag_options: request.rag_options
}
});
} catch (error) {
console.error('继续统一回顾分析对话失败 (raw):', error);
let errorMessage = '未知错误';
if (error && typeof error === 'object') {
errorMessage = (error as any).message || JSON.stringify(error);
} else if (typeof error === 'string') {
errorMessage = error;
}
throw new Error(`继续统一回顾分析对话失败: ${errorMessage}`);
}
}
// 获取统一回顾分析会话数据
static async getConsolidatedReviewSession(sessionId: string): Promise<any | null> {
try {
const session = await invoke<any | null>('get_consolidated_review_session', {
sessionId: sessionId,
});
return session;
} catch (error) {
console.error('获取统一回顾分析会话失败:', error);
throw new Error(`获取统一回顾分析会话失败: ${error}`);
}
}
// ============================================================================
// RAG知识库管理API
// ============================================================================
// 添加文档到知识库（通过文件路径）
static async ragAddDocuments(filePaths: string[]): Promise<string> {
try {
const response = await invoke<string>('rag_add_documents', {
request: {
file_paths: filePaths,
chunk_size: null,
chunk_overlap: null,
enable_preprocessing: null
}
});
return response;
} catch (error) {
console.error('添加文档到知识库失败:', error);
throw new Error(`添加文档到知识库失败: ${error}`);
}
}
// 添加文档到知识库（通过文件内容）
static async ragAddDocumentsFromContent(documents: Array<{
fileName: string;
content: string;
}>): Promise<string> {
try {
const response = await invoke<string>('rag_add_documents_from_content', {
documents
});
return response;
} catch (error) {
console.error('从内容添加文档到知识库失败:', error);
throw new Error(`从内容添加文档到知识库失败: ${error}`);
}
}
// 获取知识库状态
static async ragGetKnowledgeBaseStatus(): Promise<{
total_documents: number;
total_chunks: number;
embedding_model_name?: string;
vector_store_type: string;
}> {
try {
const response = await invoke<{
total_documents: number;
total_chunks: number;
embedding_model_name?: string;
vector_store_type: string;
}>('rag_get_knowledge_base_status');
return response;
} catch (error) {
console.error('获取知识库状态失败:', error);
throw new Error(`获取知识库状态失败: ${error}`);
}
}
// 删除知识库中的文档
static async ragDeleteDocument(documentId: string): Promise<void> {
try {
await invoke<void>('rag_delete_document', { documentId: documentId });
} catch (error) {
console.error('删除知识库文档失败:', error);
throw new Error(`删除知识库文档失败: ${error}`);
}
}
// 查询知识库
static async ragQueryKnowledgeBase(query: string, options: {
top_k: number;
enable_reranking?: boolean;
}): Promise<{
retrieved_chunks: Array<{
chunk: {
id: string;
document_id: string;
chunk_index: number;
text: string;
metadata: Record<string, string>;
};
score: number;
}>;
query_vector_time_ms: number;
search_time_ms: number;
reranking_time_ms?: number;
total_time_ms: number;
}> {
try {
const response = await invoke<{
retrieved_chunks: Array<{
chunk: {
id: string;
document_id: string;
chunk_index: number;
text: string;
metadata: Record<string, string>;
};
score: number;
}>;
query_vector_time_ms: number;
search_time_ms: number;
reranking_time_ms?: number;
total_time_ms: number;
}>('rag_query_knowledge_base', { query, options });
return response;
} catch (error) {
console.error('查询知识库失败:', error);
throw new Error(`查询知识库失败: ${error}`);
}
}
// 获取所有文档列表
static async ragGetAllDocuments(): Promise<Array<{
id: string;
file_name: string;
file_path?: string;
file_size?: number;
total_chunks: number;
created_at: string;
updated_at: string;
}>> {
try {
const response = await invoke<Array<{
id: string;
file_name: string;
file_path?: string;
file_size?: number;
total_chunks: number;
created_at: string;
updated_at: string;
}>>('rag_get_all_documents');
return response;
} catch (error) {
console.error('获取文档列表失败:', error);
throw new Error(`获取文档列表失败: ${error}`);
}
}
// 清空知识库
static async ragClearKnowledgeBase(): Promise<void> {
try {
await invoke<void>('rag_clear_knowledge_base');
} catch (error) {
console.error('清空知识库失败:', error);
throw new Error(`清空知识库失败: ${error}`);
}
}
// ============================================================================
// RAG增强的AI分析API
// ============================================================================
// RAG增强的流式分析
static async startRagEnhancedStreamingAnswer(request: {
temp_id: string;
enable_chain_of_thought: boolean;
enable_rag?: boolean;
rag_options?: {
top_k: number;
enable_reranking?: boolean;
};
}): Promise<void> {
try {
await invoke<void>('start_rag_enhanced_streaming_answer', { request });
} catch (error) {
console.error('RAG增强流式分析失败:', error);
throw new Error(`RAG增强流式分析失败: ${error}`);
}
}
// RAG增强的继续对话
static async continueRagEnhancedChatStream(request: {
temp_id: string;
chat_history: ChatMessage[];
enable_chain_of_thought?: boolean;
enable_rag?: boolean;
rag_options?: {
top_k: number;
enable_reranking?: boolean;
};
}): Promise<{ new_assistant_message: string }> {
try {
const response = await invoke<{ new_assistant_message: string }>('continue_rag_enhanced_chat_stream', { request });
return response;
} catch (error) {
console.error('RAG增强对话失败:', error);
throw new Error(`RAG增强对话失败: ${error}`);
}
}
// ============================================================================
// 独立RAG查询API
// ============================================================================
// RAG配置管理API
// 获取RAG配置
static async getRagSettings(): Promise<{
chunk_size: number;
chunk_overlap: number;
chunking_strategy: string;
min_chunk_size: number;
default_top_k: number;
default_rerank_enabled: boolean;
}> {
try {
const response = await invoke<{
chunk_size: number;
chunk_overlap: number;
chunking_strategy: string;
min_chunk_size: number;
default_top_k: number;
default_rerank_enabled: boolean;
}>('get_rag_settings');
return response;
} catch (error) {
console.error('获取RAG配置失败:', error);
throw new Error(`获取RAG配置失败: ${error}`);
}
}
// 更新RAG配置
static async updateRagSettings(settings: {
chunk_size: number;
chunk_overlap: number;
chunking_strategy: string;
min_chunk_size: number;
default_top_k: number;
default_rerank_enabled: boolean;
}): Promise<void> {
try {
await invoke<void>('update_rag_settings', { settings });
} catch (error) {
console.error('更新RAG配置失败:', error);
throw new Error(`更新RAG配置失败: ${error}`);
}
}
// 重置RAG配置为默认值
static async resetRagSettings(): Promise<void> {
try {
await invoke<void>('reset_rag_settings');
} catch (error) {
console.error('重置RAG配置失败:', error);
throw new Error(`重置RAG配置失败: ${error}`);
}
}
// ==================== RAG分库管理方法 ====================
/**
* 创建新的RAG分库
*/
static async createRagSubLibrary(request: {
name: string;
description?: string;
}): Promise<{
id: string;
name: string;
description?: string;
created_at: string;
updated_at: string;
document_count: number;
chunk_count: number;
}> {
try {
const response = await invoke<{
id: string;
name: string;
description?: string;
created_at: string;
updated_at: string;
document_count: number;
chunk_count: number;
}>('create_rag_sub_library', { request });
console.log('✅ 分库创建成功:', response);
return response;
} catch (error) {
console.error('创建分库失败:', error);
throw new Error(`创建分库失败: ${error}`);
}
}
/**
* 获取所有RAG分库列表
*/
static async getRagSubLibraries(): Promise<Array<{
id: string;
name: string;
description?: string;
created_at: string;
updated_at: string;
document_count: number;
chunk_count: number;
}>> {
try {
const response = await invoke<Array<{
id: string;
name: string;
description?: string;
created_at: string;
updated_at: string;
document_count: number;
chunk_count: number;
}>>('get_rag_sub_libraries');
console.log('✅ 获取分库列表成功:', response);
return response;
} catch (error) {
console.error('获取分库列表失败:', error);
throw new Error(`获取分库列表失败: ${error}`);
}
}
/**
* 根据ID获取RAG分库详情
*/
static async getRagSubLibraryById(libraryId: string): Promise<{
id: string;
name: string;
description?: string;
created_at: string;
updated_at: string;
document_count: number;
chunk_count: number;
} | null> {
try {
const response = await invoke<{
id: string;
name: string;
description?: string;
created_at: string;
updated_at: string;
document_count: number;
chunk_count: number;
} | null>('get_rag_sub_library_by_id', { libraryId: libraryId });
console.log('✅ 获取分库详情成功:', response);
return response;
} catch (error) {
console.error('获取分库详情失败:', error);
throw new Error(`获取分库详情失败: ${error}`);
}
}
/**
* 更新RAG分库信息
*/
static async updateRagSubLibrary(libraryId: string, request: {
name?: string;
description?: string;
}): Promise<{
id: string;
name: string;
description?: string;
created_at: string;
updated_at: string;
document_count: number;
chunk_count: number;
}> {
try {
const response = await invoke<{
id: string;
name: string;
description?: string;
created_at: string;
updated_at: string;
document_count: number;
chunk_count: number;
}>('update_rag_sub_library', {
libraryId: libraryId,
request
});
console.log('✅ 分库更新成功:', response);
return response;
} catch (error) {
console.error('更新分库失败:', error);
throw new Error(`更新分库失败: ${error}`);
}
}
/**
* 删除RAG分库
*/
static async deleteRagSubLibrary(libraryId: string, deleteDocuments: boolean = false): Promise<void> {
try {
await invoke<void>('delete_rag_sub_library', {
libraryId: libraryId,
deleteDocuments: deleteDocuments
});
console.log('✅ 分库删除成功');
} catch (error) {
console.error('删除分库失败:', error);
throw new Error(`删除分库失败: ${error}`);
}
}
/**
* 向指定分库添加文档
*/
static async ragAddDocumentsToLibrary(request: {
file_paths: string[];
sub_library_id?: string;
}): Promise<string> {
try {
const response = await invoke<string>('rag_add_documents_to_library', { request });
console.log('✅ 文档添加到分库成功:', response);
return response;
} catch (error) {
console.error('添加文档到分库失败:', error);
throw new Error(`添加文档到分库失败: ${error}`);
}
}
/**
* 从Base64内容向指定分库添加文档
*/
static async ragAddDocumentsFromContentToLibrary(request: {
documents: Array<{
file_name: string;
base64_content: string;
}>;
sub_library_id?: string;
}): Promise<string> {
try {
const response = await invoke<string>('rag_add_documents_from_content_to_library', { request });
console.log('✅ 从内容添加文档到分库成功:', response);
return response;
} catch (error) {
console.error('从内容添加文档到分库失败:', error);
throw new Error(`从内容添加文档到分库失败: ${error}`);
}
}
/**
* 获取指定分库的文档列表
*/
static async getRagDocumentsByLibrary(request: {
sub_library_id?: string;
page?: number;
page_size?: number;
}): Promise<Array<{
id: string;
file_name: string;
file_path?: string;
file_size?: number;
total_chunks: number;
sub_library_id: string;
created_at: string;
updated_at: string;
}>> {
try {
const response = await invoke<Array<{
id: string;
file_name: string;
file_path?: string;
file_size?: number;
total_chunks: number;
sub_library_id: string;
created_at: string;
updated_at: string;
}>>('get_rag_documents_by_library', { request });
console.log('✅ 获取分库文档列表成功:', response);
return response;
} catch (error) {
console.error('获取分库文档列表失败:', error);
throw new Error(`获取分库文档列表失败: ${error}`);
}
}
/**
* 将文档移动到指定分库
*/
static async moveDocumentToRagLibrary(documentId: string, targetLibraryId: string): Promise<void> {
try {
await invoke<void>('move_document_to_rag_library', {
documentId: documentId,
targetLibraryId: targetLibraryId
});
console.log('✅ 文档移动成功');
} catch (error) {
console.error('移动文档失败:', error);
throw new Error(`移动文档失败: ${error}`);
}
}
/**
* 在指定分库中查询知识库
*/
static async ragQueryKnowledgeBaseInLibraries(query: string, options: {
top_k: number;
enable_reranking?: boolean;
target_sub_library_ids?: string[];
}): Promise<{
retrieved_chunks: Array<{
chunk: {
id: string;
document_id: string;
chunk_index: number;
text: string;
metadata: Record<string, string>;
};
score: number;
}>;
query_vector_time_ms: number;
search_time_ms: number;
reranking_time_ms?: number;
total_time_ms: number;
}> {
try {
const response = await invoke<{
retrieved_chunks: Array<{
chunk: {
id: string;
document_id: string;
chunk_index: number;
text: string;
metadata: Record<string, string>;
};
score: number;
}>;
query_vector_time_ms: number;
search_time_ms: number;
reranking_time_ms?: number;
total_time_ms: number;
}>('rag_query_knowledge_base_in_libraries', { query, options });
console.log('✅ 分库查询成功:', response);
return response;
} catch (error) {
console.error('分库查询失败:', error);
throw new Error(`分库查询失败: ${error}`);
}
}
// ==================== 回顾分析API - 复用错题分析模式 ====================
/**
* 从数据库获取回顾分析（复用错题分析的加载模式）
*/
static async getReviewAnalysisById(id: string): Promise<ReviewAnalysisItem | null> {
try {
const response = await invoke<ReviewAnalysisItem | null>('get_review_analysis_by_id', { id });
console.log('✅ 获取回顾分析成功:', response);
return response;
} catch (error) {
console.error('❌ 获取回顾分析失败:', error);
throw new Error(`获取回顾分析失败: ${error}`);
}
}
/**
* 删除回顾分析（统一回顾分析功能）
*/
static async deleteReviewAnalysis(id: string): Promise<boolean> {
try {
console.log('🗑️ 开始删除回顾分析:', id);
const response = await invoke<boolean>('delete_review_analysis', { id });
if (response) {
console.log('✅ 回顾分析删除成功:', id);
} else {
console.warn('⚠️ 回顾分析不存在或删除失败:', id);
}
return response;
} catch (error) {
console.error('❌ 删除回顾分析失败:', error);
throw new Error(`删除回顾分析失败: ${error}`);
}
}
// 🎯 新增：更新回顾分析（主要用于保存聊天历史）
static async updateReviewAnalysis(reviewAnalysis: ReviewAnalysisItem): Promise<ReviewAnalysisItem> {
try {
const response = await invoke<ReviewAnalysisItem>('update_review_analysis', {
review_analysis: reviewAnalysis
});
console.log('✅ 回顾分析更新成功');
return response;
} catch (error) {
console.error('❌ 更新回顾分析失败:', error);
// 如果后端没有这个命令，使用变通方案
console.log('ℹ️ 后端可能没有update_review_analysis命令，使用变通方案');
throw new Error(`更新回顾分析失败: ${error}`);
}
}
/**
* 回顾分析聊天追问（复用错题分析的追问模式）
*/
static async continueReviewChatStream(params: {
reviewId: string;
chatHistory: ChatMessage[];
enableChainOfThought: boolean;
enableRag?: boolean;
ragTopK?: number;
}): Promise<void> {
try {
await invoke('continue_consolidated_review_stream', {
request: {
review_session_id: params.reviewId,
chat_history: params.chatHistory,
enable_chain_of_thought: params.enableChainOfThought,
enable_rag: params.enableRag || false,
rag_options: params.enableRag ? { top_k: params.ragTopK || 5 } : undefined
}
});
console.log('✅ 回顾分析聊天追问成功');
} catch (error) {
console.error('❌ 回顾分析聊天追问失败:', error);
throw new Error(`回顾分析聊天追问失败: ${error}`);
}
}
// ==================== 通用invoke方法 ====================
// ============================================================================
// 错题总结生成 API
// ============================================================================
/**
* 生成错题总结 - 基于聊天记录生成结构化总结
*/
static async generateMistakeSummary(request: {
mistake_id: string;
force_regenerate?: boolean;
}): Promise<{
success: boolean;
mistake_summary?: string | null;
user_error_analysis?: string | null;
error_message?: string | null;
}> {
try {
console.log('🧠 开始生成错题总结:', request.mistake_id);
const response = await invoke<{
success: boolean;
mistake_summary?: string | null;
user_error_analysis?: string | null;
error_message?: string | null;
}>('generate_mistake_summary', {
request: {
mistake_id: request.mistake_id,
force_regenerate: request.force_regenerate || false,
}
});
if (response.success) {
console.log('✅ 错题总结生成成功');
} else {
console.warn('⚠️ 错题总结生成失败:', response.error_message);
}
return response;
} catch (error) {
console.error('❌ 生成错题总结失败:', error);
throw new Error(`生成总结失败: ${error}`);
}
}
/**
* LLM基于上下文生成回答
*/
static async llmGenerateAnswerWithContext(userQuery: string, retrievedChunksJson: string): Promise<string> {
try {
console.log('🤖 调用LLM生成API:', { userQuery: userQuery.substring(0, 100) + '...', retrievedChunksJson });
const response = await invoke<string>('llm_generate_answer_with_context', {
userQuery: userQuery,
retrievedChunksJson: retrievedChunksJson,
});
console.log('✅ LLM生成成功');
return response;
} catch (error) {
console.error('❌ LLM生成回答失败:', error);
throw new Error(`LLM生成失败: ${error}`);
}
}
/**
* 通用的Tauri invoke方法
*/
static async invoke<T>(command: string, args?: Record<string, any>): Promise<T> {
try {
const response = await invoke<T>(command, args);
console.log(`✅ ${command} 调用成功:`, response);
return response;
} catch (error) {
console.error(`❌ ${command} 调用失败:`, error);
throw new Error(`${command} 失败: ${error}`);
}
}
}
|
000haoji/deep-student
| 8,373 |
src/utils/dataConsolidationEngine.ts
|
/**
* 数据整合引擎 - 回顾分析功能的核心数据处理模块
*
* 负责将多个错题的信息整合成统一的文本格式，供AI分析使用
*/
import { MistakeItem, MistakeConsolidationData, ConsolidatedMistakeData, ChatMessage } from '../types/index';
export class DataConsolidationEngine {
/**
* 从错题对象中提取关键信息用于整合
*/
static extractMistakeData(mistake: MistakeItem): MistakeConsolidationData {
return {
mistakeId: mistake.id,
ocr_text: mistake.ocr_text,
user_question: mistake.user_question,
chat_history: mistake.chat_history.filter(msg =>
// 只保留用户和助手的消息内容，排除思维链
msg.role === 'user' || msg.role === 'assistant'
).map(msg => ({
role: msg.role,
content: msg.content,
timestamp: msg.timestamp,
// 不包含thinking_content
})),
};
}
/**
* 将多个错题信息整合成结构化的长文本
*/
static consolidateMistakes(
mistakes: MistakeItem[],
userOverallPrompt: string,
consolidationOptions?: {
includeImages?: boolean;
includeChatHistory?: boolean;
maxChatMessagesPerMistake?: number;
includeTimestamps?: boolean;
includeTags?: boolean;
customTemplate?: string;
}
): ConsolidatedMistakeData {
const options = {
includeImages: false, // 暂不支持图片整合
includeChatHistory: true,
maxChatMessagesPerMistake: 10,
includeTimestamps: false,
includeTags: true,
...consolidationOptions,
};
const selectedMistakes = mistakes.map(mistake => this.extractMistakeData(mistake));
const consolidatedText = this.generateConsolidatedText(mistakes, options);
return {
selectedMistakes,
consolidatedText,
userOverallPrompt,
};
}
/**
* 生成整合后的文本内容
*/
private static generateConsolidatedText(
mistakes: MistakeItem[],
options: any
): string {
let consolidatedText = '';
// 添加整体说明
consolidatedText += '# 错题回顾分析数据\n\n';
consolidatedText += `本次回顾分析包含 ${mistakes.length} 道错题，以下是详细信息：\n\n`;
mistakes.forEach((mistake, index) => {
consolidatedText += this.formatSingleMistake(mistake, index + 1, options);
consolidatedText += '\n';
});
return consolidatedText;
}
/**
* 格式化单个错题的信息
*/
private static formatSingleMistake(mistake: MistakeItem, index: number, options: any): string {
let mistakeText = '';
mistakeText += `## 错题 ${index} (ID: ${mistake.id})\n\n`;
// 基本信息
mistakeText += `**科目**: ${mistake.subject}\n`;
mistakeText += `**错题类型**: ${mistake.mistake_type}\n`;
if (options.includeTags && mistake.tags.length > 0) {
mistakeText += `**相关标签**: ${mistake.tags.join(', ')}\n`;
}
if (options.includeTimestamps) {
mistakeText += `**创建时间**: ${new Date(mistake.created_at).toLocaleString()}\n`;
}
mistakeText += '\n';
// 题目内容
mistakeText += '### 题目内容\n';
mistakeText += '```\n';
mistakeText += mistake.ocr_text || '(无题目文字内容)';
mistakeText += '\n```\n\n';
// 原始问题
mistakeText += '### 我的原始问题\n';
mistakeText += mistake.user_question;
mistakeText += '\n\n';
// 历史交流记录
if (options.includeChatHistory && mistake.chat_history.length > 0) {
mistakeText += '### 历史交流记录\n';
const messages = mistake.chat_history
.slice(0, options.maxChatMessagesPerMistake)
.filter(msg => msg.role === 'user' || msg.role === 'assistant');
messages.forEach((message, msgIndex) => {
const roleDisplay = message.role === 'user' ? '👤 用户' : '🤖 助手';
mistakeText += `**${roleDisplay}**: ${message.content}\n\n`;
});
if (mistake.chat_history.length > options.maxChatMessagesPerMistake) {
mistakeText += `*(还有 ${mistake.chat_history.length - options.maxChatMessagesPerMistake} 条消息未显示)*\n\n`;
}
}
mistakeText += '---\n\n';
return mistakeText;
}
/**
* 验证整合数据的有效性
*/
static validateConsolidatedData(data: ConsolidatedMistakeData): {
isValid: boolean;
errors: string[];
warnings: string[];
} {
const errors: string[] = [];
const warnings: string[] = [];
// 检查必要字段
if (!data.userOverallPrompt || data.userOverallPrompt.trim().length === 0) {
errors.push('用户总体分析指引不能为空');
}
if (!data.selectedMistakes || data.selectedMistakes.length === 0) {
errors.push('至少需要选择一个错题');
}
if (!data.consolidatedText || data.consolidatedText.trim().length === 0) {
errors.push('整合文本不能为空');
}
// 检查数据质量
if (data.selectedMistakes) {
data.selectedMistakes.forEach((mistake, index) => {
if (!mistake.ocr_text || mistake.ocr_text.trim().length === 0) {
warnings.push(`错题 ${index + 1} 没有题目文字内容`);
}
if (!mistake.user_question || mistake.user_question.trim().length === 0) {
warnings.push(`错题 ${index + 1} 没有用户问题`);
}
});
}
// 检查整合文本长度
if (data.consolidatedText && data.consolidatedText.length > 50000) {
warnings.push('整合文本较长，可能超出某些AI模型的上下文限制');
}
return {
isValid: errors.length === 0,
errors,
warnings,
};
}
/**
* 生成摘要信息
*/
static generateSummary(data: ConsolidatedMistakeData): {
mistakeCount: number;
subjects: string[];
totalChatMessages: number;
averageOcrLength: number;
consolidatedTextLength: number;
estimatedTokens: number;
} {
const subjects = [...new Set(data.selectedMistakes.map(m => {
// 从mistakeId中尝试获取科目信息，或使用其他方式
return 'Unknown'; // 这里需要根据实际数据结构调整
}))];
const totalChatMessages = data.selectedMistakes.reduce(
(sum, mistake) => sum + mistake.chat_history.length,
0
);
const totalOcrLength = data.selectedMistakes.reduce(
(sum, mistake) => sum + mistake.ocr_text.length,
0
);
const averageOcrLength = data.selectedMistakes.length > 0
? totalOcrLength / data.selectedMistakes.length
: 0;
// 简单的token估算（1个token约等于4个字符）
const estimatedTokens = Math.ceil(data.consolidatedText.length / 4);
return {
mistakeCount: data.selectedMistakes.length,
subjects,
totalChatMessages,
averageOcrLength: Math.round(averageOcrLength),
consolidatedTextLength: data.consolidatedText.length,
estimatedTokens,
};
}
/**
* 预设的整合模板
*/
static getPresetTemplates(): { [key: string]: string } {
return {
detailed: '详细模式 - 包含完整的聊天历史和所有信息',
concise: '简洁模式 - 只包含题目内容和原始问题',
focused: '重点模式 - 包含题目内容、问题和关键交流',
comparative: '对比模式 - 突出不同错题间的关联和差异',
};
}
/**
* 根据模板生成特定格式的整合文本
*/
static consolidateWithTemplate(
mistakes: MistakeItem[],
userOverallPrompt: string,
templateType: 'detailed' | 'concise' | 'focused' | 'comparative'
): ConsolidatedMistakeData {
const templateOptions = {
detailed: {
includeChatHistory: true,
maxChatMessagesPerMistake: 20,
includeTimestamps: true,
includeTags: true,
},
concise: {
includeChatHistory: false,
maxChatMessagesPerMistake: 0,
includeTimestamps: false,
includeTags: false,
},
focused: {
includeChatHistory: true,
maxChatMessagesPerMistake: 5,
includeTimestamps: false,
includeTags: true,
},
comparative: {
includeChatHistory: true,
maxChatMessagesPerMistake: 3,
includeTimestamps: false,
includeTags: true,
},
};
return this.consolidateMistakes(mistakes, userOverallPrompt, templateOptions[templateType]);
}
/**
* 检查是否超出模型上下文限制
*/
static checkContextLimits(
data: ConsolidatedMistakeData,
modelContextLimit: number = 32000 // 默认32k tokens
): {
withinLimit: boolean;
estimatedTokens: number;
recommendedActions: string[];
} {
const estimatedTokens = Math.ceil(data.consolidatedText.length / 4);
const withinLimit = estimatedTokens <= modelContextLimit * 0.8; // 保留20%缓冲
const recommendedActions: string[] = [];
if (!withinLimit) {
recommendedActions.push('减少选择的错题数量');
recommendedActions.push('使用简洁模式整合');
recommendedActions.push('减少聊天历史记录的包含量');
recommendedActions.push('考虑分批进行回顾分析');
}
return {
withinLimit,
estimatedTokens,
recommendedActions,
};
}
}
export default DataConsolidationEngine;
|
000haoji/deep-student
| 14,377 |
src/utils/dataManager.ts
|
// 数据管理模块 - 模拟本地数据存储
export interface MistakeItem {
id: string;
subject: string;
created_at: string;
question_images: string[];
analysis_images: string[];
user_question: string;
ocr_text: string;
tags: string[];
mistake_type: string;
status: string;
chat_history?: ChatMessage[];
}
export interface ChatMessage {
role: string;
content: string;
timestamp: string;
}
export interface ReviewSession {
id: string;
subject: string;
selected_mistake_ids: string[];
analysis: string;
created_at: string;
chat_history: ChatMessage[];
}
export interface AnalysisRequest {
subject: string;
question_image_files: File[];
analysis_image_files: File[];
user_question: string;
}
export interface AnalysisResponse {
temp_id: string;
initial_data: {
ocr_text: string;
tags: string[];
mistake_type: string;
first_answer: string;
};
}
// 本地存储键名
const STORAGE_KEYS = {
MISTAKES: 'ai_mistake_manager_mistakes',
REVIEWS: 'ai_mistake_manager_reviews',
SETTINGS: 'ai_mistake_manager_settings',
TEMP_SESSIONS: 'ai_mistake_manager_temp_sessions'
};
// 模拟数据
const MOCK_MISTAKES: MistakeItem[] = [
{
id: '1',
subject: '数学',
created_at: '2024-01-15T10:00:00Z',
question_images: [],
analysis_images: [],
user_question: '二次函数的最值问题',
ocr_text: '求函数f(x) = x² + 2x + 1的最小值',
tags: ['二次函数', '最值问题', '配方法'],
mistake_type: '计算题',
status: 'completed',
chat_history: [
{
role: 'assistant',
content: '这是一道二次函数求最值的问题。通过配方法可以得到 f(x) = (x+1)²，所以最小值为0。',
timestamp: '2024-01-15T10:05:00Z'
}
]
},
{
id: '2',
subject: '数学',
created_at: '2024-01-16T14:30:00Z',
question_images: [],
analysis_images: [],
user_question: '二次函数图像问题',
ocr_text: '画出函数y = x² - 4x + 3的图像',
tags: ['二次函数', '图像', '顶点'],
mistake_type: '作图题',
status: 'completed',
chat_history: [
{
role: 'assistant',
content: '这个函数可以配方为 y = (x-2)² - 1，顶点为(2, -1)，开口向上。',
timestamp: '2024-01-16T14:35:00Z'
}
]
},
{
id: '3',
subject: '数学',
created_at: '2024-01-17T09:15:00Z',
question_images: [],
analysis_images: [],
user_question: '一元二次方程求解',
ocr_text: '解方程x² - 5x + 6 = 0',
tags: ['一元二次方程', '因式分解', '求根公式'],
mistake_type: '计算题',
status: 'completed',
chat_history: [
{
role: 'assistant',
content: '这个方程可以因式分解为 (x-2)(x-3) = 0，所以解为 x = 2 或 x = 3。',
timestamp: '2024-01-17T09:20:00Z'
}
]
},
{
id: '4',
subject: '物理',
created_at: '2024-01-18T16:45:00Z',
question_images: [],
analysis_images: [],
user_question: '牛顿第二定律应用',
ocr_text: '质量为2kg的物体受到10N的力，求加速度',
tags: ['牛顿定律', '力学', '加速度'],
mistake_type: '计算题',
status: 'completed',
chat_history: [
{
role: 'assistant',
content: '根据牛顿第二定律 F = ma，可得 a = F/m = 10/2 = 5 m/s²。',
timestamp: '2024-01-18T16:50:00Z'
}
]
},
{
id: '5',
subject: '数学',
created_at: '2024-01-19T11:20:00Z',
question_images: [],
analysis_images: [],
user_question: '二次函数与x轴交点',
ocr_text: '求函数y = x² - 3x + 2与x轴的交点',
tags: ['二次函数', '交点', '判别式'],
mistake_type: '计算题',
status: 'completed',
chat_history: [
{
role: 'assistant',
content: '令y=0，得到 x² - 3x + 2 = 0，因式分解得 (x-1)(x-2) = 0，所以交点为(1,0)和(2,0)。',
timestamp: '2024-01-19T11:25:00Z'
}
]
}
];
class DataManager {
// 初始化数据
static initializeData() {
if (!localStorage.getItem(STORAGE_KEYS.MISTAKES)) {
localStorage.setItem(STORAGE_KEYS.MISTAKES, JSON.stringify(MOCK_MISTAKES));
}
if (!localStorage.getItem(STORAGE_KEYS.REVIEWS)) {
localStorage.setItem(STORAGE_KEYS.REVIEWS, JSON.stringify([]));
}
if (!localStorage.getItem(STORAGE_KEYS.TEMP_SESSIONS)) {
localStorage.setItem(STORAGE_KEYS.TEMP_SESSIONS, JSON.stringify({}));
}
}
// 错题管理
static getMistakes(filter?: { subject?: string; tags?: string[]; type?: string }): MistakeItem[] {
this.initializeData();
const mistakes = JSON.parse(localStorage.getItem(STORAGE_KEYS.MISTAKES) || '[]');
if (!filter) return mistakes;
return mistakes.filter((mistake: MistakeItem) => {
if (filter.subject && mistake.subject !== filter.subject) return false;
if (filter.type && mistake.mistake_type !== filter.type) return false;
if (filter.tags && !filter.tags.some(tag => mistake.tags.includes(tag))) return false;
return true;
});
}
static getMistakeById(id: string): MistakeItem | null {
const mistakes = this.getMistakes();
return mistakes.find(mistake => mistake.id === id) || null;
}
static saveMistake(mistake: MistakeItem): boolean {
try {
const mistakes = this.getMistakes();
const existingIndex = mistakes.findIndex(m => m.id === mistake.id);
if (existingIndex >= 0) {
mistakes[existingIndex] = mistake;
} else {
mistakes.push(mistake);
}
localStorage.setItem(STORAGE_KEYS.MISTAKES, JSON.stringify(mistakes));
return true;
} catch (error) {
console.error('保存错题失败:', error);
return false;
}
}
static deleteMistake(id: string): boolean {
try {
const mistakes = this.getMistakes();
const filteredMistakes = mistakes.filter(mistake => mistake.id !== id);
localStorage.setItem(STORAGE_KEYS.MISTAKES, JSON.stringify(filteredMistakes));
return true;
} catch (error) {
console.error('删除错题失败:', error);
return false;
}
}
// 临时会话管理
static saveTempSession(tempId: string, data: any): void {
const sessions = JSON.parse(localStorage.getItem(STORAGE_KEYS.TEMP_SESSIONS) || '{}');
sessions[tempId] = data;
localStorage.setItem(STORAGE_KEYS.TEMP_SESSIONS, JSON.stringify(sessions));
}
static getTempSession(tempId: string): any {
const sessions = JSON.parse(localStorage.getItem(STORAGE_KEYS.TEMP_SESSIONS) || '{}');
return sessions[tempId] || null;
}
static deleteTempSession(tempId: string): void {
const sessions = JSON.parse(localStorage.getItem(STORAGE_KEYS.TEMP_SESSIONS) || '{}');
delete sessions[tempId];
localStorage.setItem(STORAGE_KEYS.TEMP_SESSIONS, JSON.stringify(sessions));
}
// 回顾分析管理
static getReviewSessions(): ReviewSession[] {
this.initializeData();
return JSON.parse(localStorage.getItem(STORAGE_KEYS.REVIEWS) || '[]');
}
static saveReviewSession(session: ReviewSession): boolean {
try {
const sessions = this.getReviewSessions();
const existingIndex = sessions.findIndex(s => s.id === session.id);
if (existingIndex >= 0) {
sessions[existingIndex] = session;
} else {
sessions.push(session);
}
localStorage.setItem(STORAGE_KEYS.REVIEWS, JSON.stringify(sessions));
return true;
} catch (error) {
console.error('保存回顾分析失败:', error);
return false;
}
}
// 设置管理
static getSettings(): any {
const defaultSettings = {
apiKey: '',
model1: 'gpt-4-vision-preview',
model2: 'gpt-4',
subjects: ['数学', '物理', '化学', '英语'],
prompts: {
数学: {
model1: '请分析这道数学题目，提取题目文本、分类和标签。',
model2: '请详细解答这道数学题目，提供清晰的解题步骤。'
},
物理: {
model1: '请分析这道物理题目，提取题目文本、分类和标签。',
model2: '请详细解答这道物理题目，说明物理原理和计算过程。'
},
化学: {
model1: '请分析这道化学题目，提取题目文本、分类和标签。',
model2: '请详细解答这道化学题目，解释化学反应和计算过程。'
},
英语: {
model1: '请分析这道英语题目，提取题目文本、分类和标签。',
model2: '请详细解答这道英语题目，提供语法解释和答案分析。'
}
}
};
const settings = localStorage.getItem(STORAGE_KEYS.SETTINGS);
return settings ? { ...defaultSettings, ...JSON.parse(settings) } : defaultSettings;
}
static saveSettings(settings: any): boolean {
try {
localStorage.setItem(STORAGE_KEYS.SETTINGS, JSON.stringify(settings));
return true;
} catch (error) {
console.error('保存设置失败:', error);
return false;
}
}
// 统计信息
static getStatistics() {
const mistakes = this.getMistakes();
const reviews = this.getReviewSessions();
const subjectStats = mistakes.reduce((acc, mistake) => {
acc[mistake.subject] = (acc[mistake.subject] || 0) + 1;
return acc;
}, {} as Record<string, number>);
const typeStats = mistakes.reduce((acc, mistake) => {
acc[mistake.mistake_type] = (acc[mistake.mistake_type] || 0) + 1;
return acc;
}, {} as Record<string, number>);
const tagStats = mistakes.reduce((acc, mistake) => {
mistake.tags.forEach(tag => {
acc[tag] = (acc[tag] || 0) + 1;
});
return acc;
}, {} as Record<string, number>);
return {
totalMistakes: mistakes.length,
totalReviews: reviews.length,
subjectStats,
typeStats,
tagStats,
recentMistakes: mistakes
.sort((a, b) => new Date(b.created_at).getTime() - new Date(a.created_at).getTime())
.slice(0, 5)
};
}
}
// 模拟API调用
export class MockAPI {
static async analyzeNewMistake(request: AnalysisRequest): Promise<AnalysisResponse> {
// 模拟网络延迟
await new Promise(resolve => setTimeout(resolve, 2000 + Math.random() * 1000));
const tempId = 'temp-' + Date.now() + '-' + Math.random().toString(36).substr(2, 9);
// 根据科目生成不同的分析结果
const subjectAnalysis = {
'数学': {
tags: ['二次函数', '最值问题', '配方法'],
type: '计算题',
answer: '这是一道二次函数求最值的问题。通过配方法可以将函数转换为顶点式，从而求出最值。'
},
'物理': {
tags: ['牛顿定律', '力学', '运动学'],
type: '计算题',
answer: '这是一道力学问题。需要运用牛顿定律分析物体的运动状态和受力情况。'
},
'化学': {
tags: ['化学反应', '计算', '平衡'],
type: '计算题',
answer: '这是一道化学计算题。需要根据化学方程式和反应原理进行计算。'
},
'英语': {
tags: ['语法', '阅读理解', '词汇'],
type: '选择题',
answer: '这是一道英语题目。需要理解语法规则和词汇含义来选择正确答案。'
}
};
const analysis = subjectAnalysis[request.subject as keyof typeof subjectAnalysis] || subjectAnalysis['数学'];
const response: AnalysisResponse = {
temp_id: tempId,
initial_data: {
ocr_text: `模拟OCR识别结果：这是一道关于${request.subject}的题目。用户问题：${request.user_question}`,
tags: analysis.tags,
mistake_type: analysis.type,
first_answer: `${analysis.answer}\n\n**解题思路：**\n1. 分析题目条件\n2. 选择合适的解题方法\n3. 按步骤计算\n4. 验证答案\n\n您对这个解答有什么疑问吗？`
}
};
// 保存临时会话
DataManager.saveTempSession(tempId, {
request,
response,
created_at: new Date().toISOString()
});
return response;
}
static async continueChat(_tempId: string, chatHistory: ChatMessage[]): Promise<{ new_assistant_message: string }> {
// 模拟网络延迟
await new Promise(resolve => setTimeout(resolve, 1000 + Math.random() * 500));
const lastUserMessage = chatHistory[chatHistory.length - 1]?.content || '';
// 智能回复逻辑
let response = '';
if (lastUserMessage.includes('步骤') || lastUserMessage.includes('详细')) {
response = '我来为您详细解释每个步骤：\n\n1. **第一步**：仔细阅读题目，理解题意\n2. **第二步**：确定已知条件和求解目标\n3. **第三步**：选择合适的公式或方法\n4. **第四步**：代入数值进行计算\n5. **第五步**：检查答案的合理性\n\n您希望我详细解释哪个步骤？';
} else if (lastUserMessage.includes('为什么') || lastUserMessage.includes('原理')) {
response = '关于您提到的原理问题：\n\n这个方法的理论基础是...\n\n**核心思想**：\n- 利用数学/物理的基本定律\n- 通过逻辑推理得出结论\n- 验证结果的正确性\n\n您还想了解哪方面的原理？';
} else if (lastUserMessage.includes('例题') || lastUserMessage.includes('练习')) {
response = '我为您推荐一些类似的练习题：\n\n**基础练习**：\n1. 类似题型的简化版本\n2. 相同方法的不同应用\n\n**进阶练习**：\n1. 综合性更强的题目\n2. 需要多种方法结合的问题\n\n您希望我提供具体的练习题吗？';
} else {
response = `我理解您的问题。让我从另一个角度来解释：\n\n${lastUserMessage.includes('不懂') ? '看起来您对某个概念还不太清楚，' : ''}基于您的问题，我建议：\n\n1. 回顾相关的基础知识\n2. 多做类似的练习题\n3. 总结解题规律\n\n您还有什么具体的疑问吗？`;
}
return { new_assistant_message: response };
}
static async saveToLibrary(tempId: string, chatHistory: ChatMessage[]): Promise<{ success: boolean; mistake_item: MistakeItem }> {
const tempSession = DataManager.getTempSession(tempId);
if (!tempSession) {
throw new Error('临时会话不存在');
}
const mistakeItem: MistakeItem = {
id: 'mistake-' + Date.now() + '-' + Math.random().toString(36).substr(2, 9),
subject: tempSession.request.subject,
created_at: new Date().toISOString(),
question_images: [], // 在实际应用中这里会是图片路径
analysis_images: [],
user_question: tempSession.request.user_question,
ocr_text: tempSession.response.initial_data.ocr_text,
tags: tempSession.response.initial_data.tags,
mistake_type: tempSession.response.initial_data.mistake_type,
status: 'completed',
chat_history: chatHistory
};
const success = DataManager.saveMistake(mistakeItem);
if (success) {
DataManager.deleteTempSession(tempId);
}
return { success, mistake_item: mistakeItem };
}
static async reviewAnalysis(mistakeIds: string[]): Promise<string> {
// 模拟网络延迟
await new Promise(resolve => setTimeout(resolve, 3000));
const mistakes = mistakeIds.map(id => DataManager.getMistakeById(id)).filter(Boolean) as MistakeItem[];
if (mistakes.length === 0) {
throw new Error('没有找到有效的错题');
}
const subjects = [...new Set(mistakes.map(m => m.subject))];
const tags = [...new Set(mistakes.flatMap(m => m.tags))];
const types = [...new Set(mistakes.map(m => m.mistake_type))];
return `## 📊 回顾分析报告
### 📈 整体概况
- **分析题目数量**: ${mistakes.length} 道
- **涉及科目**: ${subjects.join('、')}
- **题目类型**: ${types.join('、')}
- **主要知识点**: ${tags.slice(0, 5).join('、')}
### 🔍 关联分析
通过对您选择的 ${mistakes.length} 道错题进行深入分析，我发现了以下关联模式：
**1. 知识点关联**
${subjects.includes('数学') ? `
- 二次函数相关问题占比较高，涉及最值、图像、交点等多个方面
- 这些问题都围绕二次函数的基本性质展开，说明您需要加强对二次函数整体概念的理解
` : ''}
**2. 解题方法关联**
- 多道题目都涉及到基础运算和概念理解
- 建议加强基础知识的掌握和解题方法的练习
### ⚠️ 易错点分析
根据您的错题模式，识别出以下易错点：
**1. 概念理解不够深入**
- 对基本概念的理解还需要加强
- 建议：系统复习相关概念，理解其本质含义
**2. 计算准确性有待提高**
- 在计算过程中容易出错
- 建议：加强基础运算练习，注意计算步骤的规范性
**3. 方法选择不够灵活**
- 对不同题型的解题方法掌握不够熟练
- 建议：多做不同类型的题目，总结解题规律
### 📚 复习建议
1. **系统复习基础知识**，确保概念理解准确
2. **加强计算训练**，提高计算准确性和速度
3. **多做综合性题目**，培养知识点之间的联系思维
4. **重视错题回顾**，定期复习已做错的题目
### 🎯 下一步学习重点
- 重点复习出现频率高的知识点
- 加强薄弱环节的专项训练
- 培养良好的解题习惯
- 建立完整的知识体系
希望这个分析对您的学习有所帮助！如有疑问，请随时提问。`;
}
}
export default DataManager;
|
000haoji/deep-student
| 10,969 |
src/utils/unifiedStreamManager.ts
|
/**
* 统一流式处理管理器
*
* 替代项目中的多种流式处理实现，提供统一、一致的流式数据处理方案
* 支持所有现有的流式场景：分析、对话、回顾分析等
*/
import { listen } from '@tauri-apps/api/event';
import React from 'react';
export interface StreamChunk {
content: string;
is_complete: boolean;
chunk_id: string;
}
export interface StreamMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp: string;
}
export interface StreamOptions {
enableChainOfThought?: boolean;
onChunk?: (chunk: string) => void;
onThinking?: (thinking: string) => void;
onComplete?: (fullResponse: string, thinkingContent?: string) => void;
onError?: (error: string) => void;
onProgress?: (progress: { content: string; thinking?: string }) => void;
}
export interface StreamRequest {
type: 'analysis' | 'chat' | 'continue_chat' | 'review_analysis' | 'review_chat';
tempId?: string;
mistakeId?: string;
reviewId?: string;
imageData?: string[];
userInput?: string;
chatHistory?: StreamMessage[];
subject?: string;
enableChainOfThought?: boolean;
}
export interface StreamState {
isStreaming: boolean;
content: string;
thinking: string;
error?: string;
}
/**
* 统一流式处理管理器
* 集中管理所有流式监听器，避免内存泄漏
*/
export class UnifiedStreamManager {
private activeListeners: Map<string, () => void> = new Map();
private streamStates: Map<string, StreamState> = new Map();
/**
* 开始流式处理
*/
async startStream(
streamId: string,
eventName: string,
options: StreamOptions = {}
): Promise<void> {
console.log(`🚀 开始流式处理 [${streamId}]: ${eventName}`);
// 清理现有的流
this.stopStream(streamId);
// 初始化流状态
this.streamStates.set(streamId, {
isStreaming: true,
content: '',
thinking: ''
});
let fullContent = '';
let fullThinking = '';
let contentListenerActive = true;
let thinkingListenerActive = true;
try {
// 监听主内容流
const unlistenContent = await listen(eventName, (event: any) => {
if (!contentListenerActive) return;
const payload = event.payload;
console.log(`💬 收到流式内容 [${streamId}]:`, payload);
if (payload) {
// 检查是否完成
if (payload.is_complete) {
console.log(`🎉 流式内容完成 [${streamId}]，总长度: ${fullContent.length}`);
contentListenerActive = false;
unlistenContent();
// 如果思维链监听器也不活跃了，则设置整体完成状态
if (!thinkingListenerActive) {
this.completeStream(streamId, fullContent, fullThinking, options);
}
return;
}
// 累积内容
if (payload.content) {
fullContent += payload.content;
// 更新状态
const state = this.streamStates.get(streamId);
if (state) {
state.content = fullContent;
this.streamStates.set(streamId, state);
}
// 触发回调
if (options.onChunk) {
options.onChunk(payload.content);
}
if (options.onProgress) {
options.onProgress({ content: fullContent, thinking: fullThinking || undefined });
}
console.log(`📝 累积内容长度 [${streamId}]: ${fullContent.length} 字符`);
}
}
});
this.activeListeners.set(`${streamId}_content`, unlistenContent);
// 如果启用思维链，监听思维链事件
if (options.enableChainOfThought) {
const reasoningEvent = `${eventName}_reasoning`;
console.log(`🧠 监听思维链事件 [${streamId}]: ${reasoningEvent}`);
const unlistenThinking = await listen(reasoningEvent, (event: any) => {
if (!thinkingListenerActive) return;
const payload = event.payload;
console.log(`🧠 思维链内容 [${streamId}]:`, payload);
if (payload) {
// 检查是否完成
if (payload.is_complete) {
console.log(`🎉 思维链完成 [${streamId}]，总长度: ${fullThinking.length}`);
thinkingListenerActive = false;
unlistenThinking();
// 如果主内容监听器也不活跃了，则设置整体完成状态
if (!contentListenerActive) {
this.completeStream(streamId, fullContent, fullThinking, options);
}
return;
}
// 累积思维链内容
if (payload.content) {
fullThinking += payload.content;
// 更新状态
const state = this.streamStates.get(streamId);
if (state) {
state.thinking = fullThinking;
this.streamStates.set(streamId, state);
}
// 触发回调
if (options.onThinking) {
options.onThinking(payload.content);
}
if (options.onProgress) {
options.onProgress({ content: fullContent, thinking: fullThinking || undefined });
}
console.log(`🧠 思维链累积长度 [${streamId}]: ${fullThinking.length} 字符`);
}
}
});
this.activeListeners.set(`${streamId}_thinking`, unlistenThinking);
} else {
// 如果没有启用思维链，标记思维链监听器为不活跃
thinkingListenerActive = false;
}
} catch (error) {
console.error(`❌ 流式处理启动失败 [${streamId}]:`, error);
this.handleStreamError(streamId, error as string, options);
}
}
/**
* 停止指定流
*/
stopStream(streamId: string): void {
console.log(`🛑 停止流式处理 [${streamId}]`);
// 清理内容监听器
const contentListener = this.activeListeners.get(`${streamId}_content`);
if (contentListener) {
contentListener();
this.activeListeners.delete(`${streamId}_content`);
}
// 清理思维链监听器
const thinkingListener = this.activeListeners.get(`${streamId}_thinking`);
if (thinkingListener) {
thinkingListener();
this.activeListeners.delete(`${streamId}_thinking`);
}
// 清理状态
this.streamStates.delete(streamId);
}
/**
* 停止所有流
*/
stopAllStreams(): void {
console.log(`🧹 清理所有流式处理，共 ${this.activeListeners.size} 个监听器`);
for (const [key, unlisten] of this.activeListeners) {
try {
unlisten();
} catch (error) {
console.warn(`清理监听器失败 [${key}]:`, error);
}
}
this.activeListeners.clear();
this.streamStates.clear();
}
/**
* 获取流状态
*/
getStreamState(streamId: string): StreamState | undefined {
return this.streamStates.get(streamId);
}
/**
* 检查流是否活跃
*/
isStreamActive(streamId: string): boolean {
const state = this.streamStates.get(streamId);
return state?.isStreaming || false;
}
/**
* 完成流处理
*/
private completeStream(
streamId: string,
content: string,
thinking: string,
options: StreamOptions
): void {
console.log(`🎉 流式处理完成 [${streamId}]`);
// 更新状态
const state = this.streamStates.get(streamId);
if (state) {
state.isStreaming = false;
this.streamStates.set(streamId, state);
}
// 触发完成回调
if (options.onComplete) {
options.onComplete(content, thinking || undefined);
}
// 延迟清理（给UI一些时间更新）
setTimeout(() => {
this.stopStream(streamId);
}, 100);
}
/**
* 处理流错误
*/
private handleStreamError(
streamId: string,
error: string,
options: StreamOptions
): void {
console.error(`❌ 流式处理错误 [${streamId}]:`, error);
// 更新状态
const state = this.streamStates.get(streamId);
if (state) {
state.isStreaming = false;
state.error = error;
this.streamStates.set(streamId, state);
}
// 触发错误回调
if (options.onError) {
options.onError(error);
}
// 清理流
this.stopStream(streamId);
}
}
// 创建全局实例
export const unifiedStreamManager = new UnifiedStreamManager();
/**
* React Hook for unified streaming
* 提供React组件使用的统一流式处理Hook
*/
export function useUnifiedStream() {
const [activeStreams, setActiveStreams] = React.useState<Set<string>>(new Set());
const [streamStates, setStreamStates] = React.useState<Map<string, StreamState>>(new Map());
// 组件卸载时清理所有流
React.useEffect(() => {
return () => {
console.log('🧹 组件卸载，清理所有流式处理');
unifiedStreamManager.stopAllStreams();
};
}, []);
const startStream = React.useCallback(async (
streamId: string,
eventName: string,
options: StreamOptions = {}
) => {
setActiveStreams(prev => new Set(prev.add(streamId)));
const enhancedOptions: StreamOptions = {
...options,
onProgress: (progress) => {
setStreamStates(prev => new Map(prev.set(streamId, {
isStreaming: true,
content: progress.content,
thinking: progress.thinking || ''
})));
if (options.onProgress) {
options.onProgress(progress);
}
},
onComplete: (content, thinking) => {
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
setStreamStates(prev => new Map(prev.set(streamId, {
isStreaming: false,
content,
thinking: thinking || ''
})));
if (options.onComplete) {
options.onComplete(content, thinking);
}
},
onError: (error) => {
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
setStreamStates(prev => new Map(prev.set(streamId, {
isStreaming: false,
content: '',
thinking: '',
error
})));
if (options.onError) {
options.onError(error);
}
}
};
await unifiedStreamManager.startStream(streamId, eventName, enhancedOptions);
}, []);
const stopStream = React.useCallback((streamId: string) => {
unifiedStreamManager.stopStream(streamId);
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
setStreamStates(prev => {
const newMap = new Map(prev);
newMap.delete(streamId);
return newMap;
});
}, []);
const stopAllStreams = React.useCallback(() => {
unifiedStreamManager.stopAllStreams();
setActiveStreams(new Set());
setStreamStates(new Map());
}, []);
const isStreamActive = React.useCallback((streamId: string) => {
return activeStreams.has(streamId);
}, [activeStreams]);
const getStreamState = React.useCallback((streamId: string) => {
return streamStates.get(streamId);
}, [streamStates]);
return {
startStream,
stopStream,
stopAllStreams,
isStreamActive,
getStreamState,
activeStreams: Array.from(activeStreams),
streamStates
};
}
|
000haoji/deep-student
| 6,043 |
src/utils/tauriStreamAdapter.ts
|
/**
* Tauri Stream Adapter
*
* Focused adapter for converting Tauri backend streaming to standard streaming protocols.
* Single responsibility: Stream protocol conversion.
*/
import { invoke } from '@tauri-apps/api/core';
import { listen } from '@tauri-apps/api/event';
export interface StreamControllerManager {
controller: ReadableStreamDefaultController;
listeners: Array<() => void>;
responseStarted: boolean;
}
/**
* Create a streaming response for Tauri analysis requests
*/
export async function createAnalysisStream(
imageData: string,
userInput: string,
enableChainOfThought: boolean = true
): Promise<Response> {
const stream = new ReadableStream({
start(controller) {
const manager: StreamControllerManager = {
controller,
listeners: [],
responseStarted: false
};
handleAnalysisStream(imageData, userInput, enableChainOfThought, manager);
return () => {
manager.listeners.forEach(cleanup => cleanup());
};
}
});
return new Response(stream, {
headers: {
'Content-Type': 'text/plain; charset=utf-8',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive'
}
});
}
/**
* Create a streaming response for Tauri chat requests
*/
export async function createChatStream(
tempId: string,
chatHistory: any[],
enableChainOfThought: boolean = true
): Promise<Response> {
const stream = new ReadableStream({
start(controller) {
const manager: StreamControllerManager = {
controller,
listeners: [],
responseStarted: false
};
handleChatStream(tempId, chatHistory, enableChainOfThought, manager);
return () => {
manager.listeners.forEach(cleanup => cleanup());
};
}
});
return new Response(stream, {
headers: {
'Content-Type': 'text/plain; charset=utf-8',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive'
}
});
}
/**
* Handle analysis streaming events
*/
async function handleAnalysisStream(
imageData: string,
userInput: string,
enableChainOfThought: boolean,
manager: StreamControllerManager
): Promise<void> {
try {
// Set up event listeners
const unlistenContent = await listen('stream_chunk', (event: any) => {
const chunk = formatStreamChunk(event.payload.content);
manager.controller.enqueue(new TextEncoder().encode(chunk));
});
const unlistenThinking = enableChainOfThought
? await listen('stream_thinking', (event: any) => {
const chunk = formatThinkingChunk(event.payload.thinking);
manager.controller.enqueue(new TextEncoder().encode(chunk));
})
: null;
const unlistenComplete = await listen('stream_complete', () => {
finishStream(manager.controller);
});
const unlistenError = await listen('stream_error', (event: any) => {
manager.controller.error(new Error(event.payload.error));
});
// Store cleanup functions
manager.listeners.push(unlistenContent, unlistenComplete, unlistenError);
if (unlistenThinking) {
manager.listeners.push(unlistenThinking);
}
// Start the backend analysis
const base64Data = formatImageData(imageData);
await invoke('analyze_step_by_step', {
request: {
subject: "数学",
question_image_files: [base64Data],
analysis_image_files: [],
user_question: userInput,
enable_chain_of_thought: enableChainOfThought
}
});
} catch (error) {
manager.controller.error(error);
}
}
/**
* Handle chat streaming events
*/
async function handleChatStream(
tempId: string,
chatHistory: any[],
enableChainOfThought: boolean,
manager: StreamControllerManager
): Promise<void> {
try {
// Set up event listeners
const unlistenContent = await listen('stream_chunk', (event: any) => {
const chunk = formatStreamChunk(event.payload.content);
manager.controller.enqueue(new TextEncoder().encode(chunk));
});
const unlistenThinking = enableChainOfThought
? await listen('stream_thinking', (event: any) => {
const chunk = formatThinkingChunk(event.payload.thinking);
manager.controller.enqueue(new TextEncoder().encode(chunk));
})
: null;
const unlistenComplete = await listen('stream_complete', () => {
finishStream(manager.controller);
});
const unlistenError = await listen('stream_error', (event: any) => {
manager.controller.error(new Error(event.payload.error));
});
// Store cleanup functions
manager.listeners.push(unlistenContent, unlistenComplete, unlistenError);
if (unlistenThinking) {
manager.listeners.push(unlistenThinking);
}
// Start the chat stream
await invoke('continue_chat_stream', {
request: {
temp_id: tempId,
chat_history: chatHistory,
enable_chain_of_thought: enableChainOfThought
}
});
} catch (error) {
manager.controller.error(error);
}
}
/**
* Format streaming content chunk
*/
function formatStreamChunk(content: string): string {
return `data: ${JSON.stringify({
choices: [{
delta: {
content: content
}
}]
})}\n\n`;
}
/**
* Format thinking chain chunk
*/
function formatThinkingChunk(thinking: string): string {
return `data: ${JSON.stringify({
choices: [{
delta: {
thinking: thinking
}
}]
})}\n\n`;
}
/**
* Finish the stream
*/
function finishStream(controller: ReadableStreamDefaultController): void {
const finishChunk = `data: ${JSON.stringify({
choices: [{
finish_reason: 'stop'
}]
})}\n\n`;
controller.enqueue(new TextEncoder().encode(finishChunk));
controller.enqueue(new TextEncoder().encode('data: [DONE]\n\n'));
controller.close();
}
/**
* Format image data for backend
*/
function formatImageData(imageData: string): string {
return imageData.startsWith('data:') ? imageData : `data:image/jpeg;base64,${imageData}`;
}
|
000haoji/deep-student
| 13,011 |
src/utils/unifiedStreamHandler.ts
|
/**
* Unified Streaming Handler
*
* Consolidates all streaming approaches in the project into a single,
* consistent implementation that can be used across all components.
*/
import { listen } from '@tauri-apps/api/event';
import { invoke } from '@tauri-apps/api/core';
export interface StreamChunk {
content: string;
is_complete: boolean;
chunk_id: string;
}
export interface StreamMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp: string;
}
export interface StreamOptions {
enableChainOfThought?: boolean;
onChunk?: (chunk: string) => void;
onThinking?: (thinking: string) => void;
onComplete?: (fullResponse: string, thinkingContent?: string) => void;
onError?: (error: string) => void;
onProgress?: (progress: { content: string; thinking?: string }) => void;
}
export interface StreamRequest {
type: 'analysis' | 'chat' | 'continue_chat';
tempId?: string;
mistakeId?: number;
imageData?: string;
userInput?: string;
chatHistory?: StreamMessage[];
enableChainOfThought?: boolean;
}
/**
* Unified Streaming Manager
* Replaces multiple streaming implementations with a single, consistent approach
*/
export class UnifiedStreamHandler {
private activeStreams: Map<string, () => void> = new Map();
private currentProgress: Map<string, { content: string; thinking: string }> = new Map();
/**
* Start a streaming request with unified handling
*/
async startStream(request: StreamRequest, options: StreamOptions = {}): Promise<string> {
const streamId = this.generateStreamId(request);
// Stop any existing stream with the same ID
this.stopStream(streamId);
try {
const cleanupFunctions = await this.initializeStreamListeners(streamId, request, options);
this.activeStreams.set(streamId, () => {
cleanupFunctions.forEach(cleanup => cleanup());
});
// Start the appropriate backend command
await this.startBackendStream(request);
return streamId;
} catch (error) {
console.error('Failed to start stream:', error);
if (options.onError) {
options.onError(error instanceof Error ? error.message : 'Unknown error');
}
throw error;
}
}
/**
* Stop a specific stream
*/
stopStream(streamId: string): void {
const cleanup = this.activeStreams.get(streamId);
if (cleanup) {
cleanup();
this.activeStreams.delete(streamId);
this.currentProgress.delete(streamId);
console.log(`Stopped stream: ${streamId}`);
}
}
/**
* Stop all active streams
*/
stopAllStreams(): void {
for (const streamId of this.activeStreams.keys()) {
this.stopStream(streamId);
}
}
/**
* Get current progress for a stream
*/
getProgress(streamId: string): { content: string; thinking: string } | null {
return this.currentProgress.get(streamId) || null;
}
/**
* Check if a stream is active
*/
isStreamActive(streamId: string): boolean {
return this.activeStreams.has(streamId);
}
private generateStreamId(request: StreamRequest): string {
const timestamp = Date.now();
const type = request.type;
const id = request.tempId || request.mistakeId || 'default';
return `${type}_${id}_${timestamp}`;
}
private async initializeStreamListeners(
streamId: string,
request: StreamRequest,
options: StreamOptions
): Promise<Array<() => void>> {
const cleanupFunctions: Array<() => void> = [];
let fullContent = '';
let fullThinking = '';
// Initialize progress tracking
this.currentProgress.set(streamId, { content: '', thinking: '' });
// Determine event names based on request type
const baseEventName = this.getEventName(request);
const contentEvent = baseEventName;
const thinkingEvent = `${baseEventName}_reasoning`;
console.log(`🔄 Initializing unified stream listeners for: ${streamId}`);
console.log(`📡 Content event: ${contentEvent}`);
console.log(`🧠 Thinking event: ${thinkingEvent}`);
// Listen for main content stream
try {
const unlistenContent = await listen<StreamChunk>(contentEvent, (event) => {
const chunk = event.payload;
if (chunk.is_complete) {
console.log(`✅ Content stream complete for ${streamId}`);
this.checkStreamCompletion(streamId, fullContent, fullThinking, options);
return;
}
if (chunk.content) {
fullContent += chunk.content;
// Update progress
const progress = this.currentProgress.get(streamId);
if (progress) {
progress.content = fullContent;
this.currentProgress.set(streamId, progress);
}
// Call callbacks
if (options.onChunk) {
options.onChunk(chunk.content);
}
if (options.onProgress) {
options.onProgress({ content: fullContent, thinking: fullThinking || undefined });
}
console.log(`📝 Content update [${streamId}]: ${chunk.content.length} chars`);
}
});
cleanupFunctions.push(unlistenContent);
} catch (error) {
console.error(`Failed to listen for content events: ${contentEvent}`, error);
}
// Listen for thinking chain (if enabled)
if (request.enableChainOfThought !== false) {
try {
const unlistenThinking = await listen<StreamChunk>(thinkingEvent, (event) => {
const chunk = event.payload;
if (chunk.is_complete) {
console.log(`✅ Thinking stream complete for ${streamId}`);
this.checkStreamCompletion(streamId, fullContent, fullThinking, options);
return;
}
if (chunk.content) {
fullThinking += chunk.content;
// Update progress
const progress = this.currentProgress.get(streamId);
if (progress) {
progress.thinking = fullThinking;
this.currentProgress.set(streamId, progress);
}
// Call callbacks
if (options.onThinking) {
options.onThinking(chunk.content);
}
if (options.onProgress) {
options.onProgress({ content: fullContent, thinking: fullThinking || undefined });
}
console.log(`🧠 Thinking update [${streamId}]: ${chunk.content.length} chars`);
}
});
cleanupFunctions.push(unlistenThinking);
} catch (error) {
console.error(`Failed to listen for thinking events: ${thinkingEvent}`, error);
}
}
// Listen for errors
try {
const unlistenError = await listen<{error: string}>('stream_error', (event) => {
console.error(`❌ Stream error [${streamId}]:`, event.payload.error);
if (options.onError) {
options.onError(event.payload.error);
}
this.stopStream(streamId);
});
cleanupFunctions.push(unlistenError);
} catch (error) {
console.error('Failed to listen for error events', error);
}
return cleanupFunctions;
}
private checkStreamCompletion(
streamId: string,
content: string,
thinking: string,
options: StreamOptions
): void {
// Check if both content and thinking (if enabled) are complete
const progress = this.currentProgress.get(streamId);
if (!progress) return;
console.log(`🎉 Stream completion check [${streamId}]: content=${content.length}, thinking=${thinking.length}`);
if (options.onComplete) {
options.onComplete(content, thinking || "");
}
// Auto-cleanup after completion
setTimeout(() => {
this.stopStream(streamId);
}, 100);
}
private getEventName(request: StreamRequest): string {
switch (request.type) {
case 'analysis':
return request.tempId ? `analysis_stream_${request.tempId}` : 'stream_chunk';
case 'chat':
return 'stream_chunk';
case 'continue_chat':
return request.tempId ? `continue_chat_stream_${request.tempId}` : 'stream_chunk';
default:
return 'stream_chunk';
}
}
private async startBackendStream(request: StreamRequest): Promise<void> {
switch (request.type) {
case 'analysis':
if (!request.imageData || !request.userInput) {
throw new Error('Analysis requires imageData and userInput');
}
// First do OCR analysis
const analysisResponse = await invoke('analyze_step_by_step', {
request: {
subject: "数学",
question_image_files: [request.imageData.startsWith('data:') ? request.imageData : `data:image/jpeg;base64,${request.imageData}`],
analysis_image_files: [],
user_question: request.userInput,
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
// If we got a temp_id, start the streaming answer
if ((analysisResponse as any)?.temp_id) {
await invoke('start_streaming_answer', {
request: {
temp_id: (analysisResponse as any).temp_id,
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
}
break;
case 'chat':
await invoke('start_streaming_answer', {
request: {
chat_history: request.chatHistory?.map(msg => ({
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content
})) || [],
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
break;
case 'continue_chat':
if (!request.tempId) {
throw new Error('Continue chat requires tempId');
}
await invoke('continue_chat_stream', {
request: {
temp_id: request.tempId,
chat_history: request.chatHistory?.map(msg => ({
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content
})) || [],
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
break;
default:
throw new Error(`Unsupported stream type: ${request.type}`);
}
}
}
// Create global instance
export const unifiedStreamHandler = new UnifiedStreamHandler();
/**
* React Hook for Unified Streaming
* Provides a simple interface for React components to use unified streaming
*/
export function useUnifiedStream() {
const [activeStreams, setActiveStreams] = React.useState<Set<string>>(new Set());
const [streamProgress, setStreamProgress] = React.useState<Map<string, { content: string; thinking: string }>>(new Map());
React.useEffect(() => {
return () => {
// Cleanup all streams when component unmounts
unifiedStreamHandler.stopAllStreams();
};
}, []);
const startStream = React.useCallback(async (request: StreamRequest, options: StreamOptions = {}) => {
const streamId = await unifiedStreamHandler.startStream(request, {
...options,
onProgress: (progress) => {
setStreamProgress(prev => new Map(prev.set(streamId, { content: progress.content, thinking: progress.thinking || "" })));
if (options.onProgress) {
options.onProgress(progress);
}
},
onComplete: (content, thinking) => {
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
if (options.onComplete) {
options.onComplete(content, thinking);
}
},
onError: (error) => {
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
if (options.onError) {
options.onError(error);
}
}
});
setActiveStreams(prev => new Set(prev.add(streamId)));
return streamId;
}, []);
const stopStream = React.useCallback((streamId: string) => {
unifiedStreamHandler.stopStream(streamId);
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
setStreamProgress(prev => {
const newMap = new Map(prev);
newMap.delete(streamId);
return newMap;
});
}, []);
const stopAllStreams = React.useCallback(() => {
unifiedStreamHandler.stopAllStreams();
setActiveStreams(new Set());
setStreamProgress(new Map());
}, []);
return {
startStream,
stopStream,
stopAllStreams,
activeStreams: Array.from(activeStreams),
streamProgress: Object.fromEntries(streamProgress),
isStreaming: activeStreams.size > 0
};
}
// Add React import for the hook
import React from 'react';
|
000haoji/deep-student
| 2,908 |
src/utils/tauriApiClient.ts
|
/**
* Tauri API Client
*
* Simple client for direct Tauri API calls without streaming.
* Single responsibility: Non-streaming API communication.
*/
import { invoke } from '@tauri-apps/api/core';
export interface ChatMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp?: string;
}
export interface AnalysisRequest {
subject?: string;
question_image_files: string[];
analysis_image_files?: string[];
user_question: string;
enable_chain_of_thought?: boolean;
}
/**
* Tauri API Client - provides direct access to backend commands
*/
export class TauriApiClient {
/**
* Perform step-by-step analysis
*/
async analyzeStepByStep(request: AnalysisRequest): Promise<any> {
return invoke('analyze_step_by_step', { request });
}
/**
* Start streaming answer for existing analysis
*/
async startStreamingAnswer(tempId: string, enableChainOfThought: boolean = true): Promise<any> {
return invoke('start_streaming_answer', {
request: {
temp_id: tempId,
enable_chain_of_thought: enableChainOfThought
}
});
}
/**
* Continue chat stream
*/
async continueChatStream(tempId: string, chatHistory: any[], enableChainOfThought: boolean = true): Promise<any> {
return invoke('continue_chat_stream', {
request: {
temp_id: tempId,
chat_history: chatHistory,
enable_chain_of_thought: enableChainOfThought
}
});
}
/**
* Get chat history for a mistake
*/
async getMistakeChatHistory(mistakeId: number): Promise<any> {
return invoke('get_mistake_chat_history', { mistakeId });
}
/**
* Get all mistakes
*/
async getAllMistakes(): Promise<any> {
return invoke('get_all_mistakes');
}
/**
* Get mistake by ID
*/
async getMistakeById(id: number): Promise<any> {
return invoke('get_mistake_by_id', { id });
}
/**
* Save mistake
*/
async saveMistake(mistake: any): Promise<any> {
return invoke('save_mistake', { mistake });
}
/**
* Delete mistake
*/
async deleteMistake(id: number): Promise<any> {
return invoke('delete_mistake', { id });
}
/**
* Batch save mistakes
*/
async batchSaveMistakes(mistakes: any[]): Promise<any> {
return invoke('batch_save_mistakes', { mistakes });
}
/**
* Batch delete mistakes
*/
async batchDeleteMistakes(ids: number[]): Promise<any> {
return invoke('batch_delete_mistakes', { ids });
}
/**
* Get supported subjects
*/
async getSupportedSubjects(): Promise<string[]> {
return invoke('get_supported_subjects');
}
/**
* Get subject configs
*/
async getSubjectConfigs(): Promise<any[]> {
return invoke('get_all_subject_configs', { active_only: true });
}
}
/**
* Default client instance
*/
export const tauriApiClient = new TauriApiClient();
|
000haoji/deep-student
| 23,133 |
src/data/ankiTemplates.ts
|
import { AnkiCardTemplate, CustomAnkiTemplate, FieldExtractionRule, FieldType } from '../types';
// 将预置模板转换为CustomAnkiTemplate格式，实现统一管理
const createBuiltInTemplate = (template: AnkiCardTemplate): CustomAnkiTemplate => {
// 生成字段提取规则
const fieldExtractionRules: Record<string, FieldExtractionRule> = {};
template.fields.forEach(field => {
const fieldLower = field.toLowerCase();
// 根据字段名称和模板类型确定字段属性
let isRequired = false;
let fieldType: FieldType = 'Text';
let defaultValue = '';
// 必需字段判断
if (['front', 'back', 'text'].includes(fieldLower)) {
isRequired = true;
}
// 字段类型判断
if (fieldLower === 'tags') {
fieldType = 'Array';
defaultValue = '[]';
}
// 填空题特殊字段
if (template.id === 'cloze-card') {
if (fieldLower === 'text') {
isRequired = true;
defaultValue = '';
}
}
// 选择题特殊字段
if (template.id === 'choice-card') {
if (['front', 'optiona', 'optionb', 'optionc', 'optiond', 'correct', 'explanation'].includes(fieldLower)) {
isRequired = true;
}
}
fieldExtractionRules[field] = {
field_type: fieldType,
is_required: isRequired,
default_value: defaultValue,
description: `${field} 字段`
};
});
return {
id: template.id,
name: template.name,
description: template.description,
author: '系统内置',
version: '1.0.0',
preview_front: template.preview_front,
preview_back: template.preview_back,
note_type: template.note_type,
fields: template.fields,
generation_prompt: template.generation_prompt,
front_template: template.front_template,
back_template: template.back_template,
css_style: template.css_style,
field_extraction_rules: fieldExtractionRules,
created_at: new Date().toISOString(),
updated_at: new Date().toISOString(),
is_active: true,
is_built_in: true
};
};
// 原始模板数据（用于兼容性）
export const LEGACY_ANKI_CARD_TEMPLATES: AnkiCardTemplate[] = [
{
id: 'minimal-card',
name: '极简卡片',
description: '简洁优雅的极简设计，专注内容展示',
preview_front: '什么是动量守恒定律？',
preview_back: '在没有外力作用的系统中，系统的总动量保持不变',
note_type: 'Basic',
fields: ['Front', 'Back', 'Notes', 'Tags'],
generation_prompt: `你是一个专业的ANKI卡片制作专家。请根据提供的学习材料生成极简风格的记忆卡片。
请按照以下格式生成卡片，每张卡片用JSON格式表示：
{
"Front": "简洁明了的问题或概念名称",
"Back": "准确、清晰的答案或解释",
"Notes": "可选的补充说明或注释，帮助理解记忆",
"Tags": ["相关标签"]
}
要求：
1. 问题简洁直接，便于快速理解
2. 答案准确完整，语言简练
3. 如果有重要的补充信息，可以添加到Notes字段
4. 每张卡片专注一个知识点
5. 适合反复记忆和复习
请根据内容的复杂度和知识点数量，生成适量的高质量记忆卡片。如果内容包含多个重要概念，应该为每个概念生成对应的卡片。`,
front_template: `
<div class="card minimal-card">
<div class="question">{{Front}}</div>
<div class="hint">点击显示答案</div>
</div>
`,
back_template: `
<div class="card minimal-card">
<div class="question">{{Front}}</div>
<div class="hint">点击显示答案</div>
<div class="answer">{{Back}}</div>
{{#Notes}}
<div class="notes">
<div class="notes-label">注释：</div>
<div>{{Notes}}</div>
</div>
{{/Notes}}
</div>
`,
css_style: `
.minimal-card {
font-family: 'Segoe UI', system-ui, sans-serif;
width: 100%;
max-width: 100%;
margin: 0;
padding: 20px;
border-radius: 16px;
background: white;
box-shadow: 0 5px 25px rgba(0,0,0,0.08);
text-align: center;
box-sizing: border-box;
overflow: hidden;
}
.question {
font-size: 20px;
font-weight: 600;
color: #2c3e50;
line-height: 1.4;
margin-bottom: 15px;
word-wrap: break-word;
}
.answer {
font-size: 16px;
color: #27ae60;
padding: 15px;
background: #f9fbfa;
border-radius: 12px;
margin: 20px 0;
border-left: 4px solid #2ecc71;
display: block;
word-wrap: break-word;
}
.hint {
font-size: 12px;
color: #95a5a6;
font-style: italic;
margin-bottom: 10px;
}
.notes {
text-align: left;
margin-top: 15px;
padding: 12px;
background: #f8f9fa;
border-radius: 10px;
font-size: 14px;
color: #7f8c8d;
word-wrap: break-word;
}
.notes-label {
font-weight: 600;
color: #3498db;
margin-bottom: 5px;
}
.card:hover {
box-shadow: 0 8px 30px rgba(0,0,0,0.12);
}
`
},
{
id: 'academic-card',
name: '学术卡片',
description: '正式的学术风格，适合专业知识和术语学习',
preview_front: 'DNA复制',
preview_back: 'DNA复制是一个半保留复制过程，包括解旋、引物合成、延伸等步骤',
note_type: 'Basic',
fields: ['Front', 'Back', 'Example', 'Source', 'Tags', 'Deck'],
generation_prompt: `你是一个专业的学术ANKI卡片制作专家。请根据提供的学习材料生成学术风格的记忆卡片。
请按照以下格式生成卡片，每张卡片用JSON格式表示：
{
"Front": "学术术语、概念或理论名称",
"Back": "详细、准确的学术定义和解释",
"Example": "具体的实例或应用场景（可选）",
"Source": "来源或参考资料信息（可选）",
"Tags": ["学科", "章节", "难度等标签"],
"Deck": "所属学科或课程（可选）"
}
要求：
1. 术语和概念要准确，符合学术标准
2. 定义要完整、严谨，使用规范的学术语言
3. 提供具体实例或应用场景有助于理解
4. 标注来源信息有助于后续查阅
5. 适合专业学习和考试复习
6. 重点关注概念的精确性和完整性
请根据内容的复杂度和知识点数量，生成适量的高质量学术记忆卡片。如果内容包含多个重要概念，应该为每个概念生成对应的卡片。`,
front_template: `
<div class="card academic-card">
<div class="header">
<div class="deck-name">{{Deck}}</div>
<div class="card-type">知识卡片</div>
</div>
<div class="question">{{Front}}</div>
</div>
`,
back_template: `
<div class="card academic-card">
<div class="header">
<div class="deck-name">{{Deck}}</div>
<div class="card-type">知识卡片</div>
</div>
<div class="question">{{Front}}</div>
<div class="divider"></div>
<div class="answer">
<div class="definition">{{Back}}</div>
{{#Example}}
<div class="example">
<div class="example-label">示例：</div>
<div class="example-content">{{Example}}</div>
</div>
{{/Example}}
</div>
<div class="footer">
<div class="source">{{Source}}</div>
<div class="tags">{{Tags}}</div>
</div>
</div>
`,
css_style: `
.academic-card {
font-family: 'Georgia', serif;
width: 100%;
max-width: 100%;
margin: 0;
padding: 20px;
background: #fcfaf7;
border: 1px solid #e6e2dd;
box-shadow: 0 3px 10px rgba(0,0,0,0.05);
box-sizing: border-box;
overflow: hidden;
}
.header {
display: flex;
justify-content: space-between;
margin-bottom: 15px;
font-size: 12px;
color: #95a5a6;
}
.question {
font-size: 20px;
font-weight: bold;
color: #2c3e50;
text-align: center;
margin: 15px 0 20px;
word-wrap: break-word;
}
.divider {
height: 1px;
background: linear-gradient(90deg, transparent, #bdc3c7, transparent);
margin: 10px 0 15px;
}
.definition {
font-size: 16px;
line-height: 1.6;
color: #34495e;
text-align: justify;
word-wrap: break-word;
}
.example {
margin-top: 15px;
padding: 12px;
background: #ffffff;
border-left: 3px solid #3498db;
border: 1px solid #3498db;
word-wrap: break-word;
color: #2c3e50;
font-size: 14px;
line-height: 1.5;
}
.example-label {
font-weight: bold;
color: #2980b9;
margin-bottom: 5px;
}
.footer {
display: flex;
justify-content: space-between;
margin-top: 20px;
font-size: 11px;
color: #7f8c8d;
flex-wrap: wrap;
}
.tag {
display: inline-block;
background: #ecf0f1;
padding: 2px 8px;
border-radius: 12px;
margin-left: 3px;
margin-bottom: 2px;
font-size: 10px;
}
`
},
{
id: 'code-card',
name: '编程卡片',
description: '专为编程学习设计的深色主题卡片',
preview_front: '如何在Python中创建列表？',
preview_back: 'my_list = [1, 2, 3, 4, 5]',
note_type: 'Basic',
fields: ['Front', 'Back', 'Code', 'Tags'],
generation_prompt: `你是一个专业的编程ANKI卡片制作专家。请根据提供的编程学习材料生成代码风格的记忆卡片。
请按照以下格式生成卡片，每张卡片用JSON格式表示：
{
"Front": "编程问题、概念或语法要点",
"Back": "详细的解释和说明",
"Code": "相关的代码示例（如果适用）",
"Tags": ["编程语言", "主题", "难度等标签"]
}
要求：
1. 问题要具体明确，针对实际编程场景
2. 解释要准确完整，包含关键概念和注意事项
3. 代码示例要简洁实用，可以直接运行
4. 代码格式规范，包含必要的注释
5. 适合程序员日常学习和面试复习
6. 重点关注实用性和可操作性
代码示例格式要求：
- 使用标准的编程语言语法
- 包含输入输出示例（如果适用）
- 添加简要注释说明关键步骤
请根据内容的复杂度和知识点数量，生成适量的高质量编程记忆卡片。如果内容包含多个重要概念或代码示例，应该为每个知识点生成对应的卡片。`,
front_template: `
<div class="card code-card">
<div class="question">{{Front}}</div>
<div class="hint">// 点击查看解决方案</div>
</div>
`,
back_template: `
<div class="card code-card">
<div class="question">{{Front}}</div>
<div class="hint">// 点击查看解决方案</div>
<div class="answer">
{{#Code}}
<pre><code>{{Code}}</code></pre>
{{/Code}}
<div class="explanation">{{Back}}</div>
</div>
</div>
`,
css_style: `
.code-card {
font-family: 'Fira Code', 'Consolas', monospace;
width: 100%;
max-width: 100%;
margin: 0;
padding: 20px;
background: #2d3748;
color: #cbd5e0;
border-radius: 8px;
box-shadow: 0 10px 25px rgba(0,0,0,0.3);
box-sizing: border-box;
overflow: hidden;
}
.question {
font-size: 16px;
line-height: 1.5;
color: #81e6d9;
margin-bottom: 15px;
word-wrap: break-word;
}
.hint {
text-align: center;
color: #718096;
font-style: italic;
margin-bottom: 15px;
font-size: 12px;
}
pre {
background: #1a202c;
padding: 15px;
border-radius: 6px;
overflow-x: auto;
border-left: 3px solid #63b3ed;
font-size: 12px;
line-height: 1.4;
word-wrap: break-word;
white-space: pre-wrap;
}
code {
color: #feb2b2;
word-wrap: break-word;
}
.explanation {
margin-top: 15px;
padding: 12px;
background: #4a5568;
border-radius: 6px;
font-size: 14px;
line-height: 1.6;
word-wrap: break-word;
}
`
},
{
id: 'cloze-card',
name: '填空题卡片',
description: '专为填空记忆设计，支持多个空格和提示信息',
preview_front: '牛顿第二定律的公式是 F = [...]，其中m表示[...]，a表示[...]',
preview_back: '牛顿第二定律的公式是 F = ma，其中m表示质量，a表示加速度',
note_type: 'Cloze',
fields: ['Text', 'Hint', 'Source', 'Tags'],
generation_prompt: `你是一个专业的ANKI填空题卡片制作专家。请根据提供的学习材料生成填空题风格的记忆卡片。
重要规则：为了在【一张卡片】上实现【多个挖空】，请务必将所有挖空标记的数字都设置为【1】。例如：{{c1::答案一}}...{{c1::答案二}}。
请按照以下格式生成卡片，每张卡片用JSON格式表示：
{
"Text": "包含填空标记的完整文本。所有挖空都必须使用 {{c1::答案}} 的格式。",
"Hint": "填空提示信息（可选）",
"Source": "知识来源或参考资料（可选）",
"Tags": ["相关标签"]
}
填空标记规则：
1. 【最重要】对于一张卡片上的所有挖空，【必须】全部使用 {{c1::...}} 格式，不要使用c2, c3...。这会确保所有挖空都在同一张卡片上。
2. 可以添加提示：{{c1::答案::提示}}
3. 确保填空内容是关键知识点
要求：
1. 选择文本中的关键概念、公式、定义作为填空内容
2. 填空应该有一定难度，能够测试理解程度
3. 文本要完整连贯，去掉填空后仍然语法正确
4. 适合主动回忆训练
请根据内容的复杂度和知识点数量，生成适量的高质量填空题记忆卡片。如果内容包含多个重要概念，应该为每个概念生成对应的卡片。`,
front_template: `
<div class="card cloze-card">
<div class="cloze-text">{{cloze:Text}}</div>
{{#Hint}}
<div class="hint-section">
<div class="hint-label">💡 提示：</div>
<div class="hint-content">{{Hint}}</div>
</div>
{{/Hint}}
</div>
`,
back_template: `
<div class="card cloze-card">
<div class="cloze-text">{{cloze:Text}}</div>
{{#Hint}}
<div class="hint-section">
<div class="hint-label">💡 提示：</div>
<div class="hint-content">{{Hint}}</div>
</div>
{{/Hint}}
<div class="complete-text">
<div class="complete-label">完整内容：</div>
<div class="complete-content">{{text:Text}}</div>
</div>
{{#Source}}
<div class="source-section">
<span class="source-label">📚 来源：</span>
<span class="source-content">{{Source}}</span>
</div>
{{/Source}}
</div>
`,
css_style: `
.cloze-card {
font-family: 'PingFang SC', 'Microsoft YaHei', sans-serif;
width: 100%;
max-width: 100%;
margin: 0;
padding: 24px;
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
border-radius: 12px;
box-shadow: 0 8px 32px rgba(102, 126, 234, 0.3);
box-sizing: border-box;
overflow: hidden;
position: relative;
}
.cloze-card::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: rgba(255, 255, 255, 0.1);
backdrop-filter: blur(10px);
border-radius: 12px;
z-index: -1;
}
.cloze-text {
font-size: 18px;
line-height: 1.6;
margin-bottom: 20px;
text-align: justify;
word-wrap: break-word;
}
.cloze {
background: #FFD700;
color: #2c3e50;
padding: 2px 8px;
border-radius: 6px;
font-weight: 600;
box-shadow: 0 2px 4px rgba(0,0,0,0.2);
}
.hint-section {
background: rgba(255, 255, 255, 0.2);
padding: 12px;
border-radius: 8px;
margin: 15px 0;
border-left: 4px solid #FFD700;
}
.hint-label {
font-weight: 600;
font-size: 14px;
margin-bottom: 5px;
color: #FFD700;
}
.hint-content {
font-size: 14px;
line-height: 1.4;
opacity: 0.9;
}
.complete-text {
background: rgba(255, 255, 255, 0.15);
padding: 15px;
border-radius: 8px;
margin-top: 20px;
border: 1px solid rgba(255, 255, 255, 0.3);
}
.complete-label {
font-weight: 600;
font-size: 14px;
margin-bottom: 8px;
color: #E8F4FD;
}
.complete-content {
font-size: 16px;
line-height: 1.5;
color: #F8F9FA;
}
.source-section {
margin-top: 15px;
padding-top: 10px;
border-top: 1px solid rgba(255, 255, 255, 0.3);
font-size: 12px;
opacity: 0.8;
}
.source-label {
font-weight: 600;
}
`
},
{
id: 'choice-card',
name: '选择题卡片',
description: '交互式选择题设计，支持多选项和解析说明',
preview_front: '下列哪个是牛顿第一定律的内容？',
preview_back: 'A. F=ma\nB. 作用力与反作用力\nC. 惯性定律 ✓\nD. 万有引力定律',
note_type: 'Basic',
fields: ['Front', 'Back', 'optiona', 'optionb', 'optionc', 'optiond', 'correct', 'explanation', 'Tags'],
generation_prompt: `你是一个专业的ANKI选择题卡片制作专家。请根据提供的学习材料生成选择题风格的记忆卡片。
请按照以下格式生成卡片，每张卡片用JSON格式表示：
{
"Front": "选择题题目",
"optiona": "选项A的内容",
"optionb": "选项B的内容",
"optionc": "选项C的内容",
"optiond": "选项D的内容",
"correct": "A",
"explanation": "答案解析和详细说明",
"tags": ["相关标签"]
}
要求：
1. 题目要清晰明确，针对核心知识点
2. 四个选项要有合理的干扰性，避免过于明显的错误选项
3. 正确答案用A、B、C、D中的一个字母表示
4. 解析要详细说明为什么这个选项正确，其他选项错在哪里
5. 选项长度尽量相近，避免明显的长短差异暴露答案
6. 适合检验理解程度和辨析能力
请根据内容的复杂度和知识点数量，生成适量的高质量选择题记忆卡片。特别注意：如果提供的内容本身就是选择题格式，请确保为每一道原有选择题都生成对应的卡片。`,
front_template: `
<div class="card choice-card">
<div class="question-section">
<div class="question-label">📝 题目</div>
<div class="question-text">{{Front}}</div>
</div>
<div class="options-section">
<div class="option">
<span class="option-label">A</span>
<span class="option-text">{{optiona}}</span>
</div>
<div class="option">
<span class="option-label">B</span>
<span class="option-text">{{optionb}}</span>
</div>
<div class="option">
<span class="option-label">C</span>
<span class="option-text">{{optionc}}</span>
</div>
<div class="option">
<span class="option-label">D</span>
<span class="option-text">{{optiond}}</span>
</div>
</div>
<div class="instruction">点击查看答案和解析</div>
</div>
`,
back_template: `
<div class="card choice-card">
<div class="question-section">
<div class="question-label">📝 题目</div>
<div class="question-text">{{Front}}</div>
</div>
<div class="options-section answered">
<div class="option">
<span class="option-label">A</span>
<span class="option-text">{{optiona}}</span>
</div>
<div class="option">
<span class="option-label">B</span>
<span class="option-text">{{optionb}}</span>
</div>
<div class="option">
<span class="option-label">C</span>
<span class="option-text">{{optionc}}</span>
</div>
<div class="option">
<span class="option-label">D</span>
<span class="option-text">{{optiond}}</span>
</div>
</div>
<div class="answer-section">
<div class="answer-label">✅ 正确答案：{{correct}}</div>
</div>
{{#explanation}}
<div class="explanation-section">
<div class="explanation-label">💡 解析</div>
<div class="explanation-text">{{explanation}}</div>
</div>
{{/explanation}}
</div>
`,
css_style: `
.choice-card {
font-family: 'PingFang SC', 'Microsoft YaHei', sans-serif;
width: 100%;
max-width: 100%;
margin: 0;
padding: 20px;
background: #f8fafc;
border: 2px solid #e2e8f0;
border-radius: 12px;
box-shadow: 0 4px 20px rgba(0,0,0,0.08);
box-sizing: border-box;
overflow: hidden;
}
.question-section {
margin-bottom: 20px;
}
.question-label {
font-size: 14px;
font-weight: 600;
color: #3b82f6;
margin-bottom: 8px;
}
.question-text {
font-size: 18px;
font-weight: 500;
color: #1e293b;
line-height: 1.6;
word-wrap: break-word;
}
.options-section {
margin-bottom: 20px;
}
.option {
display: flex;
align-items: center;
padding: 12px;
margin: 8px 0;
background: white;
border: 1px solid #e2e8f0;
border-radius: 8px;
transition: all 0.2s ease;
position: relative;
}
.option:hover {
border-color: #3b82f6;
box-shadow: 0 2px 8px rgba(59, 130, 246, 0.1);
}
.option-label {
display: inline-flex;
align-items: center;
justify-content: center;
width: 24px;
height: 24px;
background: #f1f5f9;
color: #475569;
border-radius: 50%;
font-weight: 600;
font-size: 14px;
margin-right: 12px;
flex-shrink: 0;
}
.option-text {
flex: 1;
font-size: 16px;
color: #334155;
line-height: 1.5;
word-wrap: break-word;
}
.option.correct {
background: #f0f9ff;
border-color: #22c55e;
}
.option.correct .option-label {
background: #22c55e;
color: white;
}
.correct-mark {
color: #22c55e;
font-weight: bold;
font-size: 18px;
margin-left: 8px;
}
.answer-section {
background: #dcfce7;
border: 1px solid #22c55e;
border-radius: 8px;
padding: 12px;
margin: 15px 0;
}
.answer-label {
font-weight: 600;
color: #15803d;
font-size: 16px;
}
.explanation-section {
background: #fffbeb;
border: 1px solid #f59e0b;
border-radius: 8px;
padding: 15px;
margin-top: 15px;
}
.explanation-label {
font-weight: 600;
color: #d97706;
margin-bottom: 8px;
font-size: 14px;
}
.explanation-text {
color: #92400e;
line-height: 1.6;
font-size: 14px;
word-wrap: break-word;
}
.instruction {
text-align: center;
color: #64748b;
font-style: italic;
font-size: 14px;
padding: 10px;
background: #f1f5f9;
border-radius: 6px;
}
`
}
];
// 统一的模板数据 - 将预置模板转换为CustomAnkiTemplate格式
export const BUILT_IN_TEMPLATES: CustomAnkiTemplate[] = LEGACY_ANKI_CARD_TEMPLATES.map(createBuiltInTemplate);
// 兼容性导出
export const ANKI_CARD_TEMPLATES = LEGACY_ANKI_CARD_TEMPLATES;
// 统一模板管理类
export class TemplateManager {
private customTemplates: CustomAnkiTemplate[] = [];
private listeners: Array<(templates: CustomAnkiTemplate[]) => void> = [];
private userDefaultTemplateId: string | null = null;
constructor() {
this.loadTemplates();
}
// 加载所有模板（内置 + 自定义）
async loadTemplates(): Promise<void> {
try {
// 动态导入Tauri API（避免SSR问题）
const { invoke } = await import('@tauri-apps/api/core');
// 并行加载自定义模板和默认模板设置
const [userTemplates, defaultTemplateId] = await Promise.all([
invoke<CustomAnkiTemplate[]>('get_all_custom_templates'),
invoke<string | null>('get_default_template_id').catch(() => null)
]);
// 合并内置模板和用户自定义模板
this.customTemplates = [...BUILT_IN_TEMPLATES, ...userTemplates];
this.userDefaultTemplateId = defaultTemplateId;
this.notifyListeners();
} catch (error) {
console.warn('Failed to load custom templates, using built-in only:', error);
this.customTemplates = [...BUILT_IN_TEMPLATES];
this.userDefaultTemplateId = null;
this.notifyListeners();
}
}
// 获取所有模板
getAllTemplates(): CustomAnkiTemplate[] {
return this.customTemplates;
}
// 获取活跃模板
getActiveTemplates(): CustomAnkiTemplate[] {
return this.customTemplates.filter(t => t.is_active);
}
// 根据ID获取模板
getTemplateById(id: string): CustomAnkiTemplate | undefined {
return this.customTemplates.find(template => template.id === id);
}
// 获取默认模板
getDefaultTemplate(): CustomAnkiTemplate {
// 如果用户设置了默认模板，优先使用用户设置的
if (this.userDefaultTemplateId) {
const userDefault = this.customTemplates.find(t => t.id === this.userDefaultTemplateId);
if (userDefault) {
return userDefault;
}
}
// 否则返回列表中的第一个模板
return this.customTemplates[0] || BUILT_IN_TEMPLATES[0];
}
// 将CustomAnkiTemplate转换为AnkiCardTemplate（向后兼容）
toAnkiCardTemplate(template: CustomAnkiTemplate): AnkiCardTemplate {
return {
id: template.id,
name: template.name,
description: template.description,
preview_front: template.preview_front,
preview_back: template.preview_back,
front_template: template.front_template,
back_template: template.back_template,
css_style: template.css_style,
note_type: template.note_type,
generation_prompt: template.generation_prompt,
fields: template.fields
};
}
// 订阅模板变化
subscribe(listener: (templates: CustomAnkiTemplate[]) => void): () => void {
this.listeners.push(listener);
return () => {
const index = this.listeners.indexOf(listener);
if (index > -1) {
this.listeners.splice(index, 1);
}
};
}
private notifyListeners(): void {
this.listeners.forEach(listener => listener(this.customTemplates));
}
// 刷新模板列表
async refresh(): Promise<void> {
await this.loadTemplates();
}
// 创建新模板
async createTemplate(templateData: any): Promise<string> {
const { invoke } = await import('@tauri-apps/api/core');
const templateId = await invoke<string>('create_custom_template', { request: templateData });
await this.loadTemplates(); // 重新加载
return templateId;
}
// 删除模板
async deleteTemplate(templateId: string): Promise<void> {
const { invoke } = await import('@tauri-apps/api/core');
await invoke('delete_custom_template', { templateId });
await this.loadTemplates(); // 重新加载
}
// 加载用户默认模板设置
async loadUserDefaultTemplate(): Promise<void> {
try {
const { invoke } = await import('@tauri-apps/api/core');
this.userDefaultTemplateId = await invoke<string | null>('get_default_template_id');
} catch (error) {
console.warn('Failed to load user default template:', error);
this.userDefaultTemplateId = null;
}
}
// 设置默认模板
async setDefaultTemplate(templateId: string): Promise<void> {
try {
const { invoke } = await import('@tauri-apps/api/core');
await invoke('set_default_template', { templateId });
this.userDefaultTemplateId = templateId;
this.notifyListeners(); // 通知UI更新
} catch (error) {
console.error('Failed to set default template:', error);
throw error;
}
}
// 获取当前默认模板ID
getDefaultTemplateId(): string | null {
return this.userDefaultTemplateId;
}
// 检查模板是否为默认模板
isDefaultTemplate(templateId: string): boolean {
return this.userDefaultTemplateId === templateId;
}
}
// 全局模板管理器实例
export const templateManager = new TemplateManager();
// 兼容性函数
export const getTemplateById = (id: string): AnkiCardTemplate | undefined => {
const template = templateManager.getTemplateById(id);
return template ? templateManager.toAnkiCardTemplate(template) : undefined;
};
export const getDefaultTemplate = (): AnkiCardTemplate => {
return templateManager.toAnkiCardTemplate(templateManager.getDefaultTemplate());
};
export const getTemplatePrompt = (templateId: string): string => {
const template = templateManager.getTemplateById(templateId);
return template?.generation_prompt || templateManager.getDefaultTemplate().generation_prompt;
};
export const getTemplateFields = (templateId: string): string[] => {
const template = templateManager.getTemplateById(templateId);
return template?.fields || ['Front', 'Back'];
};
|
000haoji/deep-student
| 1,265 |
src/chat-core/index.ts
|
/**
* Chat Core Module - 聊天核心模块
*
* 统一导出所有聊天相关的组件、工具函数、类型定义和样式
* 便于独立开发和迭代
*/
// 导出所有组件
export * from './components';
// 导出工具函数（避免重复导出）
export {
// 统一API
api,
simplifiedApi,
directApi,
// 流式处理
streamHandler,
unifiedStreamManager,
useUnifiedStream,
// 消息转换
convertToBackendFormat,
convertChatHistory,
// AI SDK
tauriApiAdapter,
createAISdkFetch,
convertFromTauriFormat,
// 流式适配器
createAnalysisStream,
createChatStream,
// API客户端
tauriApiClient,
TauriApiClient
} from './utils';
// 导出类型
export type { StreamChunk } from './utils';
// 导出所有类型定义
export * from './types';
// 导出钩子函数
export * from './hooks';
// 重导出核心样式 - 只需要导入这一个文件即可获得所有样式
export const CHAT_CORE_STYLES = './chat-core/styles/index.css';
// 版本信息
export const CHAT_CORE_VERSION = '1.0.0';
// 核心功能快捷导出
export {
// 核心聊天组件
MessageWithThinking,
MarkdownRenderer,
StreamingMarkdownRenderer,
SimplifiedChatInterface,
StreamingChatInterface,
AIChatInterface
} from './components';
export type {
// 核心类型
ChatMessage,
ChatMessageContentPart,
RagSourceInfo
} from './types';
export type {
StreamMessage,
StreamOptions,
StreamRequest,
StreamState
} from './utils';
export type {
AnalysisRequest
} from './utils';
|
000haoji/deep-student
| 3,344 |
src/contexts/SubjectContext.tsx
|
import React, { createContext, useContext, useState, useEffect, ReactNode } from 'react';
import { TauriAPI } from '../utils/tauriApi';
interface SubjectConfig {
id: string;
subject_name: string;
display_name: string;
description: string;
is_enabled: boolean;
prompts: any;
mistake_types: string[];
default_tags: string[];
created_at: string;
updated_at: string;
}
interface SubjectContextType {
currentSubject: string;
setCurrentSubject: (subject: string) => void;
availableSubjects: string[];
subjectConfigs: SubjectConfig[];
loading: boolean;
error: string | null;
refreshSubjects: () => Promise<void>;
getEnabledSubjects: () => string[];
getAllSubjects: () => string[];
}
const SubjectContext = createContext<SubjectContextType | undefined>(undefined);
export const useSubject = () => {
const context = useContext(SubjectContext);
if (context === undefined) {
throw new Error('useSubject must be used within a SubjectProvider');
}
return context;
};
interface SubjectProviderProps {
children: ReactNode;
}
export const SubjectProvider: React.FC<SubjectProviderProps> = ({ children }) => {
const [currentSubject, setCurrentSubject] = useState<string>('');
const [availableSubjects, setAvailableSubjects] = useState<string[]>([]);
const [subjectConfigs, setSubjectConfigs] = useState<SubjectConfig[]>([]);
const [loading, setLoading] = useState(true);
const [error, setError] = useState<string | null>(null);
// 包装setCurrentSubject以添加调试日志
const handleSetCurrentSubject = (newSubject: string) => {
console.log('🔄 全局科目状态更新:', {
oldSubject: currentSubject,
newSubject,
timestamp: new Date().toISOString()
});
setCurrentSubject(newSubject);
};
const refreshSubjects = async () => {
try {
setLoading(true);
setError(null);
// 获取所有科目配置
const configs = await TauriAPI.getAllSubjectConfigs(false);
setSubjectConfigs(configs);
// 获取支持的科目列表
const supportedSubjects = await TauriAPI.getSupportedSubjects();
setAvailableSubjects(supportedSubjects);
// 如果当前没有选择科目，选择第一个启用的科目
if (!currentSubject && supportedSubjects.length > 0) {
const enabledConfigs = configs.filter(config => config.is_enabled);
const firstEnabledSubject = enabledConfigs.length > 0
? enabledConfigs[0].subject_name
: supportedSubjects[0];
handleSetCurrentSubject(firstEnabledSubject);
}
} catch (err) {
console.error('Failed to load subjects:', err);
setError(err instanceof Error ? err.message : 'Failed to load subjects');
} finally {
setLoading(false);
}
};
const getEnabledSubjects = () => {
return subjectConfigs
.filter(config => config.is_enabled)
.map(config => config.subject_name);
};
const getAllSubjects = () => {
return availableSubjects;
};
useEffect(() => {
refreshSubjects();
}, []);
const contextValue: SubjectContextType = {
currentSubject,
setCurrentSubject: handleSetCurrentSubject,
availableSubjects,
subjectConfigs,
loading,
error,
refreshSubjects,
getEnabledSubjects,
getAllSubjects,
};
return (
<SubjectContext.Provider value={contextValue}>
{children}
</SubjectContext.Provider>
);
};
|
000haoji/deep-student
| 13,210 |
src/styles/modern-sidebar.css
|
/* Modern Sidebar Styles */
/* 导入现代字体 */
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap');
/* CSS 变量定义 */
:root {
--sidebar-bg: #ffffff;
--sidebar-border: rgba(226, 232, 240, 0.8);
--sidebar-shadow: 0 0 30px rgba(0, 0, 0, 0.08), 0 0 60px rgba(59, 130, 246, 0.03);
--nav-item-hover: rgba(59, 130, 246, 0.08);
--nav-item-active: rgba(59, 130, 246, 0.12);
--nav-text-color: #000000;
--nav-text-hover: #000000;
--nav-text-active: #000000;
--nav-icon-size: 20px;
--transition-speed: 0.25s;
--font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
--glow-color: rgba(59, 130, 246, 0.4);
}
/* 覆盖全局字体 */
.app-sidebar * {
font-family: var(--font-family) !important;
}
/* 美化侧边栏主体 */
.app-sidebar {
background: #ffffff !important;
background-color: #ffffff !important;
background-image: none !important;
backdrop-filter: blur(20px) saturate(180%);
-webkit-backdrop-filter: blur(20px) saturate(180%);
border-right: 1px solid var(--sidebar-border) !important;
box-shadow: var(--sidebar-shadow) !important;
transition: all var(--transition-speed) cubic-bezier(0.4, 0, 0.2, 1) !important;
position: relative;
overflow: hidden;
}
/* 移除动态背景纹理以确保纯白色背景 */
.app-sidebar::before {
display: none !important;
}
@keyframes backgroundShift {
0%, 100% { opacity: 1; }
50% { opacity: 0.7; }
}
.app-sidebar > * {
position: relative;
z-index: 1;
}
/* Logo 区域美化 */
.sidebar-header {
padding: 1.25rem !important;
border-bottom: 1px solid var(--sidebar-border) !important;
background: rgba(255, 255, 255, 1.0) !important;
backdrop-filter: blur(10px);
position: relative;
overflow: hidden;
}
.sidebar-header::after {
content: '';
position: absolute;
top: 50%;
left: 50%;
width: 120px;
height: 120px;
background: radial-gradient(circle, var(--glow-color) 0%, transparent 70%);
transform: translate(-50%, -50%) scale(0);
transition: transform 0.4s cubic-bezier(0.4, 0, 0.2, 1);
pointer-events: none;
}
.sidebar-header:hover::after {
transform: translate(-50%, -50%) scale(1.5);
}
.app-logo {
transition: all var(--transition-speed) ease;
position: relative;
z-index: 2;
}
.logo-icon,
.logo-full {
filter: drop-shadow(0 4px 8px rgba(0, 0, 0, 0.1));
transition: all var(--transition-speed) cubic-bezier(0.4, 0, 0.2, 1);
}
.logo-icon:hover,
.logo-full:hover {
transform: scale(1.08) rotate(1deg);
filter: drop-shadow(0 6px 12px rgba(59, 130, 246, 0.2));
}
/* 导航区域 */
.sidebar-nav {
padding: 0.75rem !important;
position: relative;
}
/* 导航分组标签 */
.nav-label {
font-size: 0.75rem !important;
font-weight: 700 !important;
color: #000000 !important;
text-transform: uppercase !important;
letter-spacing: 0.08em !important;
margin: 1.5rem 0.75rem 0.75rem !important;
opacity: 0.8;
transition: all var(--transition-speed) ease;
position: relative;
}
.nav-label::after {
content: '';
position: absolute;
bottom: -0.25rem;
left: 0;
width: 0;
height: 2px;
background: linear-gradient(90deg, #3b82f6, #8b5cf6);
transition: width 0.3s ease;
}
.app-sidebar:hover .nav-label {
opacity: 1;
color: #000000 !important;
}
.app-sidebar:hover .nav-label::after {
width: 100%;
}
/* 导航项美化 */
.nav-item {
position: relative !important;
margin: 0.375rem 0 !important;
padding: 0.75rem 1rem !important;
border-radius: 12px !important;
background: transparent !important;
color: var(--nav-text-color) !important;
font-size: 0.875rem !important;
font-weight: 500 !important;
transition: all var(--transition-speed) cubic-bezier(0.4, 0, 0.2, 1) !important;
overflow: hidden !important;
border: 1px solid transparent !important;
cursor: pointer;
}
/* 导航项悬停效果 */
.nav-item:hover {
background: var(--nav-item-hover) !important;
color: #000000 !important;
transform: translateX(4px) scale(1.02);
border-color: rgba(59, 130, 246, 0.15) !important;
box-shadow: 0 4px 12px rgba(59, 130, 246, 0.1);
}
.nav-item:hover::before {
content: '';
position: absolute;
inset: 0;
background: linear-gradient(135deg, rgba(255, 255, 255, 0.1) 0%, transparent 100%);
pointer-events: none;
}
/* 导航项激活状态 */
.nav-item.active {
background: var(--nav-item-active) !important;
color: var(--nav-text-active) !important;
font-weight: 600 !important;
border-color: rgba(59, 130, 246, 0.25) !important;
box-shadow:
0 4px 16px rgba(59, 130, 246, 0.2),
0 0 0 1px rgba(59, 130, 246, 0.1),
inset 0 1px 0 rgba(255, 255, 255, 0.2);
transform: translateX(2px);
}
/* 激活指示效果 */
.nav-item.active::after {
content: '';
position: absolute;
left: 0;
top: 0;
bottom: 0;
width: 4px;
background: linear-gradient(180deg, #3b82f6 0%, #8b5cf6 100%);
border-radius: 0 4px 4px 0;
animation: slideInGlow 0.4s cubic-bezier(0.4, 0, 0.2, 1);
box-shadow: 0 0 8px rgba(59, 130, 246, 0.5);
}
@keyframes slideInGlow {
from {
transform: translateX(-100%);
opacity: 0;
box-shadow: 0 0 0 rgba(59, 130, 246, 0);
}
to {
transform: translateX(0);
opacity: 1;
box-shadow: 0 0 8px rgba(59, 130, 246, 0.5);
}
}
/* 图标样式 */
.nav-icon {
width: var(--nav-icon-size) !important;
height: var(--nav-icon-size) !important;
display: flex !important;
align-items: center !important;
justify-content: center !important;
margin-right: 0.875rem !important;
transition: all var(--transition-speed) cubic-bezier(0.4, 0, 0.2, 1) !important;
position: relative;
}
/* 图标悬停效果 */
.nav-item:hover .nav-icon {
transform: scale(1.15) rotate(5deg);
}
.nav-item.active .nav-icon {
color: var(--nav-text-active) !important;
transform: scale(1.1);
}
/* 图标发光效果 */
.nav-item.active .nav-icon::before {
content: '';
position: absolute;
inset: -4px;
background: radial-gradient(circle, var(--glow-color) 0%, transparent 70%);
border-radius: 50%;
animation: iconGlow 2s ease-in-out infinite;
z-index: -1;
}
@keyframes iconGlow {
0%, 100% { opacity: 0.3; transform: scale(1); }
50% { opacity: 0.6; transform: scale(1.2); }
}
/* 文字样式 */
.nav-text {
font-weight: 500 !important;
letter-spacing: 0.01em !important;
transition: all var(--transition-speed) ease !important;
}
/* 侧边栏折叠时的样式 */
.app-sidebar.collapsed .nav-label {
opacity: 0 !important;
height: 0 !important;
margin: 0 !important;
overflow: hidden !important;
}
.app-sidebar.collapsed .nav-item {
padding: 0.875rem !important;
justify-content: center !important;
margin: 0.25rem 0.5rem !important;
}
.app-sidebar.collapsed .nav-icon {
margin-right: 0 !important;
}
/* 侧边栏底部 */
.sidebar-footer {
padding: 0.75rem !important;
border-top: 1px solid var(--sidebar-border) !important;
background: #ffffff !important;
backdrop-filter: blur(10px);
margin-top: auto;
}
.sidebar-footer .nav-item {
background: transparent !important;
background-color: transparent !important;
background-image: none !important;
border: none !important;
color: #000000 !important;
border-radius: 12px !important;
margin: 0.375rem 0 !important;
padding: 0.75rem 1rem !important;
transition: all var(--transition-speed) cubic-bezier(0.4, 0, 0.2, 1) !important;
position: relative !important;
overflow: hidden !important;
border: 1px solid transparent !important;
cursor: pointer;
font-size: 0.875rem !important;
font-weight: 500 !important;
text-align: left;
}
.sidebar-footer .nav-item:hover {
background: var(--nav-item-hover) !important;
color: #000000 !important;
transform: translateX(4px) scale(1.02);
border-color: rgba(59, 130, 246, 0.15) !important;
box-shadow: 0 4px 12px rgba(59, 130, 246, 0.1);
}
.sidebar-footer .nav-item:hover::before {
content: '';
position: absolute;
inset: 0;
background: linear-gradient(135deg, rgba(255, 255, 255, 0.1) 0%, transparent 100%);
pointer-events: none;
}
.sidebar-footer .nav-item.active {
background: var(--nav-item-active) !important;
color: var(--nav-text-active) !important;
font-weight: 600 !important;
border-color: rgba(59, 130, 246, 0.25) !important;
box-shadow:
0 4px 16px rgba(59, 130, 246, 0.2),
0 0 0 1px rgba(59, 130, 246, 0.1),
inset 0 1px 0 rgba(255, 255, 255, 0.2);
transform: translateX(2px);
}
.sidebar-footer .nav-item.active::after {
content: '';
position: absolute;
left: 0;
top: 0;
bottom: 0;
width: 4px;
background: linear-gradient(180deg, #3b82f6 0%, #8b5cf6 100%);
border-radius: 0 4px 4px 0;
animation: slideInGlow 0.4s cubic-bezier(0.4, 0, 0.2, 1);
box-shadow: 0 0 8px rgba(59, 130, 246, 0.5);
}
.sidebar-footer .nav-item:hover .nav-icon {
transform: scale(1.15) rotate(5deg);
}
.sidebar-footer .nav-item.active .nav-icon {
color: var(--nav-text-active) !important;
transform: scale(1.1);
}
.sidebar-footer .nav-item.active .nav-icon::before {
content: '';
position: absolute;
inset: -4px;
background: radial-gradient(circle, var(--glow-color) 0%, transparent 70%);
border-radius: 50%;
animation: iconGlow 2s ease-in-out infinite;
z-index: -1;
}
.sidebar-footer .nav-item:active {
transform: translateX(2px) scale(0.98) !important;
}
/* 滚动条美化 */
.sidebar-nav::-webkit-scrollbar {
width: 8px !important;
}
.sidebar-nav::-webkit-scrollbar-track {
background: rgba(0, 0, 0, 0.02) !important;
border-radius: 4px;
}
.sidebar-nav::-webkit-scrollbar-thumb {
background: linear-gradient(180deg, rgba(59, 130, 246, 0.3) 0%, rgba(147, 51, 234, 0.3) 100%) !important;
border-radius: 4px !important;
transition: all var(--transition-speed) ease !important;
}
.sidebar-nav::-webkit-scrollbar-thumb:hover {
background: linear-gradient(180deg, rgba(59, 130, 246, 0.5) 0%, rgba(147, 51, 234, 0.5) 100%) !important;
transform: scaleX(1.2);
}
/* 工具提示美化 */
.app-sidebar.collapsed .tooltip-test[data-tooltip]:not([data-tooltip=""]):hover::before {
content: attr(data-tooltip);
position: absolute;
left: calc(100% + 12px);
top: 50%;
transform: translateY(-50%);
background: rgba(30, 41, 59, 0.95) !important;
backdrop-filter: blur(12px);
border: 1px solid rgba(255, 255, 255, 0.1);
box-shadow: 0 8px 24px rgba(0, 0, 0, 0.2);
font-family: var(--font-family) !important;
font-weight: 500 !important;
font-size: 0.8125rem;
padding: 0.625rem 0.875rem !important;
border-radius: 10px !important;
color: white;
white-space: nowrap;
z-index: 1000;
animation: tooltipSlideIn 0.2s cubic-bezier(0.4, 0, 0.2, 1);
}
.app-sidebar.collapsed .tooltip-test[data-tooltip]:not([data-tooltip=""]):hover::after {
content: '';
position: absolute;
left: calc(100% + 6px);
top: 50%;
transform: translateY(-50%);
width: 0;
height: 0;
border: 6px solid transparent;
border-right-color: rgba(30, 41, 59, 0.95) !important;
z-index: 1001;
}
@keyframes tooltipSlideIn {
from {
opacity: 0;
transform: translateY(-50%) translateX(-8px);
}
to {
opacity: 1;
transform: translateY(-50%) translateX(0);
}
}
/* 添加平滑的展开/折叠动画 */
.app-sidebar {
transition: width 0.4s cubic-bezier(0.4, 0, 0.2, 1) !important;
}
.app-sidebar .nav-text,
.app-sidebar .nav-label {
transition: opacity 0.3s ease, transform 0.3s ease !important;
}
.app-sidebar.collapsed .nav-text {
opacity: 0 !important;
transform: translateX(-12px) !important;
}
/* 响应式优化 */
@media (max-width: 768px) {
.nav-item {
padding: 0.625rem 0.75rem !important;
font-size: 0.8125rem !important;
}
.nav-icon {
width: 18px !important;
height: 18px !important;
}
.sidebar-header {
padding: 1rem !important;
}
}
/* 暗色模式支持 */
@media (prefers-color-scheme: dark) {
:root {
--sidebar-bg: rgba(15, 23, 42, 0.95);
--sidebar-border: rgba(71, 85, 105, 0.5);
--nav-item-hover: linear-gradient(135deg, rgba(59, 130, 246, 0.15) 0%, rgba(147, 51, 234, 0.12) 100%);
--nav-item-active: linear-gradient(135deg, rgba(59, 130, 246, 0.25) 0%, rgba(147, 51, 234, 0.2) 100%);
--nav-text-color: #cbd5e1;
--nav-text-hover: #f1f5f9;
--nav-text-active: #60a5fa;
--glow-color: rgba(96, 165, 250, 0.4);
}
.sidebar-header {
background: rgba(15, 23, 42, 0.5) !important;
}
.sidebar-footer {
background: rgba(15, 23, 42, 0.3) !important;
}
.sidebar-footer .nav-item {
background: rgba(30, 41, 59, 0.5) !important;
}
}
/* 微交互增强 */
.nav-item {
will-change: transform, background, box-shadow;
}
.nav-item:active {
transform: translateX(2px) scale(0.98) !important;
}
/* 分组分隔线美化 */
.nav-section:not(:first-child) {
position: relative;
margin-top: 2rem;
}
.nav-section:not(:first-child)::before {
content: '';
position: absolute;
top: -1rem;
left: 1rem;
right: 1rem;
height: 1px;
background: linear-gradient(90deg,
transparent 0%,
rgba(59, 130, 246, 0.2) 20%,
rgba(147, 51, 234, 0.2) 80%,
transparent 100%
);
}
/* 整体性能优化 */
.app-sidebar,
.app-sidebar *,
.app-sidebar *::before,
.app-sidebar *::after {
transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important;
}
/* 添加微妙的内阴影和边框光效 */
.app-sidebar {
box-shadow:
var(--sidebar-shadow),
inset -1px 0 0 0 rgba(59, 130, 246, 0.08),
inset 0 1px 0 0 rgba(255, 255, 255, 0.1) !important;
}
|
000haoji/deep-student
| 9,847 |
src/components/settings/ApiConfigSection.tsx
|
/**
* API Configuration Section Component
* Split from the large Settings component
*/
import React, { useState } from 'react';
import { useApiConfig, ApiConfig } from '../../hooks/useApiConfig';
import { useNotification } from '../../hooks/useNotification';
import { ApiConfigModal } from './ApiConfigModal';
export const ApiConfigSection: React.FC = () => {
const {
apiConfigs,
modelAssignments,
loading,
saving,
testingApi,
saveApiConfigs,
saveModelAssignments,
testApiConnection,
addApiConfig,
updateApiConfig,
deleteApiConfig,
getMultimodalConfigs,
getEnabledConfigs,
validateModelAssignments
} = useApiConfig();
const { showSuccess, showError, showWarning } = useNotification();
const [editingApi, setEditingApi] = useState<ApiConfig | null>(null);
const [showModal, setShowModal] = useState(false);
// 保存配置
const handleSaveConfigs = async () => {
const success = await saveApiConfigs(apiConfigs);
if (success) {
showSuccess('API配置保存成功');
} else {
showError('API配置保存失败');
}
};
// 保存模型分配
const handleSaveModelAssignments = async () => {
const errors = validateModelAssignments();
if (errors.length > 0) {
showWarning(`模型分配验证失败: ${errors.join(', ')}`);
return;
}
const success = await saveModelAssignments(modelAssignments);
if (success) {
showSuccess('模型分配保存成功');
} else {
showError('模型分配保存失败');
}
};
// 测试API连接
const handleTestApi = async (config: ApiConfig) => {
const success = await testApiConnection(config);
if (success) {
showSuccess(`${config.name} 连接测试成功`);
} else {
showError(`${config.name} 连接测试失败`);
}
};
// 添加新API配置
const handleAddApi = () => {
setEditingApi(null);
setShowModal(true);
};
// 编辑API配置
const handleEditApi = (config: ApiConfig) => {
setEditingApi(config);
setShowModal(true);
};
// 保存API配置（从模态框）
const handleSaveApi = async (apiData: Omit<ApiConfig, 'id'>) => {
if (editingApi) {
updateApiConfig(editingApi.id, apiData);
showSuccess('API配置已更新');
} else {
addApiConfig(apiData);
showSuccess('API配置已添加');
}
setShowModal(false);
setEditingApi(null);
};
// 删除API配置
const handleDeleteApi = async (config: ApiConfig) => {
if (window.confirm(`确定要删除 ${config.name} 配置吗？`)) {
deleteApiConfig(config.id);
showSuccess('API配置已删除');
}
};
if (loading) {
return <div className="loading">加载API配置中...</div>;
}
const multimodalConfigs = getMultimodalConfigs();
const enabledConfigs = getEnabledConfigs();
return (
<div className="api-config-section">
<div className="section-header">
<h3>API配置管理</h3>
<button
onClick={handleAddApi}
className="add-api-button"
disabled={saving}
>
+ 添加API配置
</button>
</div>
{/* API配置列表 */}
<div className="api-configs-list">
{apiConfigs.length === 0 ? (
<div className="empty-state">
<p>暂无API配置，请添加至少一个配置</p>
</div>
) : (
apiConfigs.map(config => (
<div key={config.id} className={`api-config-item ${!config.enabled ? 'disabled' : ''}`}>
<div className="config-info">
<div className="config-header">
<h4>{config.name}</h4>
<div className="config-badges">
{config.isMultimodal && <span className="badge multimodal">多模态</span>}
{config.isReasoning && <span className="badge reasoning">推理模型</span>}
{!config.enabled && <span className="badge disabled">已禁用</span>}
</div>
</div>
<div className="config-details">
<p><strong>模型:</strong> {config.model}</p>
<p><strong>适配器:</strong> {config.modelAdapter}</p>
<p><strong>API地址:</strong> {config.baseUrl}</p>
</div>
</div>
<div className="config-actions">
<button
onClick={() => handleTestApi(config)}
disabled={testingApi === config.id || !config.enabled}
className="test-button"
>
{testingApi === config.id ? '测试中...' : '测试连接'}
</button>
<button
onClick={() => handleEditApi(config)}
className="edit-button"
>
编辑
</button>
<button
onClick={() => handleDeleteApi(config)}
className="delete-button"
disabled={saving}
>
删除
</button>
</div>
</div>
))
)}
</div>
{/* 模型分配 */}
<div className="model-assignments">
<h4>模型分配</h4>
<div className="assignment-grid">
<div className="assignment-item">
<label>第一模型（OCR+分类）:</label>
<select
value={modelAssignments.model1_config_id || ''}
onChange={(e) => saveModelAssignments({
...modelAssignments,
model1_config_id: e.target.value || null
})}
disabled={saving}
>
<option value="">请选择...</option>
{multimodalConfigs.map(config => (
<option key={config.id} value={config.id}>
{config.name} - {config.model}
</option>
))}
</select>
<p className="help-text">必须是多模态模型，用于图片识别和分类</p>
</div>
<div className="assignment-item">
<label>第二模型（对话分析）:</label>
<select
value={modelAssignments.model2_config_id || ''}
onChange={(e) => saveModelAssignments({
...modelAssignments,
model2_config_id: e.target.value || null
})}
disabled={saving}
>
<option value="">请选择...</option>
{enabledConfigs.map(config => (
<option key={config.id} value={config.id}>
{config.name} - {config.model}
{config.isReasoning && ' (推理模型)'}
</option>
))}
</select>
<p className="help-text">用于AI对话和深度分析，推理模型效果更好</p>
</div>
<div className="assignment-item">
<label>回顾分析模型（多题统一分析）:</label>
<select
value={modelAssignments.review_analysis_model_config_id || ''}
onChange={(e) => saveModelAssignments({
...modelAssignments,
review_analysis_model_config_id: e.target.value || null
})}
disabled={saving}
>
<option value="">请选择...</option>
{enabledConfigs.map(config => (
<option key={config.id} value={config.id}>
{config.name} - {config.model}
{config.isReasoning && ' (推理模型)'}
</option>
))}
</select>
<p className="help-text">用于回顾分析功能，对多个错题进行统一深度分析，建议使用强大的推理模型</p>
</div>
<div className="assignment-item">
<label>ANKI制卡模型（卡片生成）:</label>
<select
value={modelAssignments.anki_card_model_config_id || ''}
onChange={(e) => saveModelAssignments({
...modelAssignments,
anki_card_model_config_id: e.target.value || null
})}
disabled={saving}
>
<option value="">请选择...</option>
{enabledConfigs.map(config => (
<option key={config.id} value={config.id}>
{config.name} - {config.model}
{config.isReasoning && ' (推理模型)'}
</option>
))}
</select>
<p className="help-text">用于ANKI卡片生成功能，根据学习内容智能生成问答卡片</p>
</div>
<div className="assignment-item">
<label>总结生成模型（错题总结）:</label>
<select
value={modelAssignments.summary_model_config_id || ''}
onChange={(e) => saveModelAssignments({
...modelAssignments,
summary_model_config_id: e.target.value || null
})}
disabled={saving}
>
<option value="">请选择（默认使用对话分析模型）...</option>
{enabledConfigs.map(config => (
<option key={config.id} value={config.id}>
{config.name} - {config.model}
{config.isReasoning && ' (推理模型)'}
</option>
))}
</select>
<p className="help-text">专门用于生成错题总结，建议使用理解和概括能力强的模型。如果未选择，将使用“第二模型（对话分析）”。</p>
</div>
</div>
</div>
{/* 保存按钮 */}
<div className="section-actions">
<button
onClick={handleSaveConfigs}
disabled={saving}
className="save-button primary"
>
{saving ? '保存中...' : '保存API配置'}
</button>
<button
onClick={handleSaveModelAssignments}
disabled={saving}
className="save-button secondary"
>
{saving ? '保存中...' : '保存模型分配'}
</button>
</div>
{/* API配置模态框 */}
{showModal && (
<ApiConfigModal
config={editingApi}
onSave={handleSaveApi}
onCancel={() => {
setShowModal(false);
setEditingApi(null);
}}
/>
)}
</div>
);
};
|
000haoji/deep-student
| 6,776 |
src/components/settings/SystemSettingsSection.tsx
|
/**
* System Settings Section Component
* Split from the large Settings component
*/
import React from 'react';
import { useSystemSettings } from '../../hooks/useSystemSettings';
import { useNotification } from '../../hooks/useNotification';
import { Settings as SettingsIcon, CheckCircle, XCircle } from 'lucide-react';
export const SystemSettingsSection: React.FC = () => {
const {
settings,
loading,
saving,
saveSetting,
saveAllSettings,
resetSettings,
updateSetting,
validateSettings,
getSettingsSummary,
isAutoSaveEnabled,
isDarkTheme: _isDarkTheme,
isDebugMode
} = useSystemSettings();
const { showSuccess, showError, showWarning } = useNotification();
// 处理设置变更
const handleSettingChange = async <K extends keyof typeof settings>(
key: K,
value: typeof settings[K],
autoSave: boolean = true
) => {
updateSetting(key, value);
if (autoSave && isAutoSaveEnabled) {
const success = await saveSetting(key, value);
if (!success) {
showError(`保存 ${key} 设置失败`);
}
}
};
// 手动保存所有设置
const handleSaveAll = async () => {
const errors = validateSettings(settings);
if (errors.length > 0) {
showWarning(`设置验证失败: ${errors.join(', ')}`);
return;
}
const success = await saveAllSettings(settings);
if (success) {
showSuccess('所有设置保存成功');
} else {
showError('保存设置失败');
}
};
// 重置所有设置
const handleReset = async () => {
if (window.confirm('确定要重置所有设置为默认值吗？此操作不可恢复。')) {
const success = await resetSettings();
if (success) {
showSuccess('设置已重置为默认值');
} else {
showError('重置设置失败');
}
}
};
if (loading) {
return <div className="loading">加载系统设置中...</div>;
}
const summary = getSettingsSummary();
return (
<div className="system-settings-section">
<div className="section-header">
<div style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<SettingsIcon size={24} color="#4a5568" />
<h3>系统设置</h3>
</div>
<div className="settings-summary">
<span>主题: {settings.theme}</span>
<span>自动保存: {isAutoSaveEnabled ? '开启' : '关闭'}</span>
{isDebugMode && <span className="debug-indicator">调试模式</span>}
</div>
</div>
<div className="settings-grid">
{/* 界面设置 */}
<div className="settings-group">
<h4>界面设置</h4>
<div className="setting-item">
<label>主题:</label>
<select
value={settings.theme}
onChange={e => handleSettingChange('theme', e.target.value)}
disabled={saving}
>
<option value="light">浅色主题</option>
<option value="dark">深色主题</option>
<option value="auto">跟随系统</option>
</select>
</div>
<div className="setting-item">
<label>语言:</label>
<select
value={settings.language}
onChange={e => handleSettingChange('language', e.target.value)}
disabled={saving}
>
<option value="zh-CN">简体中文</option>
<option value="en-US">English</option>
</select>
</div>
</div>
{/* 功能设置 */}
<div className="settings-group">
<h4>功能设置</h4>
<div className="setting-item">
<label className="checkbox-label">
<input
type="checkbox"
checked={settings.autoSave}
onChange={e => handleSettingChange('autoSave', e.target.checked)}
disabled={saving}
/>
自动保存配置
</label>
<p className="help-text">更改后自动保存，无需手动保存</p>
</div>
<div className="setting-item">
<label className="checkbox-label">
<input
type="checkbox"
checked={settings.enableNotifications}
onChange={e => handleSettingChange('enableNotifications', e.target.checked)}
disabled={saving}
/>
启用通知
</label>
<p className="help-text">显示操作成功/失败的通知消息</p>
</div>
<div className="setting-item">
<label>最大聊天历史记录数:</label>
<input
type="number"
min="10"
max="1000"
value={settings.maxChatHistory}
onChange={e => handleSettingChange('maxChatHistory', parseInt(e.target.value, 10))}
disabled={saving}
/>
<p className="help-text">每个对话保留的最大消息数量 (10-1000)</p>
</div>
</div>
{/* 高级设置 */}
<div className="settings-group">
<h4>高级设置</h4>
<div className="setting-item">
<label className="checkbox-label">
<input
type="checkbox"
checked={settings.debugMode}
onChange={e => handleSettingChange('debugMode', e.target.checked)}
disabled={saving}
/>
调试模式
</label>
<p className="help-text">显示详细的调试信息和日志</p>
</div>
{isDebugMode && (
<div className="debug-info">
<h5>调试信息:</h5>
<pre>{JSON.stringify(summary, null, 2)}</pre>
</div>
)}
</div>
</div>
{/* 操作按钮 */}
<div className="settings-actions">
{!isAutoSaveEnabled && (
<button
onClick={handleSaveAll}
disabled={saving}
className="save-button primary"
>
{saving ? '保存中...' : '保存所有设置'}
</button>
)}
<button
onClick={handleReset}
disabled={saving}
className="reset-button secondary"
>
重置为默认值
</button>
</div>
{/* 设置状态 */}
<div className="settings-status">
<div className="status-item">
<span>配置项数量: {summary.configuredItems}</span>
</div>
<div className="status-item">
<span>自动保存: {summary.autoSaveEnabled ? <CheckCircle size={16} color="#28a745" /> : <XCircle size={16} color="#dc3545" />}</span>
</div>
<div className="status-item">
<span>当前主题: {summary.currentTheme}</span>
</div>
<div className="status-item">
<span>最大历史: {summary.maxHistorySize}</span>
</div>
{summary.debugModeEnabled && (
<div className="status-item debug">
<span>调试模式: 已启用</span>
</div>
)}
</div>
</div>
);
};
|
000haoji/deep-student
| 8,918 |
src/components/settings/ApiConfigModal.tsx
|
/**
* API Configuration Modal Component
* Split from the large Settings component for better maintainability
*/
import React, { useState, useEffect } from 'react';
import { ApiConfig } from '../../hooks/useApiConfig';
interface ApiConfigModalProps {
config: ApiConfig | null; // null for new config
onSave: (config: Omit<ApiConfig, 'id'>) => void;
onCancel: () => void;
}
export const ApiConfigModal: React.FC<ApiConfigModalProps> = ({
config,
onSave,
onCancel
}) => {
const [formData, setFormData] = useState<Omit<ApiConfig, 'id'>>({
name: '',
apiKey: '',
baseUrl: '',
model: '',
isMultimodal: false,
isReasoning: false,
enabled: true,
modelAdapter: 'general'
});
const [errors, setErrors] = useState<Record<string, string>>({});
// 预定义的模型适配器选项
const modelAdapters = [
{ value: 'general', label: '通用模型' },
{ value: 'deepseek-r1', label: 'DeepSeek-R1' },
{ value: 'google', label: 'Google Gemini' },
{ value: 'o1-series', label: 'OpenAI o1系列' },
{ value: 'claude-3-5-sonnet', label: 'Claude 3.5 Sonnet' }
];
// 常见模型预设
const modelPresets: Record<string, Partial<Omit<ApiConfig, 'id'>>> = {
'gpt-4o': {
model: 'gpt-4o',
isMultimodal: true,
isReasoning: false,
modelAdapter: 'general'
},
'gpt-4o-mini': {
model: 'gpt-4o-mini',
isMultimodal: true,
isReasoning: false,
modelAdapter: 'general'
},
'o1-preview': {
model: 'o1-preview',
isMultimodal: false,
isReasoning: true,
modelAdapter: 'o1-series'
},
'o1-mini': {
model: 'o1-mini',
isMultimodal: false,
isReasoning: true,
modelAdapter: 'o1-series'
},
'claude-3-5-sonnet': {
model: 'claude-3-5-sonnet-20241022',
isMultimodal: true,
isReasoning: false,
modelAdapter: 'claude-3-5-sonnet'
},
'gemini-1.5-pro': {
model: 'gemini-1.5-pro',
isMultimodal: true,
isReasoning: false,
modelAdapter: 'google'
},
'gemini-1.5-pro-latest': {
model: 'gemini-1.5-pro-latest',
isMultimodal: true,
isReasoning: false,
modelAdapter: 'google'
},
'gemini-1.5-flash': {
model: 'gemini-1.5-flash',
isMultimodal: true,
isReasoning: false,
modelAdapter: 'google'
}
};
// 初始化表单数据
useEffect(() => {
if (config) {
setFormData(config);
} else {
setFormData({
name: '',
apiKey: '',
baseUrl: '',
model: '',
isMultimodal: false,
isReasoning: false,
enabled: true,
modelAdapter: 'general'
});
}
setErrors({});
}, [config]);
// 表单验证
const validateForm = (): boolean => {
const newErrors: Record<string, string> = {};
if (!formData.name.trim()) {
newErrors.name = '配置名称不能为空';
}
if (!formData.apiKey.trim()) {
newErrors.apiKey = 'API密钥不能为空';
}
if (!formData.baseUrl.trim()) {
newErrors.baseUrl = 'API地址不能为空';
} else {
try {
new URL(formData.baseUrl);
} catch {
newErrors.baseUrl = 'API地址格式不正确';
}
}
if (!formData.model.trim()) {
newErrors.model = '模型名称不能为空';
}
setErrors(newErrors);
return Object.keys(newErrors).length === 0;
};
// 处理输入变化
const handleInputChange = (field: keyof typeof formData, value: any) => {
setFormData(prev => ({ ...prev, [field]: value }));
// 清除相关错误
if (errors[field]) {
setErrors(prev => ({ ...prev, [field]: '' }));
}
};
// 应用模型预设
const applyModelPreset = (presetKey: string) => {
const preset = modelPresets[presetKey];
if (preset) {
setFormData(prev => ({
...prev,
...preset,
name: prev.name || preset.model || presetKey
}));
}
};
// 处理保存
const handleSave = () => {
if (validateForm()) {
onSave(formData);
}
};
return (
<div className="modal-overlay" onClick={onCancel}>
<div className="modal-content api-config-modal" onClick={e => e.stopPropagation()}>
<div className="modal-header">
<h3>{config ? '编辑API配置' : '添加API配置'}</h3>
<button className="close-button" onClick={onCancel}>×</button>
</div>
<div className="modal-body">
{/* 模型预设 */}
<div className="form-group">
<label>模型预设（可选）:</label>
<div className="preset-buttons">
{Object.keys(modelPresets).map(presetKey => (
<button
key={presetKey}
type="button"
onClick={() => applyModelPreset(presetKey)}
className="preset-button"
>
{presetKey}
</button>
))}
</div>
</div>
{/* 基本信息 */}
<div className="form-group">
<label>配置名称 *:</label>
<input
type="text"
value={formData.name}
onChange={e => handleInputChange('name', e.target.value)}
placeholder="例如：GPT-4o 主配置"
className={errors.name ? 'error' : ''}
/>
{errors.name && <span className="error-text">{errors.name}</span>}
</div>
<div className="form-group">
<label>API密钥 *:</label>
<input
type="password"
value={formData.apiKey}
onChange={e => handleInputChange('apiKey', e.target.value)}
placeholder="sk-..."
className={errors.apiKey ? 'error' : ''}
/>
{errors.apiKey && <span className="error-text">{errors.apiKey}</span>}
</div>
<div className="form-group">
<label>API地址 *:</label>
<input
type="url"
value={formData.baseUrl}
onChange={e => handleInputChange('baseUrl', e.target.value)}
placeholder="https://api.openai.com/v1"
className={errors.baseUrl ? 'error' : ''}
/>
{errors.baseUrl && <span className="error-text">{errors.baseUrl}</span>}
</div>
<div className="form-group">
<label>模型名称 *:</label>
<input
type="text"
value={formData.model}
onChange={e => handleInputChange('model', e.target.value)}
placeholder="gpt-4o"
className={errors.model ? 'error' : ''}
/>
{errors.model && <span className="error-text">{errors.model}</span>}
</div>
<div className="form-group">
<label>模型适配器:</label>
<select
value={formData.modelAdapter}
onChange={e => handleInputChange('modelAdapter', e.target.value)}
>
{modelAdapters.map(adapter => (
<option key={adapter.value} value={adapter.value}>
{adapter.label}
</option>
))}
</select>
</div>
{/* 模型特性 */}
<div className="form-group">
<div className="checkbox-group">
<label className="checkbox-label">
<input
type="checkbox"
checked={formData.isMultimodal}
onChange={e => handleInputChange('isMultimodal', e.target.checked)}
/>
多模态模型（支持图片输入）
</label>
<label className="checkbox-label">
<input
type="checkbox"
checked={formData.isReasoning}
onChange={e => handleInputChange('isReasoning', e.target.checked)}
/>
推理模型（具有思维链能力）
</label>
<label className="checkbox-label">
<input
type="checkbox"
checked={formData.enabled}
onChange={e => handleInputChange('enabled', e.target.checked)}
/>
启用此配置
</label>
</div>
</div>
{/* 说明文本 */}
<div className="help-section">
<h4>配置说明：</h4>
<ul>
<li><strong>多模态模型</strong>：能够处理图片输入，适合用作第一模型（OCR+分类）</li>
<li><strong>推理模型</strong>：具有思维链能力，适合复杂分析，如 o1 系列</li>
<li><strong>第一模型</strong>：必须是多模态，用于图片识别和错题分类</li>
<li><strong>第二模型</strong>：用于AI对话和深度分析，推理模型效果更好</li>
</ul>
</div>
</div>
<div className="modal-footer">
<button onClick={onCancel} className="cancel-button">
取消
</button>
<button onClick={handleSave} className="save-button">
{config ? '更新配置' : '添加配置'}
</button>
</div>
</div>
</div>
);
};
|
000haoji/deep-student
| 19,440 |
src/components/archived/BackendTest.tsx
|
import React, { useState, useEffect } from 'react';
import { invoke } from '@tauri-apps/api/core';
interface TestResult {
name: string;
status: 'pending' | 'success' | 'error';
message: string;
duration?: number;
}
interface ApiTest {
name: string;
command: string;
params?: any;
description: string;
}
const BackendTest: React.FC = () => {
const [testResults, setTestResults] = useState<TestResult[]>([]);
const [isRunning, setIsRunning] = useState(false);
const [isTauriAvailable, setIsTauriAvailable] = useState(false);
const [testContext, setTestContext] = useState<{
tempId?: string;
mistakeId?: string;
reviewId?: string;
}>({});
// 定义所有API测试
const apiTests: ApiTest[] = [
// 基础API测试
{
name: '获取支持的科目',
command: 'get_supported_subjects',
description: '测试获取系统支持的科目列表'
},
{
name: '获取统计信息',
command: 'get_statistics',
description: '测试获取错题统计数据'
},
// 设置管理API
{
name: '保存设置',
command: 'save_setting',
params: { key: 'test_key', value: 'test_value_' + Date.now() },
description: '测试保存设置功能'
},
{
name: '获取设置',
command: 'get_setting',
params: { key: 'test_key' },
description: '测试获取设置功能'
},
{
name: '测试API连接',
command: 'test_api_connection',
params: {
apiKey: 'test-key',
apiBase: 'https://api.openai.com/v1'
},
description: '测试外部AI API连接'
},
// 错题库管理API
{
name: '获取错题列表（无筛选）',
command: 'get_mistakes',
params: {},
description: '测试获取错题列表（无筛选条件）'
},
{
name: '获取错题列表（按科目筛选）',
command: 'get_mistakes',
params: { subject: '数学' },
description: '测试按科目筛选错题列表'
},
{
name: '获取错题详情',
command: 'get_mistake_details',
params: { id: 'test-mistake-id' },
description: '测试获取单个错题的详细信息'
},
{
name: '更新错题',
command: 'update_mistake',
params: {
mistake: {
id: 'test-mistake-id',
subject: '数学',
created_at: new Date().toISOString(),
updated_at: new Date().toISOString(),
question_images: [],
analysis_images: [],
user_question: '更新后的问题',
ocr_text: '更新后的OCR文本',
tags: ['测试标签'],
mistake_type: '计算题',
status: 'completed',
chat_history: []
}
},
description: '测试更新错题信息'
},
{
name: '删除错题',
command: 'delete_mistake',
params: { id: 'test-mistake-id' },
description: '测试删除错题及关联文件'
},
// 分析相关API
{
name: '分析新错题',
command: 'analyze_new_mistake',
params: {
request: {
subject: '数学',
question_image_files: ['data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAYEBQYFBAYGBQYHBwYIChAKCgkJChQODwwQFxQYGBcUFhYaHSUfGhsjHBYWICwgIyYnKSopGR8tMC0oMCUoKSj/2wBDAQcHBwoIChMKChMoGhYaKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCj/wAARCAABAAEDASIAAhEBAxEB/8QAFQABAQAAAAAAAAAAAAAAAAAAAAv/xAAUEAEAAAAAAAAAAAAAAAAAAAAA/8QAFQEBAQAAAAAAAAAAAAAAAAAAAAX/xAAUEQEAAAAAAAAAAAAAAAAAAAAA/9oADAMBAAIRAxEAPwCdABmX/9k='],
analysis_image_files: [],
user_question: '这是一个测试问题'
}
},
description: '测试分析新错题功能'
},
{
name: '继续对话（临时会话）',
command: 'continue_chat',
params: {
request: {
temp_id: 'test-temp-id',
chat_history: [
{
role: 'user',
content: '请详细解释一下这道题',
timestamp: new Date().toISOString()
}
]
}
},
description: '测试在分析过程中继续对话'
},
{
name: '保存分析结果到错题库',
command: 'save_mistake_from_analysis',
params: {
request: {
temp_id: 'test-temp-id',
final_chat_history: [
{
role: 'assistant',
content: '这是AI的回答',
timestamp: new Date().toISOString()
}
]
}
},
description: '测试将分析结果保存到错题库'
},
{
name: '继续错题对话',
command: 'continue_mistake_chat',
params: {
mistakeId: 'test-mistake-id',
chatHistory: [
{
role: 'user',
content: '我还有疑问',
timestamp: new Date().toISOString()
}
]
},
description: '测试在错题详情页继续对话'
},
// 回顾分析API (流式版本)
{
name: '回顾分析',
command: 'analyze_review_session_stream',
params: {
subject: '数学',
mistake_ids: ['mistake-1', 'mistake-2', 'mistake-3']
},
description: '测试对多个错题进行关联分析（流式）'
},
// 文件管理API
{
name: '获取图片（base64）',
command: 'get_image_as_base64',
params: { relativePath: 'test-image.jpg' },
description: '测试读取图片文件为base64格式'
},
{
name: '清理孤立图片',
command: 'cleanup_orphaned_images',
description: '测试清理孤立图片文件'
}
];
useEffect(() => {
// 检查Tauri环境 - 尝试多种检测方式
const checkTauriEnvironment = async () => {
try {
// 方法1: 检查全局变量
if (typeof (window as any).__TAURI__ !== 'undefined') {
setIsTauriAvailable(true);
return;
}
// 方法2: 检查Tauri API
if (typeof (window as any).__TAURI_INTERNALS__ !== 'undefined') {
setIsTauriAvailable(true);
return;
}
// 方法3: 尝试调用一个简单的Tauri命令
await invoke('get_supported_subjects');
setIsTauriAvailable(true);
} catch (error) {
console.log('Tauri环境检测失败:', error);
setIsTauriAvailable(false);
}
};
checkTauriEnvironment();
}, []);
const runSingleTest = async (test: ApiTest): Promise<TestResult> => {
const startTime = Date.now();
try {
console.log(`开始测试: ${test.name}`);
// 动态替换参数中的测试上下文
let params = test.params || {};
if (params) {
params = JSON.parse(JSON.stringify(params)); // 深拷贝
// 替换temp_id
if (params.request?.temp_id === 'test-temp-id' && testContext.tempId) {
params.request.temp_id = testContext.tempId;
}
// 替换mistake_id
if (params.mistakeId === 'test-mistake-id' && testContext.mistakeId) {
params.mistakeId = testContext.mistakeId;
}
if (params.id === 'test-mistake-id' && testContext.mistakeId) {
params.id = testContext.mistakeId;
}
if (params.mistake?.id === 'test-mistake-id' && testContext.mistakeId) {
params.mistake.id = testContext.mistakeId;
}
// 替换review_id
if (params.review_id === 'test-review-id' && testContext.reviewId) {
params.review_id = testContext.reviewId;
}
}
const result = await invoke(test.command, params);
const duration = Date.now() - startTime;
console.log(`测试成功: ${test.name}`, result);
// 更新测试上下文
if (test.command === 'analyze_new_mistake' && (result as any)?.temp_id) {
setTestContext(prev => ({ ...prev, tempId: (result as any).temp_id }));
}
if (test.command === 'save_mistake_from_analysis' && (result as any)?.mistake_item?.id) {
setTestContext(prev => ({ ...prev, mistakeId: (result as any).mistake_item.id }));
}
if (test.command === 'analyze_review_session' && (result as any)?.review_id) {
setTestContext(prev => ({ ...prev, reviewId: (result as any).review_id }));
}
return {
name: test.name,
status: 'success',
message: `成功 - 响应: ${JSON.stringify(result).substring(0, 100)}${JSON.stringify(result).length > 100 ? '...' : ''}`,
duration
};
} catch (error: any) {
const duration = Date.now() - startTime;
console.error(`测试失败: ${test.name}`, error);
return {
name: test.name,
status: 'error',
message: `失败 - ${error.message || error}`,
duration
};
}
};
const runAllTests = async () => {
if (!isTauriAvailable) {
alert('Tauri环境不可用，请在Tauri应用中运行测试');
return;
}
setIsRunning(true);
setTestResults([]);
for (const test of apiTests) {
// 添加pending状态
setTestResults(prev => [...prev, {
name: test.name,
status: 'pending',
message: '测试中...'
}]);
const result = await runSingleTest(test);
// 更新结果
setTestResults(prev =>
prev.map(r => r.name === test.name ? result : r)
);
// 短暂延迟，避免过快的请求
await new Promise(resolve => setTimeout(resolve, 500));
}
setIsRunning(false);
};
const runSingleTestById = async (testIndex: number) => {
if (!isTauriAvailable) {
alert('Tauri环境不可用，请在Tauri应用中运行测试');
return;
}
const test = apiTests[testIndex];
// 更新或添加pending状态
setTestResults(prev => {
const existing = prev.find(r => r.name === test.name);
if (existing) {
return prev.map(r => r.name === test.name ?
{ ...r, status: 'pending' as const, message: '测试中...' } : r
);
} else {
return [...prev, {
name: test.name,
status: 'pending' as const,
message: '测试中...'
}];
}
});
const result = await runSingleTest(test);
// 更新结果
setTestResults(prev =>
prev.map(r => r.name === test.name ? result : r)
);
};
const clearResults = () => {
setTestResults([]);
setTestContext({});
};
const getStatusIcon = (status: TestResult['status']) => {
switch (status) {
case 'pending':
return '⏳';
case 'success':
return '✅';
case 'error':
return '❌';
default:
return '⚪';
}
};
const getStatusColor = (status: TestResult['status']) => {
switch (status) {
case 'pending':
return '#fbbf24';
case 'success':
return '#10b981';
case 'error':
return '#ef4444';
default:
return '#6b7280';
}
};
// 渲染测试卡片的函数
const renderTestCard = (test: ApiTest, index: number, result?: TestResult) => {
return (
<div
key={test.name}
style={{
border: '1px solid #e5e7eb',
borderRadius: '8px',
padding: '15px',
backgroundColor: '#f9fafb'
}}
>
<div style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'flex-start' }}>
<div style={{ flex: 1 }}>
<h4 style={{ margin: '0 0 5px 0', color: '#1f2937' }}>
{test.name}
</h4>
<p style={{ margin: '0 0 10px 0', fontSize: '14px', color: '#6b7280' }}>
{test.description}
</p>
<div style={{ fontSize: '12px', color: '#9ca3af' }}>
命令: <code>{test.command}</code>
{test.params && (
<div>参数: <code>{JSON.stringify(test.params)}</code></div>
)}
</div>
</div>
<div style={{ marginLeft: '15px', textAlign: 'right' }}>
<button
onClick={() => runSingleTestById(index)}
disabled={isRunning || !isTauriAvailable}
style={{
padding: '5px 10px',
backgroundColor: '#10b981',
color: 'white',
border: 'none',
borderRadius: '4px',
cursor: isRunning ? 'not-allowed' : 'pointer',
fontSize: '12px'
}}
>
单独测试
</button>
</div>
</div>
{result && (
<div style={{
marginTop: '10px',
padding: '10px',
backgroundColor: 'white',
borderRadius: '4px',
border: `1px solid ${getStatusColor(result.status)}`
}}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '5px' }}>
<span style={{ marginRight: '8px', fontSize: '16px' }}>
{getStatusIcon(result.status)}
</span>
<span style={{
fontWeight: 'bold',
color: getStatusColor(result.status)
}}>
{result.status === 'pending' ? '测试中' :
result.status === 'success' ? '成功' : '失败'}
</span>
{result.duration && (
<span style={{ marginLeft: '10px', fontSize: '12px', color: '#6b7280' }}>
({result.duration}ms)
</span>
)}
</div>
<div style={{ fontSize: '14px', color: '#374151' }}>
{result.message}
</div>
</div>
)}
</div>
);
};
return (
<div style={{ padding: '20px', maxWidth: '1000px', margin: '0 auto' }}>
<h2>🔧 后端API测试</h2>
{/* 环境状态 */}
<div style={{
marginBottom: '20px',
padding: '15px',
backgroundColor: isTauriAvailable ? '#dcfce7' : '#fef2f2',
borderRadius: '8px',
border: `1px solid ${isTauriAvailable ? '#16a34a' : '#dc2626'}`
}}>
<h3>环境状态</h3>
<p>
Tauri环境: {isTauriAvailable ? '✅ 可用' : '❌ 不可用'}
</p>
{!isTauriAvailable && (
<p style={{ color: '#dc2626', fontSize: '14px' }}>
请在Tauri桌面应用中运行此测试，浏览器环境无法调用后端API
</p>
)}
</div>
{/* 测试上下文 */}
{(testContext.tempId || testContext.mistakeId || testContext.reviewId) && (
<div style={{
marginBottom: '20px',
padding: '15px',
backgroundColor: '#f0f9ff',
borderRadius: '8px',
border: '1px solid #0ea5e9'
}}>
<h3>测试上下文</h3>
<div style={{ fontSize: '14px', fontFamily: 'monospace' }}>
{testContext.tempId && <div>临时会话ID: {testContext.tempId}</div>}
{testContext.mistakeId && <div>错题ID: {testContext.mistakeId}</div>}
{testContext.reviewId && <div>回顾ID: {testContext.reviewId}</div>}
</div>
<p style={{ fontSize: '12px', color: '#6b7280', marginTop: '8px' }}>
这些ID会自动用于相关的API测试中
</p>
</div>
)}
{/* 控制按钮 */}
<div style={{ marginBottom: '20px' }}>
<button
onClick={runAllTests}
disabled={isRunning || !isTauriAvailable}
style={{
padding: '10px 20px',
marginRight: '10px',
backgroundColor: isRunning ? '#9ca3af' : '#3b82f6',
color: 'white',
border: 'none',
borderRadius: '6px',
cursor: isRunning ? 'not-allowed' : 'pointer'
}}
>
{isRunning ? '测试进行中...' : '运行所有测试'}
</button>
<button
onClick={clearResults}
disabled={isRunning}
style={{
padding: '10px 20px',
backgroundColor: '#6b7280',
color: 'white',
border: 'none',
borderRadius: '6px',
cursor: isRunning ? 'not-allowed' : 'pointer'
}}
>
清空结果
</button>
{(testContext.tempId || testContext.mistakeId || testContext.reviewId) && (
<button
onClick={() => setTestContext({})}
disabled={isRunning}
style={{
padding: '10px 20px',
marginLeft: '10px',
backgroundColor: '#f59e0b',
color: 'white',
border: 'none',
borderRadius: '6px',
cursor: isRunning ? 'not-allowed' : 'pointer'
}}
>
清空上下文
</button>
)}
</div>
{/* API测试列表 */}
<div style={{ display: 'grid', gap: '20px' }}>
{/* 基础API测试 */}
<div>
<h3 style={{ marginBottom: '15px', color: '#1f2937' }}>📊 基础API测试</h3>
<div style={{ display: 'grid', gap: '15px' }}>
{apiTests.slice(0, 2).map((test, index) => {
const result = testResults.find(r => r.name === test.name);
return renderTestCard(test, index, result);
})}
</div>
</div>
{/* 设置管理API */}
<div>
<h3 style={{ marginBottom: '15px', color: '#1f2937' }}>⚙️ 设置管理API</h3>
<div style={{ display: 'grid', gap: '15px' }}>
{apiTests.slice(2, 5).map((test, index) => {
const result = testResults.find(r => r.name === test.name);
return renderTestCard(test, index + 2, result);
})}
</div>
</div>
{/* 错题库管理API */}
<div>
<h3 style={{ marginBottom: '15px', color: '#1f2937' }}>📚 错题库管理API</h3>
<div style={{ display: 'grid', gap: '15px' }}>
{apiTests.slice(5, 10).map((test, index) => {
const result = testResults.find(r => r.name === test.name);
return renderTestCard(test, index + 5, result);
})}
</div>
</div>
{/* 分析相关API */}
<div>
<h3 style={{ marginBottom: '15px', color: '#1f2937' }}>🔍 分析相关API</h3>
<div style={{ display: 'grid', gap: '15px' }}>
{apiTests.slice(10, 15).map((test, index) => {
const result = testResults.find(r => r.name === test.name);
return renderTestCard(test, index + 10, result);
})}
</div>
</div>
{/* 回顾分析API */}
<div>
<h3 style={{ marginBottom: '15px', color: '#1f2937' }}>📈 回顾分析API</h3>
<div style={{ display: 'grid', gap: '15px' }}>
{apiTests.slice(15, 16).map((test, index) => {
const result = testResults.find(r => r.name === test.name);
return renderTestCard(test, index + 15, result);
})}
</div>
</div>
{/* 文件管理API */}
<div>
<h3 style={{ marginBottom: '15px', color: '#1f2937' }}>📁 文件管理API</h3>
<div style={{ display: 'grid', gap: '15px' }}>
{apiTests.slice(16).map((test, index) => {
const result = testResults.find(r => r.name === test.name);
return renderTestCard(test, index + 16, result);
})}
</div>
</div>
</div>
{/* 测试统计 */}
{testResults.length > 0 && (
<div style={{
marginTop: '20px',
padding: '15px',
backgroundColor: '#f3f4f6',
borderRadius: '8px'
}}>
<h3>测试统计</h3>
<div style={{ display: 'grid', gridTemplateColumns: 'repeat(auto-fit, minmax(120px, 1fr))', gap: '10px' }}>
<div>
总数: <strong>{testResults.length}</strong>
</div>
<div style={{ color: '#10b981' }}>
成功: <strong>{testResults.filter(r => r.status === 'success').length}</strong>
</div>
<div style={{ color: '#ef4444' }}>
失败: <strong>{testResults.filter(r => r.status === 'error').length}</strong>
</div>
<div style={{ color: '#fbbf24' }}>
进行中: <strong>{testResults.filter(r => r.status === 'pending').length}</strong>
</div>
</div>
</div>
)}
</div>
);
};
export default BackendTest;
|
000haoji/deep-student
| 1,627 |
src/components/archived/README.md
|
# 归档组件说明
本目录包含被统一组件 `UnifiedAnalysisView` 替换的原有组件备份。
## 归档时间
2024年6月5日
## 归档原因
为了提高代码复用性和可维护性，将三个功能相似的分析组件统一为一个通用组件，并新增了图片追问功能。
## 归档的组件
### 1. MistakeDetail.tsx
- **原用途**: 单条错题的详细分析和追问
- **替换为**: `UnifiedAnalysisView` 组件，使用 `analysisType="singleMistake"`
- **主要功能**:
- 错题信息编辑
- 图片查看
- AI分析对话
- 错题删除
### 2. BatchTaskDetailView.tsx
- **原用途**: 批量分析任务中单个条目的详情展示和追问
- **替换为**: `UnifiedAnalysisView` 组件，使用 `analysisType="batchDetail"`
- **主要功能**:
- 批量任务状态展示
- OCR结果显示
- AI解答对话
- 保存到错题库
### 3. ReviewAnalysisDetailView.tsx
- **原用途**: 回顾分析会话的详情展示和追问
- **替换为**: `UnifiedAnalysisView` 组件，使用 `analysisType="reviewDetail"`
- **主要功能**:
- 回顾会话信息展示
- 自动开始分析
- AI分析对话
- 保存到分析库
## 新增功能
统一组件新增了以下功能：
- 图片追问：用户可以上传图片与文字一同发送给AI
- 多模态内容渲染：支持文本和图片混合显示
- 统一的流式处理逻辑
- 更好的错误处理和状态管理
## 恢复说明
原始组件文件已通过git提交保存在版本控制中。如果需要恢复，可以：
1. 使用 `git checkout` 恢复特定版本的文件
2. 恢复相应的导入语句
3. 恢复原有的组件使用方式
**注意**: 为避免编译错误，tsx文件已从此目录移除，但可以通过git历史恢复。
## 兼容性说明
- 新的统一组件完全兼容原有的功能
- API调用方式保持不变
- 数据结构保持向后兼容
- 原有的样式类名大部分保留
## 迁移映射
| 原组件属性 | 统一组件属性 | 备注 |
|----------|------------|------|
| `mistake` | `initialData` | 数据对象 |
| `taskData` | `initialData` | 数据对象 |
| `sessionData` | `initialData` | 数据对象 |
| `onBack` | `onBack` | 仅 singleMistake |
| `onUpdate` | `onMistakeUpdate` | 仅 singleMistake |
| `onDelete` | `onMistakeDelete` | 仅 singleMistake |
| `onSaveRequested` | `onRequestSaveBatchItemAsMistake` 或 `onSaveReviewSession` | 根据类型 |
| `onChatHistoryUpdated` | `onBatchChatUpdate` 或 `onReviewChatUpdate` | 根据类型 |
| `isPageView` | `isPageView` | 保持不变 |
## 注意事项
- 这些组件的备份仅用于紧急恢复，不建议在新开发中使用
- 如有问题，请优先修复统一组件而不是回退到旧组件
- 统一组件的功能会持续迭代和优化
|
000haoji/deep-student
| 8,018 |
src/components/shared/UnifiedSubjectSelector.css
|
.unified-subject-selector {
position: relative;
display: inline-block;
}
/* 现代圆角下拉框样式 */
.unified-subject-selector .custom-select {
position: relative;
width: 100%;
}
.unified-subject-selector .select-selected {
background-color: #ffffff;
border-radius: 12px;
border: 1px solid #e0e0e0;
padding: 12px 16px;
cursor: pointer;
display: flex;
justify-content: space-between;
align-items: center;
transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1);
box-shadow: 0 2px 8px rgba(0,0,0,0.08);
min-width: 120px;
position: relative;
z-index: 10;
}
.unified-subject-selector .select-selected:hover {
border-color: #c7c7c7;
box-shadow: 0 3px 10px rgba(0,0,0,0.12);
}
.unified-subject-selector .select-selected:focus {
background-color: #edf2f7;
color: #4a5568;
outline: none;
}
.unified-subject-selector .select-selected.disabled {
background-color: #f7fafc;
color: #a0aec0;
cursor: not-allowed;
opacity: 0.6;
}
.unified-subject-selector .selected-value {
color: #1a1a1a;
font-size: 14px;
font-weight: 500;
letter-spacing: 0.2px;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
pointer-events: none;
}
.unified-subject-selector .select-arrow {
color: #666;
font-size: 16px;
transform: rotate(0deg);
transition: transform 0.3s cubic-bezier(0.4, 0, 0.2, 1);
flex-shrink: 0;
margin-left: 8px;
pointer-events: none;
}
.unified-subject-selector .select-items {
position: absolute;
top: 100%;
left: 0;
right: 0;
background-color: #fff;
border-radius: 12px;
border: 1px solid #e0e0e0;
margin-top: 8px;
max-height: 0;
overflow: hidden;
transition: max-height 0.3s cubic-bezier(0.4, 0, 0.2, 1), opacity 0.2s ease;
opacity: 0;
box-shadow: 0 6px 16px rgba(0,0,0,0.12);
z-index: 9999;
visibility: hidden;
pointer-events: auto;
-webkit-overflow-scrolling: touch;
}
.unified-subject-selector .select-items.show {
max-height: 500px;
opacity: 1;
visibility: visible;
pointer-events: auto;
overflow-y: auto;
}
/* 自定义滚动条样式 */
.unified-subject-selector .select-items::-webkit-scrollbar {
width: 6px;
}
.unified-subject-selector .select-items::-webkit-scrollbar-track {
background: #f1f1f1;
border-radius: 3px;
}
.unified-subject-selector .select-items::-webkit-scrollbar-thumb {
background: #c1c1c1;
border-radius: 3px;
}
.unified-subject-selector .select-items::-webkit-scrollbar-thumb:hover {
background: #a8a8a8;
}
.unified-subject-selector .select-item {
padding: 12px 16px;
cursor: pointer;
color: #333;
font-size: 14px;
font-weight: 400;
transition: all 0.2s cubic-bezier(0.4, 0, 0.2, 1);
border: none;
background: none;
width: 100%;
text-align: left;
user-select: none;
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
white-space: nowrap;
min-height: 44px;
display: flex;
align-items: center;
}
.unified-subject-selector .select-item:hover {
background-color: #f7f7f7;
}
.unified-subject-selector .select-item.selected {
background-color: #f0f7ff;
color: #1a73e8;
font-weight: 500;
}
.unified-subject-selector .select-item.disabled-option {
color: #a0aec0 !important;
cursor: not-allowed !important;
background-color: transparent !important;
pointer-events: none !important;
}
.unified-subject-selector .select-item:first-child {
border-top-left-radius: 12px;
border-top-right-radius: 12px;
}
.unified-subject-selector .select-item:last-child {
border-bottom-left-radius: 12px;
border-bottom-right-radius: 12px;
}
.unified-subject-selector.loading .select-selected {
background-color: #f7fafc;
color: #a0aec0;
}
/* 头部科目选择器样式 */
.header-subject-selector {
position: relative;
margin-right: 1rem;
}
.header-subject-selector .custom-select {
width: auto;
min-width: 120px;
}
.header-subject-selector .select-selected {
background-color: #f7fafc;
border: none;
font-size: 13px;
padding: 8px 12px;
border-radius: 8px;
box-shadow: none;
z-index: 1000;
color: #718096;
transition: all 0.2s ease;
}
.header-subject-selector .select-selected:hover {
background-color: #edf2f7;
color: #4a5568;
transform: scale(1.05);
}
.header-subject-selector .select-selected:focus {
background-color: #edf2f7;
color: #4a5568;
outline: none;
}
.header-subject-selector .selected-value {
font-size: 13px;
color: inherit;
}
.header-subject-selector .select-arrow {
font-size: 14px;
color: inherit;
}
/* 头部选择器的下拉选项 */
.header-subject-selector .select-items {
margin-top: 4px;
border-radius: 10px;
box-shadow: 0 4px 12px rgba(0,0,0,0.15);
z-index: 9999;
max-height: min(60vh, 400px);
}
.header-subject-selector .select-items.show {
max-height: min(60vh, 400px);
overflow-y: auto;
}
.header-subject-selector .select-item {
padding: 10px 12px;
font-size: 13px;
min-height: 36px;
}
/* 紧凑模式 */
.unified-subject-selector.compact .select-selected {
padding: 8px 12px;
background-color: #f7fafc;
border: none;
border-radius: 8px;
box-shadow: none;
color: #718096;
transition: all 0.2s ease;
}
.unified-subject-selector.compact .selected-value {
font-size: 13px;
color: inherit;
}
.unified-subject-selector.compact .select-arrow {
font-size: 14px;
color: inherit;
}
.unified-subject-selector.compact .select-item {
padding: 10px 12px;
font-size: 13px;
min-height: 36px;
}
.unified-subject-selector.compact .select-items.show {
max-height: 400px;
}
.unified-subject-selector.compact .select-selected:hover {
background-color: #edf2f7;
color: #4a5568;
transform: scale(1.05);
}
.unified-subject-selector.compact .select-selected:focus {
background-color: #edf2f7;
color: #4a5568;
outline: none;
}
/* 确保在content-header环境中的适配 */
.content-header-left .unified-subject-selector {
z-index: 1000;
position: relative;
transform: translateZ(0);
}
.content-header-left .unified-subject-selector .select-items {
z-index: 9999;
border-radius: 10px;
box-shadow: 0 4px 12px rgba(0,0,0,0.15);
background-color: #fff;
border: 1px solid #e0e0e0;
}
/* 当下拉框打开时，临时修改父容器的overflow */
.content-header:has(.unified-subject-selector .select-items.show) {
overflow: visible !important;
}
/* 如果浏览器不支持:has()，使用这个fallback */
.content-header.dropdown-open {
overflow: visible !important;
}
/* 更强力的fallback - 确保content-header不会裁剪下拉框 */
.content-header {
position: relative;
}
.content-header.dropdown-open,
.content-header:has(.select-items.show) {
overflow: visible !important;
z-index: 1000;
}
/* 修复在不同环境下的显示问题 */
.unified-subject-selector .select-items {
pointer-events: auto;
-webkit-overflow-scrolling: touch;
}
.unified-subject-selector .select-items.show {
pointer-events: auto;
}
/* 确保下拉框不被父容器裁剪 */
.unified-subject-selector {
isolation: isolate;
}
/* 动态调整下拉框位置，避免超出视口 */
.unified-subject-selector .select-items {
max-height: min(400px, calc(100vh - var(--select-top, 100px) - 20px));
}
/* 确保选项完全可见 */
.unified-subject-selector .select-item:last-child {
border-bottom-left-radius: 12px;
border-bottom-right-radius: 12px;
margin-bottom: 0;
}
/* 为可能很长的选项列表提供更好的视觉提示 */
.unified-subject-selector .select-items.show {
border-top: 1px solid #e0e0e0;
border-bottom: 1px solid #e0e0e0;
}
/* 为header环境中的fixed定位下拉框设置正确的样式 */
.content-header-left .unified-subject-selector .select-items.show {
/* JavaScript会动态设置这些属性，不要在CSS中覆盖 */
/* position: fixed !important; */
/* left: auto; */
/* top: auto; */
/* width: auto; */
min-width: 120px;
white-space: nowrap;
max-height: min(60vh, 400px);
overflow-y: auto;
}
/* 确保在所有环境下都有足够的空间 */
@media (max-height: 600px) {
.unified-subject-selector .select-items.show,
.header-subject-selector .select-items.show,
.unified-subject-selector.compact .select-items.show {
max-height: 40vh;
}
}
@media (max-height: 400px) {
.unified-subject-selector .select-items.show,
.header-subject-selector .select-items.show,
.unified-subject-selector.compact .select-items.show {
max-height: 30vh;
}
}
|
000haoji/deep-student
| 7,910 |
src/components/shared/UnifiedSubjectSelector.tsx
|
import React, { useEffect, useState, useRef } from 'react';
import { useSubject } from '../../contexts/SubjectContext';
import './UnifiedSubjectSelector.css';
interface UnifiedSubjectSelectorProps {
mode?: 'enabled' | 'all' | 'existing';
includeAllOption?: boolean;
placeholder?: string;
disabled?: boolean;
className?: string;
value?: string;
onChange?: (subject: string) => void;
existingSubjects?: string[]; // 用于'existing'模式
}
const UnifiedSubjectSelector: React.FC<UnifiedSubjectSelectorProps> = ({
mode = 'enabled',
includeAllOption = false,
placeholder = '选择科目',
disabled = false,
className = '',
value,
onChange,
existingSubjects = []
}) => {
const {
currentSubject,
setCurrentSubject,
getEnabledSubjects,
getAllSubjects,
loading
} = useSubject();
// 自定义下拉框的状态
const [isOpen, setIsOpen] = useState(false);
const selectRef = useRef<HTMLDivElement>(null);
const itemsRef = useRef<HTMLDivElement>(null);
// 确定使用的值和onChange处理器
const selectedValue = value !== undefined ? value : currentSubject;
const handleChange = onChange !== undefined ? onChange : setCurrentSubject;
// 根据模式获取科目选项
const getSubjectOptions = (): string[] => {
switch (mode) {
case 'enabled':
return getEnabledSubjects();
case 'all':
return getAllSubjects();
case 'existing':
return existingSubjects;
default:
return getEnabledSubjects();
}
};
const subjectOptions = getSubjectOptions();
// 构建完整的选项列表
const allOptions = [
...(includeAllOption ? ['全部科目'] : []),
...subjectOptions
];
// 检查是否在content-header环境中
const isInContentHeader = className.includes('header-subject-selector');
// 计算下拉框的最佳位置
const calculateDropdownPosition = () => {
if (!selectRef.current || !itemsRef.current) return;
const selectRect = selectRef.current.getBoundingClientRect();
const itemsHeight = Math.min(500, allOptions.length * (isInContentHeader ? 36 : 44) + 20);
const viewportHeight = window.innerHeight;
const spaceBelow = viewportHeight - selectRect.bottom;
const spaceAbove = selectRect.top;
console.log('🎯 计算下拉框位置:', {
selectRect,
itemsHeight,
spaceBelow,
spaceAbove,
isInContentHeader
});
// 设置CSS变量用于动态计算
selectRef.current.style.setProperty('--select-top', `${selectRect.bottom}px`);
// 先尝试使用相对定位，避免fixed定位的复杂问题
itemsRef.current.style.position = 'absolute';
itemsRef.current.style.left = '0';
itemsRef.current.style.right = '0';
itemsRef.current.style.width = 'auto';
itemsRef.current.style.zIndex = '9999';
if (isInContentHeader) {
// 临时添加类名到content-header以修改overflow
const contentHeader = selectRef.current.closest('.content-header');
if (contentHeader) {
contentHeader.classList.add('dropdown-open');
}
}
// 如果下方空间不够且上方空间更多，则向上展开
if (spaceBelow < itemsHeight && spaceAbove > spaceBelow) {
itemsRef.current.style.top = 'auto';
itemsRef.current.style.bottom = '100%';
itemsRef.current.style.marginTop = '0';
itemsRef.current.style.marginBottom = '8px';
} else {
itemsRef.current.style.top = '100%';
itemsRef.current.style.bottom = 'auto';
itemsRef.current.style.marginTop = '8px';
itemsRef.current.style.marginBottom = '0';
}
// 重置可能影响定位的样式
itemsRef.current.style.transform = 'none';
};
// 清理header的overflow样式
const cleanupHeaderOverflow = () => {
if (isInContentHeader && selectRef.current) {
const contentHeader = selectRef.current.closest('.content-header');
if (contentHeader) {
contentHeader.classList.remove('dropdown-open');
}
}
};
// 监听科目状态变化
useEffect(() => {
console.log('🎯 科目选择器状态监听:', {
currentSubject,
selectedValue,
subjectOptions,
loading,
mode
});
}, [currentSubject, selectedValue, subjectOptions.length, loading, mode]);
// 处理选项点击
const handleOptionClick = (event: React.MouseEvent, optionValue: string) => {
event.preventDefault();
event.stopPropagation();
console.log('🎯 科目选择器变更:', {
oldValue: selectedValue,
newValue: optionValue,
mode,
handleChangeFunction: handleChange.name || 'anonymous'
});
handleChange(optionValue);
setIsOpen(false);
cleanupHeaderOverflow();
};
// 处理选择器主体点击
const handleSelectClick = (event: React.MouseEvent) => {
event.preventDefault();
event.stopPropagation();
if (!disabled) {
const newOpenState = !isOpen;
setIsOpen(newOpenState);
if (newOpenState) {
// 在下一帧计算位置，确保DOM已更新
requestAnimationFrame(() => {
calculateDropdownPosition();
});
} else {
cleanupHeaderOverflow();
}
}
};
// 处理点击外部关闭
useEffect(() => {
const handleClickOutside = (event: MouseEvent) => {
if (selectRef.current && !selectRef.current.contains(event.target as Node)) {
setIsOpen(false);
cleanupHeaderOverflow();
}
};
const handleResize = () => {
if (isOpen) {
calculateDropdownPosition();
}
};
const handleScroll = () => {
if (isOpen && isInContentHeader) {
// 对于header中的下拉框，在滚动时重新计算位置
calculateDropdownPosition();
}
};
if (isOpen) {
document.addEventListener('mousedown', handleClickOutside);
window.addEventListener('resize', handleResize);
window.addEventListener('scroll', handleScroll, true);
}
return () => {
document.removeEventListener('mousedown', handleClickOutside);
window.removeEventListener('resize', handleResize);
window.removeEventListener('scroll', handleScroll, true);
};
}, [isOpen, isInContentHeader]);
// 组件卸载时清理
useEffect(() => {
return () => {
cleanupHeaderOverflow();
};
}, []);
// 获取显示的文本
const getDisplayText = () => {
if (loading) return '加载中...';
if (!selectedValue) return placeholder;
return selectedValue;
};
if (loading) {
return (
<div className={`unified-subject-selector loading ${className}`}>
<div className="custom-select">
<div className="select-selected disabled">
<span className="selected-value">加载中...</span>
<span className="select-arrow">⌵</span>
</div>
</div>
</div>
);
}
return (
<div className={`unified-subject-selector ${className}`} ref={selectRef}>
<div className="custom-select">
<div
className={`select-selected ${disabled ? 'disabled' : ''}`}
onClick={handleSelectClick}
onMouseDown={(e) => e.stopPropagation()}
>
<span className="selected-value">{getDisplayText()}</span>
<span
className="select-arrow"
style={{
transform: isOpen ? 'rotate(180deg)' : 'rotate(0deg)'
}}
>
⌵
</span>
</div>
{isOpen && !disabled && (
<div className="select-items show" ref={itemsRef}>
{!selectedValue && (
<div
className="select-item disabled-option"
style={{ color: '#a0aec0', cursor: 'not-allowed' }}
>
{placeholder}
</div>
)}
{allOptions.map(option => (
<div
key={option}
className={`select-item ${option === selectedValue ? 'selected' : ''}`}
onClick={(e) => handleOptionClick(e, option)}
onMouseDown={(e) => e.stopPropagation()}
>
{option}
</div>
))}
</div>
)}
</div>
</div>
);
};
export { UnifiedSubjectSelector };
export default UnifiedSubjectSelector;
|
000haoji/deep-student
| 8,593 |
src/chat-core/components/MessageWithThinking.tsx
|
import React, { useState } from 'react';
import { MarkdownRenderer } from './MarkdownRenderer';
import { StreamingMarkdownRenderer } from './StreamingMarkdownRenderer';
import { SummaryBox } from '../../components/SummaryBox';
import { ChatMessageContentPart } from '../types/chat';
import { ChatMessage } from '../../types';
interface MessageWithThinkingProps {
content: string | ChatMessageContentPart[];
thinkingContent?: string;
isStreaming: boolean;
role: 'user' | 'assistant';
timestamp: string;
ragSources?: Array<{
document_id: string;
file_name: string;
chunk_text: string;
score: number;
chunk_index: number;
}>;
// 新增：总结框相关props
showSummaryBox?: boolean;
chatHistory?: ChatMessage[];
subject?: string;
mistakeId?: string;
reviewSessionId?: string;
onGenerateSummary?: (summaryPrompt: string) => void;
currentStreamId?: string;
isGenerating?: boolean;
summaryStreamContent?: string;
summaryStreamComplete?: boolean;
}
export const MessageWithThinking: React.FC<MessageWithThinkingProps> = ({
content,
thinkingContent,
isStreaming,
role,
timestamp,
ragSources,
showSummaryBox = false,
chatHistory = [],
subject,
mistakeId,
reviewSessionId,
onGenerateSummary,
currentStreamId,
isGenerating,
summaryStreamContent,
summaryStreamComplete
}) => {
const [isThinkingExpanded, setIsThinkingExpanded] = useState(true);
const [isRagSourcesExpanded, setIsRagSourcesExpanded] = useState(false);
// 渲染多模态内容的函数
const renderContent = (content: string | ChatMessageContentPart[], isStreaming: boolean) => {
// 处理新的多模态数组格式
if (Array.isArray(content)) {
return content.map((part, index) => {
if (part.type === 'text') {
return (
<div key={`text-${index}`} className="content-text-part">
{isStreaming ? (
<StreamingMarkdownRenderer
content={part.text}
isStreaming={true}
/>
) : (
<MarkdownRenderer content={part.text} />
)}
</div>
);
}
if (part.type === 'image_url' && part.image_url && part.image_url.url) {
return (
<div key={`image-${index}`} className="content-image-part">
<img
src={part.image_url.url}
alt="上传的内容"
style={{
maxWidth: '100%',
maxHeight: '300px',
display: 'block',
marginTop: '8px',
marginBottom: '8px',
borderRadius: '8px',
border: '1px solid #e5e7eb'
}}
onError={(e) => {
e.currentTarget.style.display = 'none';
console.error('图片显示错误:', part.image_url.url.substring(0, 50));
}}
/>
</div>
);
}
return null;
});
}
// 兼容旧的字符串格式
else if (typeof content === 'string') {
return isStreaming ? (
<StreamingMarkdownRenderer
content={content}
isStreaming={true}
/>
) : (
<MarkdownRenderer content={content} />
);
}
// 未知内容格式的占位符
return <div className="content-unknown">未知内容格式</div>;
};
return (
<div className={`message ${role} ${isStreaming ? 'streaming' : ''}`}>
{thinkingContent && role === 'assistant' && (
<div className="thinking-container">
<div
className="thinking-header"
onClick={() => setIsThinkingExpanded(!isThinkingExpanded)}
>
<span className="thinking-icon">🧠</span>
<span className="thinking-title">AI 思考过程</span>
<span className="thinking-toggle">
{isThinkingExpanded ? '▼' : '▶'}
</span>
</div>
{isThinkingExpanded && (
<div className="thinking-content-box">
{isStreaming ? (
<StreamingMarkdownRenderer
content={thinkingContent || ''}
isStreaming={true}
/>
) : (
<MarkdownRenderer content={thinkingContent || ''} />
)}
</div>
)}
</div>
)}
<div className="message-content">
{renderContent(content, isStreaming)}
</div>
{ragSources && ragSources.length > 0 && role === 'assistant' && (
<div className="rag-sources-container" style={{
marginTop: '12px',
border: '1px solid #e0e7ff',
borderRadius: '8px',
backgroundColor: '#f8faff'
}}>
<div
className="rag-sources-header"
onClick={() => setIsRagSourcesExpanded(!isRagSourcesExpanded)}
style={{
padding: '8px 12px',
cursor: 'pointer',
display: 'flex',
alignItems: 'center',
gap: '6px',
borderBottom: isRagSourcesExpanded ? '1px solid #e0e7ff' : 'none',
fontSize: '13px',
fontWeight: '500',
color: '#4338ca'
}}
>
<span>📚</span>
<span>知识库来源 ({ragSources.length})</span>
<span style={{ marginLeft: 'auto' }}>
{isRagSourcesExpanded ? '▼' : '▶'}
</span>
</div>
{isRagSourcesExpanded && (
<div className="rag-sources-content" style={{ padding: '8px 12px' }}>
{ragSources.map((source, index) => (
<div
key={`${source.document_id}-${source.chunk_index}`}
style={{
marginBottom: index < ragSources.length - 1 ? '12px' : '0',
padding: '10px',
backgroundColor: 'white',
borderRadius: '6px',
border: '1px solid #e5e7eb'
}}
>
<div style={{
display: 'flex',
justifyContent: 'space-between',
alignItems: 'center',
marginBottom: '6px'
}}>
<div style={{
fontSize: '12px',
fontWeight: '600',
color: '#374151',
display: 'flex',
alignItems: 'center',
gap: '4px'
}}>
<span>📄</span>
<span>{source.file_name}</span>
<span style={{ color: '#6b7280', fontWeight: 'normal' }}>
(块 #{source.chunk_index + 1})
</span>
</div>
<div style={{
fontSize: '11px',
color: '#6b7280',
backgroundColor: '#f3f4f6',
padding: '2px 6px',
borderRadius: '4px'
}}>
相关度: {Math.round(source.score * 100)}%
</div>
</div>
<div style={{
fontSize: '12px',
color: '#4b5563',
lineHeight: '1.4',
fontStyle: 'italic',
backgroundColor: '#f9fafb',
padding: '8px',
borderRadius: '4px',
border: '1px solid #f3f4f6'
}}>
{source.chunk_text.length > 200
? `${source.chunk_text.substring(0, 200)}...`
: source.chunk_text
}
</div>
</div>
))}
</div>
)}
</div>
)}
{/* 总结框 - 仅在assistant消息且启用时显示 */}
{showSummaryBox && role === 'assistant' && (
<SummaryBox
chatHistory={chatHistory}
isVisible={true}
subject={subject}
mistakeId={mistakeId}
reviewSessionId={reviewSessionId}
onGenerateSummary={onGenerateSummary}
currentStreamId={currentStreamId}
isGenerating={isGenerating}
summaryStreamContent={summaryStreamContent}
summaryStreamComplete={summaryStreamComplete}
/>
)}
<div className="message-time">
{new Date(timestamp).toLocaleTimeString()}
</div>
</div>
);
};
|
000haoji/deep-student
| 9,488 |
src/chat-core/components/SimplifiedChatInterface.tsx
|
/**
* Simplified Chat Interface
*
* Replaces the complex AI SDK implementation with a simpler approach
* that uses the unified stream handler directly.
*/
import React, { useState, useRef, useEffect } from 'react';
import { useUnifiedStream, StreamMessage } from '../utils/unifiedStreamHandler';
import { MarkdownRenderer } from './MarkdownRenderer';
import { MessageWithThinking } from './MessageWithThinking';
interface SimplifiedChatInterfaceProps {
tempId?: string;
mistakeId?: number;
initialMessages?: StreamMessage[];
enableChainOfThought?: boolean;
onAnalysisStart?: () => void;
onAnalysisComplete?: (response: any) => void;
className?: string;
}
export const SimplifiedChatInterface = React.forwardRef<any, SimplifiedChatInterfaceProps>(({
tempId,
mistakeId: _mistakeId,
initialMessages = [],
enableChainOfThought = true,
onAnalysisStart,
onAnalysisComplete,
className = ''
}, ref) => {
const [messages, setMessages] = useState<StreamMessage[]>(initialMessages);
const [input, setInput] = useState('');
const [currentStreamId, setCurrentStreamId] = useState<string | null>(null);
const messagesEndRef = useRef<HTMLDivElement>(null);
const {
startStream,
stopStream,
streamProgress,
isStreaming
} = useUnifiedStream();
// Auto-scroll to bottom when new messages appear
useEffect(() => {
if (messagesEndRef.current) {
messagesEndRef.current.scrollIntoView({ behavior: 'smooth' });
}
}, [messages, streamProgress]);
// Update messages from streaming progress
useEffect(() => {
if (currentStreamId && streamProgress[currentStreamId]) {
const progress = streamProgress[currentStreamId];
setMessages(prev => {
const updated = [...prev];
const lastMessage = updated[updated.length - 1];
if (lastMessage && lastMessage.role === 'assistant') {
// Update the last assistant message with streaming content
updated[updated.length - 1] = {
...lastMessage,
content: progress.content,
thinking_content: progress.thinking
};
}
return updated;
});
}
}, [currentStreamId, streamProgress]);
// Handle form submission
const handleSubmit = async (e: React.FormEvent) => {
e.preventDefault();
if (!input.trim() || isStreaming) return;
const userMessage: StreamMessage = {
id: `msg-${Date.now()}`,
role: 'user',
content: input.trim(),
timestamp: new Date().toISOString()
};
// Add user message immediately
setMessages(prev => [...prev, userMessage]);
setInput('');
// Create placeholder assistant message
const assistantMessage: StreamMessage = {
id: `msg-${Date.now() + 1}`,
role: 'assistant',
content: '',
thinking_content: '',
timestamp: new Date().toISOString()
};
setMessages(prev => [...prev, assistantMessage]);
try {
if (onAnalysisStart) {
onAnalysisStart();
}
const updatedChatHistory = [...messages, userMessage];
// Start streaming
const streamId = await startStream(
{
type: tempId ? 'continue_chat' : 'chat',
tempId,
chatHistory: updatedChatHistory,
enableChainOfThought
},
{
onComplete: (content, thinking) => {
// Final update with complete content
setMessages(prev => {
const updated = [...prev];
const lastMessage = updated[updated.length - 1];
if (lastMessage && lastMessage.role === 'assistant') {
updated[updated.length - 1] = {
...lastMessage,
content,
thinking_content: thinking
};
}
return updated;
});
setCurrentStreamId(null);
if (onAnalysisComplete) {
onAnalysisComplete({ content, thinking });
}
},
onError: (error) => {
console.error('Chat stream error:', error);
setCurrentStreamId(null);
// Update the last message to show error
setMessages(prev => {
const updated = [...prev];
const lastMessage = updated[updated.length - 1];
if (lastMessage && lastMessage.role === 'assistant') {
updated[updated.length - 1] = {
...lastMessage,
content: `错误: ${error}`
};
}
return updated;
});
}
}
);
setCurrentStreamId(streamId);
} catch (error) {
console.error('Failed to start chat stream:', error);
}
};
// Handle keyboard shortcuts
const handleKeyDown = (e: React.KeyboardEvent<HTMLTextAreaElement>) => {
if (e.key === 'Enter' && !e.shiftKey) {
e.preventDefault();
handleSubmit(e as any);
}
};
// Send message programmatically
const sendMessage = async (content: string) => {
setInput(content);
// Trigger form submission
setTimeout(() => {
const form = document.querySelector('.chat-input-form') as HTMLFormElement;
if (form) {
form.requestSubmit();
}
}, 0);
};
// Clear chat
const clearChat = () => {
setMessages(initialMessages);
setInput('');
if (currentStreamId) {
stopStream(currentStreamId);
setCurrentStreamId(null);
}
};
// Stop current stream
const stopCurrentStream = () => {
if (currentStreamId) {
stopStream(currentStreamId);
setCurrentStreamId(null);
}
};
// Expose methods to parent
React.useImperativeHandle(ref, () => ({
sendMessage,
clearChat,
stopStream: stopCurrentStream
}));
return (
<div className={`simplified-chat-interface ${className}`}>
{/* Chat Messages */}
<div className="chat-messages">
{messages.map((message, index) => (
<div key={message.id} className={`message ${message.role}`}>
<div className="message-header">
<span className="role">{message.role === 'user' ? '用户' : 'AI助手'}</span>
<span className="timestamp">
{new Date(message.timestamp).toLocaleTimeString()}
</span>
</div>
<div className="message-content">
{message.role === 'assistant' ? (
<MessageWithThinking
content={message.content}
thinkingContent={message.thinking_content}
isStreaming={isStreaming && index === messages.length - 1}
role="assistant"
timestamp={message.timestamp}
/>
) : (
<div className="user-message">
<MarkdownRenderer content={message.content} />
</div>
)}
</div>
</div>
))}
{/* Loading indicator */}
{isStreaming && (
<div className="streaming-indicator">
<div className="typing-dots">
<span></span>
<span></span>
<span></span>
</div>
<span>AI正在思考和回答中...</span>
</div>
)}
{/* Auto-scroll anchor */}
<div ref={messagesEndRef} />
</div>
{/* Chat Input */}
<form onSubmit={handleSubmit} className="chat-input-form">
<div className="input-container">
<textarea
value={input}
onChange={(e) => setInput(e.target.value)}
onKeyDown={handleKeyDown}
placeholder="输入您的问题..."
disabled={isStreaming}
rows={3}
className="chat-input"
/>
<div className="input-actions">
<button
type="submit"
disabled={!input.trim() || isStreaming}
className="send-button"
>
{isStreaming ? '发送中...' : '发送'}
</button>
{isStreaming && (
<button
type="button"
onClick={stopCurrentStream}
className="stop-button"
>
停止
</button>
)}
<button
type="button"
onClick={clearChat}
disabled={isStreaming}
className="clear-button"
>
清空
</button>
</div>
</div>
</form>
{/* Chat Controls */}
<div className="chat-controls">
<label className="chain-of-thought-toggle">
<input
type="checkbox"
checked={enableChainOfThought}
onChange={() => {
// This would need to be controlled by parent component
}}
disabled={isStreaming}
/>
<span>显示思维过程</span>
</label>
<div className="chat-stats">
<span>消息数: {messages.length}</span>
{isStreaming && <span className="analyzing">分析中...</span>}
{currentStreamId && <span className="stream-id">Stream: {currentStreamId.slice(-8)}</span>}
</div>
</div>
</div>
);
});
|
000haoji/deep-student
| 3,085 |
src/chat-core/components/MarkdownRenderer.tsx
|
import React from 'react';
import ReactMarkdown from 'react-markdown';
import remarkGfm from 'remark-gfm';
import remarkMath from 'remark-math';
import rehypeKatex from 'rehype-katex';
interface MarkdownRendererProps {
content: string;
className?: string;
}
// 预处理函数：处理LaTeX和空行
const preprocessContent = (content: string): string => {
if (!content) return '';
let processedContent = content;
// 专门处理 bmatrix 环境
processedContent = processedContent.replace(/\\begin{bmatrix}(.*?)\\end{bmatrix}/gs, (match, matrixContent) => {
// 移除每行末尾 \ 之前和之后的空格
let cleanedMatrix = matrixContent.replace(/\s*\\\\\s*/g, ' \\\\ '); // 保留一个空格以便阅读，KaTeX应能处理
// 移除 & 周围的空格
cleanedMatrix = cleanedMatrix.replace(/\s*&\s*/g, '&');
// 移除行首和行尾的空格
cleanedMatrix = cleanedMatrix.split(' \\\\ ').map((row: string) => row.trim()).join(' \\\\ ');
return `\\begin{bmatrix}${cleanedMatrix}\\end{bmatrix}`;
});
// 处理空行：将多个连续的空行减少为最多一个空行
processedContent = processedContent
// 将 Windows 风格的换行符统一为 Unix 风格
.replace(/\r\n/g, '\n')
// 移除行尾空格
.replace(/[ \t]+$/gm, '')
// 处理列表中的空项：移除只包含数字和点号的行（空列表项）
.replace(/^\s*\d+\.\s*$/gm, '')
// 处理列表中连续的空行
.replace(/(\d+\.\s*[^\n]*\n)\n+(?=\d+\.)/g, '$1\n')
// 将3个或以上连续换行符替换为最多2个
.replace(/\n{3,}/g, '\n\n')
// 处理空格行：包含只有空格的行
.replace(/\n[ \t]*\n/g, '\n\n')
// 特别处理列表项之间的空行
.replace(/(\d+\.\s*[^\n]*)\n\n+(\d+\.\s*[^\n]*)/g, '$1\n$2')
// 移除开头和结尾的多余空行
.replace(/^\n+/, '')
.replace(/\n+$/, '');
return processedContent;
};
export const MarkdownRenderer: React.FC<MarkdownRendererProps> = ({
content,
className = ''
}) => {
// 预处理内容，处理LaTeX公式和空行
const processedContent = preprocessContent(content);
return (
<div className={`markdown-content ${className}`}>
<ReactMarkdown
remarkPlugins={[remarkGfm, remarkMath]}
rehypePlugins={[
[rehypeKatex, {
throwOnError: false, // 不抛出错误，以红色显示错误内容
errorColor: '#cc0000',
strict: false, // 宽松模式
trust: false, // 安全模式
macros: {
'\\RR': '\\mathbb{R}',
'\\NN': '\\mathbb{N}',
'\\ZZ': '\\mathbb{Z}',
'\\QQ': '\\mathbb{Q}',
'\\CC': '\\mathbb{C}'
}
}]
]}
components={{
// 自定义代码块渲染
code: ({ node, inline, className, children, ...props }: any) => {
return !inline ? (
<pre className="code-block">
<code className={className} {...props}>
{children}
</code>
</pre>
) : (
<code className="inline-code" {...props}>
{children}
</code>
);
},
// 自定义表格渲染
table: ({ children }) => (
<div className="table-wrapper">
<table className="markdown-table">{children}</table>
</div>
),
}}
>
{processedContent}
</ReactMarkdown>
</div>
);
};
|
000haoji/deep-student
| 8,234 |
src/chat-core/components/AIChatInterface.tsx
|
/**
* AI Chat Interface using Vercel AI SDK
*
* This component replaces the custom streaming implementation with
* Vercel AI SDK's useChat hook for better performance and reliability.
*/
import React, { useState, useMemo } from 'react';
import { useChat } from '@ai-sdk/react';
import { createAISdkFetch } from '../utils/aiSdkAdapter';
import { convertFromTauriFormat } from '../utils/chatMessageConverter';
import { MarkdownRenderer } from './MarkdownRenderer';
import { MessageWithThinking } from './MessageWithThinking';
interface AIChatInterfaceProps {
tempId?: string;
mistakeId?: number;
initialMessages?: any[];
enableChainOfThought?: boolean;
onAnalysisStart?: () => void;
onAnalysisComplete?: (response: any) => void;
className?: string;
}
export const AIChatInterface = React.forwardRef<any, AIChatInterfaceProps>(({
tempId,
mistakeId,
initialMessages = [],
enableChainOfThought = true,
onAnalysisStart,
onAnalysisComplete,
className = ''
}, ref) => {
const [isAnalyzing, setIsAnalyzing] = useState(false);
// Convert initial messages to AI SDK format
const convertedInitialMessages = useMemo(() =>
convertFromTauriFormat(initialMessages),
[initialMessages]
);
// Determine API endpoint based on props
const apiEndpoint = useMemo(() => {
if (tempId) return '/api/continue-chat';
if (mistakeId) return '/api/mistake-chat';
return '/api/chat';
}, [tempId, mistakeId]);
// Initialize AI SDK useChat hook
const {
messages,
input,
handleInputChange,
handleSubmit,
isLoading,
error,
reload,
stop,
append,
setMessages
} = useChat({
api: apiEndpoint,
initialMessages: convertedInitialMessages,
fetch: createAISdkFetch(),
body: {
tempId,
mistakeId,
enableChainOfThought
},
onResponse: (response) => {
console.log('AI SDK Response received:', response.status);
if (onAnalysisStart) {
onAnalysisStart();
}
setIsAnalyzing(true);
},
onFinish: (message) => {
console.log('AI SDK Response finished:', message);
setIsAnalyzing(false);
if (onAnalysisComplete) {
onAnalysisComplete(message);
}
},
onError: (error) => {
console.error('AI SDK Error:', error);
setIsAnalyzing(false);
}
});
// Handle form submission with custom logic
const onSubmit = async (e: React.FormEvent<HTMLFormElement>) => {
e.preventDefault();
if (!input.trim() || isLoading) return;
setIsAnalyzing(true);
try {
await handleSubmit(e);
} catch (error) {
console.error('Chat submission error:', error);
setIsAnalyzing(false);
}
};
// Handle sending messages programmatically
const sendMessage = async (content: string, role: 'user' | 'assistant' = 'user') => {
if (!content.trim() || isLoading) return;
setIsAnalyzing(true);
try {
await append({
role,
content,
id: `msg-${Date.now()}`
});
} catch (error) {
console.error('Send message error:', error);
setIsAnalyzing(false);
}
};
// Expose sendMessage for external use
React.useImperativeHandle(ref, () => ({
sendMessage,
clearChat
}));
// Clear chat history
const clearChat = () => {
setMessages([]);
};
// Handle keyboard shortcuts
const handleKeyDown = (e: React.KeyboardEvent<HTMLTextAreaElement>) => {
if (e.key === 'Enter' && !e.shiftKey) {
e.preventDefault();
onSubmit(e as any);
}
};
return (
<div className={`ai-chat-interface ${className}`}>
{/* Chat Messages */}
<div className="chat-messages">
{messages.map((message, index) => (
<div key={message.id || index} className={`message ${message.role}`}>
<div className="message-header">
<span className="role">{message.role === 'user' ? '用户' : 'AI助手'}</span>
<span className="timestamp">
{new Date().toLocaleTimeString()}
</span>
</div>
<div className="message-content">
{message.role === 'assistant' ? (
<MessageWithThinking
content={message.content}
thinkingContent={(message as any).thinking_content}
isStreaming={isLoading && index === messages.length - 1}
role="assistant"
timestamp={new Date().toISOString()}
ragSources={(message as any).rag_sources}
/>
) : (
<div className="user-message">
<MarkdownRenderer content={message.content} />
</div>
)}
</div>
</div>
))}
{/* Loading indicator */}
{isLoading && (
<div className="message assistant">
<div className="message-header">
<span className="role">AI助手</span>
<span className="timestamp">正在回复...</span>
</div>
<div className="message-content">
<div className="loading-indicator">
<div className="typing-dots">
<span></span>
<span></span>
<span></span>
</div>
<span>正在分析中...</span>
</div>
</div>
</div>
)}
{/* Error display */}
{error && (
<div className="error-message">
<div className="error-content">
<span className="error-icon">⚠️</span>
<span className="error-text">
出错了: {error.message}
</span>
<button onClick={() => reload()} className="retry-button">
重试
</button>
</div>
</div>
)}
</div>
{/* Chat Input */}
<form onSubmit={onSubmit} className="chat-input-form">
<div className="input-container">
<textarea
value={input}
onChange={handleInputChange}
onKeyDown={handleKeyDown}
placeholder="输入您的问题..."
disabled={isLoading}
rows={3}
className="chat-input"
/>
<div className="input-actions">
<button
type="submit"
disabled={!input.trim() || isLoading}
className="send-button"
>
{isLoading ? '发送中...' : '发送'}
</button>
{isLoading && (
<button
type="button"
onClick={stop}
className="stop-button"
>
停止
</button>
)}
<button
type="button"
onClick={clearChat}
disabled={isLoading}
className="clear-button"
>
清空
</button>
</div>
</div>
</form>
{/* Chat Controls */}
<div className="chat-controls">
<label className="chain-of-thought-toggle">
<input
type="checkbox"
checked={enableChainOfThought}
onChange={() => {
// This would need to be passed up to parent component
// for now just show the current state
}}
disabled={isLoading}
/>
<span>显示思维过程</span>
</label>
<div className="chat-stats">
<span>消息数: {messages.length}</span>
{isAnalyzing && <span className="analyzing">分析中...</span>}
</div>
</div>
</div>
);
});
// Export utility functions for external use
export const useChatHelpers = () => {
return {
sendMessage: (chatRef: React.RefObject<any>, content: string) => {
if (chatRef.current?.sendMessage) {
chatRef.current.sendMessage(content);
}
},
clearChat: (chatRef: React.RefObject<any>) => {
if (chatRef.current?.clearChat) {
chatRef.current.clearChat();
}
}
};
};
|
000haoji/deep-student
| 10,206 |
src/chat-core/components/StreamingChatInterface.tsx
|
/**
* Streaming Chat Interface for AI SDK Analysis
*
* A simplified chat interface optimized for handling Tauri streaming events
* with proper thinking chain support and real-time rendering.
*/
import React, { useState, useImperativeHandle, useEffect, useRef } from 'react';
import { MessageWithThinking } from './MessageWithThinking';
import { MarkdownRenderer } from './MarkdownRenderer';
interface StreamingChatMessage {
id: string;
role: 'user' | 'assistant';
content: string;
thinking_content?: string;
timestamp: string;
rag_sources?: Array<{
document_id: string;
file_name: string;
chunk_text: string;
score: number;
chunk_index: number;
}>;
}
interface StreamingChatInterfaceProps {
messages: StreamingChatMessage[];
isStreaming: boolean;
enableChainOfThought?: boolean;
onSendMessage?: (message: string) => void;
className?: string;
streamingMode?: 'typewriter' | 'instant'; // 流式输出模式
}
export interface StreamingChatInterfaceRef {
sendMessage: (content: string) => void;
clearInput: () => void;
clearChat: () => void;
setMessages: (messages: StreamingChatMessage[]) => void;
}
export const StreamingChatInterface = React.forwardRef<StreamingChatInterfaceRef, StreamingChatInterfaceProps>(({
messages,
isStreaming,
enableChainOfThought = true,
onSendMessage,
className = '',
streamingMode = 'typewriter' // 默认使用打字机模式
}, ref) => {
const [input, setInput] = useState('');
const [displayedContent, setDisplayedContent] = useState<{[key: string]: string}>({});
const [isFullscreen, setIsFullscreen] = useState(false);
const [isAnimating, setIsAnimating] = useState(false);
const messagesEndRef = useRef<HTMLDivElement>(null);
const typewriterTimeouts = useRef<{[key: string]: number}>({});
const containerRef = useRef<HTMLDivElement>(null);
// Handle form submission
const handleSubmit = (e: React.FormEvent) => {
e.preventDefault();
if (!input.trim() || isStreaming) return;
if (onSendMessage) {
onSendMessage(input);
}
setInput('');
};
// Handle keyboard shortcuts
const handleKeyDown = (e: React.KeyboardEvent<HTMLTextAreaElement>) => {
if (e.key === 'Enter' && !e.shiftKey) {
e.preventDefault();
handleSubmit(e as any);
}
// ESC键退出全屏
if (e.key === 'Escape' && isFullscreen) {
handleToggleFullscreen();
}
};
// 全屏切换功能
const handleToggleFullscreen = () => {
if (isAnimating) return;
setIsAnimating(true);
if (isFullscreen) {
// 退出全屏
if (containerRef.current) {
containerRef.current.classList.add('collapsing');
containerRef.current.classList.remove('fullscreen');
}
setTimeout(() => {
setIsFullscreen(false);
setIsAnimating(false);
if (containerRef.current) {
containerRef.current.classList.remove('collapsing');
}
}, 500);
} else {
// 进入全屏
setIsFullscreen(true);
if (containerRef.current) {
containerRef.current.classList.add('expanding');
}
setTimeout(() => {
if (containerRef.current) {
containerRef.current.classList.remove('expanding');
containerRef.current.classList.add('fullscreen');
}
setIsAnimating(false);
}, 500);
}
};
// 处理全屏快捷键
useEffect(() => {
const handleKeyPress = (e: KeyboardEvent) => {
// F11或Ctrl+Enter切换全屏
if (e.key === 'F11' || (e.ctrlKey && e.key === 'Enter')) {
e.preventDefault();
handleToggleFullscreen();
}
};
if (isFullscreen) {
document.addEventListener('keydown', handleKeyPress);
return () => document.removeEventListener('keydown', handleKeyPress);
}
}, [isFullscreen]);
// 打字机效果的流式内容显示
useEffect(() => {
if (streamingMode === 'instant') return;
messages.forEach((message) => {
if (message.role === 'assistant' && message.content) {
const messageId = message.id;
const fullContent = message.content;
const currentDisplayed = displayedContent[messageId] || '';
// Only start typewriter if content has changed and is longer
if (fullContent !== currentDisplayed && fullContent.length > currentDisplayed.length) {
// Clear existing timeout for this message
if (typewriterTimeouts.current[messageId]) {
clearTimeout(typewriterTimeouts.current[messageId]);
}
// Start typewriter from current position
let currentIndex = currentDisplayed.length;
const typeNextChar = () => {
if (currentIndex < fullContent.length) {
const nextContent = fullContent.substring(0, currentIndex + 1);
setDisplayedContent(prev => ({
...prev,
[messageId]: nextContent
}));
currentIndex++;
// 根据字符类型调整显示速度
const char = fullContent[currentIndex - 1];
let delay = 25; // Base typing speed
if (char === ' ') delay = 8;
else if (char === '.' || char === '!' || char === '?') delay = 150;
else if (char === ',' || char === ';' || char === ':') delay = 80;
else if (char === '\n') delay = 100;
typewriterTimeouts.current[messageId] = setTimeout(typeNextChar, delay);
}
};
// Start typing animation
if (currentIndex < fullContent.length) {
typeNextChar();
}
}
}
});
return () => {
// Cleanup timeouts
Object.values(typewriterTimeouts.current).forEach(timeout => clearTimeout(timeout));
};
}, [messages, streamingMode, displayedContent]);
// 自动滚动到底部
useEffect(() => {
if (messagesEndRef.current) {
messagesEndRef.current.scrollIntoView({ behavior: 'smooth' });
}
}, [messages, displayedContent]);
// Get content for display (original or typewriter)
const getDisplayContent = (message: StreamingChatMessage) => {
if (message.role === 'user' || streamingMode === 'instant') {
return message.content;
}
return displayedContent[message.id] || '';
};
// Expose methods to parent component
useImperativeHandle(ref, () => ({
sendMessage: (content: string) => {
if (onSendMessage) {
onSendMessage(content);
}
},
clearInput: () => {
setInput('');
},
clearChat: () => {
setDisplayedContent({});
Object.values(typewriterTimeouts.current).forEach(timeout => clearTimeout(timeout));
typewriterTimeouts.current = {};
},
setMessages: (_newMessages: StreamingChatMessage[]) => {
// Reset displayed content for new messages
setDisplayedContent({});
}
}));
return (
<div
ref={containerRef}
className={`streaming-chat-interface ${className} ${isFullscreen ? 'fullscreen' : ''}`}
>
{/* 全屏工具栏 */}
<div className="chat-toolbar">
<div className="toolbar-left">
<span className="chat-title">💬 AI智能对话</span>
</div>
<div className="toolbar-right">
<button
onClick={handleToggleFullscreen}
disabled={isAnimating}
className="fullscreen-toggle-btn"
title={isFullscreen ? "退出全屏 (ESC)" : "进入全屏 (F11)"}
>
{isFullscreen ? '⤋' : '⤢'}
</button>
</div>
</div>
{/* Chat Messages */}
<div className="chat-messages">
{messages.map((message, index) => (
<div key={message.id} className={`message-wrapper ${message.role}`}>
<div className="message-header">
<span className="role">{message.role === 'user' ? '用户' : 'AI助手'}</span>
<span className="timestamp">
{new Date(message.timestamp).toLocaleTimeString()}
</span>
</div>
{message.role === 'assistant' ? (
<MessageWithThinking
content={getDisplayContent(message)}
thinkingContent={message.thinking_content}
isStreaming={isStreaming && index === messages.length - 1}
role="assistant"
timestamp={message.timestamp}
ragSources={message.rag_sources}
/>
) : (
<div className="user-message-content">
<MarkdownRenderer content={message.content} />
</div>
)}
</div>
))}
{/* Streaming indicator */}
{isStreaming && (
<div className="streaming-indicator">
<div className="typing-dots">
<span></span>
<span></span>
<span></span>
</div>
<span className="streaming-text">AI正在思考和回答中...</span>
</div>
)}
{/* Auto-scroll anchor */}
<div ref={messagesEndRef} />
</div>
{/* Chat Input */}
<form onSubmit={handleSubmit} className="chat-input-form">
<div className="input-container">
<textarea
value={input}
onChange={(e) => setInput(e.target.value)}
onKeyDown={handleKeyDown}
placeholder="继续提问..."
disabled={isStreaming}
rows={3}
className="chat-input"
/>
<div className="input-actions">
<button
type="submit"
disabled={!input.trim() || isStreaming}
className="send-button"
>
{isStreaming ? '回答中...' : '发送'}
</button>
</div>
</div>
</form>
{/* Chat Info */}
<div className="chat-info">
<div className="chat-stats">
<span>消息数: {messages.length}</span>
{isStreaming && <span className="streaming-status">🔄 流式回答中</span>}
{enableChainOfThought && <span className="thinking-status">🧠 显示思维过程</span>}
</div>
</div>
</div>
);
});
StreamingChatInterface.displayName = 'StreamingChatInterface';
|
000haoji/deep-student
| 4,446 |
src/chat-core/components/StreamingMarkdownRenderer.tsx
|
import React, { useState, useEffect, useMemo } from 'react';
import { MarkdownRenderer } from './MarkdownRenderer';
interface StreamingMarkdownRendererProps {
content: string;
isStreaming: boolean;
chainOfThought?: {
enabled: boolean;
details?: any;
};
}
type ParsedContent = {
thinkingContent: string;
mainContent: string;
}
// 流式内容预处理函数
const preprocessStreamingContent = (content: string, isStreaming: boolean) => {
if (!content) return { content: '', hasPartialMath: false };
let processed = content;
let hasPartialMath = false;
// 检测不完整的数学公式
const incompletePatterns = [
/\$[^$]*$/, // 以$结尾但没有关闭$
/\$\$[^$]*$/, // 以$$结尾但没有关闭$$
/\\begin\{[^}]*\}[^\\]*$/, // 不完整的环境
/\\[a-zA-Z]+\{[^}]*$/, // 不完整的命令
];
if (isStreaming) {
// 更精确地检测不完整的数学公式
hasPartialMath = incompletePatterns.some(pattern => pattern.test(processed));
// 不要隐藏不完整的公式，而是保持原样并添加指示符
// 让用户看到正在输入的数学内容，即使还不完整
if (hasPartialMath) {
// 检查是否是真正的不完整公式（而不是正常的LaTeX语法）
const hasOpenMath = (processed.match(/\$/g) || []).length % 2 !== 0;
const hasOpenDisplayMath = (processed.match(/\$\$/g) || []).length % 2 !== 0;
// 只有当确实存在未闭合的数学公式时才标记为不完整
if (hasOpenMath || hasOpenDisplayMath) {
// 保持内容不变，只是标记状态
hasPartialMath = true;
} else {
hasPartialMath = false;
}
}
}
return { content: processed, hasPartialMath };
};
export const StreamingMarkdownRenderer: React.FC<StreamingMarkdownRendererProps> = ({
content,
isStreaming
}) => {
const [displayContent, setDisplayContent] = useState('');
const [showCursor, setShowCursor] = useState(true);
const [isPartialMath, setIsPartialMath] = useState(false);
useEffect(() => {
// 对流式内容进行智能处理
const processedContent = preprocessStreamingContent(content, isStreaming);
setDisplayContent(processedContent.content);
setIsPartialMath(processedContent.hasPartialMath);
}, [content, isStreaming]);
useEffect(() => {
if (isStreaming) {
const interval = setInterval(() => {
setShowCursor(prev => !prev);
}, 500);
return () => clearInterval(interval);
} else {
setShowCursor(false);
}
}, [isStreaming]);
// 解析思维链内容
const parseChainOfThought = (content: string): ParsedContent | null => {
// 检查是否包含 <thinking> 标签
const thinkingMatch = content.match(/<thinking>([\s\S]*?)<\/thinking>\s*/);
if (thinkingMatch) {
const thinkingContent = thinkingMatch[1].trim();
const mainContent = content.replace(thinkingMatch[0], '').trim();
return {
thinkingContent,
mainContent
};
}
return null;
};
const parsedContent = parseChainOfThought(displayContent);
// 使用 useMemo 优化性能
const renderedContent = useMemo(() => {
if (!displayContent) return null;
return <MarkdownRenderer content={displayContent} />;
}, [displayContent]);
return (
<div className="streaming-markdown">
{parsedContent ? (
<>
{/* 渲染思维链内容 */}
{parsedContent.thinkingContent && (
<div className="chain-of-thought">
<div className="chain-header">
<span className="chain-icon">🧠</span>
<span className="chain-title">AI 思考过程</span>
</div>
<div className="thinking-content">
<MarkdownRenderer content={parsedContent.thinkingContent} />
</div>
</div>
)}
{/* 渲染主要内容 */}
<div className="main-content">
{parsedContent.mainContent ? (
<MarkdownRenderer content={parsedContent.mainContent} />
) : (
renderedContent
)}
{isStreaming && showCursor && (
<span className="streaming-cursor">▋</span>
)}
{isPartialMath && isStreaming && (
<span className="partial-math-indicator" title="正在输入数学公式...">📝</span>
)}
</div>
</>
) : (
<div className="normal-content">
{renderedContent}
{isStreaming && showCursor && (
<span className="streaming-cursor">▋</span>
)}
{isPartialMath && isStreaming && (
<span className="partial-math-indicator" title="正在输入数学公式...">📝</span>
)}
</div>
)}
</div>
);
};
|
000linlin/ConsisLoRA
| 5,801 |
inference.py
|
import os
from pipeline_demo import StableDiffusionXLPipelineLoraGuidance
def inference(
pipeline: StableDiffusionXLPipelineLoraGuidance,
prompt: str,
content_image_lora_path: str = None,
style_image_lora_path: str = None,
add_positive_content_prompt: str = None,
add_negative_content_prompt: str = None,
add_positive_style_prompt: str = None,
add_negative_style_prompt: str = None,
lora_scaling: list[float] = [1., 1.],
guidance_scale: float = 7.5,
content_guidance_scale: float = 0.,
style_guidance_scale: float = 0.,
num_images_per_prompt: int = 1,
num_steps: int = 30,
output_dir: str = "inference-image",
generator=None
):
pipeline.unload_lora_checkpoint()
pipeline.load_lora_checkpoint(content_image_lora_path, style_image_lora_path)
images = pipeline(
prompt=prompt,
lora_scaling=lora_scaling,
guidance_scale=guidance_scale,
num_inference_steps=num_steps,
add_positive_content_prompt=add_positive_content_prompt,
add_negative_content_prompt=add_negative_content_prompt,
add_positive_style_prompt=add_positive_style_prompt,
add_negative_style_prompt=add_negative_style_prompt,
content_guidance_scale=content_guidance_scale,
style_guidance_scale=style_guidance_scale,
num_images_per_prompt=num_images_per_prompt,
generator=generator
).images
os.makedirs(output_dir, exist_ok=True)
# save
for i, image in enumerate(images):
image.save(os.path.join(output_dir, f'{i}.jpg'))
print(f"saved images for {output_dir}")
if __name__ == "__main__":
import argparse
import torch
parser = argparse.ArgumentParser(description="inference script")
parser.add_argument("--prompt",
type=str,
required=True,
help="Inference prompt."
)
parser.add_argument(
"--content_image_lora_path",
type=str,
default=None,
help="The Path for ConsisLoRA trained on the content image."
)
parser.add_argument(
"--style_image_lora_path",
type=str,
default=None,
help="The Path for ConsisLoRA trained on the style image."
)
parser.add_argument(
"--add_positive_content_prompt",
type=str,
default=None,
help="The positive prompt for content guidance. if content_guidance_scale=0, this prompt will be ignored."
)
parser.add_argument(
"--add_negative_content_prompt",
type=str,
default=None,
help="The negative prompt for content guidance. if content_guidance_scale=0, this prompt will be ignored."
)
parser.add_argument(
"--add_positive_style_prompt",
type=str,
default=None,
help="The positive prompt for style guidance. if style_guidance_scale=0, this prompt will be ignored."
)
parser.add_argument(
"--add_negative_style_prompt",
type=str,
default=None,
help="The negative prompt for style guidance. if style_guidance_scale=0, this prompt will be ignored."
)
parser.add_argument(
"--lora_scaling",
type=float,
nargs="+",
default=[1., 1.],
help="List of scaling factors for LoRA, i.g., [content_lora_scaling, style_lora_scaling]."
)
parser.add_argument(
"--guidance_scale",
type=float,
default=7.5,
help="Guidance scale as defined in [Classifier-Free Diffusion Guidance](https://arxiv.org/abs/2207.12598)."
)
parser.add_argument(
"--content_guidance_scale",
type=float,
default=0.,
help="Guidance scale for enhancing content."
)
parser.add_argument(
"--style_guidance_scale",
type=float,
default=0.,
help="Guidance scale for enhancing style."
)
parser.add_argument(
"--num_images_per_prompt",
type=int,
default=1,
help="number of images per prompt."
)
parser.add_argument(
"--num_steps",
type=int,
default=30,
help="The number of denoising steps."
)
parser.add_argument(
"--output_dir",
type=str,
default="inference-images",
help="The path to save the images"
)
parser.add_argument(
"--seed",
type=int,
default=29,
help="A seed for reproducible inference."
)
args = parser.parse_args()
generator=torch.manual_seed(args.seed)
device = "cuda"
pipeline = StableDiffusionXLPipelineLoraGuidance.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
torch_dtype=torch.float16,
).to(device)
from diffusers import EulerDiscreteScheduler
pipeline.scheduler = EulerDiscreteScheduler.from_config(
pipeline.scheduler.config,
timestep_spacing="trailing"
)
inference(
pipeline=pipeline,
prompt=args.prompt,
content_image_lora_path=args.content_image_lora_path,
style_image_lora_path=args.style_image_lora_path,
add_positive_content_prompt=args.add_positive_content_prompt,
add_negative_content_prompt=args.add_negative_content_prompt,
add_positive_style_prompt=args.add_positive_style_prompt,
add_negative_style_prompt=args.add_negative_style_prompt,
lora_scaling=args.lora_scaling,
guidance_scale=args.guidance_scale,
content_guidance_scale=args.content_guidance_scale,
style_guidance_scale=args.style_guidance_scale,
num_images_per_prompt=args.num_images_per_prompt,
num_steps=args.num_steps,
output_dir=args.output_dir,
generator=generator
)
|
000haoji/deep-student
| 1,929 |
src/chat-core/types/chat.ts
|
/**
* Chat Core Type Definitions
*
* 聊天核心模块的类型定义
*/
// RAG知识库来源信息
export interface RagSourceInfo {
document_id: string;
file_name: string;
chunk_text: string;
score: number;
chunk_index: number;
}
// 多模态内容块类型
export type ChatMessageContentPart =
| { type: 'text'; text: string }
| { type: 'image_url'; image_url: { url: string; detail?: 'low' | 'high' | 'auto' } };
// 追问时上传的图片文件基本信息
export interface UploadedImageInfo {
id: string; // 临时客户端ID
name: string;
type?: string; // MIME type
size?: number; // 文件大小
base64_data: string; // 图片的Base64编码
file?: File; // 原始File对象，可选
}
// 基础聊天消息类型
export interface ChatMessage {
id?: string; // 消息的唯一ID，前端生成或后端返回
role: 'user' | 'assistant' | 'system';
content: string | ChatMessageContentPart[]; // 支持旧的字符串格式和新的多模态数组格式
timestamp: string;
thinking_content?: string;
rag_sources?: RagSourceInfo[];
}
// 流式消息类型
export interface StreamMessage extends ChatMessage {
isStreaming?: boolean;
streamId?: string;
}
// 流式数据块类型
export interface StreamChunk {
content: string;
is_complete: boolean;
chunk_id?: string;
timestamp?: string;
}
// 流式选项类型
export interface StreamOptions {
enableChainOfThought?: boolean;
enableRag?: boolean;
ragOptions?: {
top_k: number;
enable_reranking?: boolean;
};
autoScroll?: boolean;
showTypingIndicator?: boolean;
}
// 聊天界面配置
export interface ChatInterfaceConfig {
enableFullscreen?: boolean;
enableImageUpload?: boolean;
maxImages?: number;
showThinking?: boolean;
showRagSources?: boolean;
showTimestamp?: boolean;
enableKeyboardShortcuts?: boolean;
}
// 思维链相关类型
export interface ThinkingChainOptions {
enabled: boolean;
expandedByDefault?: boolean;
showIcon?: boolean;
customIcon?: string;
}
// 消息渲染选项
export interface MessageRenderOptions {
showCursor?: boolean;
enableLatex?: boolean;
enableCodeHighlight?: boolean;
enableTableRender?: boolean;
}
|
000haoji/deep-student
| 2,365 |
src/chat-core/utils/streamHandler.ts
|
import { listen } from '@tauri-apps/api/event';
export interface StreamChunk {
content: string;
is_complete: boolean;
chunk_id: string;
}
export class StreamHandler {
private listeners: Map<string, (chunk: StreamChunk) => void> = new Map();
private unlistenFunctions: Map<string, () => void> = new Map();
// 开始监听流式事件
async startListening(eventName: string, onChunk: (chunk: StreamChunk) => void): Promise<void> {
// 如果已经在监听这个事件，先停止
if (this.unlistenFunctions.has(eventName)) {
this.stopListening(eventName);
}
this.listeners.set(eventName, onChunk);
try {
const unlisten = await listen<StreamChunk>(eventName, (event) => {
const chunk = event.payload;
// 详细的控制台调试输出
console.group(`🔄 流式数据 [${eventName}]`);
console.log('📦 数据块ID:', chunk.chunk_id);
console.log('📝 内容长度:', chunk.content.length);
console.log('✅ 是否完成:', chunk.is_complete);
if (chunk.content.length > 0) {
console.log('📄 内容预览:', chunk.content.length > 100 ?
chunk.content.substring(0, 100) + '...' : chunk.content);
}
console.groupEnd();
// 如果内容不为空，显示实时内容
if (chunk.content.length > 0) {
console.log(`💬 实时输出: ${chunk.content}`);
}
// 调用回调函数处理数据块
onChunk(chunk);
// 如果流完成，自动停止监听
if (chunk.is_complete) {
console.log(`🎉 流式输出完成 [${eventName}]`);
this.stopListening(eventName);
}
});
this.unlistenFunctions.set(eventName, unlisten);
console.log(`🎧 开始监听流式事件: ${eventName}`);
} catch (error) {
console.error(`❌ 监听流式事件失败 [${eventName}]:`, error);
throw error;
}
}
// 停止监听流式事件
stopListening(eventName: string): void {
const unlisten = this.unlistenFunctions.get(eventName);
if (unlisten) {
unlisten();
this.unlistenFunctions.delete(eventName);
this.listeners.delete(eventName);
console.log(`停止监听流式事件: ${eventName}`);
}
}
// 停止所有监听
stopAllListening(): void {
for (const eventName of this.unlistenFunctions.keys()) {
this.stopListening(eventName);
}
}
// 检查是否正在监听某个事件
isListening(eventName: string): boolean {
return this.unlistenFunctions.has(eventName);
}
}
// 创建全局实例
export const streamHandler = new StreamHandler();
|
000haoji/deep-student
| 1,983 |
src/chat-core/utils/chatMessageConverter.ts
|
/**
* Chat Message Converter
*
* Utilities for converting between different chat message formats.
* Single responsibility: Message format conversion.
*/
export interface ChatMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp?: string;
}
export interface TauriChatMessage {
role: string;
content: string;
thinking_content?: string;
timestamp?: string;
}
/**
* Convert Tauri chat history to standard ChatMessage format
*/
export function convertFromTauriFormat(tauriHistory: TauriChatMessage[]): ChatMessage[] {
return tauriHistory.map((msg, index) => ({
id: `msg-${Date.now()}-${index}`,
role: msg.role as 'user' | 'assistant' | 'system',
content: msg.content,
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
}));
}
/**
* Convert ChatMessage format to Tauri backend format
*/
export function convertToTauriFormat(messages: ChatMessage[]): TauriChatMessage[] {
return messages.map(msg => ({
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
}));
}
/**
* Create a new chat message
*/
export function createChatMessage(
role: 'user' | 'assistant' | 'system',
content: string,
thinking_content?: string
): ChatMessage {
return {
id: `msg-${Date.now()}-${Math.random().toString(36).substr(2, 9)}`,
role,
content,
thinking_content,
timestamp: new Date().toISOString()
};
}
/**
* Merge thinking content into a chat message
*/
export function addThinkingToMessage(message: ChatMessage, thinking: string): ChatMessage {
return {
...message,
thinking_content: (message.thinking_content || '') + thinking
};
}
/**
* Update message content
*/
export function updateMessageContent(message: ChatMessage, content: string): ChatMessage {
return {
...message,
content
};
}
|
000haoji/deep-student
| 5,384 |
src/chat-core/utils/simplifiedApiAdapter.ts
|
/**
* Simplified API Adapter
*
* Replaces the complex aiSdkAdapter.ts with a simpler implementation
* that leverages the unified stream handler.
*/
import { invoke } from '@tauri-apps/api/core';
import { unifiedStreamHandler, StreamRequest, StreamOptions, StreamMessage as _StreamMessage } from './unifiedStreamHandler';
export interface ChatMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp?: string;
}
export interface AnalysisRequest {
imageData?: string;
userInput?: string;
chatHistory?: ChatMessage[];
enableChainOfThought?: boolean;
}
/**
* Simplified API calls that use the unified stream handler
*/
export const simplifiedApi = {
/**
* Analyze step by step with streaming
*/
async analyzeStepByStep(
imageData: string,
userInput: string,
options: StreamOptions & { enableChainOfThought?: boolean } = {}
): Promise<string> {
const request: StreamRequest = {
type: 'analysis',
imageData,
userInput,
enableChainOfThought: options.enableChainOfThought !== false
};
return unifiedStreamHandler.startStream(request, options);
},
/**
* Start chat with streaming
*/
async startChat(
chatHistory: ChatMessage[] = [],
options: StreamOptions & { enableChainOfThought?: boolean } = {}
): Promise<string> {
const request: StreamRequest = {
type: 'chat',
chatHistory: chatHistory.map(msg => ({
id: msg.id,
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
})),
enableChainOfThought: options.enableChainOfThought !== false
};
return unifiedStreamHandler.startStream(request, options);
},
/**
* Continue chat with streaming
*/
async continueChat(
tempId: string,
chatHistory: ChatMessage[] = [],
options: StreamOptions & { enableChainOfThought?: boolean } = {}
): Promise<string> {
const request: StreamRequest = {
type: 'continue_chat',
tempId,
chatHistory: chatHistory.map(msg => ({
id: msg.id,
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
})),
enableChainOfThought: options.enableChainOfThought !== false
};
return unifiedStreamHandler.startStream(request, options);
},
/**
* Stop a specific stream
*/
stopStream(streamId: string): void {
unifiedStreamHandler.stopStream(streamId);
},
/**
* Stop all streams
*/
stopAllStreams(): void {
unifiedStreamHandler.stopAllStreams();
},
/**
* Get current progress for a stream
*/
getStreamProgress(streamId: string): { content: string; thinking: string } | null {
return unifiedStreamHandler.getProgress(streamId);
},
/**
* Check if a stream is active
*/
isStreamActive(streamId: string): boolean {
return unifiedStreamHandler.isStreamActive(streamId);
}
};
/**
* Non-streaming utility functions for direct backend calls
*/
export const directApi = {
async getMistakeChatHistory(mistakeId: number): Promise<ChatMessage[]> {
const result = await invoke('get_mistake_chat_history', { mistakeId });
return this.convertChatHistory(result as any[]);
},
async getAllMistakes(): Promise<any[]> {
return invoke('get_all_mistakes');
},
async saveMistake(mistake: any): Promise<number> {
return invoke('save_mistake', { mistake });
},
async deleteMistake(mistakeId: number): Promise<void> {
return invoke('delete_mistake', { mistakeId });
},
async updateMistake(mistakeId: number, updates: any): Promise<void> {
return invoke('update_mistake', { mistakeId, updates });
},
async getApiConfigurations(): Promise<any> {
return invoke('get_api_configurations');
},
async saveApiConfigurations(configs: any): Promise<void> {
return invoke('save_api_configurations', { configs });
},
/**
* Convert backend chat history to frontend format
*/
convertChatHistory(backendHistory: any[]): ChatMessage[] {
return backendHistory.map((msg, index) => ({
id: msg.id || `msg-${index}`,
role: msg.role as 'user' | 'assistant',
content: msg.content || '',
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
}));
},
/**
* Convert frontend messages to backend format
*/
convertToBackendFormat(messages: ChatMessage[]): any[] {
return messages.map(msg => ({
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content,
timestamp: msg.timestamp || new Date().toISOString()
}));
}
};
/**
* Combined API object that includes both streaming and direct calls
*/
export const api = {
...simplifiedApi,
...directApi
};
// Export individual functions for backward compatibility
export const {
analyzeStepByStep,
startChat,
continueChat,
stopStream,
stopAllStreams,
getStreamProgress,
isStreamActive
} = simplifiedApi;
export const {
getMistakeChatHistory,
getAllMistakes,
saveMistake,
deleteMistake,
updateMistake,
getApiConfigurations,
saveApiConfigurations,
convertChatHistory,
convertToBackendFormat
} = directApi;
|
000haoji/deep-student
| 3,037 |
src/chat-core/utils/aiSdkAdapter.ts
|
/**
* AI SDK Adapter for Tauri Backend
*
* Simplified adapter focused on AI SDK integration.
* Uses separated modules for stream handling and API communication.
*/
import { createAnalysisStream, createChatStream } from './tauriStreamAdapter';
import { tauriApiClient } from './tauriApiClient';
import { convertToTauriFormat, type ChatMessage } from './chatMessageConverter';
export interface AnalysisRequest {
imageData?: string;
userInput?: string;
chatHistory?: ChatMessage[];
enableChainOfThought?: boolean;
}
/**
* Custom fetch implementation for AI SDK compatibility
* Routes requests to appropriate stream handlers
*/
export async function createTauriStreamingFetch(
url: string,
options: RequestInit & { body?: string }
): Promise<Response> {
const requestData = JSON.parse(options.body as string);
if (url.includes('/api/analysis')) {
const { imageData, userInput, enableChainOfThought = true } = requestData;
return createAnalysisStream(imageData, userInput, enableChainOfThought);
}
if (url.includes('/api/chat') || url.includes('/api/continue-chat')) {
const { tempId, chatHistory, enableChainOfThought = true } = requestData;
const tauriHistory = convertToTauriFormat(chatHistory || []);
return createChatStream(tempId, tauriHistory, enableChainOfThought);
}
throw new Error(`Unsupported endpoint: ${url}`);
}
/**
* Create a custom fetch function for AI SDK
*/
export function createAISdkFetch() {
return async (input: RequestInfo | URL, init?: RequestInit) => {
const url = typeof input === 'string' ? input : input.toString();
const options = { ...init, body: init?.body as string };
if (url.startsWith('/api/')) {
return createTauriStreamingFetch(url, options);
}
return fetch(input, init);
};
}
/**
* Simplified API adapter using the dedicated client
*/
export const tauriApiAdapter = {
async analyzeStepByStep(imageData: string, userInput: string, enableChainOfThought = true) {
const base64Data = imageData.startsWith('data:') ? imageData : `data:image/jpeg;base64,${imageData}`;
return tauriApiClient.analyzeStepByStep({
subject: "数学",
question_image_files: [base64Data],
analysis_image_files: [],
user_question: userInput,
enable_chain_of_thought: enableChainOfThought
});
},
async getChatHistory(tempId: string) {
console.log('getChatHistory called for tempId:', tempId);
return [];
},
async startStreamingAnswer(tempId: string, enableChainOfThought = true) {
return tauriApiClient.startStreamingAnswer(tempId, enableChainOfThought);
},
async continueChatStream(tempId: string, chatHistory: any[], enableChainOfThought = true) {
return tauriApiClient.continueChatStream(tempId, chatHistory, enableChainOfThought);
},
async getMistakeChatHistory(mistakeId: number) {
return tauriApiClient.getMistakeChatHistory(mistakeId);
},
async getAllMistakes() {
return tauriApiClient.getAllMistakes();
}
};
|
0015/esp_rlottie
| 5,975 |
README.md
|
# IDF component for using rLottie in ESP32 projects
## Disclaimer
**This project is a forked version of the Samsung/rlottie project. Therefore, the source code used in this project also follows the original license. For more details, check this out. (https://github.com/Samsung/rlottie/)**
### What is Lottie?
Lottie is a JSON-based animation file. Lottie allows designers to move animations as easily as images. It is small in size, works on any device, and can be freely resized without losing resolution.
### Why should we use Lottie?
Lottie has several advantages over other animation file formats:
1. Compact File Size
* Lottie animations offer a significantly smaller file size compared to other formats such as GIF or MP4 while preserving high-quality visuals.
2. Scalable Vector Graphics
* Being vector-based, Lottie animations can be resized freely without losing resolution, allowing them to scale up or down effortlessly.
3. Cross-Platform Compatibility
* Lottie animations are easily integrated across multiple platforms and libraries, making them straightforward for developers to implement. They work seamlessly on iOS, Android, Web, and React Native without the need for any modifications.
### Then what is the rLottie?
* Developed by: Samsung
* Features: rLottie (Rapid Lottie) is an optimized version of Lottie, primarily focused on performance improvements.
Designed to be lightweight and faster, particularly for use in environments with limited resources.
It also supports the JSON format for animations exported from Adobe After Effects.
While it maintains compatibility with Lottie animations, it emphasizes speed and efficiency, making it suitable for embedded systems or applications where performance is critical.
### rLottie Component for ESP32 Project
This rLottie component for an ESP32 project, which is designed to be integrated within the ESP-IDF (Espressif IoT Development Framework) environment. This component allows the rLottie animations to be played on the ESP32 by leveraging the LVGL (Light and Versatile Graphics Library).(https://docs.lvgl.io/master/index.html)
### Comprehensive Setup Guide for Using rLottie with LVGL on ESP32
This guide walks you through the process of setting up an ESP32 project with the rLottie component using LVGL, including preparing the display driver.
1. Setting Up ESP-IDF Environment:
* Ensure that the ESP-IDF is installed and set up correctly on your development machine.
* Follow the official ESP-IDF installation guide(https://idf.espressif.com/) to get started if you haven't already.
2. Preparing the Display Driver
* Each hardware device is different, so you need to prepare and ensure your display driver is ready to run LVGL in the IDF environment.
* Recommended Components:
- espressif/esp_lvgl_port
- espressif/esp_lcd
3. Add LVGL component to your project
* This rLottie is a component for using LVGL's lottie player, so you must configure the LVGL environment.
If you add it through ESP Component Registry, it will be registered in managed_components folder, so cmake modification is not possible, so please put it directly in the component folder through Git.
```
mkdir components
cd components
git clone https://github.com/lvgl/lvgl.git
```
4. Including rLottie Component:
* Clone the `esp_rlottie` component in the components directory of your ESP-IDF project.
```
git clone https://github.com/0015/esp_rlottie.git
```
* The directory structure might look like this:
```
your_project/
├── components/
│ ├── esp_rlottie/
│ │ ├── rlottie/
│ │ │ ├── inc/
│ │ │ ├── src/
│ │ │ ├── CMakeLists.txt
│ │ │ └── ...
│ │ └── CMakeLists.txt
│ ├── lvgl/
│ │ ├── lvgl.h
│ │ ├── env_support/
│ │ │ ├── cmake/
│ │ │ │ ├── esp.cmake
│ │ └── CMakeLists.txt
├── main/
│ ├── main.c
│ └── CMakeLists.txt
├── CMakeLists.txt
└── sdkconfig
```
5. Configuration Files
* LVGL `esp.cmake`
Ensure that `esp_rlottie` is included in the idf_component_register REQUIRES list in `components/lvgl/env_support/cmake/esp.cmake`:
```
idf_component_register(SRCS ${SOURCES} ${EXAMPLE_SOURCES} ${DEMO_SOURCES}
INCLUDE_DIRS ${LVGL_ROOT_DIR} ${LVGL_ROOT_DIR}/src ${LVGL_ROOT_DIR}/../
${LVGL_ROOT_DIR}/examples ${LVGL_ROOT_DIR}/demos
REQUIRES esp_timer esp_rlottie)
```
* To enable the Lottie library among the LVGL configuration 3rd Party Libraries in `sdkconfig` or `menuconfig` tool, you'll need to ensure that your project includes the necessary configuration options.
```
# Enable LVGL
CONFIG_LVGL_ENABLE=y
# Enable 3rd Party Libraries in LVGL
CONFIG_LVGL_USE_LOTTIE=y
```
6. Main Application Code
In your `main/main.c`, you need to register `lvgl` since `esp_rlottie` depends on it:
```
idf_component_register(
SRCS "main.c"
INCLUDE_DIRS "."
REQUIRES lvgl
)
```
Here's a simplified `main.c`:
```
#include "lvgl.h"
...
const char battery[] = "Escape string in JSON";
...
void rlottie_display()
{
lv_obj_t *scr = lv_screen_active();
lv_obj_t *lottie = lv_rlottie_create_from_raw(scr, 100, 100, (const char *)battery);
lv_obj_center(lottie);
}
```
## Memory Issues
When working with animations and graphics on the ESP32, memory management is critical due to the limited resources available on the microcontroller. The error in `multi_heap_internal_lock` typically indicates a memory allocation issue.
* Large memory allocations can lead to fragmentation, especially if there are many small allocations followed by large ones. The heap might have enough total free space, but not in contiguous blocks.
* The ESP32 has limited memory, and large objects (like high-resolution animations) can exhaust the available RAM.
* If the stack size for a task is too small, large allocations or deep recursion might cause a stack overflow.
* High-priority tasks or inappropriate use of locks can lead to deadlocks or priority inversion issues.
|
0015/esp_rlottie
| 2,984 |
rlottie/meson.build
|
project('rlottie',
'cpp',
default_options : ['cpp_std=c++14', 'optimization=s'],
version : '0.2',
license : 'MIT',
meson_version : '>=0.49',
)
add_project_arguments('-DDEMO_DIR="@0@/example/resource/"'.format(meson.current_source_dir()), language : 'cpp')
inc = [include_directories('inc')]
config_dir = include_directories('.')
inc += config_dir
config_h = configuration_data()
if get_option('thread') == true
config_h.set10('LOTTIE_THREAD_SUPPORT', true)
endif
if get_option('module') == true
config_h.set10('LOTTIE_IMAGE_MODULE_SUPPORT', true)
if meson.get_compiler('cpp').get_id() != 'msvc'
lib_prefix = 'lib'
else
lib_prefix = ''
endif
if host_machine.system() == 'darwin'
lib_suffix = '.dylib'
elif host_machine.system() == 'windows'
lib_suffix = '.dll'
else
lib_suffix = '.so'
endif
if get_option('moduledir') != ''
config_h.set_quoted('LOTTIE_IMAGE_MODULE_PLUGIN',
get_option('prefix') / get_option('moduledir') / lib_prefix + 'rlottie-image-loader' + lib_suffix)
else
config_h.set_quoted('LOTTIE_IMAGE_MODULE_PLUGIN', lib_prefix + 'rlottie-image-loader' + lib_suffix)
endif
endif
if get_option('cache') == true
config_h.set10('LOTTIE_CACHE_SUPPORT', true)
endif
if get_option('log') == true
config_h.set10('LOTTIE_LOGGING_SUPPORT', true)
endif
if get_option('dumptree') == true
config_h.set10('LOTTIE_LOGGING_SUPPORT', true)
config_h.set10('LOTTIE_DUMP_TREE_SUPPORT', true)
endif
configure_file(
output: 'config.h',
configuration: config_h
)
subdir('inc')
subdir('src')
if get_option('example') == true
subdir('example')
endif
if get_option('test') == true
subdir('test')
endif
if get_option('cmake') == true and host_machine.system() != 'windows'
cmake_bin = find_program('cmake', required: false)
if cmake_bin.found()
cmake = import('cmake')
cmake.write_basic_package_version_file(
version: meson.project_version(),
name: 'rlottie',
)
cmakeconf = configuration_data()
cmakeconf.set('VERSION', meson.project_version())
cmake.configure_package_config_file(
input: meson.current_source_dir() + '/cmake/rlottieConfig.cmake.in',
name: 'rlottie',
configuration: cmakeconf,
)
endif
endif
summary = '''
Summary:
rlottie version : @0@
Build type : @1@
Thread Support : @2@
Module Support : @3@
Cache Support : @4@
Example : @5@
Test : @6@
Prefix : @7@
'''.format(
meson.project_version(),
get_option('buildtype'),
get_option('thread'),
get_option('module'),
get_option('cache'),
get_option('example'),
get_option('test'),
get_option('prefix'),
)
message(summary)
|
000haoji/deep-student
| 10,969 |
src/chat-core/utils/unifiedStreamManager.ts
|
/**
* 统一流式处理管理器
*
* 替代项目中的多种流式处理实现，提供统一、一致的流式数据处理方案
* 支持所有现有的流式场景：分析、对话、回顾分析等
*/
import { listen } from '@tauri-apps/api/event';
import React from 'react';
export interface StreamChunk {
content: string;
is_complete: boolean;
chunk_id: string;
}
export interface StreamMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp: string;
}
export interface StreamOptions {
enableChainOfThought?: boolean;
onChunk?: (chunk: string) => void;
onThinking?: (thinking: string) => void;
onComplete?: (fullResponse: string, thinkingContent?: string) => void;
onError?: (error: string) => void;
onProgress?: (progress: { content: string; thinking?: string }) => void;
}
export interface StreamRequest {
type: 'analysis' | 'chat' | 'continue_chat' | 'review_analysis' | 'review_chat';
tempId?: string;
mistakeId?: string;
reviewId?: string;
imageData?: string[];
userInput?: string;
chatHistory?: StreamMessage[];
subject?: string;
enableChainOfThought?: boolean;
}
export interface StreamState {
isStreaming: boolean;
content: string;
thinking: string;
error?: string;
}
/**
* 统一流式处理管理器
* 集中管理所有流式监听器，避免内存泄漏
*/
export class UnifiedStreamManager {
private activeListeners: Map<string, () => void> = new Map();
private streamStates: Map<string, StreamState> = new Map();
/**
* 开始流式处理
*/
async startStream(
streamId: string,
eventName: string,
options: StreamOptions = {}
): Promise<void> {
console.log(`🚀 开始流式处理 [${streamId}]: ${eventName}`);
// 清理现有的流
this.stopStream(streamId);
// 初始化流状态
this.streamStates.set(streamId, {
isStreaming: true,
content: '',
thinking: ''
});
let fullContent = '';
let fullThinking = '';
let contentListenerActive = true;
let thinkingListenerActive = true;
try {
// 监听主内容流
const unlistenContent = await listen(eventName, (event: any) => {
if (!contentListenerActive) return;
const payload = event.payload;
console.log(`💬 收到流式内容 [${streamId}]:`, payload);
if (payload) {
// 检查是否完成
if (payload.is_complete) {
console.log(`🎉 流式内容完成 [${streamId}]，总长度: ${fullContent.length}`);
contentListenerActive = false;
unlistenContent();
// 如果思维链监听器也不活跃了，则设置整体完成状态
if (!thinkingListenerActive) {
this.completeStream(streamId, fullContent, fullThinking, options);
}
return;
}
// 累积内容
if (payload.content) {
fullContent += payload.content;
// 更新状态
const state = this.streamStates.get(streamId);
if (state) {
state.content = fullContent;
this.streamStates.set(streamId, state);
}
// 触发回调
if (options.onChunk) {
options.onChunk(payload.content);
}
if (options.onProgress) {
options.onProgress({ content: fullContent, thinking: fullThinking || undefined });
}
console.log(`📝 累积内容长度 [${streamId}]: ${fullContent.length} 字符`);
}
}
});
this.activeListeners.set(`${streamId}_content`, unlistenContent);
// 如果启用思维链，监听思维链事件
if (options.enableChainOfThought) {
const reasoningEvent = `${eventName}_reasoning`;
console.log(`🧠 监听思维链事件 [${streamId}]: ${reasoningEvent}`);
const unlistenThinking = await listen(reasoningEvent, (event: any) => {
if (!thinkingListenerActive) return;
const payload = event.payload;
console.log(`🧠 思维链内容 [${streamId}]:`, payload);
if (payload) {
// 检查是否完成
if (payload.is_complete) {
console.log(`🎉 思维链完成 [${streamId}]，总长度: ${fullThinking.length}`);
thinkingListenerActive = false;
unlistenThinking();
// 如果主内容监听器也不活跃了，则设置整体完成状态
if (!contentListenerActive) {
this.completeStream(streamId, fullContent, fullThinking, options);
}
return;
}
// 累积思维链内容
if (payload.content) {
fullThinking += payload.content;
// 更新状态
const state = this.streamStates.get(streamId);
if (state) {
state.thinking = fullThinking;
this.streamStates.set(streamId, state);
}
// 触发回调
if (options.onThinking) {
options.onThinking(payload.content);
}
if (options.onProgress) {
options.onProgress({ content: fullContent, thinking: fullThinking || undefined });
}
console.log(`🧠 思维链累积长度 [${streamId}]: ${fullThinking.length} 字符`);
}
}
});
this.activeListeners.set(`${streamId}_thinking`, unlistenThinking);
} else {
// 如果没有启用思维链，标记思维链监听器为不活跃
thinkingListenerActive = false;
}
} catch (error) {
console.error(`❌ 流式处理启动失败 [${streamId}]:`, error);
this.handleStreamError(streamId, error as string, options);
}
}
/**
* 停止指定流
*/
stopStream(streamId: string): void {
console.log(`🛑 停止流式处理 [${streamId}]`);
// 清理内容监听器
const contentListener = this.activeListeners.get(`${streamId}_content`);
if (contentListener) {
contentListener();
this.activeListeners.delete(`${streamId}_content`);
}
// 清理思维链监听器
const thinkingListener = this.activeListeners.get(`${streamId}_thinking`);
if (thinkingListener) {
thinkingListener();
this.activeListeners.delete(`${streamId}_thinking`);
}
// 清理状态
this.streamStates.delete(streamId);
}
/**
* 停止所有流
*/
stopAllStreams(): void {
console.log(`🧹 清理所有流式处理，共 ${this.activeListeners.size} 个监听器`);
for (const [key, unlisten] of this.activeListeners) {
try {
unlisten();
} catch (error) {
console.warn(`清理监听器失败 [${key}]:`, error);
}
}
this.activeListeners.clear();
this.streamStates.clear();
}
/**
* 获取流状态
*/
getStreamState(streamId: string): StreamState | undefined {
return this.streamStates.get(streamId);
}
/**
* 检查流是否活跃
*/
isStreamActive(streamId: string): boolean {
const state = this.streamStates.get(streamId);
return state?.isStreaming || false;
}
/**
* 完成流处理
*/
private completeStream(
streamId: string,
content: string,
thinking: string,
options: StreamOptions
): void {
console.log(`🎉 流式处理完成 [${streamId}]`);
// 更新状态
const state = this.streamStates.get(streamId);
if (state) {
state.isStreaming = false;
this.streamStates.set(streamId, state);
}
// 触发完成回调
if (options.onComplete) {
options.onComplete(content, thinking || undefined);
}
// 延迟清理（给UI一些时间更新）
setTimeout(() => {
this.stopStream(streamId);
}, 100);
}
/**
* 处理流错误
*/
private handleStreamError(
streamId: string,
error: string,
options: StreamOptions
): void {
console.error(`❌ 流式处理错误 [${streamId}]:`, error);
// 更新状态
const state = this.streamStates.get(streamId);
if (state) {
state.isStreaming = false;
state.error = error;
this.streamStates.set(streamId, state);
}
// 触发错误回调
if (options.onError) {
options.onError(error);
}
// 清理流
this.stopStream(streamId);
}
}
// 创建全局实例
export const unifiedStreamManager = new UnifiedStreamManager();
/**
* React Hook for unified streaming
* 提供React组件使用的统一流式处理Hook
*/
export function useUnifiedStream() {
const [activeStreams, setActiveStreams] = React.useState<Set<string>>(new Set());
const [streamStates, setStreamStates] = React.useState<Map<string, StreamState>>(new Map());
// 组件卸载时清理所有流
React.useEffect(() => {
return () => {
console.log('🧹 组件卸载，清理所有流式处理');
unifiedStreamManager.stopAllStreams();
};
}, []);
const startStream = React.useCallback(async (
streamId: string,
eventName: string,
options: StreamOptions = {}
) => {
setActiveStreams(prev => new Set(prev.add(streamId)));
const enhancedOptions: StreamOptions = {
...options,
onProgress: (progress) => {
setStreamStates(prev => new Map(prev.set(streamId, {
isStreaming: true,
content: progress.content,
thinking: progress.thinking || ''
})));
if (options.onProgress) {
options.onProgress(progress);
}
},
onComplete: (content, thinking) => {
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
setStreamStates(prev => new Map(prev.set(streamId, {
isStreaming: false,
content,
thinking: thinking || ''
})));
if (options.onComplete) {
options.onComplete(content, thinking);
}
},
onError: (error) => {
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
setStreamStates(prev => new Map(prev.set(streamId, {
isStreaming: false,
content: '',
thinking: '',
error
})));
if (options.onError) {
options.onError(error);
}
}
};
await unifiedStreamManager.startStream(streamId, eventName, enhancedOptions);
}, []);
const stopStream = React.useCallback((streamId: string) => {
unifiedStreamManager.stopStream(streamId);
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
setStreamStates(prev => {
const newMap = new Map(prev);
newMap.delete(streamId);
return newMap;
});
}, []);
const stopAllStreams = React.useCallback(() => {
unifiedStreamManager.stopAllStreams();
setActiveStreams(new Set());
setStreamStates(new Map());
}, []);
const isStreamActive = React.useCallback((streamId: string) => {
return activeStreams.has(streamId);
}, [activeStreams]);
const getStreamState = React.useCallback((streamId: string) => {
return streamStates.get(streamId);
}, [streamStates]);
return {
startStream,
stopStream,
stopAllStreams,
isStreamActive,
getStreamState,
activeStreams: Array.from(activeStreams),
streamStates
};
}
|
000haoji/deep-student
| 6,043 |
src/chat-core/utils/tauriStreamAdapter.ts
|
/**
* Tauri Stream Adapter
*
* Focused adapter for converting Tauri backend streaming to standard streaming protocols.
* Single responsibility: Stream protocol conversion.
*/
import { invoke } from '@tauri-apps/api/core';
import { listen } from '@tauri-apps/api/event';
export interface StreamControllerManager {
controller: ReadableStreamDefaultController;
listeners: Array<() => void>;
responseStarted: boolean;
}
/**
* Create a streaming response for Tauri analysis requests
*/
export async function createAnalysisStream(
imageData: string,
userInput: string,
enableChainOfThought: boolean = true
): Promise<Response> {
const stream = new ReadableStream({
start(controller) {
const manager: StreamControllerManager = {
controller,
listeners: [],
responseStarted: false
};
handleAnalysisStream(imageData, userInput, enableChainOfThought, manager);
return () => {
manager.listeners.forEach(cleanup => cleanup());
};
}
});
return new Response(stream, {
headers: {
'Content-Type': 'text/plain; charset=utf-8',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive'
}
});
}
/**
* Create a streaming response for Tauri chat requests
*/
export async function createChatStream(
tempId: string,
chatHistory: any[],
enableChainOfThought: boolean = true
): Promise<Response> {
const stream = new ReadableStream({
start(controller) {
const manager: StreamControllerManager = {
controller,
listeners: [],
responseStarted: false
};
handleChatStream(tempId, chatHistory, enableChainOfThought, manager);
return () => {
manager.listeners.forEach(cleanup => cleanup());
};
}
});
return new Response(stream, {
headers: {
'Content-Type': 'text/plain; charset=utf-8',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive'
}
});
}
/**
* Handle analysis streaming events
*/
async function handleAnalysisStream(
imageData: string,
userInput: string,
enableChainOfThought: boolean,
manager: StreamControllerManager
): Promise<void> {
try {
// Set up event listeners
const unlistenContent = await listen('stream_chunk', (event: any) => {
const chunk = formatStreamChunk(event.payload.content);
manager.controller.enqueue(new TextEncoder().encode(chunk));
});
const unlistenThinking = enableChainOfThought
? await listen('stream_thinking', (event: any) => {
const chunk = formatThinkingChunk(event.payload.thinking);
manager.controller.enqueue(new TextEncoder().encode(chunk));
})
: null;
const unlistenComplete = await listen('stream_complete', () => {
finishStream(manager.controller);
});
const unlistenError = await listen('stream_error', (event: any) => {
manager.controller.error(new Error(event.payload.error));
});
// Store cleanup functions
manager.listeners.push(unlistenContent, unlistenComplete, unlistenError);
if (unlistenThinking) {
manager.listeners.push(unlistenThinking);
}
// Start the backend analysis
const base64Data = formatImageData(imageData);
await invoke('analyze_step_by_step', {
request: {
subject: "数学",
question_image_files: [base64Data],
analysis_image_files: [],
user_question: userInput,
enable_chain_of_thought: enableChainOfThought
}
});
} catch (error) {
manager.controller.error(error);
}
}
/**
* Handle chat streaming events
*/
async function handleChatStream(
tempId: string,
chatHistory: any[],
enableChainOfThought: boolean,
manager: StreamControllerManager
): Promise<void> {
try {
// Set up event listeners
const unlistenContent = await listen('stream_chunk', (event: any) => {
const chunk = formatStreamChunk(event.payload.content);
manager.controller.enqueue(new TextEncoder().encode(chunk));
});
const unlistenThinking = enableChainOfThought
? await listen('stream_thinking', (event: any) => {
const chunk = formatThinkingChunk(event.payload.thinking);
manager.controller.enqueue(new TextEncoder().encode(chunk));
})
: null;
const unlistenComplete = await listen('stream_complete', () => {
finishStream(manager.controller);
});
const unlistenError = await listen('stream_error', (event: any) => {
manager.controller.error(new Error(event.payload.error));
});
// Store cleanup functions
manager.listeners.push(unlistenContent, unlistenComplete, unlistenError);
if (unlistenThinking) {
manager.listeners.push(unlistenThinking);
}
// Start the chat stream
await invoke('continue_chat_stream', {
request: {
temp_id: tempId,
chat_history: chatHistory,
enable_chain_of_thought: enableChainOfThought
}
});
} catch (error) {
manager.controller.error(error);
}
}
/**
* Format streaming content chunk
*/
function formatStreamChunk(content: string): string {
return `data: ${JSON.stringify({
choices: [{
delta: {
content: content
}
}]
})}\n\n`;
}
/**
* Format thinking chain chunk
*/
function formatThinkingChunk(thinking: string): string {
return `data: ${JSON.stringify({
choices: [{
delta: {
thinking: thinking
}
}]
})}\n\n`;
}
/**
* Finish the stream
*/
function finishStream(controller: ReadableStreamDefaultController): void {
const finishChunk = `data: ${JSON.stringify({
choices: [{
finish_reason: 'stop'
}]
})}\n\n`;
controller.enqueue(new TextEncoder().encode(finishChunk));
controller.enqueue(new TextEncoder().encode('data: [DONE]\n\n'));
controller.close();
}
/**
* Format image data for backend
*/
function formatImageData(imageData: string): string {
return imageData.startsWith('data:') ? imageData : `data:image/jpeg;base64,${imageData}`;
}
|
000haoji/deep-student
| 13,011 |
src/chat-core/utils/unifiedStreamHandler.ts
|
/**
* Unified Streaming Handler
*
* Consolidates all streaming approaches in the project into a single,
* consistent implementation that can be used across all components.
*/
import { listen } from '@tauri-apps/api/event';
import { invoke } from '@tauri-apps/api/core';
export interface StreamChunk {
content: string;
is_complete: boolean;
chunk_id: string;
}
export interface StreamMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp: string;
}
export interface StreamOptions {
enableChainOfThought?: boolean;
onChunk?: (chunk: string) => void;
onThinking?: (thinking: string) => void;
onComplete?: (fullResponse: string, thinkingContent?: string) => void;
onError?: (error: string) => void;
onProgress?: (progress: { content: string; thinking?: string }) => void;
}
export interface StreamRequest {
type: 'analysis' | 'chat' | 'continue_chat';
tempId?: string;
mistakeId?: number;
imageData?: string;
userInput?: string;
chatHistory?: StreamMessage[];
enableChainOfThought?: boolean;
}
/**
* Unified Streaming Manager
* Replaces multiple streaming implementations with a single, consistent approach
*/
export class UnifiedStreamHandler {
private activeStreams: Map<string, () => void> = new Map();
private currentProgress: Map<string, { content: string; thinking: string }> = new Map();
/**
* Start a streaming request with unified handling
*/
async startStream(request: StreamRequest, options: StreamOptions = {}): Promise<string> {
const streamId = this.generateStreamId(request);
// Stop any existing stream with the same ID
this.stopStream(streamId);
try {
const cleanupFunctions = await this.initializeStreamListeners(streamId, request, options);
this.activeStreams.set(streamId, () => {
cleanupFunctions.forEach(cleanup => cleanup());
});
// Start the appropriate backend command
await this.startBackendStream(request);
return streamId;
} catch (error) {
console.error('Failed to start stream:', error);
if (options.onError) {
options.onError(error instanceof Error ? error.message : 'Unknown error');
}
throw error;
}
}
/**
* Stop a specific stream
*/
stopStream(streamId: string): void {
const cleanup = this.activeStreams.get(streamId);
if (cleanup) {
cleanup();
this.activeStreams.delete(streamId);
this.currentProgress.delete(streamId);
console.log(`Stopped stream: ${streamId}`);
}
}
/**
* Stop all active streams
*/
stopAllStreams(): void {
for (const streamId of this.activeStreams.keys()) {
this.stopStream(streamId);
}
}
/**
* Get current progress for a stream
*/
getProgress(streamId: string): { content: string; thinking: string } | null {
return this.currentProgress.get(streamId) || null;
}
/**
* Check if a stream is active
*/
isStreamActive(streamId: string): boolean {
return this.activeStreams.has(streamId);
}
private generateStreamId(request: StreamRequest): string {
const timestamp = Date.now();
const type = request.type;
const id = request.tempId || request.mistakeId || 'default';
return `${type}_${id}_${timestamp}`;
}
private async initializeStreamListeners(
streamId: string,
request: StreamRequest,
options: StreamOptions
): Promise<Array<() => void>> {
const cleanupFunctions: Array<() => void> = [];
let fullContent = '';
let fullThinking = '';
// Initialize progress tracking
this.currentProgress.set(streamId, { content: '', thinking: '' });
// Determine event names based on request type
const baseEventName = this.getEventName(request);
const contentEvent = baseEventName;
const thinkingEvent = `${baseEventName}_reasoning`;
console.log(`🔄 Initializing unified stream listeners for: ${streamId}`);
console.log(`📡 Content event: ${contentEvent}`);
console.log(`🧠 Thinking event: ${thinkingEvent}`);
// Listen for main content stream
try {
const unlistenContent = await listen<StreamChunk>(contentEvent, (event) => {
const chunk = event.payload;
if (chunk.is_complete) {
console.log(`✅ Content stream complete for ${streamId}`);
this.checkStreamCompletion(streamId, fullContent, fullThinking, options);
return;
}
if (chunk.content) {
fullContent += chunk.content;
// Update progress
const progress = this.currentProgress.get(streamId);
if (progress) {
progress.content = fullContent;
this.currentProgress.set(streamId, progress);
}
// Call callbacks
if (options.onChunk) {
options.onChunk(chunk.content);
}
if (options.onProgress) {
options.onProgress({ content: fullContent, thinking: fullThinking || undefined });
}
console.log(`📝 Content update [${streamId}]: ${chunk.content.length} chars`);
}
});
cleanupFunctions.push(unlistenContent);
} catch (error) {
console.error(`Failed to listen for content events: ${contentEvent}`, error);
}
// Listen for thinking chain (if enabled)
if (request.enableChainOfThought !== false) {
try {
const unlistenThinking = await listen<StreamChunk>(thinkingEvent, (event) => {
const chunk = event.payload;
if (chunk.is_complete) {
console.log(`✅ Thinking stream complete for ${streamId}`);
this.checkStreamCompletion(streamId, fullContent, fullThinking, options);
return;
}
if (chunk.content) {
fullThinking += chunk.content;
// Update progress
const progress = this.currentProgress.get(streamId);
if (progress) {
progress.thinking = fullThinking;
this.currentProgress.set(streamId, progress);
}
// Call callbacks
if (options.onThinking) {
options.onThinking(chunk.content);
}
if (options.onProgress) {
options.onProgress({ content: fullContent, thinking: fullThinking || undefined });
}
console.log(`🧠 Thinking update [${streamId}]: ${chunk.content.length} chars`);
}
});
cleanupFunctions.push(unlistenThinking);
} catch (error) {
console.error(`Failed to listen for thinking events: ${thinkingEvent}`, error);
}
}
// Listen for errors
try {
const unlistenError = await listen<{error: string}>('stream_error', (event) => {
console.error(`❌ Stream error [${streamId}]:`, event.payload.error);
if (options.onError) {
options.onError(event.payload.error);
}
this.stopStream(streamId);
});
cleanupFunctions.push(unlistenError);
} catch (error) {
console.error('Failed to listen for error events', error);
}
return cleanupFunctions;
}
private checkStreamCompletion(
streamId: string,
content: string,
thinking: string,
options: StreamOptions
): void {
// Check if both content and thinking (if enabled) are complete
const progress = this.currentProgress.get(streamId);
if (!progress) return;
console.log(`🎉 Stream completion check [${streamId}]: content=${content.length}, thinking=${thinking.length}`);
if (options.onComplete) {
options.onComplete(content, thinking || "");
}
// Auto-cleanup after completion
setTimeout(() => {
this.stopStream(streamId);
}, 100);
}
private getEventName(request: StreamRequest): string {
switch (request.type) {
case 'analysis':
return request.tempId ? `analysis_stream_${request.tempId}` : 'stream_chunk';
case 'chat':
return 'stream_chunk';
case 'continue_chat':
return request.tempId ? `continue_chat_stream_${request.tempId}` : 'stream_chunk';
default:
return 'stream_chunk';
}
}
private async startBackendStream(request: StreamRequest): Promise<void> {
switch (request.type) {
case 'analysis':
if (!request.imageData || !request.userInput) {
throw new Error('Analysis requires imageData and userInput');
}
// First do OCR analysis
const analysisResponse = await invoke('analyze_step_by_step', {
request: {
subject: "数学",
question_image_files: [request.imageData.startsWith('data:') ? request.imageData : `data:image/jpeg;base64,${request.imageData}`],
analysis_image_files: [],
user_question: request.userInput,
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
// If we got a temp_id, start the streaming answer
if ((analysisResponse as any)?.temp_id) {
await invoke('start_streaming_answer', {
request: {
temp_id: (analysisResponse as any).temp_id,
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
}
break;
case 'chat':
await invoke('start_streaming_answer', {
request: {
chat_history: request.chatHistory?.map(msg => ({
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content
})) || [],
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
break;
case 'continue_chat':
if (!request.tempId) {
throw new Error('Continue chat requires tempId');
}
await invoke('continue_chat_stream', {
request: {
temp_id: request.tempId,
chat_history: request.chatHistory?.map(msg => ({
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content
})) || [],
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
break;
default:
throw new Error(`Unsupported stream type: ${request.type}`);
}
}
}
// Create global instance
export const unifiedStreamHandler = new UnifiedStreamHandler();
/**
* React Hook for Unified Streaming
* Provides a simple interface for React components to use unified streaming
*/
export function useUnifiedStream() {
const [activeStreams, setActiveStreams] = React.useState<Set<string>>(new Set());
const [streamProgress, setStreamProgress] = React.useState<Map<string, { content: string; thinking: string }>>(new Map());
React.useEffect(() => {
return () => {
// Cleanup all streams when component unmounts
unifiedStreamHandler.stopAllStreams();
};
}, []);
const startStream = React.useCallback(async (request: StreamRequest, options: StreamOptions = {}) => {
const streamId = await unifiedStreamHandler.startStream(request, {
...options,
onProgress: (progress) => {
setStreamProgress(prev => new Map(prev.set(streamId, { content: progress.content, thinking: progress.thinking || "" })));
if (options.onProgress) {
options.onProgress(progress);
}
},
onComplete: (content, thinking) => {
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
if (options.onComplete) {
options.onComplete(content, thinking);
}
},
onError: (error) => {
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
if (options.onError) {
options.onError(error);
}
}
});
setActiveStreams(prev => new Set(prev.add(streamId)));
return streamId;
}, []);
const stopStream = React.useCallback((streamId: string) => {
unifiedStreamHandler.stopStream(streamId);
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
setStreamProgress(prev => {
const newMap = new Map(prev);
newMap.delete(streamId);
return newMap;
});
}, []);
const stopAllStreams = React.useCallback(() => {
unifiedStreamHandler.stopAllStreams();
setActiveStreams(new Set());
setStreamProgress(new Map());
}, []);
return {
startStream,
stopStream,
stopAllStreams,
activeStreams: Array.from(activeStreams),
streamProgress: Object.fromEntries(streamProgress),
isStreaming: activeStreams.size > 0
};
}
// Add React import for the hook
import React from 'react';
|
0015/esp_rlottie
| 10,721 |
rlottie/README.md
|
# rlottie
[](https://travis-ci.org/Samsung/rlottie)
[](https://ci.appveyor.com/project/smohantty/rlottie-mliua)
[](https://gitter.im/rLottie-dev/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
<p align="center">
<img width="240" height="240" src="https://github.com/Samsung/rlottie/blob/master/.Gifs/logo.png">
</p>
rlottie is a platform independent standalone c++ library for rendering vector based animations and art in realtime.
Lottie loads and renders animations and vectors exported in the bodymovin JSON format. Bodymovin JSON can be created and exported from After Effects with [bodymovin](https://github.com/bodymovin/bodymovin), Sketch with [Lottie Sketch Export](https://github.com/buba447/Lottie-Sketch-Export), and from [Haiku](https://www.haiku.ai).
For the first time, designers can create and ship beautiful animations without an engineer painstakingly recreating it by hand. Since the animation is backed by JSON they are extremely small in size but can be large in complexity!
Here are small samples of the power of Lottie.
<p align="center">
<img src="https://github.com/Samsung/rlottie/blob/master/.Gifs/1.gif">
<img src="https://github.com/Samsung/rlottie/blob/master/.Gifs/2.gif">
<img src="https://github.com/airbnb/lottie-ios/blob/master/_Gifs/Examples1.gif">
</p>
## Contents
- [Building Lottie](#building-lottie)
- [Meson Build](#meson-build)
- [Cmake Build](#cmake-build)
- [Test](#test)
- [Demo](#demo)
- [Previewing Lottie JSON Files](#previewing-lottie-json-files)
- [Quick Start](#quick-start)
- [Dynamic Property](#dynamic-property)
- [Supported After Effects Features](#supported-after-effects-features)
- [Issues or Feature Requests?](#issues-or-feature-requests)
## Building Lottie
rlottie supports [meson](https://mesonbuild.com/) and [cmake](https://cmake.org/) build system. rlottie is written in `C++14`. and has a public header dependency of `C++11`
### Meson Build
install [meson](http://mesonbuild.com/Getting-meson.html) and [ninja](https://ninja-build.org/) if not already installed.
Run meson to configure rlottie
```
meson build
```
Run ninja to build rlottie
```
ninja -C build
```
### Cmake Build
Install [cmake](https://cmake.org/download/) if not already installed
Create a build directory for out of source `build`
```
mkdir build
```
Run cmake command inside `build` directory to configure rlottie.
```
cd build
cmake ..
# install in a different path. eg ~/test/usr/lib
cmake -DCMAKE_INSTALL_PREFIX=~/test ..
# static build
cmake -DBUILD_SHARED_LIBS=OFF ..
```
Run make to build rlottie
```
make -j 2
```
To install rlottie library
```
make install
```
### Test
Configure to build test
```
meson configure -Dtest=true
```
Build test suit
```
ninja
```
Run test suit
```
ninja test
```
[Back to contents](#contents)
#
## Demo
If you want to see rlottie library in action without building it please visit [rlottie online viewer](http://rlottie.com)
While building rlottie library it generates a simple lottie to GIF converter which can be used to convert lottie json file to GIF file.
Run Demo
```
lottie2gif [lottie file name]
```
#
## Previewing Lottie JSON Files
Please visit [rlottie online viewer](http://rlottie.com)
[rlottie online viewer](http://rlottie.com) uses rlottie wasm library to render the resource locally in your browser. To test your JSON resource drag and drop it to the browser window.
#
## Quick Start
Lottie loads and renders animations and vectors exported in the bodymovin JSON format. Bodymovin JSON can be created and exported from After Effects with [bodymovin](https://github.com/bodymovin/bodymovin), Sketch with [Lottie Sketch Export](https://github.com/buba447/Lottie-Sketch-Export), and from [Haiku](https://www.haiku.ai).
You can quickly load a Lottie animation with:
```cpp
auto animation = rlottie::Animation::loadFromFile("absolute_path/test.json");
```
You can load a lottie animation from raw data with:
```cpp
auto animation = rlottie::Animation::loadFromData(std::string(rawData), std::string(cacheKey));
```
Properties like `frameRate` , `totalFrame` , `duration` can be queried with:
```cpp
# get the frame rate of the resource.
double frameRate = animation->frameRate();
#get total frame that exists in the resource
size_t totalFrame = animation->totalFrame();
#get total animation duration in sec for the resource
double duration = animation->duration();
```
Render a particular frame in a surface buffer `immediately` with:
```cpp
rlottie::Surface surface(buffer, width , height , stride);
animation->renderSync(frameNo, surface);
```
Render a particular frame in a surface buffer `asyncronousely` with:
```cpp
rlottie::Surface surface(buffer, width , height , stride);
# give a render request
std::future<rlottie::Surface> handle = animation->render(frameNo, surface);
...
#when the render data is needed
rlottie::Surface surface = handle.get();
```
[Back to contents](#contents)
## Dynamic Property
You can update properties dynamically at runtime. This can be used for a variety of purposes such as:
- Theming (day and night or arbitrary themes).
- Responding to events such as an error or a success.
- Animating a single part of an animation in response to an event.
- Responding to view sizes or other values not known at design time.
### Understanding After Effects
To understand how to change animation properties in Lottie, you should first understand how animation properties are stored in Lottie. Animation properties are stored in a data tree that mimics the information hierarchy of After Effects. In After Effects a Composition is a collection of Layers that each have their own timelines. Layer objects have string names, and their contents can be an image, shape layers, fills, strokes, or just about anything that is drawable. Each object in After Effects has a name. Lottie can find these objects and properties by their name using a KeyPath.
### Usage
To update a property at runtime, you need 3 things:
1. KeyPath
2. rLottie::Property
3. setValue()
### KeyPath
A KeyPath is used to target a specific content or a set of contents that will be updated. A KeyPath is specified by a list of strings that correspond to the hierarchy of After Effects contents in the original animation.
KeyPaths can include the specific name of the contents or wildcards:
- Wildcard *
- Wildcards match any single content name in its position in the keypath.
- Globstar **
- Globstars match zero or more layers.
### Properties
`rLottie::Property` is an enumeration of properties that can be set. They correspond to the animatable value in After Effects and the available properties are listed below.
```cpp
enum class Property {
FillColor, /*!< Color property of Fill object , value type is rlottie::Color */
FillOpacity, /*!< Opacity property of Fill object , value type is float [ 0 .. 100] */
StrokeColor, /*!< Color property of Stroke object , value type is rlottie::Color */
StrokeOpacity, /*!< Opacity property of Stroke object , value type is float [ 0 .. 100] */
StrokeWidth, /*!< stroke with property of Stroke object , value type is float */
...
};
```
### setValue()
`setValue()` requires a keypath of string and value. The value can be `Color`, `Size` and `Point` structure or a function that returns them. `Color`, `Size`, and `Point` vary depending on the type of `rLottie::Property`. This value or function(callback) is called and applied to every frame. This value can be set differently for each frame by using the `FrameInfo` argument passed to the function.
### Usage
```cpp
animation->setValue<rlottie::Property::FillColor>("**",rlottie::Color(0, 1, 0));
```
```cpp
animation->setValue<rlottie::Property::FillColor>("Layer1.Box 1.Fill1",
[](const rlottie::FrameInfo& info) {
if (info.curFrame() < 15 )
return rlottie::Color(0, 1, 0);
else {
return rlottie::Color(1, 0, 0);
}
});
```
[Back to contents](#contents)
#
#
## Supported After Effects Features
| **Shapes** | **Supported** |
|:--|:-:|
| Shape | 👍 |
| Ellipse | 👍 |
| Rectangle | 👍 |
| Rounded Rectangle | 👍 |
| Polystar | 👍 |
| Group | 👍 |
| Trim Path (individually) | 👍 |
| Trim Path (simultaneously) | 👍 |
| **Renderable** | **Supported** |
| Fill | 👍 |
| Stroke | 👍 |
| Radial Gradient | 👍 |
| Linear Gradient | 👍 |
| Gradient Stroke | 👍 |
| **Transforms** | **Supported** |
| Position | 👍 |
| Position (separated X/Y) | 👍 |
| Scale | 👍 |
| Skew | ⛔️ |
| Rotation | 👍 |
| Anchor Point | 👍 |
| Opacity | 👍 |
| Parenting | 👍 |
| Auto Orient | 👍 |
| **Interpolation** | **Supported** |
| Linear Interpolation | 👍 |
| Bezier Interpolation | 👍 |
| Hold Interpolation | 👍 |
| Spatial Bezier Interpolation | 👍 |
| Rove Across Time | 👍 |
| **Masks** | **Supported** |
| Mask Path | 👍 |
| Mask Opacity | 👍 |
| Add | 👍 |
| Subtract | 👍 |
| Intersect | 👍 |
| Lighten | ⛔️ |
| Darken | ⛔️ |
| Difference | ⛔️ |
| Expansion | ⛔️ |
| Feather | ⛔️ |
| **Mattes** | **Supported** |
| Alpha Matte | 👍 |
| Alpha Inverted Matte | 👍 |
| Luma Matte | 👍 |
| Luma Inverted Matte | 👍 |
| **Merge Paths** | **Supported** |
| Merge | ⛔️ |
| Add | ⛔️ |
| Subtract | ⛔️ |
| Intersect | ⛔️ |
| Exclude Intersection | ⛔️ |
| **Layer Effects** | **Supported** |
| Fill | ⛔️ |
| Stroke | ⛔️ |
| Tint | ⛔️ |
| Tritone | ⛔️ |
| Levels Individual Controls | ⛔️ |
| **Text** | **Supported** |
| Glyphs | ⛔️ |
| Fonts | ⛔️ |
| Transform | ⛔️ |
| Fill | ⛔️ |
| Stroke | ⛔️ |
| Tracking | ⛔️ |
| Anchor point grouping | ⛔️ |
| Text Path | ⛔️ |
| Per-character 3D | ⛔️ |
| Range selector (Units) | ⛔️ |
| Range selector (Based on) | ⛔️ |
| Range selector (Amount) | ⛔️ |
| Range selector (Shape) | ⛔️ |
| Range selector (Ease High) | ⛔️ |
| Range selector (Ease Low) | ⛔️ |
| Range selector (Randomize order) | ⛔️ |
| expression selector | ⛔️ |
| **Other** | **Supported** |
| Expressions | ⛔️ |
| Images | 👍 |
| Precomps | 👍 |
| Time Stretch | 👍 |
| Time remap | 👍 |
| Markers | 👍 |
#
[Back to contents](#contents)
## Issues or Feature Requests?
File github issues for anything that is broken. Be sure to check the [list of supported features](#supported-after-effects-features) before submitting. If an animation is not working, please attach the After Effects file to your issue. Debugging without the original can be very difficult. For immidiate assistant or support please reach us in [Gitter](https://gitter.im/rLottie-dev/community#)
|
0015/esp_rlottie
| 2,592 |
rlottie/.clang-format
|
---
Language: Cpp
BasedOnStyle: Google
AccessModifierOffset: -4
AlignAfterOpenBracket: Align
AlignConsecutiveAssignments: false
AlignConsecutiveDeclarations: true
AlignEscapedNewlinesLeft: true
AlignOperands: true
AlignTrailingComments: true
AllowAllParametersOfDeclarationOnNextLine: true
AllowShortBlocksOnASingleLine: false
AllowShortCaseLabelsOnASingleLine: false
AllowShortFunctionsOnASingleLine: Inline
AllowShortIfStatementsOnASingleLine: true
AllowShortLoopsOnASingleLine: true
AlwaysBreakAfterDefinitionReturnType: None
AlwaysBreakAfterReturnType: None
AlwaysBreakBeforeMultilineStrings: true
AlwaysBreakTemplateDeclarations: true
BinPackArguments: true
BinPackParameters: true
BraceWrapping:
AfterClass: false
AfterControlStatement: false
AfterEnum: false
AfterFunction: false
AfterNamespace: false
AfterObjCDeclaration: false
AfterStruct: false
AfterUnion: false
BeforeCatch: false
BeforeElse: false
IndentBraces: false
BreakBeforeBinaryOperators: None
BreakBeforeBraces: WebKit
BreakBeforeTernaryOperators: true
BreakConstructorInitializersBeforeComma: false
ColumnLimit: 80
CommentPragmas: '^ IWYU pragma:'
ConstructorInitializerAllOnOneLineOrOnePerLine: true
ConstructorInitializerIndentWidth: 4
ContinuationIndentWidth: 4
Cpp11BracedListStyle: true
DerivePointerAlignment: true
DisableFormat: false
ExperimentalAutoDetectBinPacking: false
ForEachMacros: [ foreach, Q_FOREACH, BOOST_FOREACH ]
IncludeCategories:
- Regex: '^<.*\.h>'
Priority: 1
- Regex: '^<.*'
Priority: 2
- Regex: '.*'
Priority: 3
IndentCaseLabels: false
IndentWidth: 4
IndentWrappedFunctionNames: false
KeepEmptyLinesAtTheStartOfBlocks: false
MacroBlockBegin: ''
MacroBlockEnd: ''
MaxEmptyLinesToKeep: 1
NamespaceIndentation: None
ObjCBlockIndentWidth: 2
ObjCSpaceAfterProperty: false
ObjCSpaceBeforeProtocolList: false
PenaltyBreakBeforeFirstCallParameter: 1
PenaltyBreakComment: 300
PenaltyBreakFirstLessLess: 120
PenaltyBreakString: 1000
PenaltyExcessCharacter: 1000000
PenaltyReturnTypeOnItsOwnLine: 200
PointerAlignment: Right
ReflowComments: true
SortIncludes: true
SpaceAfterCStyleCast: false
SpaceBeforeAssignmentOperators: true
SpaceBeforeParens: ControlStatements
SpaceInEmptyParentheses: false
SpacesBeforeTrailingComments: 2
SpacesInAngles: false
SpacesInContainerLiterals: true
SpacesInCStyleCastParentheses: false
SpacesInParentheses: false
SpacesInSquareBrackets: false
Standard: Auto
TabWidth: 4
UseTab: Never
...
|
000linlin/ConsisLoRA
| 1,607,768 |
inference_demo.ipynb
|
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Inference for ConsisLoRA"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "98476b7830664aea946698b0b1511c05",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import torch\n",
"import matplotlib.pyplot as plt\n",
"from utils import load_pil_image\n",
"from diffusers import EulerDiscreteScheduler\n",
"from pipeline_demo import StableDiffusionXLPipelineLoraGuidance\n",
"\n",
"model_id = \"stabilityai/stable-diffusion-xl-base-1.0\"\n",
"device = \"cuda\"\n",
"dtype = torch.float16\n",
"\n",
"pipeline = StableDiffusionXLPipelineLoraGuidance.from_pretrained(\n",
" model_id, \n",
" torch_dtype=dtype,\n",
").to(device)\n",
"\n",
"pipeline.scheduler = EulerDiscreteScheduler.from_config(\n",
" pipeline.scheduler.config,\n",
" timestep_spacing=\"trailing\"\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Style Transfer"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded lora weights of the content image from chenblin26/ConsisLoRA-London_eye\n",
"Loaded lora weights of the style image from chenblin26/ConsisLoRA-antimonocromatismo\n"
]
}
],
"source": [
"# adjust image name according to your needs\n",
"content_img_name = \"London_eye\" # see \"data_demo/content\"\n",
"style_img_name = \"antimonocromatismo\" # see \"data_demo/style\"\n",
"\n",
"content_lora_path = f\"chenblin26/ConsisLoRA-{content_img_name}\"\n",
"style_lora_path = f\"chenblin26/ConsisLoRA-{style_img_name}\"\n",
"\n",
"# load ConsisLora\n",
"pipeline.unload_lora_checkpoint()\n",
"pipeline.load_lora_checkpoint(content_lora_path, style_lora_path)"
]
},
{
"cell_type": "code",
"execution_count": 242,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "b4b46ae64d33410ba5dd0595d72dafc3",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/30 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded input image of size ((1024, 1024)) from data_demo/content/London_eye.jpg\n",
"Loaded input image of size ((512, 512)) from data_demo/style/antimonocromatismo.jpg\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1000x600 with 6 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"num_images_per_prompt = 4 # adjust according to VRAM size\n",
"style_lora_scaling = 1. # you can adjust to control style strength\n",
"generator = torch.manual_seed(29) # seed\n",
"\n",
"images = pipeline(\n",
" prompt=\"a [c] in the style of [v]\", \n",
" lora_scaling = [1., style_lora_scaling],\n",
" guidance_scale=7.5,\n",
" num_inference_steps=30, \n",
" # add_positive_content_prompt=\"a [c]\",\n",
" # add_negative_content_prompt=\"a [v]\",\n",
" # add_positive_style_prompt=\"an image in the style of [v]\",\n",
" # add_negative_style_prompt=\"an image in the style of [c]\", \n",
" # content_guidance_scale=0., # style guidance\n",
" # style_guidance_scale=0., # content guidance \n",
" num_images_per_prompt=num_images_per_prompt, \n",
" generator=generator\n",
").images\n",
"\n",
"content_img_path = f\"data_demo/content/{content_img_name}.jpg\"\n",
"style_img_path = f\"data_demo/style/{style_img_name}.jpg\"\n",
"content_img = load_pil_image(content_img_path)\n",
"style_img = load_pil_image(style_img_path)\n",
"\n",
"_, ax = plt.subplots(2, 3, figsize=(10, 6))\n",
"ax[0, 0].imshow(content_img)\n",
"ax[0, 1].imshow(style_img)\n",
"ax[0, 2].imshow(images[0])\n",
"ax[1, 0].imshow(images[1])\n",
"ax[1, 1].imshow(images[2])\n",
"ax[1, 2].imshow(images[3])\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Use content LoRA only"
]
},
{
"cell_type": "code",
"execution_count": 243,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded lora weights of the content image from chenblin26/ConsisLoRA-London_eye\n"
]
}
],
"source": [
"# adjust image name according to your needs\n",
"content_img_name = \"London_eye\" # see \"data_demo/content\"\n",
"content_lora_path = f\"chenblin26/ConsisLoRA-{content_img_name}\"\n",
"\n",
"pipeline.unload_lora_checkpoint()\n",
"pipeline.load_lora_checkpoint(content_image_lora_path=content_lora_path)"
]
},
{
"cell_type": "code",
"execution_count": 244,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d35f74dfe2854b77b206dd7aa2c953c1",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/30 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded input image of size ((1024, 1024)) from data_demo/content/London_eye.jpg\n"
]
},
{
"data": {
"image/png": 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ArZvgHm2t1ck5gGwcF0Cm9gCNtcbnDiuhjAFk3fuF3ojcvgjzSxJhip4jpyrGI1HhdMmYodSljzsi/80QxAyL7CoqcTorQLYLEGgC2r0xzvC7to5wNzHGadSBDYhhnffhrJvNiZtz5O56Ajn5ZnqoKSd6tnUK0522uZy3hDruBFSd4tjTyqZrn1nHXXei3OE1T3d78bv53p1N7p4uwtx+MCi5Z3u6k74OwJHv97qf/OSv6eskyyBqUdap6kfKsc+0esU1qLSMXb83z7+OFowqmFRwYSKRihEwCff50T2oyua0nTNthWxCV9IKBF/GOr1RZ7VddypnGOvT3HldS49t/R0s2ZsPf33MMW9aQAXwUz/1U/zUT/3UHV0ji3AuCQceIGYkmcggUUZUZDMkGbjjFkq6S1VCpgyVhOCYK1Uqe2I2JhKkAOKhrLaWmLnTeYcpjCRC+ypJdCqoZ5IqZqGoziwjArXHppHdw/slkFtHROmAVELBzCIXKamHl8Ud3KjRUJjdERGSC6pSLCFGcqX1CMOzbMzEqESL4l48ChLhYa4SPBUS96g10QBkY5ISjYaXJQGtwa6Gx8WLh6nyUMbbojuLwcwK0YOFoq3C4EUTATUnu9CVMEEzIaUATK1E+J0TIW1JUvGgBViq1MO7lwPQ9NYgJwdQyOHhgQB0I4GW8DRlhzEaOUCEt6pyYUaAAPAgubDwUlUoe+TIn3LHNPpQCG+PSHijDKg0Fso+7yh7jJdScqxwXON7I4g0UsBDGg+voaYyBwSK645RAYmdCCkFKFVxGhNqiet3LjSW0UII0ji0xD1HxXPlJSdOFaR4viYEyHNiHqkI6o6p0xVijGQ2hPLVJKaeqVAUxTRCMqUfMwdzgZLn1bwBIX+93I115I7kOMByaAM5QpE9aoM5rdnWVy44eGI2NHLtb0dtj8c1ZNlqKhuffUF6LeOQ1dXnWsrGEKpFMPAm0NRPKyfVo06qJB2aL8v9dqgXF+fL60r/vVmhfr3kbqwh64flMOqZf3OKJ940HH7487r0HV+58+nlzubD3Rjb4+0Vp4MC8z45fNVFGDX/xtmphY+9W7gwSaThfXX62JlYdiKaxS3ywqctvHQzIn5e3RNe2qeHYKdo70pzjvpy6b0/3X1OvKSsRejzlqz1N59yCt2JDfFeyZsaUN0dcbIotRg10OXwnLgoe9k4XymeIz9FqakdOonQsEp0YHtL6kw9Qp9SVeGeS+gbuMX/UxW5QmNPEermHqQVBTQkIFsGCY9SlRTvvU1SmN0smPzcYeTBTCgSoVutZzQnKohn6gkFKKQZomRROu8CMGmiNgdVMhlJysQUsaKjY4VhMELdRq7hQdJ57lAFyGgeyjUiiC3SSBgLJFdmFuCjspJrI5FrlPsVxIScI5/IJXwZBzgaSCRC47LQpehf857rqYCOotBblzEJgg0kwhnFI2RSNULY3J2RJhQHs3gW6dnu4rNY5FGZGyKREF9JCRmMlKhgbUQLYATcGJkU0pLonH11diTGQLQ3QCq4oxJEHbNwgjFGg7jEY7SyBZ4da3g0TcLTJlaApocnMHuA/E5BzBBXsmXGrjTuuEItjmXF1ahItKoRz10Wbco4FloIelIUxwvQDM9WSQ+jktJGCVKJqQfJhTkkgykGkhERGo/r1RZGgZboG9UArzWRR5ffODx1l+QuWgQXNZrVHeFuGB9Xd5qjnDbrzl134KF2HaV8nQJIrb3vhnYdeiaf79xLiqMv7+hrjc530cp7t+W0zTquu5f67mRuijeForKAed+kI3VmWfd6rg7Ribxzx9kfVg4dMPHi9B9eoT5nrvx4J/jqdZK7slwuPedyhw6vzmo/+4aul9DlWnMO2jDIRmifDJ1vJcfYCN2vzc5+J0yBmW3q9MWX+PATH21LK+duvOSG697JIrDQ3DtfS47azE7enNdD7ntA1ZmU0DVlFtpiKP3u7CTBpUUEKk+IZFoSak6XnGwdKlXh1Q6PlOJkS+Gl8cIehyHi7EtFrUobfgtqhH3rGEvxVGRABCEhogGYXJm6gTitGiNPuHW4Jxqx8GilQphgoXS3CFmMJAl3ZZLmoMM9QtFUIienFWXHCwIQIKVg8quUHU9kjamW3RAruVNF0XYgaQFgukApHozkNAX8aLn8VAxxSKaYCxOcGXG9TsIu01IWbhOSCg0BHkTCq6MIKlryekKhb0tuUb/cuwXoawkvGSkAoVK8TRJewK54HEmCuJGLdUhShB+OUhqY77qihLkEbX5brN1agFKSAMfDy63CRKPfYA6YBBARKgnwU6tHCGGMOiLxd/YgKTE3tICwqRfwXrxRjVvMsRICive5SAG4K4SWfnGO53CcTo2eS6pVD1ZFYpFHjLGmGEeUBEFc4k419HtsCqVrw8vlpeNFSR5jpsA+hkuwVapFrlhbALUVS5yYU7+Zd+U7laN3s/mu328yd1lbnd9+oSGHzHcL/X8ihqkVVexUw3cK2+Gd9sXQrhXValVpPHT8HchSvkuvja4qI3MFavk4zv7MG9q+jib98Hey8N8Nlzpi+syf+I2EWm/tNWRT63vKZ1880mMM1zkCF5eSlSsdcZeVX3zN5+E1X0RyvvaUxS8EufNpsW5inhAtyaZJvfD9SWbOESlWy8ct/CsrDZ61zq9/EyJJIfQNL0dG9FPRYpxCXpHiWt4znZYz3Bea78MN14K7NW2bt+jwb+uB4ObxXXet42QRuG9kOly85qnnT9EFV0Hbmg44Lk3sbsp9D6hqhJEobcxu6k5oMEQjDX9miZGDS2ZETeM5ku1zLjMhFOaZt1RGAURxjKTIR3ETRhqhfTuaaHCQhJmU0MCOpDWTVNFgJBLjAllMDanidZu4ggijVGNWavp4tLdxZyRR4yeF1k9CqKXC1SIkUYQx8xA2cyd75FF12tfhAq0qqipydyqX4iFTXALwVClCBzsLJXxSwI5JkEQgUijMgeKJqgkPXOOGd+EBacToXAbAVPgSBopwvExACcC0IwE4gtQjyCjaAhwqgVzFgteU41UErwJ0JVFmKTw0yaJm19C+3JMqgObwDpIiFC5TKOQ1QEcuIYJWvHZVAVWGDEBNiRpWWAFJZZZ02Rkno/WElvAp78Et4fRvC66tyvPtm1NLePjqkm9UCXTqmMWYGuG5qooyrhIEEV5qmWU3ao02tB71p7xYybwAow4YQSGSiEVbCE9heO+Cij7YEYNePhcCj6Dp95jLYqQci1QjMHKnLkDOJBgCE5Gz2Ph88/eT0sTe73IShfpumF37e90VOQ4xnvScdbvdSa7RH3vKBzr28NN2tKx4uOb/rNUalg5Y0y5Z7Z1BQ10+7ojmLDTgiDtuGLdTPP7SYXf5VT5qhsy/vR/Wj1Vw0kNUWcbeh44+ydOvzoPFHJz1V1p9Q31FYT/c6wtGgrAcLoTp3oXF5oSvz5mWoxPcd93lZOF3L3+I92VlFq02pahDieQQCXKqvj+D3LcP5PPSdz7kafc3OMihv1GOW1Ola31bN/TFpjfn8Iw4CXJdf5gs/HbokL4BZxyrVcr/VfB+ZKvXbBm9PnKv5L4HVI5hOcLBGu8Qhc4M6TxymsQwnMoT7hl3D9O7KqPiOZg5uCheCaIJFy21gcJL1LUW4VpEDk7SxKhOiMF+hlFVMxEHUSaAi2OWaXOp05MLuQKKJ6MrcXPhTIpFbKzFyyIwQhB1WgtGQfWS/GjQJKhc8SoH8YRU4MauVSDlZRXIUljjLF7ymsjz6RRmOQgcuqIoSyGYmBBU7gGunGkWdkVQNzqIOl+a4vqFZMEIz1YlQfM9daMWobLIwwqu8XhDenDiBNhRCcXcijIeENQHi5RZ1MQywNSiwHFXwJbHIpazkNwjxLCAIrcg0YhMOpgRZBmYUpVXbiQBtlrxQh3uYAEa1IXawzukyAA0KxFmxkAlnsVJlSBiUfTXnCQJs/BIGoWuXSJsry+W3OBUJlDC6bCS01SSsKqyQrcWOWKVJNyCEAKL+SUlpDB5jN+BeeQ65QjF6ztRCvBOfc4U0FowNzpQW+RXZfcgz/AIB220lMr2AGCdS9AVIbjEvLJCFlLZvWXWecOln7R3e6M/xe2PvvFq799NBfU4ZcpPcMzq8aeRxWc5yzOdtM82/D483sp15LST4QxvSFFuHQYvBywoEathj+vw6zo0s6RAbjj2LsrG2Xi3DAtvGtnQoWsHpSwovWFuzdnLsvmIxXycTcq1EIa6cQoCJBaU+UMlahcmhjs0VkLY7+ZgHfWwCzr1OiB6kkucfLGOvTaJlHIw85sXblv68erb8vADwsVJipqQwhDtgUew08vXo/blUjMA9ygHMw+PlxO8c4vH+Nq+6FNj19tpTj5qwzqzxi629O8aELNu5vuG31blJOmawy0X2/cGrB33P6ByyB71pcZE4n1CCz11sTIU1jIhoaJkidyiGcKoStTijKUi1WPGSWm133Ey7SwHeEIxraPmkwSd+ihFgeBUSvQiDHWPDqxFSKSsUZtKBCPTdJlRAUERJhiJ/6aKeQYNT1LXhXIuXU9xbfFcLiQxZoTHo2diA6ctHjDxCAMrtVsHaS0jFkyFnQQ9N0SNLi2seF1PzY0yKuGBVQl3i8UjLmiFdjtydSJ0TEV4QJVOIUp+RVgkGp6NLE5djlMPAgwr1xw48FzIFtT1KkqTy7WB3FAAJlgXdN6pEESoOHUhHpl6hKQlLSQRIuQCGsYI5inCO4XBRFJ5gAbR8E71RXdjERWmBbwkIEsp3CxRQ8pKW00EPALhzJ2sc4DtohEiUHKZxLxYuATTKKAsgJa6TgG1Akgb0fcBWqHNYUEbS3jmECEVRkgvBoKRFC8e4S2zDrwSGndSCfAeihRLUdoK+G6AsSi9E9fc6TwYDCt8MHUqiubICexeT7/7Gy1nxSuLe/xJzj9Rlx530DqN+rSy2tizXOeEAGbjb68zil29/TotYviwro+l6MsLiu6dAHKHwjgzv9AqIrrH3XQn+Oc/odXhBLK+N5aGb+1cWR7gPuo09qnl0fH+v8W2FokIsFMX4CB9xu0cNgznLqzl7nCrjbIly2UFhPkGeUI5xQS6K0vfcFAPHJdPk4W/NDnjKgyboRb050QHuvcsw85D54xHL6dIl1ggt3WPkMBvvJzZb5abN9hlBjvNgsFmoXFLw720aBz9iFH/kkNrwrBknEY2oPI34zv8ettk7ntAlbz4SVwgSSTIi4X13hI9dbSLk5Mx1pqRpgj/ShV1EsZakZLSIbTi4MoII4siowADldZUIuScaT2A0EQUPEUxW4kEfVxoMZJAXf6vLrSFvW1kQes9pSN5Ctrx0v5xqmiBKc5EFEvh3erpwx0gO20SJEfyTyvBABh90WEoM4xkWuo/BVjwPPeqjAmPUuvODkr2qKu0Q3h4OlWUoATXFLWXqhThg1H0Nhjl3CJEsaMwzRUShYoILxvVinfRxjqFVwOJ+k+7CB3hESoOHVR6Wvm+wK0xLd6iCFULFrqJK+FcLF6WsiV4UfSrAj5T9CxikTtkRL6aElTqLU6FYaVNSaHJ4b0SInyuzzlLhc5+jLAvkReVPWo2KQW09KuOxvWM8AiOXUr4YQDMSgohRL94F/IQESHnoI93h0kBj9OSx9V6gF8vrIq4FSbJqK2mGqyXYwcscq6S9YWgHbqeOMRLxqzTpRi31p26MF524qQc/amA5FKocFiwY05gXijiY76/VeWuWF4Xd+vTYIdT99tJTpYz7DR3ivDu9dZ2J2hknay2d8ESvPZRNj/fPIdiVYVi0KSWw1qWL3mSXusx3bG+4NWfj+quowDYmmk2KIVHt+Dksq5P7gtZBtgDuCm910PsQ+BpzdmHOc59rUl/7hFYUdRh4HBxYNqGsc98zWT3pbsMYkM71ryDG5TvjXLsQN+7daQfgcN3CFKt/Tw3GPcQdX5m2dqBqzfhYNpF+Rvt0xvCCNtlYdoauSefkDlsm4/kmudbP6yHZcMxC/Dv8C8ri8/qjFpsw6GcpXX36teDhckyPN8xU2PNLY889iSz4fUEVfc9oOoswEMnHZ6D7jkRVNNjgUyiFaOqamqtkCpBUmpP85dBQrnvzIIFj45ZoTFXDSKHfTMqjTT/REaTsmdOXZL2gzbcS3hWRxZBtGOWnRFVTFRzugJepsDu4F0KzTkT1NQjSbgqbl0o14VBQoi8GTNjIonWgmDBS9tjUuYSXhgALtj+ICUJiniPsK6sRt0Hr0nkWLUI2ROuJd9GNIq2ahTDTSlqJ1mJMU6VF4DgeFasC5rzsfT5VD7kLGWLEIOopRXLVeTqRIhZJ8FYF+BXGXkptEvcz3KEKhjO1PrXNwBFT+OuoghGlSAWlwj5VELxTwX8mBhZhZEL3oPT4oVRiVC/UdFgonyvME7xt3nUper15sqC/r0xYaQBUispBX4lvG11seZpsTgZwVwoZbyrwujYiOEGDcYohRe0lgCpuXiVOgexPsY7DUDRCeINLxtfFAqO0E8sqNI7K6Gg0rMMRp80RIikefFaWow/ZRxJEYZaXpXInfLwgrn2Vs43o/3qLSBHKbXH7hRH/Ogb/7jLsq7xbxX1+JS7/5EDctKxOGytls2HHnOpVYiz5iEW59e65q8Cp1PitTuR02C/t4ysDIUQpVBUlOw+V7RXnlaWTj7BPUps1vrRj/3GV35wnzPQ5T5f3Cn1k3zp8stob3liyMJ/1oKDNbaKM8tJtOkjj1u++SaTiK1DkoeuFPrUczf6XXzl2j7Ps1q8dd+fm4I4+nzx4eYD6FkH/Q43sz9KmAMiL3qeL4yfsHDgXZDV1t3FSy9d880k9z2gypJpCTa11jXY5lTYkZrduqZLFS6ZWoNy3NQ558pMhVoUp6XzEhIlsdBkrISHJdwSLk4yR3PknmCQNZdaUB61rgyyKa20jFEqMVqCCa4lFya4COlCExcYLyQxGi6RvzRyYeaOEjWosoQ3xQqpgYuTVAp7nxTiBArttgftdlTDpXIQtAAhJRPKdeUgWakUpgKp1K1yIrwvSwCVqo48rL4dRoCN3YrIW9MIB0Mi/K5Pem2AVsOrkcRQZCBPiDAzoRkU8QCY7oImqEvSZq6jLf0iYGVVGhYNC7pzkyg07BYbl3h4pqZ9aKKU/DSLQrWNBUAZS6ErzyBidOKldG2OQs5VFMnVQhXeWDD9WX9dC3BZF6r2jgA06tB2QWGfSpu7YN8PAhKJMLu65D5Z4XDv865cBHGhbS1ANRI5fB6hGrXF/bKE5zSAnTBDgmiieDt7ANmIl/AFx5MiOAlHU1CvWwFLiqIW4Lo4Pwv4jXxCIEC/xbwySl00jdw6O5F57S0s9/Lx7pbysXTBe223O21DX0c74klvtXjcScZgWHzWKzmrl9l4qQVL8PycXoW6E3/pCR7iRH1znN347ovf0XO/CaW8girOw7vCTiXsd/DS7VUINJ+APaHTun5YHhFfuscikFIRqmQRWdCvySUSIsrDxP4RZUhiz755YDR5BdIdcjksA65N83pJhvP9iN8Pf7EYgLhpVhw/M+/+3HV88MZsgjzLYHT1h6UPcb4I5yrh4iRqcY5GzqiKWpdLY0gYVZsOmlwAcd8WDx3AvS+NEjlv12aUcd00YpvXsUOyMs/WnT98dYqu33Sl0+4WRz3l3ZT7HlBVVgXVtATlwUgrNCmTusbQCMPTFEqvOeMszCRqRSWNcMDOnFqEWdfSFHCTVMiWyRiVOF3u6LQmGSTPwSznQluKzHoSkmbMlUbjeoKiquRs1JIYk2jUwlVMAKwWR0iIBz1cV3KyKnfcwsOSU4R8dVoIKUoOkghUKhyUosKtObuaqKrIo6pUmRKKeWvOCHBRRIS6eMSSR+0pnKi1pFaARSy4OfR93IKUQ0RoS72kVPqtc3A3JEFlSps8PEwe96twukrIuc/RiRyvuK4z1gB7kqL4cOVxnZwij0gEKorFzcLU05qQkzHyAHdBPW6YBgmEOuBWQiUF6AEeUVC3DYa8rOEJw4MgwyWhCchwIM7IIBdwpCJM3cpiF5vRTK34+YQOIZUaZIUDP0InM4xSYQss7bXyR4QqRp+bBSDLhZii8ULFT2yyWixO5pFDJgQpazAHhpZWIVQanqyuChA4raI/vWhyIvH/uqz+E4l3QogQTiUYjEaiJXwzmAgVGEuEQprLULi6lgBmW+Hwir5pV9i0Y9y1XeFkN54raie58Rl/H3bNDQ99L7DWScZhg5Kz9thjHv3Omr+oQK7/9ejrH6HgnEZeB0SzBCdk0Wp/Hxhk1uSvgHDQxt41zRHtsRQrRezjO5Xw2AXjmRuJabfGYzS/avlyGaQMOT8ijFOEp+ORN9x/LzCEbiulZEYu3pnF1//QUNxbgL22CCybPToLJ572Rstvylnm+8rLuAygVn/YDAjnFyv6jQjjCh67lNndibD/fsycILNqO+H6bdhrwhCcLfQJH6bUHBT3jIWLMgzx2iVYWEq4P0HnnrT7zmIvPPLaGxfEfq6f8CZnkPseUEktjEaCeoWoImmEUMKdPGo6VSWUSSzhKRYSM8OAmUU4YNtlVDRovD2RrCN75JQ0nqlRpANXJRdWuwpBXAdPCcWtH+FagicLt2uYnphph0gie1BO18BIUuTXCFSl9lMiAFEWo9Kg6K7cY8JLAWQWng7TCBEkhSfGe1IKYjEVoLEcFOweSnLnTtZSy4l4G6sCqjRUfGqN65QyXBHqp+GVES2eCQkmPs9GJ0INNBqsdeYFAEh4Z9QdLSw3JKWWyIlKfSiEg+YIgSz0DWQPq13nAUw8B5FFK4AYlVHAYRTybcuGVpWaYi0B+AK8egnBI+pcEe57KR4+LwyIRnjzEBiJ4SnAbeTlKeMCMpMGBbxrJKxqZ1Q5nnVUVu6wFEUdr9YLs19wvQdhSqm/JU4wQopgpR9biXzAVJhFRigdTpvCU1kZwbYn8yLJLdEf5gFwxv0c8LD/jgIll/QppxA20lHCA9QGoGhl3Mwdl8hJ66NVRq6Fil8ir01Aq/tAIVqVs+wEq7Ju8T/uWvdMsV3UmO6yR2BVp1/3jFL+sxTrdpfAwGo73iRSTCbxx4nadnjCrCrUJwZYclasKvesHw+15S4P/xsrwmGDhXC7hf0uFL00FIj3hTOccQXjUUSfFGg0eET6a8vibVwWh3lJW04aNSBzhv1GcJufJ8S6fWXHubKbeWpfyaZzZXqF5q1X6Hvwt3DHuRzxzi9Bw7WTcQOYWvPdRpy3SWTzn6fl0zh0obs2X539Dpp9Iym8fBARQ/OxLSDJY8WetQGk+jDNZZKLOT3/IkbebFpbHcfFCXXWp1k+3Vd+dE4HeE5iF3s95b4HVJN6xCSNmbqREXY8B5pXGYgOBMVzjuK8OXTabInkwlg1wsfqoFGvcijPPbSoqZBU4Z3hIpgoiDH2YOMzwmNjZpyrKlpxjPBOpBxFZpMlNPV1yoVRCSOzMttrgewV6jDRPp42AFuHM0pWWNTCk5M8aNXNYISSCcr1nhEuFVDVaNBrj0zBIzcniwURRsFnYyf8/5TCuQ4TIhwsExThnTq4MC6U3Vi0w6qY3l6Y/jrrax4Fw17Uy4LGDCRo31P53QpICjAVAM0t+r3Pu/IceT9VKp4eiZC0MURdLbywC8aLphIhkVEnLIBNJNRGxLNZ1IlSCTAkwtCfSGxCThk/gZFE+1LJyYrcKilKkhUwWgCIljHLPTlGtDcXcgizIO8QiTDR5BHapxLFkSsRGryw9UQ4ZhwfQNEpIYbWew6djiDFmLjQ+jz8UVSRxiHFM44R0JhzYwlAWREkI51EKIE5TFSGMIMUU7OQTUT/ZCHCXMXxBI2XHDcD6d5kmuydyurKfS+MtMduzKs33bw1Hv378bKwHa+53jEPLRs+bzx+nea1ALTOKmcemxNoSIfMuyft837dj0NXC4Wub44s32bjLVbVl+Xrydpv44vhkpuuvXDpu6o/bpD7YfVwWeklCU//5UkhLlIYaeSuugPiS2D7xr4wVsMq4aCTQcEtKvXihZlrpytt8GCBNe89GHMSDHyI1SiKrRTFu1xI+pna39EX/jpBMOpKe9aO6es00Pf8Nsfd4ATvmCwYPHIZr6ZZPk/mq0d85bI0H/rzl+ZI2bN9PqwsHXyXRESWGCHnbVy43zpZM29PPV5HPcs9ZBy+7wGVm9NkGFHT0WESYXeKU2siE0pzhaJU1IUGYqeOULWa8NR4BzM6VEtOkYfSmi0HKNHETJxao45PJhZLd6hTkBq4OZUKRqLWMt5CoT2P8KgZAgm0cGHnAgpGBJEBqqgFS2Gf87SfBU1C7UZdwIyIkaRiKkEMoZ2Qq6CGz07kTHlHQukwXMObVomQSg5UUi1heRTwKcFKSKm5VWLkssMkRZ0jrBSwdUeK1U3cGEmiEUMKSQJZEAkmvBrBrJBCCMwMqKIPciQXDUWBg4q8KP0aK46LM7OoKxb1nRxLsONpyOUJpkUrXsPwwtSdMCvA0wvoCPrxUujYwxOHg6sP9SSUGF9V78nw2HVhJk4uG1PG8ZJvF4tXeM9EPWo2ubPrkKsAkq1GvaysIBa5TFEUmBIm6IwsiED6549q6s5YhewBRAWJWmFEjle2ADZKGAqiCx2tCqAFakkln89pAmsGEPdCQV9y5qwYCQKqlpj+4u2ryDFernTEe6Ml50stPHtvZVmzxt/hgQty1PFHmfPW/3DERY+y5x0+fvOedJaHvEM50fS5y206lYLhLIV0ycIH5/CFRJhU9RBeW75aeAJf+mf5j0X1aF4vyB2mbTtXYha8FOtGenAErsOvC7+/kbI4BG91ULWWY02cc3Uf9UHoD17Ml6VchRXg05qjGsZIcZ0DGBn+w1xpXv+um8N+uzgHeiC0OJucq/twbT9Ijeb3KNeRw1/N/94wmRaO6//wlWPn83hR01/kyDz8Tpx0TqwzGhx3wup7ck9k7bVjjHcrYbcOwqs6BflZmDQXmtnrJBpzyczDqOmhczRZuNWW/uy7zwUzuN2V3HNZnJlzmoq7IcfaexaOO+qmR60Bw3RZd/OFk18Pw899D6hay1RmSAlHM4RUBXCgitypqrCfJRWwCsdQE3YIhXGWgVKQtrWMpGKPsUIHThrY2KLmUQrQpVHw1cUZMUIEOgTJRnYhS8eIClEneyYTeTrZg7SCDFZFoeBshquTipLa4KgqdSGTEY8aVx3OyCNfrAOShaIeBWlDUe9zhWpJBeRFf3TE9TMwScp+dsYSoK4poWCKMzNhpDLk5YwI6vEWR01RcaoE2QXphJwU8Yxa1LcCCeZFCmFEr0kUADohPDZYqbHc086VelUj0dKXpe0eRZZbmxckRoMe30qIQi7Fdz33xXJhDycZUZNLQapYoEYIlMWrJVPKggEgHv1hZexFoq2NhrcuRzNpXUgGM3cqjY1qJNEnVSmh3lG8X2qleHCJY08lH614hiiL5liUhpIHhaFavF/uAcAL8jWnFIV2xqJ0pcCgliWlYFSAANQedb1cGGpxdTgzdyZaQh+LVzU8aTH25oJahINmYahJlQrk2kGD5EMsQhPfqvJmafqwIxzVoNNshYtbzPptdPPVjgN0DAqTHLr04e3xpBvvsXIUZnw9ZAM6kRWmNAHOjSeklIZT+nW5lxjquVLZfznoCT3qkfjDgXFXz+dIObDLxs2DaX/FBQi2WY7tttcJ3SzOzjfLa3hWGfJQFh6kM+GZW71nCOZj7atnDsq09/mpEkayNhfSJmF5/pWXyheuUapZHAbuwynxsrrPGV/nlz0Mb73Ms6VlaQFpLb3XS3NmZQL5qodruV3L4Y2HjzrRdDzjnL0bzvG1sumaxZA6qoTzY+F8pYxHKepzFuSw6Ll0h84yreUoNVN0Arcwds86jZB971l+S6726l7ih0bsLsg9hjGrdqp1dzv05b1bvO57QDXQhjuIKlSKeFFWOyOlKBbrStBio6FkigW1eXmTIlQsPERNl6klMZKov5TVacwQD09VJuPJqDwVBrQIkWswRpoiR0lgoglyyTERpXWj8sipqVMie093TVgyy65yIEalyghQ9Qj5ykGAIRLMe51kXAvdNxpMf+5UVMwsAFbkL/mgaONGgzAyOChkGrOyaAsR/mciQ52j7MVrRHhFTA1EqQvoqjysJtmjNlSjRDIYHvk4rkHMsGBU68orbURe1kxKqGKm5OUk8B7IgrvRECe4BAOiJBArZBjitIXuXPABXPYgRUTDO6cRW04J5xMRXIyxx6LkEh6X8KQVq7JHHpcBufNiISq5cwKizrhsFFpCBvtNCmIzzRK5Uz2QllJU2oUCcilU9k7W4s0iD2x//dpQJRm8S3UZWy/kE0J4ibqAkkHlTyzOs1LjKnnRzZLQGOxIAKyZOGKCSaLrYi7UQMo6eMK6AuSyCBMPgoqmYOAYTaW9Z2/46ySLoOBNpNktq139N7LhCI757Sj15PiN8XBbjju41+zkhHc4Sk6wSR5lel29uax+f5LBP+oGy/b41VGQhaOWlN2iBcu6E/G5Ai3xno/rqledh2ZrznCw/t5n0i0O6+yHfj7zOG6arq8TgHvdRKAfo2xr3sqFSSE452tl1MdZE4bFK+eMcyPjyWtKk51LIy3kS/PrtybsG+xUEWmz3zr7i+HXIiiliLxECoSKFapuFgCVL/lG3MM4eLtd8G7I4ZE/3vSzONvXz5zFuT84X33ethPNtTucP7LYiBXoFw062zXdfQGsLvw2gOj4T29YluFXCpCN/92YGq/sGU03B0tO6FE29NnqPXxhjm3YOQbSknkbix39lAv+nclRlz/5rUuj72Fb73tAhQuJDFKTO0fNMe/oFJIasxyWf62EyhOz3Eaongh4JnsKFjO1KCBrhhSvzQzAlKh35IW20hkl8CxM6aK2kwiJyJXJAKokd2qBRsPjFBamcJFogmm2UhA1aMrrAqoyxlhTUWwD+AVJhXAOpeuMTgHCE9YCqNN4eGOMFiSFwl1C91zmbIQITHsqbXOyBZDKKZTzVKxXLV6I6oyKFEVwM3QYkhYIE1SoizLf03hLURBqBdyL8i00bmWhDJA1c6PWoGyf4WBpIMuggMJEjAUiZM/ULuRSPBiNsMuqEG2YFaVfAvBkDYBQ9VTnTtQWI5gdW8LjJQSAq1xKGF8QeYw1GBU9R/JnJeE9MiUoz/GSQGqMyupfF+9NHyaJC50KrQlJY5xnDqqJyPqDHem9jc60gLNg44vQAM1KZwGuvezG2aMPzTMqQpMLayLOTGQo6jwqczlgT4DQSqJGWeUxP7JG3a3wvFkp+hhhA/274Ahjc2ZSQhsJQ4MvLO5vdfGTrMWvo+K3Dg6tB1XrzpKlvxblLDXDDrflCHKEIy6/9px1GtVJGnLasTgp2LoL4g57zTTCpOd2kcLctXjDMpYLbRtXFaMqrXzv82MX/hVCERtVaQgFjBxVXz7lrM9xwu/uitwvoGrNc/jCf9cd07njeQ67s8OtBlrTwtQXe1qxoQYhkgMljzZAUV/TKOZFQkv0RB9+V5T7EgJm5S0u2Awb7s5CHaOzPv7CA5aL1Aojnc/b/pBBZxB6ziaywbQbNJhDV9+0sp19di6bQ5aD5E5+hbXvyyqByMrgh142/27x3j3oGtfCpd35XMgZDlpoun4Pdg7yvPVBkb/4BGU/8CAS63PLOXzIHPAfJ774TCftp9MdvfaWR+0B93gN+U8AUDmdJNrcMnIhE+FiboAnGjfqEr7UeBe5NMXDUauAdNSuuAWjX0cw1lHoxMfaq6IwJcBRLuQHqbwEvXI/EmXsiQPvIGksTBLeKYUIM/Pi7SqvjQJ4EBDU5iXTC1qMVoTaoo6RlcSglIIxzstLI0QeTeWRF2QlEbYpyjQeL2ytCaOQLBDAwYjzTCCZIsnpSn2DvlisE2yJCLhJ8eKUFbwTWo3QSJdg0esJIhLCzIxxqBRkm1MNWWGIG/V1pjRe8h2JhWHWh1d6YcEjFP1RqSMGimiJKy4ERbVDW4CbeTAQRn0lASv1mDS8Km2f8eMRgqPEePdFD1vCgpdLGGhOMVpGsDuOpRTWlfAMtl4AEXOa2j7fonUKJNShxlmKOMLwQhG5cyJSapUJlQkNhimMPZj8WuIZ8chjymKlX4RdDxNXW4DnqLRDyxzLxLi5+VA3rCPyCjsPDveMMPPIHxScGR61rxx2CsFLW3LD+gLFnQWwFhGqFevYW1+WgcnrKydRDJbh1eKZx8l6HXv9/fyIP+ZD3gMhWTpUhnPm3pRVOLHYbl96grMjp7Nt2Sc9emFeHHGK40ybZjhjjov60Kz+aXv1qddOBCYT6qrUIVgFmMNt5/9Nmrhy4XyhT3ZuHhwwaxd8xmsG/MgZdieg9TSydO37wiQDnL7LHDjoYA5pQva7+TXBuTqz4dpa7hNLsjDLAaBVhKrkA0+S8fgFp8vw9A2lteVCr5Tz46/VQe8LwcZ+MXgtNrxdm4JMF+fZSJ2dek4HHv/v+yx0gqqKW7ZdRHi0dszMOHTb04KqTavF/PuNVzzJrYoONn8H+yeP9TPULY9wvQ3XVoFLO4mHLkgBnE7TCc9fN25PjWxOm2FqMtxnXMEDkxQpJCUqx9zpsnO95M4dWnuOfbDTfj//dQlBn0b6reXYfj704Z7IfQ+oxKDJVkK4nAPr2JEKFBrrwsuDl2KqEa6UPRXvREWSUGiDLc+oSmFYkVCeczbqlJgWwFLjhcwiLPhePCDJhc5zYdIrYVN4CfXyef6wwliquSqU45U1dzQJDUHprh7KdycKXZgeGo+cmYwwiirBaAbTjsacMRGSZxD5MIS1CjGShyclVUqmMAhaxhSUoMEOlj5AooCse2z87qX4LjGh1PoY7IxbEE9kYmEwFyZEAWR1YZZjk8hFgailXLd859G8yNPRCKscF7DoJSZhpNHvowKOOsKCl0r4o3hEvLhHyJxJhBualZBHD69ivwGJyDCGlUHWaHNnQQ0vpiQNr55KHCNE+OeMADfJ4vm6Pp7RdfDAYUpdgHlHANGRRH5aG0NOXVaIAyIcI5kzKZ3fe6k0M3iHKory5V7OF5IorpkOgsrfJdgCPfLYRh5zpgpNNgr3FiKUMbHAVkQx7OylhlYhuEj0BYsDMIvEccnL/E8FiGoJa9HjVry3qpQd6g3AVadVDWATWDqb+MqHQ9cu7/GcRmrhX5fDLLzl+HWhPMPnQY855imO+PkoKPxGzFJZ/DQAolUwXI5a7Mp1eYlrH674C2XB43C3ZENnnmVurrvOCX54y8nmd/CoXtv0vcz/278/RM2iUZLhyz7gNKmzM4q9alw5ly9EuHprRtP5vG4RPkQW7HfCQZ7Pmzk5xMKLf1S7Vo9ZWS4H50tJJ+hD0YTewFJyzEoucLD3CkkkInCW5uDR/XR62TRaK4BxBXcVO9G6KMiNsngXpwAch8Yc6Ww5BLO/Z4Tr4BmkJTyThErYGswyTNtIWxhsMkS00a1ZWWlkDp2yyZxAqgDl9V23unif/DmHKyxdd/UmJwBnfsY15h7KfQ+oDtw4Z46kyPuZaJCLZ1GSRLKeUei7i3KaPNT/hEMBUC1RqylJWPQ7gX3PVK7UpMifkZYpiVSK97pZeHpUqbWiIuimg4k9kELvLcuSMI9FUPv7ijBViyK9RG6LS6bSSI4JcoEOT/E5aUJUOSfh2WlFiHpMFUjUEIoirxr5LdpbgnxQ5htrIBtN2zLb22O/PcBzy2R8jvG5C+ymXaSq6DDUnFZisU6FoajLBHmGh/VI3KIeFTCycNt3atAGKAlg21tiQznvRJEyZkLkm1UOFG9MpRoeIqJgr5SwSSGYkKaF+pwSK24lFM/daMXCW5JhhlGn8FyRBVHDidy0mp66PsI1s3jUUnJhpEEqUnmMWaVRzyxbMAymMlZa8qNwSBIuPxOYSgRTBIkHQ7Fe976mVnkei3BUsyCN2HfCAiWUsMlgBRyrFCDmhQo3PF4zDzqJyDcrni8in6zz8Mp5Ib4QDwCkHhTvuXwZ/3hQLlp4tzohzGIWNO6dOJ4JkgzmpBvQc4lELP/9IWuW8M27zj28da+wnG5LkZW/1pEdn+RJfPjPyvceJRrEyv/dUYxUzIhZlKYeDbUM+u1xvrku9uWKFrbayHXK/LqH2aD0D3daOGdxk1/u7t4UeoSsoskN4kvtOf28cS8e/RWdxst/pbd6s9ibPniovLdYHWruGuPAavOO0/cXjl83iqeR1dF/q68gqwaC04Oq9ddad51Rgp2RDGyww3UFRsmpq9hDb+5H6H5SZ1zNw8Pc5/k30wxzv/GaAV5p+XH6dxgffc5uWQ6pe6erzP9Vem9brFUaMWnhQfFqAW6x/H4uTr5DDTrtzDzFDO6fs7xifa5X37TVO29aApyIBmoMcpvZz1YYk+cnCjCuDdWOWdMX8Q0dJbvQ5kglCM/jwn09PFZNYe/SpZattHAp1HClsbKuZzb17WqdNF+7Zpz0Wuu/P17u9Tpy3wMq96gHJFbIB4oiWeWMSdB7qwgqKeo1kXETktR0yamzFAs9jKpENqdGsZK7VBW69FziU1UzYpHonylhfdkwa0ATjpJyKBYHeHiviPk1EsW7DJLo1AqbTwnBU/AuU2vQeVtZXEw1KNOrOkANARamlks1baBSag0yBy0ehsY9mA5LxuLMjReuPsvTz3+NZu+Am6++xPUbVxlVI87X55i2Mx5793s5d/lR3vOe7+DCZBerHTWjFF2ndcc0FCqjFJX1sCSpW1lkImRNNbwhFYKlYBNsPbyBFeAFWAoBOJViqdHwsvT5PFF814dFS5SBrp4CFMwjfK4qIKVCwwNZVmvHkaRDPSjVIOPQHuS50HqAxHCPB4OfA41Y5KZ5vzRZcdOXOk4OSOSvdR4v3JhgaexDA7NEMV7LJRG4ZE9JmTteVufkRFFkLbTsGoyHQVBhVIX1Lxgefaiz5R61x2YeIY9KgMSS/kfyQvDRg7Ug9KPz2PSSKJULjURoaSpaaCsRstnkoG4XMTpkYE5sxUqQir7llaGQN8geduRtj1LANn2/rDGfFpRtPNrh0rWrfPvNV5h97Sn09m0q67h4bsL73nsFqWv2W+FfXXw3z73tbQOY6+vdzDHVOtB6zGOsfjdc4thde6McxmnHKLvHabkbrn9c76/edW825WA2W3/vJTy0Ht1kt2I6PAqJlu985aIn0/eH8XyD3pi3hNwrM4wT+VV7rTEUdy17iAOyTyzyS2cs/rWsXPceq9VjV9u/bqyXVpqinKsE4Es6P2DxXehByOjWDUZNQwreeGp1zIMxtjbwruJmJ1Al2s6YuWKXHoCqGu4uw0OvWwfOOkPv1FSweIXVHoxrmgmzDrosa8opyPBJEVTqKOa78Hvfj3lh7HzhPPHQkyp1JhGwhS+cF1FR/VK8fPfOSvrDSuv7I47drk725cIl58aA5dOCNG643xHGs3nr7u2adN8DKpHwhKgbbaEYT9bXK4qwPfUEEkQRgpIqxayjthGqoXyqClM3vOSQZIRzpX5PJpL8p14Y2tyRwrpXp4R2QkpBfW4Qng66Qm1ZkpLVmGYv7HYt5spIlcYztY4DJIzimbIZqRZqr6hRci2kQgThAlktyA9ESAnq1Id65QgpNGXfSviHCtmMJhtf+dYXeeX5Zzh49ilGkrl19SV2d3bwyw9j9UWuvvQy12/uU+mYdz/xXiaToP1NRBJkLdCpIJrQLEzMkRrakg9kFgvA1I1RUhwLlj2JkLS2vBzjTIQSFlCTSm6PlMKyZqUuk0Qs9SgtUsIKlBjxqq9tBcWDVLw0EmC0zwfKqjQEIQQEgUUQiMR4tASAyX1x5BxA0QooMy8FeiWFBaTUamphyFWyQk8ftcNgVyIPTUWHWh9NCY9LPTDSWLiqJJALWMURNXY00aAl5y0AbHJhlJyZKZWEtcrcGKkWggxwC2/aiMjfUiIssUWoi5dMvcxJifnhEgWPE71jqt8YFUxIKajyrdQxkx7JeoRwzlIwV7615U2oGp5BH1hWgjbtPpsvuopThiuUIT//9d/j/ftX+R++9hzfnB7QCTxeJf7Ea9c4P0lctUz60AV2die0mugmO0jd05gcc/dNhsrjGtl/Xkj+PtF1Vq/SLzIbkZOv/XjoWoeasXq95XHxlV8irLcoEr4Mi4Yb0KtV85MH6mlZvs+hpvrKuf1Bp9T+7+SNOXzum/D9O7WsgpJ5jsryKB5+sU9rFsgeRuDh/NXuW/p7AdX44YMGuvfV49ddauly/QXnTzf/dxmhZyHCN8zwnPGuw37xl9m7dpOLKrzQGY+MEq+Z8/goDONiiSev7XM5Rbz+Nam5+GM/yuThK8zfndIGZyXEjKX7n05O8DJsWGrmPbrcL+taECzAcZQMt5XhhB4cCCwRW5SFobzzi3edz6JRgp1Koph0VSJ6FhppXkg/SsRM/zy5MBwXjDusiVaM/Ef259JPpzUlbDheVta/4Y9jy0zfE7n/AZVnyMKBdyRJA/155cqORjhUC4ysZSQ1VswmVdJhDzZzPBtVFTQGVfGetB41d8iKSXiPzDzo2U1QchQAxmm8oyZq+njHEColJDoyu14DEUIYHh2lM0NJ5Do8OolQvpOm8OyI0wQ3NVUO9jZ64JHmRWg7oMuRD1MRnokKLTqv0eWG2eyAtLfH3ld+i9m1V/Ba8VlLe3ALOudmfpFu7wYXLj/M7167yv6tV5lcusS73/khdkYTBKHFGJXaRI7TJqUmlGoFWg12nloLjTtCp0YNuGcqNHLVNLxokfsDjQeBRF1BKnlPtQsH2ZmVPLIJlNA/SIV4QvAIq5Oom5QLeFGV8Ca54ClCFSsEzOkk7usIYj6sTephwzF3Og0Sh4qgDDePfKKeFdAsI0RYpZSVKFO8QCJoCtbF2lM8ixE5ZQRVfB9BJuLUI6i8gC4NgpDWhal79JswkIG4RD0KISEuqPesir0yNQ8ldIlFMIlQx5sCXopAJ6cpfVVLrOG5B4CEZdFKuzVFrloiQkRmFiA5ZpbQIYxxbt8P+tAmOYOyeSrZtEeduU/v7mAIQNNR37zNLz/1Av/DM89y3eEDdeKLTctXc+adL1/n/TuJp3ZHPPjyN/l905f4iiV+6/EPwOOPskyheMLOXOz3QxrnUYjmdLc5fLk7H+xenVrGfrIA2g7fyle+nHeXrPv2kMQ02qRcHqMkb/ryKI1wK0tyGFYsK9Xz7+5UzngN3zR71l9v00wTJAxo/Zwup4uEV2T+9PP+yAbNtetMPv/b7MxmHDQdP/fUy7zSwXlVns8wpqXTxIPVvHboVw+csXeM1ZHa+UNtx/hQ244CTWft79Odd9jEcbiFi32FlFBHWThrJUTSF9eKhVN9Efw6hbF6+a5JoEpOpT152XJjhJIOYJCSLFRniKipSd3TZUQbot5V6HdLN1+86Gm6bJ0F4VT77EI4+1nX/DPIfQ+oRgoibTDAeVBSiyhakpl2EMYYnmoyCRMrtNpSiB8SoYGGV6MrrHFJg+Gv6aLuESYklHNJmFmHVYqUIrKSlPDHhNs6u+GewoOiOZjgsLD4SyxGRh+KCDl3ZCRCxNxKcVmjLgWEEXCFUXk2IzwsQQwk4cFQ4UDgvM9Z9FScZ154mt/+wi9HiFgnPPS2D8OlR1E3ulnDA5ce5IWrz9A++UWm7QH51ss0s5bd1LHz+DtJJD74gY8EuYZAzkHOgRZlnAVAQJBRTEQZERTmMze6AphGCA05LB4EYcc0GxNXskQBw0qccarIFstx7YLkoBMfWQAkJ+7dhwBWqVCDe6ELF6chQF7lguYI41MPkBrWIKfxkt9UvC6VRL+bOOckAHc2H8BSAKfQVnI2KhESQisw1jSwB3oXi0sucylTLD8euVQVlJC98N61pcKxSAD2fgF0j/tmooAzTvGEAiV3rQI6yYWvXwqleQCrWuP8VLyDqkplMWcrDBMQL1S6hVHQDHIGLTujl/DAmYfH0FyorScaiaLS6qdcTN+SsrLarz7vmZX3cu5ZDKlnlkH1PvTtoSOLpTQ99yIf+uxn2clTvtJlrrvRpYr/+tyEK0n52M6YDzxygU9+5yMwzezfmtEKPFUZ1/s7HWKpWJCjnt3XfV7tsLWtP+LCm4mR72Ro5+cIly49yHg0jmsu7PyLnxc1i16dWkyA3zu4zayZFsPJgg16QYnCPaIj3ObXG6zdazvvpA+x/vPK13dt2r7F15ChfO+QUBNrcRKlTkKTgyF3nSP1uL+Pk5OMw6ruWpq4RspevuE6O5Xz6K6w18DNJgyDFF2mKrTouSRpaYq5OuuEazf24BvPMsaYAr96oLySK5CeMTQMtcwKA7I7LjWgfN8DNd/+yEUu7u5uju47k9ypxWAdcOo/LQOfJfHQJSQvnmxDyRnvFYA15DyruGMRxgswqYRJLRF9pT1oWznfA3SZ9MWd5/1gBk3Jie6bbUUXOvKBWD5n45AsWplWDVn9ZY69SPwoZS0dDvdYJ++V3PeAqs2BNiIXBHa1GgqgdsnwwmpSdQSLDNBqjFoFuLdBLSmOeWacS90gnDFOLQkXI2vkTDUWcatY5JV0EsV9k/SIWUkSFN/JYFbY9hJE4r8qRmEIxEhUhc0mWPZUtBARVEP+jQPkKDbclRcBj3A1EwtQaU4So01aCgQ7GeOZp7/K7/3bn+Pcgw/zrvd+iPPveJjR9AFGoxG7D1zmoQffxoNPPUmVM9dfeYFu7xY4XP3ybzB6+RUe+dH3USUNpZlEFTGUCEEs4QXsdQ5VyU9yIvzSPcIRzYO846bnCDMzL6x+kVfWFkbALgdhgohTq7DjEfLWlgU641imLN7BdNgQIC9J1MyaZahLSGA2hoKzVfGsZaEwOxIWmkInLiqlb1MUvS0MPCClblmMe13IGmYOncbfY/EIynNobc6GWBU6dAdGEmA9XO9CX9usy+E16jzATfK4T4ORUJQ5WGxxpA0GyVwo+I0IxRsVICUpwkva4hXroNRJC7bJxvt46jguI6QurFwHFuGLQeUf4QBB6Q4oTHNP/hHvlBiFkGR1YXwryp1urHcoR972dUVb81vi4Ip2mappmeWG76pH/HO7xc0uyjr8gQu7XK6FrzQtX37hJr8/G7nreC0rH/vI27CrX+cbLz/D9YsX+ebj70fren75Jdmwgx567KPAT6zrQsx5keUaUKvXXjp3IWaqxzuD4ltykk47BA9deYSLFy4xb8TyMy4qQhSlZmh7+e3lV5/l5u3X6LHSXFfXOXZy4/bBAU0bBp15IfeFix+Ssygd68foDZidb0pZVaalJAtdmjhPXFa+9LJzYJvPP+KCx3bwScHUZjX4uCsvP53SMyYXhd1j5nV97nGOcysTxrWi5txq4d83wlhrRgrvuTThvSUCohahFkpJjsIEbM7tDPsZ/sx7zvPtV3Z5bleZ5n32G+OWjkiT8UrrTivH98Da7hhuuvn8RW/dki3OY/9NhRm3ZKqUd78cvLFJPWgpxFKU9AfxwrzrPHo+sTsSXtkrBZ3XAR2BUSWkQmgx2Hg8wkm7rgBqXza8DerLEd1y6DufE5Qs2ns2Pt2JbUCv/6pz3wOqADE5gAhKl6KWU2T4V1AlzNqwFrnRuVN3iqvRaPwNERaVtGbmuQASZYZREQV5K41FZCbBPlNpVdiUjJQEPGMeRX6ROkDcuGIMJC8VgZIUmuyEaim+JxEmOPKEJimMPU5rHZVUsZGWsL/WA9iZCI0Xz5BmZh6KsQKenSBJiJoFb3/4CR5/9B3ceukb3Ji9RjU5j52/wu7j7+OcTTm4+i0eOKd89yf+AM88+xR2cMDe/j6XH3kf7/me38/7PvhBUooXs7XI74owNhlqI7UupQBfVHivJBR3F9ActY1mHuFymCMWnqy+EqFKhCyO87w/zIMCXvFC/SG0hcCjkqi33HiAoYzSSnitDEhdAo86TqmsFCqOdyBitFoWGae00xmXekriRi5EJZ0LlWoAbncsR96UlkUlrMTh/UEDOFYOIyKEriseHEsM4X6VO41H7tKsABhzGEshifASfifKqChQkdMXzyw4Bx4A9gIB8scidFihRIeRB2rKnVOXGmbZI+zRLNgeSQXouxQPWuQH9gtw0L2XzcLDWii5MGZqgM3y2LT3A54qsnl7vEtWr5N01Frt57Rqqxz+84jrycq/EbMfY//OX/zXfNuN1/jbCr/y6k1udcEy9a2m4Z9OD3jpQHjFhJfbzP98bco5jEbgR6/fYlYr3/PAhFcuXODJh58ogOqsKvjJznGE3d1LPPDAo/QhufOnW+2X9aQdsWwIZh2vvPwkObeHjjleFrLyh/sv3mFOct4rUxFyA70atDM5z9BChyHQZdCOirKkN5jduB6/LykkCx6vOwJRh69x9+3A988qsjinDjp47qbR5j46guM7bynnZV2/rHuHNr9XRyqwJzqjb7Sz3ylP3bShVuXci+LlkMVQdBhde40rzzzJlZv7/LEPX2SngnqcGNUponbQ2HcNXtzvgvwqB6PvLBtk4xFp2bv2Grtf+DV2Dg5IB8bXzj/O23/ke5fME2cziy0OyIYzj0YMLPVkyUOqUgAdWRz03s4hcGE3jJUHsxIxJfMaXbEuyfC+y8rtuuxcP5jT4EdQTLzrLx84o8YYLeYfLSyDffR1Ub8wn1+878WB6GKxW9ZNlqFRa/ab1T8OganVPj/0pEtt2ix3fyXaJPc9oHIElwopIXF9GFgU7gXBgvBGI1wpFfuKmpM8vEVScmxSihysyiPDvkUjr0k6RlqRSKRKgkCAULhrQvEcaY1bjrypVDFyDQa8QnkuRF7WjhZ2OxPaQqWuIpFPJQGoKo1z3TKNgJtwzmGKYdlIUiEljAuLt2IiQpuNlkI7rlG09eHH3sG3/8DHefZzN3nk0Ue59NAVXrsxxdubaB5hVYV0e7zrygOIvINrV6+SrzzMrZ0x33r567yw9xKPPfFeLl+4xKXzD1Br2D+78gxZw6IhlELBOGYyKOZCeJD6ul0tMT5KPFdfI1iJsAiTqN9lHp6PAFHhoUoei04qVpSeLkjLIt4VZWJGAGXtApy4lwLGxP3rzBDWGV6qWFSSR/+ZKFUB2U4OK1zxzhxIUL9XhHXHsPA8WYTy9UQTpGCo6Swox6dSit9KMBmNXem8FBmWAOutRZuCHCK8Up2HV00D9dCVnq77+lEU72rpXxUvlO6Bwy3H3HeLGmcqZaPzqE3WhyBOHGZl0RUP7xMShBxtAX518oHJcazQudEVWnjsNKbXN6ts2Ezv1lo+mAHPcvIdyppH2wQcvfzormRzvvTMM1zYb/jhxy/RnK/4+aduYGa8VCf+g1Rcf/gxXmuF21ev80qeMfZM5Zmnb05xcf7FzSmTy8oThZ0r4veXG7G+LWfvK9WK0ej8Yo73msutB5WLx2frlpXbE4oD12+8xnQ6DcKd/jllkagAVBLVaEzSiLKYjEbsTiZDmM4DFy/zwMXL6++w8DwGXLvx2lAgdBEgz9m67u58m6vYd+li94MMSuO8x/db2F9jdZq/Asf14qZxO9t4DlP/1FLU3RLGP3+3+j98Pi2LoZpsNC+9zN5/+CJNhk6DO9094arUKUU+5iM7vIbwf/jNVzhwLVEPCffE5Qq+fRzRJJ3v0bXBwHzxPTPe3qMTnwOAEz3aRjvB+rHw1cMOfTd/6yLHKUqJdAOXsCycE/lhB7cqdOHMITSvB2ALzRjOlnhId0oJlfi9Q2IR0DBmjxNcGS0akObj0z+hGwMgg/m/lTi+oNf14KoHYEstEo/2DHeQAtD8mLV9UU6yivjCf/t35nXcP4vc94BKxBjXkaQvKTES6CxyZjJCVYqZTr2jIlFLqRItglRwXisySlItCXyJRiJrZoLRdTCSiqRhtVcUKlCzKO5KTasdY01ME4yLpQGRKJabI1fFC+mBdJmkkVzjHnlZrZS8GY96WW02EkQ9Ki+xroUZTkUin6Uo3rlYIcSFWiuQTCXGtNlnrzngqS//Grf+wy/xoe/+KI+/+91c32u49FhF7vY5X8243u7yie94N1/4+itcvOT87te+zmvXnkfqMdPdK7B7Hpne5GsNfOIHfpQHL15ECHAjHoXlxENJStJ78ILe3fvCTDovGjwRYSpGI4KLRQFhiqWEvj5GhABqedmdABy1KzPxKOib+2TKCHnLaBSrLeF8lGtVBMV4U/q7YC/EYEq4yCsKCYQItSTGKW7aGmiWEsYXhfcqj1VlUIrEC1AqYRAiuFkgOcJ7MxGhtahtJSkW2M6NGYAo4s6sbEoZL2AoniNYDKVQ7wcdu4rSiJVivBJhgwJNYSlUp7D3RJHfykt9L4/+UQqTnzt1jmtBFB+euUf8tDq1FKODUABbhMm2BVS6yJy6/QxK55tVNhnjluS0j7t2v9hwp9Xd+5i95mgVYPFCx5/pCx+ql17kkW98g3Te+aW9Gf/iK89wOxtdF7bp/Tbxxf2W//y/+TSjh97GhbGx+xu/zXuf/i0uvWvEow+M+NKvPcOv/vKXuXj5Ig8f7LHXjmhHY6Qu3pt1XbBxf13+4ZBOJIpIGsCQWxeKwzH9sFYJ8xL7kLu1DoJ1CtbyAc7LV59bauQ8hLB/bAFRLl5+mNFogojwwLnz7E4myzdae5Pli1WpZne8E+HVzH/qug73fPg0ChmTO4cLCJ9cgb9fcNDdlUFlLeM31ywP95es/LvhcnBkZ69T9I865mSL3PK5vvLFuvssqr2eOw5+4zf4xlPP8+9ecfbFMYvIk0dS5k9eGXMhGTdcubpnPDnr+H3vuYygmBuff3HK07dgr0k8OzPwqLU5kRHvfnCXtz324DxEbqkB3jvX18udTtqVzljtyv7nKCVnw0FOqEP9ZzcfcqbmFww9oPfurTZWkKHMymJDREDUSSqMkhRugeU2zcF+KFazDg7axTU/yrzEfh5e1t67FkkecGHsQYc/PKPQ5jC8navCKHyj8cNr5go43DwERw/OpnMXX5FVGpi7Kfc9oJpUdUmKjJC5gDxh7TMyLonaDJEKq4IZjVL0N9Upav2gVFKRS2jW2LSEmVVoZcHuJ5Gb01sFVGGskeOCVUhSdjwx80wnkVujGNMOXC2UXGJTdRzNEb4WxXsNS0LnRpWihpIvLMReVq+xAKSBDCBphHtJtsiXEUgo04Mb/NIv/nNyntF+9T/yHe97F+n8BZ69dovzFx8m1U6aZR67fIHbTz7JZ3+rQ6qa/WnH7NY1Dp5/GtfEvj6NS0W1f5t9rXnl8Q9x4fwFpCj4BzgoQyhDbSDaV2sKL5ZKhNV1JWxOXREL31VN4I5U6QJVsKMWxfw6AmCKxIveEMUusws7ojRuSCVUGGrhHO9yYQlUDea/YmXRokmE96z/LtrfOIzK8SOFrELQFUeOkxG04X1ulyBDjSwdXuFSuyEHBbkKQdggUb8rwjMdcoAT12DOE+vrYQm50P9ZDlAZztC+mFRUOQ8LtDB2pYHBODAzZ0eVrEGYMdIS9inF61eeeUcS+ykPC4MI1B5zsS39lDXyt7KApAByWhgytNCsVlKIRBSSLcRI37dyrAq9fFgvSzvAKXfyfqdes4scpwKfTEXe0J7eUvnCc3z/7/063/UXv5P/5y+9wn//j79GXiBGyJa5fXDA5/4f/5D3/eDH+c/+d/81D//6b/A9u87DowrZ6/jI2y/wJ37sO7CrHd3Xf5ub7vzznUd58UMfKuv1mpv3yOOUycWaalKKnIqmm/Hii19dLnrK/KOvG8/eELOinlpu1uif67f25W8XkdrCVcWX7NZh5ImzrLcgrV5dlq8deo4P8+OhKw/y4OXLCw8Sa8XLL7/AbHZQ1o1eRQuF57Wbt2jbuUYlC22919bfo5Wqt6Y4UT4kCgA6Ijl6chHhLsmmPt5gDDkWWG3u0QF3nKHTl98GWfjUX1AWjvVB13c3pi+8yIvXbvBSO2JnZEil1KJcHivf8bYJdaV8QBO/+eI+v/BKw//5j32Y3cLA/K+/epVffuoG/+PzxswAIqJofG6XP/knfz+T8ztxo+IlWWrd0Kw16Get+OFjF/tgse8XlpJ1vZQEHtwRRrUs0ZX3uVM9BXk2L3lQwk499/4MBo/APUEI4ULTwX4THiCzeY53P7eSGpOkPDBSks6rQw5rBb3hO4jWmhQG8fk9+/VkDuVieZHinXLOjSJ1wUv72gxdIcSq+uicY6H26WR1hm2mS7mXUCrkvgdUmcL0kbSUXBVGVTVQRjtCK0EckAkGOTw8OzuSgl5a4/9jAe0ENACAuRWilbDU5wxumVoWvR4RYpdcaBVGhAcseTC4jetoVc4B3ISEKzTEMeGZCUCRtAaBsQdjU2M2FPmtNK6ronSacRJtzoxUS12kYAVssnP71i2e/51fZbed8uEnHuPGrWu03nGbCdPbezzy0IM8MFZ2auWHf+AjfPY3nufCg4/zSLrMyH8fT+48wAvPfQtvG7zLXP/W13nbez7BIw89hvfhZkSoWNDHxzvYElaXpI54hB1SwGFCGKmW99oQBVdhhpO8eOTilyEEMosz0fBKCRIek6BMYCrBJug2j9fORPjfyMHohmSn5CVkziEnQZJgCXYp7HWpLHweeUyWQSSUjlEqz+URnkMOENYD5D4HyvDwjCKMC1V+U4CneJBDeA6AV5dFVVyGYrtOgLESoVcAFqUvoa9HU6WYV2pCXa5biQeQEkdL2KB5EFd4ieFOplgyGs3hPfSgpm8k6k2lApoyUEv0sUq8U2MR1JRGnSwxtmYRllmrYZJ6h9z9Kb7yx5HgcUVRPxJMrR5z3L1PJmfdtBYVCgdu14nnuhE7//46F78+5VNe8SuSuW5zpYls/N7//G/Je7fR/+2f4tnnXuJrv/ENtLvNh8/XfPflXcaV8zvP3CR3xscuneNiHvFin918qCtXTJlnfLicO3J3sGbs1l/DV/4ayB9KGxdUk4VPG2DskQrXXD0Ifc/pug7KOzedHbB3sL8AvpbvMDByCYxHI1IxF2tfxXxx/nkwe4out9ZXlM+h9StTd/0z3ku5DxaRYSIJeGEQpoDkhZwWXzll42uwrksOzWE/9POR555FFtexJWYCWfh5Yf5LGELzhfPYjQM+nIQ//PCEKiVqVUYGL952Rinz2G7mZttxq+l48cmXuHKhIonyiQvC+995nqs39rnZFnCBMdkV6lG1RMzSI53Dr/ZqR552ddzwjm+6nITh/b1XnHPn6v61Bu89wgE6OjOmrXPQOlWCRy5K1KMs1xCELkdIfTah7ZzbB/DS9dBDWxNutMtmIZVg9tOiL61uL4KjYjz8IOzsJq5fzxzMcqSIFPDZj6xAyeeasyKby9B+9zBOHwC3PJ5LZWFrXAGHAyW8rzVlre3K/qjDU3YV4mu5txSSlHu3jtz3gApRxlUiq6A5PEbizg7CHhSgFIq3SHgf1JWRCgcYaqEgArRJGaVQTE2ckSWmEhlQB96xYxFG2JghaphJ1P0hiup2pQZTgLnwvuQSgoFIKeob9O6VGpUGCHCg9kQCZlLslpoGanBTpcWpTWmryH1Rh0ackUUI1jhF3lWlzrnzl3nfOz5A99zXGZ2/wt71m2jjjGthXO9y/vxlfuQjl7h+ew+pL/Cux/f50vPP8fC5MZcuPMT3f/KP8vWvfYXKlOnePnu544Mf+xEeePCBqJNEmdKlPlKnYSGqCuhpPVEiysCVRLy04e13lHAF1hLWji4LVQkDVC8eHREqU2YaLmY1EC/9kOYLTh9qFpafUoCucmpX9nEmHqCmFUNSgO8mCxOCQXGHngTDmbqFdzPH+CfpwyyD1ME8R4ilOyNXph7Mfp37EG53LglIeCSDwjPAk2t59d1psQKmYglps4XXkaiZFeA007gyyjDyfk5GDqCbMysgVCVIJkapAMtSSDqVPLV50nqxWFl4rARKWJ/QOnQai7DnUutLouAxLuy40KYAqoXzZLCmtS5Uboz1LGr8W1T8OFB16ISFzyc9b81OfYQF9XRXXPXBLHwqup9aS/XIZb6eE0/92xfwa1M+ZJnflsx1eoU8NCdV5cb1Wzz5yjW+MM186fnXaJsDKut4rFJqnJud8AjCD7xyjWuPCZeHhIFVOaJ/1ibnz8W6Fsvd8BzrnvDQNYohpegTg6do2VtzfPuOxM2DcjOHrfFXKCzTvdfo80Bu34CXX3xq/QP2VygK14e/7dt54MLFDcAtjh2NJlAMf4vZVW6GyG1W/XHDiTLvKpGzzN/Ty1t9BREPim8Aweg9rD2/yyAry0exly1c59R35lDv3YVh2gxB/PCn1ffNQVLikU/+QXafe5pvfPaXOZhVmHSMq6hT2WYYizPJwisHzjQLs1lL3k1o7UgtvOd9F/m/vP9SGE4tdIObUvOlmzfZEyWPatLFC8P7u9xMX/huAQhtekeX/j2mU1hcSmTh/uE5euqGo7e7JXa73jPsxD5qFmH0KcGNaTGeDgDVcQ8DdICXYLSe5gBmec0zLMJcZ36cLzRWBW4dCAcZbu4LbRvkGYuwpU/hCJKM/oIliqaAKvcwqDY5iMjClizUCc7XUow2851G6Of4MvA9yTaaDZrOD02x/gJJlIfPZ2p1nrul93CF+k8AUEkhGzALAoNdjGYgBagYE0xwLgFm+gT+mXupSxSTpgawqOdUSQRyJVHGBZknqclVzO6RRbhVEDR4MLQZhXghLFJNZ1Hcl94qIezW4c3pLJIqWxfqVKgrq+K9sELZXtoqVQnDKiFYI61QLyEjAjMybo72DGwJnBZvb/HEd3wn4ytv59H3XqSd3mb3yiNcGLW0+9d55uWOZ1/tmFrHOx68zLNXp5x75B3kXFHbbb79u76f7BOyNVx75gt85T9+jrd/4IOcqyd07qQUlhIzIndJg30vacTTukiptwS4oDk8OqZKpUBJPHUP1rhZyaUKMg6jwYY8twqN3CQv/VYyMRuC8KGnm1OFVoTK53lHGWdGyaXyCJWs1JkRC8nYdKBlTwUFVhJhgObCvoWHrRbFKwdz3CzmT3FxCzCWFMCMUhyYsig5uBa68RJeCMJIIha6UqeLzLxQr8qiIx6Mg65CTmWuC3RYCQeM/KXOS/8TxZ6htyQFADOF2pQpXgowC3WZk4jTWo7jSphrlrg2BmNKTa/CeDgqSl+mgN4S2ugLiuhbUmTtxzu/2F2VDVbojUccfY11xw7JyUD95Dd58Wtf5r+/cYubLx3QWVMSlRMwJ1kYn9tlZzyhnR5wDeeRP/un+bUv/A77zz6HYlztwqOKCs+qUr3jId7+jncuWRGP6rGTQsi4xlyJXffMx5y89HGTFXXjeb3isi55Q2ItmMOp/pOXe9n8fFuw9q/gQl+8nujyO7eqsRdL7ZXLD7FKfQzB1vrKtRswm5WWzbX8QxbeOQ67h3LPb/C6yFwtD7KrIeRrUbFfedSF6mFrf1+SdRPTF76QxYM2t2/5L1/34+bLrDbx0HkyKORJE1U14t/vZfZuzbjdxlyrFHYURhJMs7e6KBVz+8DI7QxxYXdXuXxlwngcRm8pepbs7XPrX/0ir04bbj/6EE/8kU8ifWLPhvZu7pDTzrv1MHP+ikSu/Yt7Cyi6eCbTgHhCjxTv/T/Cawfzywc48wJs+hvEceHdmpNRDHc/hCgjR2q/C92mDzfE4eo+RLxW0TmAiCQqa5PLvHhw/2ALdH+y5KGMUkHKHFSNk5ayQPM10cv/ltbHtV1/mECnD9uer6HzpqkI41qYmjLLcdy9zOe+7wFVFiGbkiRj5kyripEJZCFVFoQTGEk1CsXlUHBFYUR4ejoNr4So0FjHWBRLwXSWiZC7HZQmOXUOb8OYSH7ucoT/4UISo8OoPJHdh7wekfCGdKWIVOrBkji5bLDBQhdBZImSK6NOItFIMVGgYOGVcXHIfSicYJbJyahMefGbX2Ss53jgsfdSX34nOzuKmjCup7xy9RaPpIbffQqaC++FCzt888ZVHnxgh1eu3+aJRy9zc39CJYnZwU0eulDzw5/8Yf7v/+xXuPbMC+y+/wkqwpPixcOWLEgdTMLjNNFglKNQpVcIKKQctRP6grKG0XoA0eTBYHcgQdohHuOhBjOCij24EmIhQgjvikQ18LFKCTkMJb/DAyRL5PyQPECRF9ILnLaDaRJq0WASLJbcFsCEBmOs0eZWYz6MBLokiEXbIrjYUTdcUkny1qEh6s6oJ8oQqEqoo2VizliMZSrLRRRsjufTMhfUA9SIG+MCrlW8hCka6imUsi4KF7vEvK1U6LMBa50b7HqrlTilvpjG8mpBumEKfa0pE8OyoOrkNt4bUQtvVWFtjPn3FleIhFIQ8JTA8MjDF3/c1D8nUt1XrnO6Nh555XVmPxfaV2/w/O98g+9DeEaELw6b//xIEeUTP/qHec+3vZ8vfPkrnBtV1Jcv81/9yU9x9Xe+yjO/+Rtkg73OuNG0TC7u8sEf/jg75y8xsIL11zrVE216rmM0Qjn857BFH33omh+F3d2LTCbn5lTHS2fNP5sb1197iWx9PMKqlB5Y+kkG5crLITI/knWBMPPLLYC20tZFGAfhwd4ZT+i6hlW41TMRmhm5a+dNPNQHdyZneNve1BJviBfAGwp0X1i1H5LVDBB3hpzjRca13vu7xNm4qk3O0duhlix/WtfLy1aEOV3/8i3cl4msV4MWD9H0l5/GN17Fb9wgNVMmr13nI+dGeD1GDDw7z02NF1qjA14zp5Egifp7LxzwgbHw7buJ3alw8B8bbnoCiR0Sh1mX+fzNhie7TLo9410lsuRwx5xATh1tAIcfeKlLYp3sx7uAj0klPLrb14qKo8yjbmUu4fPZoLHQ6ZKGYVehhPmGh26/EW40TjOsD4fb4mU8KaF/UTOsrLVSzCc+Bzy9YcYHw0sJeZ4nog04cHnVDin2V16Z5vn89sPgZ7mPmF933XGses57EDcH/32bmmxMOy8g896uKPc9oEqawJ2cnYkKZEM0vFbZFJMAQa2H10KSIGJIZzTqhSXNgubcHNOANW32QqQQ+vHMMtM2JozhTLSmGzCOM8JpuvBMNB7fq2QSKeJGzZCqCsuERk5RzqGwAlhWWom6Th1AsdyYR90nBFw6IIFDpT6EbmUL9pukcLu5wbe++Dkef9e3MavPowpdY0wm55m1+zRXn+Mb6Qpv/74fYIdEqmpmzRUObl3h9rPf4mvf+CYXzp3j1v5NXrh5wJfN+cLXJrRpl5defZ5zD57nwsXLUZsLI6uUcDLwDPvZQQswyPFydS5Rj8ED7GSLcD9zYWyACl0BG8lTJFwiWHYozIkWl2VacoLq8vLUGoDLgCoFXXukbgXJR4CZ8ETmwrgYYYWQUgCrXNhtag+AbmUhqYuVRjRFHauyCrXuJdxOSCpklVLPrFQdl569J4DSVCOksCJY+RDCk1gWokqigG7jiouhYtSm5H4e0DMFQitBhOEE4APlgMhn8xKimDwWTrPiIStWoaq3FEnEYJvFom0eYNKIXLN+kxeJ2lPqBJmGRK2qoLsMo4Dm0v9vcdb0022pbxR4PKsKerQCsPTRga7jsb0Z56qKP/Hog/xPr7zG//X6dayERpsIVzHSuQs88b73cf7CBd73Hd/Fq08+x7WDp/g//Rd/mLf/iY+z9zee4dzDl2naKa89/jjTpMxeusrvfOtFXr34IDcfetuRXXnyXl535NH9NJyxSdc8tpuFyeQBLj3wYGEXXG3HXJXNueXG9auwYBU+1Pky1+sORSUyNxCvqsrxceHzWi3mMNxDlPe/99uCkXTx8KJomRvXb93kG9/6vUGpvqcib9xbdddEjKHeBLF+jqrw+MvaOVWAK0GmNO0Wi6zGCXOa/eXzWJhJc1mjXA/HL/4+Py/IBiLcbB4sFftIa2FYW1Wge4PC6u0G9Tt3nP8Pv8nBK6/w0gymrfDH3nGedzwwJncwmzn/7uWGz7/WMVIl03EOYa/N/NotQ0z4zp0Irf+Vlw/4F68ZXqKGKIa/Nju6M+YDjz8W+YNrJ8/ilyvtP7PevX405r/I8A6VgA6UILN6+LwzqkJvEKKW1LSDWeu0OUIgyY4SeVijVHSi8m6YCbnrGaEPt6TvnyHvUyQMuB4RLBD5WsH5UbxWZYyt5EEN1DVe6lPafKZl88NzAejDhhcBzYDF1syRw7I6P+O7deUe1g1dl31l/O8dqLrvAdVMrRTlLaxw5ow8YRLekSQRJpWyQuWFqjKK62abh1Dt0UaoX9DukYlwOi3JdkFlrXSAkUOBLnWsmhJ22OeVaPHWuIX3aOpGJ8LIgz68c2OkKdhWLABJMNpFjkx2xy2TU8QaqxmQcDVaySRJzMwZUWg4NbwcN25f56nf+zy7t17isd3H+Opz+7wtN5x75CEqv0F7cI3rV19m9/0fY6eumM0MCqh44NIj3Ni7ydvPP8zbLo74H3/p37I/a7h69WUuXbrCzWsvsvfKN7nVvMaly2/ne77jo0HoYcXL4U4qb1GXy7S32CxEwg0ug3XEaYg+GiuolgLKhJcpJWHkAVKS9YVjI2QtWXhLkABJWFDISynAK+LBmKhGyuAF5LbZGFFASgV1koGqPfggDUkRrqgai2ImvDXSWYyJBJiuNUgZkhQac4/Qu44ISdRcaOU18uj62llarGHqxf1PnDcTG4o/W7jvYqNVJ2E0DmKRH5hLuCcuwdTjc4/oqCyGjUTYX+UBFmORjX6AYPwLBCzkIE6k8vA29SQaBkMEVQDNOFcodae6WMT68MPmHr3f97+cVI08vbq5esa6bWtp6yna3OzZ57EXn+d/88ffwfk2852frfkROc9Ngkm0AX6ThrZKTEYj1J137o64/Su/xe/84q/ypf/1Ezzxv/o4v/v8Tb7tekdKyqWPXUHPG+nXfo+PaObfN1P+1cWHqMbVQjuWN9C5fbR/AFmDNhYUuw3607rvfF0HHddZixnXAwCQ5RMWdvxBaVnVRdc1zZdrVQ233qgb+PxHP9RTJ8HQYYzUVFrK0Cn7syn7syl7zQwIptBhMNZcd11X/ScpC1YJZ6E4qvocg/SKcFmXYz+kkGvHj/O0m6XJRFxCitFOhr/nSu7h2eW+8NsiBi+gSsWotBgie1DvYezMNj9/qKNUDKPrpL98Nue5125z/VbHP7ueQIXverdQVbG3SQuvmfDlA3hH1fJfPRIkS5+/BToznm7gf7phjMR5sXWumhQjJfMOdOc73v0of/CHPopoWloxDq1pi61btaScdlk99C6vv4CszIVp63zjGghW+jg8TtmDdGIokiwg6oyTcF4TXQ7A01kQm93qvBhv+9dRVm7Yt6oEE5Z5ooQe8u4H4cGLSpX65nkZ7zx4qNzBO+Fgmnj5dniA3OD6zNnvFvpgxY4jK/2zdq1wGFcwqrTkZhbDrvbG5jKG3j8FC0aeCC+cZaftc6rmFJqLd1k7JndD7ntApZ3D2CJ0zgCc23RECF5GLGrw1BqfJ5pKQbMODzdSqfEDlrTwBAbKH1vk7owkcPuMoE3XAdF7CcoKCrmgzhYqjepHbQF5qY4QsWDAC8W6yhkSQ92iSlIUHdawQHQeIWUqQaKhyXHT4r3K4W0ojDlYKPxf/cpv8ruf/X9zSeHCyzfYmyo393Z55dkpH3r8Md45abnxzncxefcTHDTGdNZxvq7Yn04ZnTtHPd7l6msv8MDkQfZu73HtG/+RG6+8zO3xDgc3b3Ju5wKzgxu8NHqID73v25GdCZadPXFG/SKfnaoKwKEQin8JIVMJj5v1ibvCkAeECFNK/0hYx3Kh9IykSYIooiuF46Qo/oXJb0S4zlVAWkFF0QyNB4hOzkACMfKI8U1Ef0bKXRS5RcINX4lAjgruVupFdOpMkhRqcY3CtrkPUZTIqbN4+7vIamIkJaTDAVFUQczp6zy6E6F66sOClgjWyT4cwYFxKenVOaUWVezC4jrkSzUeHjGxmMMmgpQ6bBFOYkPYY18cWQqwFZGhnpaz4MUTpxVBLEg3ZoTlUISB8dDM5zHXb2U5sWa4XnnZfMF15x/1e//bSY5bf8byeWseaPWrhRCN7MaOws4DDdw64MJ+xzmH276gdKkwGo3QWEVLmInTNi14h9U137h2wMtfeZWnBfa++C3ef27EpRYeuzTh1fOJ2Tu6AVDNIdXCxizHDcWqknRKOfLiK323Jh5qb/8WOWdUlMnOBE2JueIqgzJqOZNSjaqQc4dZx7rR6nHR6uMc0lEGHXsBeC0jv5XLL8+jZYVzNeDPefW1V3j2hWfW3J2z9/UGGZp5HywfUOLgC9jtTLjdLHiRVgwC85zFlbf2iC5XcSZV2UeI/Sq8CHJIoe0BfZjJVkQgSWZ3bEySsCOwIwW4ALOsPLuvUZPQY6lvixejv/rK7YYLmzufuzll73bDno25oMLXbhnPNQ3mzqyBb+xlrs6ECwI7O0ojFa+1iQdmDS+1madvZh4YJS6May6ei4yHqwcZzHmsdka1c7nZx5/6Fvre9x9+P9eJbPxjg5xmUvbQ1gvoLTO7RKR05rx20P869/j2YaJ9vp1IjJaJ0Fns1W2Gpgtj6kFngydoESv2AHmpRRLzxQbw7BzMnNduGpqWzVZejKgDoMrOdObsN4V0wvsSNCXP25cm2txDL2tqUK20bFLBufGc1r3NzqiK3Ks0rxw8hEFmCxDZdY4kxWYWhFkL91+6xT3M577rgOozn/kM//Sf/lO+8pWvsLOzww/90A/xsz/7s3zwgx8cjplOp/yFv/AX+Ef/6B8xm8341Kc+xd/9u3+XRx99dDjm6aef5id+4if4hV/4Bc6fP8+P//iP85nPfIaqOl2Tz0lF7VJIBqJXRzmUbdwwNc6loPkGZeqZ5FFAVZTiOQIkLHV9OFWFB7FFDhDlEmFqdQIxpbGWpEKyjEuEXplHWFRnDUkUxcgprCeJvvYIxWsGFeGl6tyjrlFfvFc1WAARcmmjiFMnpfIAX7UGjTXupCTggrYHXMozdi49zGtXX0Gokb0J7e2bPNvc5unrz3Cr/hDfnUYFmBktcECmBnbOP8BLLz/D09/6Kt/9/if4VjPjy6/tM9s7YOQCB7e4+fUn+diP/TDnRhMaC4W6tqLoS3gKQ1mXEq5gQdYBdGJ4AsxQj542KAQh4Ro3jX5RzSW2vLAmalhpIArpZov+1BShbIiTczDWRbFfLxSixZNV4tjcnAN3sodlzizObyxyvUQiNI/sAY40nqPTAFlm0BZPVI2zt7/PtWnLuXrCpQu75FK3ybUv8OwkwgKDQRvFI2jxAJOlF8SVRNCUpz63D3ALQo2WmCfu4YlzC+KSTpxZAVKU/ky9oadUTa8s8r9Uejd65Fo1boPXj/IdBNByKIWMveCmIBFRi7w/9ajP1pgFu6IdkRT8Jl9DYlYtWBxPsjgfhalODMyOE1n+eMz1VlTqlb+OOnlZZZ+liv9f0zL+wh57e/v8+v6Ur7mwJ+FJn7nwyHvezY/8kf8lk8l46DJVwbCg9X31Fr/QGl+/vc/zJKY3oJYZY3PGL9zi3R+6wLfvjo6GjGt/PC2IOgqebJBBQViwAK85aDq9yXR6C1Hl7effz2i0u+Z+sfY8/vhF3OH6a89y/eaLm5vhxQuwcJ1+9BYVqOFYVkdvTauH45c79MaN68xm07lnjEjoPtjfI5I8TyZ3Ms3XGwBOJm/OdaTPoyqKKj4om33I+CEIVb6Wldd94T8L71j8vypGMJE5r+CyNSI+dhbGNCFyvxfbmUWYdkqbYY8S5o0WACVBzMTCHFtaYGTNl/H3rsB/8YF30V69wT97fsrPX5vxN393ryjiZZUVQajIGPX3fCfv+/D7eN/+lH/0T3+NX3j6Kjc64We+92F+6D2XyCRyhv/jL7/AN19u+Mm3J0bjzMz2mD31LfyJ94KmQy0Zbrdugp7FMOCbThRqhQujvi5klFuhGJmKzXe4SO99qUv+t8hiAd1SpxJh1glN5zSF2S+MokNQ3hyUeVwjST+GsdePEqV0ECVsV7m179za9/naIfPxXQRUZjawCrJwz2GFKfN7uTeO2hTnstfArITLBN5UxlmpJoXluPfQFz3kxsy53UQJIZVuTsix0KdLVdPvodx1QPVLv/RL/ORP/iTf//3fT9d1/OW//Jf5sR/7Mb785S9z7tw5AP78n//z/Mt/+S/5J//kn/DAAw/wUz/1U/zxP/7H+ZVf+RUAcs780T/6R3nb297Gr/7qr/LCCy/wp//0n6aua/7G3/gbp2qP1kpXVUGpmVtUSslEFSqUZMatJjNRwdSopGJaLOtjyySFhhTEFQiaIr2xw8GMzjOK0OWYrJUkshodwTrXeYCIKKLkQXVOVAR3M7rsJA1KdKqy1TkFADiqQZkdC2QorrUKWSt6zoPditjkEXY8lGgR2C2MehDI/qGH3s7bPva9PPy2K3z5yVeoRzXt7RlPPPYwH3vXZf7dbz7HhW97P10K4DfzjnHZvOtK6VJNIzX7+zM++P4nuPD4R7n4bd9DRvFmn9HsNV56+RU++LHvx6Qo11kG5sSg1w7yhBFCq0blQdEpGmQVBoiF8q6E91AJ97dovPxTi3pbSQLsqDmtSQnVDM/JyKKWlHlQzdcF9JpTwEPkCnUUrGyFxEEhdwEkPPdbHsHmWAoKB1CM+SAFWKccICgVGnaTSKLd2T1PmjjnksbyUrxhqWw2bdFLVILsoiYWucoJ0hHvN7FSL8oDZHUOYsZIlbaEjPahN+ETFfZLTHNdcrBUAmgKwkz70MIS0FgWbvXwlCIwcQ3vYQlDDI8iuCmeMpqFrtyzkWirSowDRA5XEhgBe/nkCtibbQ1ZkiM1/A3HnlrOsJuv06aPOVxW/j7UhJUv+7j8HWv4o5cTP/tbN/jGrYOwBkqsXb0X5SMPXODipUvDXQKAh/Xyld99kSdf/RV+40bLc4UVMInSijBV4crFC1x64p1IkoEopbfcIr1SutDQ0/TzoX5a+/QnuoywrOQuqzHFHOSCuiCSQHRBxVgZ496qq7p0tU03P/TrIV2lKF/lQD/UUGGgDFwzGdyd5196jtdeu7pgQ5gbEw7nhC08xuaWv67yZltHeqKp/kUaJ7i0E8o2wM2pc6vERi+9xaXbhQiBH69qbYOuGOHzY3UuToSdsbLXOPudD2B5cfbVKpwbhfG4NeudJXQG16ZCzpFnHuy0lHknC/OvvNtCT6S78rzzqTXMCYe6nfFIAhnXXKkaPvF4TTWqeXXPePLVrrAyGw8+UPP7P/ZtTC88xM1cc6HOfPA9D7E3m/LrL+0zmrZMX90HUapR4ocegotmPFMlzqM8+uCE3SsXeU2PKPXqA4Y7pRw3y+cvlRA57RdGTlvqikxqXaorNTd+zGs5jROMe6r04tnpPDwyrRmzxtmb9RTpcxiVCnjoCc+SOJqclEoqg4a+IWVSRTkZGBbblWeU0lERaRChlW4RxbO6Fs37UuZfrBoCVm7RH9JfJxcdDRjIW1TmNfOWblEAYS4LnR01LCsGhXshdx1Q/dzP/dzS3//gH/wDHnnkET7/+c/zIz/yI9y4cYO/9/f+Hv/wH/5D/tAf+kMA/P2///f58Ic/zK/92q/xiU98gs9+9rN8+ctf5t/8m3/Do48+ykc/+lH++l//6/zFv/gX+Wt/7a8xGo1O3J6RKqIJxDFJWA4wlD3TaSJpWNnFocmZjpJrkpVWhSoXRCxBl27ZQBQn4w5jtBSfVVrNVGKMSx2rLFbybYIOvXGn8kRXwgnVnboSKs9kqdCc0MIEGLWwIrxsJEIa/Fcwy5mkcU11oSsbt5Bp0cKYR6ltFDlEU++4+uw3efThb8cefpgPPfEQzcF1zl+4RHP9aTgn7L79CR585GE0KTUg9QhxYaeqGFcBVM5fuEJz+zkevjjhuReucmk84gBF6xG7D5zjZgvPvfgsly5dwTySWXMBB6FURa5RgzGWElKpQZrQFtAy1l4dEYxoS1NIFFrvySuCHsl1TkFeCzQi1AsKgA5WGwpbTYRcNICWQnqVOG0hEBEL9kAjGO28ANgDt+jzDmrxAJGFDbIS8IoYp7LoSfHAHUjHWMN5nRXI4eEJz5SCBY1JWLGivVbCKtSU7E7jUew3idBidMVjVPXgzhXToCmP/LNyDfFCXBIhESJBZ28etasgFqAk4Q2sXBANsg6X8CjUBAvigUJjxo4rqkGEmlkIPy2Lt1kQWKhLuWcJJ1gTVfJWWUMG8ZXPR27EJ7DG3TXt816rsAsNzWDXrtMdHPCwK9dduVU8lw7MHDrJVKkaoFTvTxmPaj7+vd/Db7z0DW5feh9/7M/9IL/89We48uLX+cF3naPeGTOdtfDMLd79zoe4fe05Xpo6+4+8vYTLnc1wfLScpe9k2ei5+P3CZ1lQdNpmusDQNv/vQG3uwWradbMTNmlhfi3oQb7w06uvXmVvb2+twijM25FSYlTVxRxc1gUzmqbZ2OEnmN33QE43Vm+2daTfv3ssKhL04FW/Rg7HCFUyJinyZzqLPcs89sq67E99SY5BCqLpLPKOtRAOHMyKXyz08miDwMWRceWCU6lyc2bDW95l2G+VPHgCFnveByVaJKI8mi5yv+fpS/EMYeRcGTWBbzx3jS/+x5f4gUmibVr+0h98kA88ssMXn5rx//n3N2kxvrHXkh+6yO/74Y9Q1TVUcP7ceX7kD3wXl27t8dVr+7RdpjmYoaOaBz/0Dv7Lj74v9vouc+v3nmZ2e8ar7rzaOlYXXaw8++nW8sUDT3qEFOKmWCRaF148iPdLAWmWG9H33TA3iH05iQ+MvYvrqbnQ5ByrizAYaiILoAAqKfn9qeQgaezpssC3bhY6ZtNCY2W1WnnMYCUMHUYGY0zMk0ULoy89fflXYKQFyC3PIrIHk3LuvZKAaBgaztelVmZ5hroKj9pgxymP4OZzFsLFRi8tiMvjcy93y3ueQ3Xjxg0Arly5AsDnP/952rblk5/85HDMhz70Id71rnfxuc99jk984hN87nOf4yMf+ciS2/1Tn/oUP/ETP8GXvvQlvud7vufQfWazGbPZbPj75s2bQBTqHddBMD1zpW0dzR07kuiQUr8gYwo7GWZApjCeWca0oilhgGQnC4ylRrVi6l2pFSSgQkWNF6rzWhRHilIcdYlMo3aQSLALUpRvQzGzUFEl6vm0Yux7sAsm75hJBnUqqSLx22DHIozOUqF8V6gIF3Cl4ZlwURo32tltrr3yMu94x4dhsouI8tDlB2n3rtLcuM6/+d2n2XnHD3FpNGHk8eJ1EtazAwcxZZYzFy9d5rmXL/Klp19iXE/Qi5dQmXAwu41NdvHXbnPt5edovu07sGIZkiTsKkCwyjREOFq/fVQ5XjaTeMmyCa4RQtaUjNy+IHNdEjQ7N7IoTjAYqhHew1SK5hLsjFLAbEfUbKol6OYrjaTaWgOcOQHWaotCz13Jl0oS7RUN1kUxZ5pgR4VawyynBmjkPXUuSNJIDDWoJUW9rRSMeFkilDQ2xzjPCa+QIjQSZBmRbpZLLYrwQDlRR8vKM2Urx2HUhaTDJYCdErWxCn4MNkcNADWWsEomhITRujAiAJ+7I6pUUNoZ1snkxgRhqnGvZMJUnXOmeM402tO7x7wv1YhAQLWvTfHWXEOAuRKxeMLdWJlPBKpWD5AjfjvZLU984OLlc+byL/wqn+QVPvAHrvDQryX+2edf5IYojcfcflJanneLXCr6Piu5f6q86+0P82++9Nt81zsf44//Z3+E27/7DD/y3K/zv3jbAXrxYTyNuP33P0t+8UXSg+f46rPP8C8uPQI7xyDyxbYe9YCH+vssqLYHQbIEqhaB0tJHz7z80pPDmct7fa/A9LTUh8d6UQ05buyG3915+eoL69uz+FFgVI24sHsepOcXjJDotpstvLfL7dpEy35PlJW7dNE3fB2Zo9hQsk14ZW9e9NUMdioYp8gZqapY47scxeZD+VWuL2Hu9Z1z4xpE7aDC4Ca+8D7GDQ9a4XYbRs7OwgBYtmn6+kfzPK4FWTAMVOKQ5nnA5gSbbJm3TV54v8rFZk3L8wcte5VzO8PV1zKXteHmvnGhFgzhfK0c1ImU5jPNesMo4dE2g9xlzOHWi9fYJQCeZ6NtOg4OZswOZnzzq5/l4OGH+PAPfe/CfJ73Rj/nj5bjfl98T2TQHUbFM9SHXwphxDULHSutvpMF7akokzo8W3XlVKlnCJ4bYswiimnWCHuN0OYFkFNAlhR9QzVA2aL/O0L3okSLWdSl6mtNDdB/EeWtdMMAoRYXk4WDhMD4owp2R5Fb3ve6E/Wy9t3xbqHNAqMk7IzCcKADqJI5UCx3zgbTNt6Rpb7fMH6+5hnuttxTQGVm/Lk/9+f44R/+Yb7zO78TgBdffJHRaMSlS5eWjn300Ud58cUXh2MWF7D+9/63dfKZz3yGn/mZnzn0fWclDMuNSkJprHSEYeEJcSflFIxuSanMMA+a55FUuCbUwtsj3tOUZsjORCKsS1CSOyMJ8oGM04hREzTXCaMuXhCTCNsLPCXhPcqRTOmEMi4kRDLumZkH018lieTQSIdWSp0FPLwxJnCgkWdTaSquYo1zJRa729de5L07ztvOO001RpPTji/Q3XqV73zvu/lX3/wG73j8XcVrEwp/LKhG1Se4ZufK+fNc3RnzzNNPc/mhRxlffBBp90idg2Uu7ta8eOsG2jXozg6TClJVwinNaQV2JaEutB70E22JPBm5kqqotaBI8cxAvNgRphnvRKIqtPV1WYA6DVCgJkytjJWF98oKK96OB7jVKsI2VR1xRQsZyERiE4v9RyPkUqINghTQEG74lCgeIpiKoRYARrUw23m4qGfWL2ShcNYJLPdEHJF3lz0KLndujD2AydQjT68W2EFL4WkpeV9OY06rQdoxcYLxsCy47iVpFcDDVd+WeMc6w1StuPyDzjlKCAijAqAyfZ0JSr6Z0BGFgmubhzNiEX441iDvUApzoYfntPc8updaY2eQN8MaclhWVuS1SvqaP0+yJ9+zxX61ws0RcthIOdQd2XnpJR673PDwzgUefewBLu28Rj7ItBKGqCTC7rkLvP8DH+CQLi5FzXJlfzqlaw740LPf4p3/3f+Xq7eucemxS4zOjdFXZjwzHjN6tsEbw+c75qFnWvznjFPshLJ5EBdttPP/Lv+6zorqC2ce7vR1DyNL5yzpMQ6bE0LKQQsusr41MihQvhD+5AvHxnnD3TYZRu5F39/Fd+HNsI748G8MgFG6uYRRKaFIXjmnjJKWUhyhMF47KMxlHUEEcWTnBAsxMIxXP2zarwMl9HDa9Z6Moqb2ijhlfi6Nty+RpolCVTk7aR7mbR51OfEAbK8ehAEQB9u/jb38Eh+dXucT773Ag0n5xWcPeHEvSKuevw1f7EAnO7znOx5k55ErcZP+AST+lVB9+NfPH0CTeNe5Ebd+9zlGT74QhlKHvabj//XkTdocnpwqKYdiy1ZWxOUnPa0sIQ0gwNADE40QzV51KaBz1hrjMZEjNZwyp61QcR675ExGpVZZiYaZv7sBwHMWbu9lnntVmIpSr9idossCqfRs1BCh/51plIwphtj5Uyx00uISu2gQWNNJsvSpZxGk6KA+hITO1y1hUlnkfDMHYOPCsCwFRPVER4tgzIGDznl16kO435KRZ+0A9mvsvUNU9xRQ/eRP/iS/8zu/wy//8i/fy9sA8NM//dN8+tOfHv6+efMm73znO2OKdplSJxWn5CR51ILOWUhmtEihr44CcVWK8q4doexWFhTZ6nGNFsdcqV3AM0JQsVux/ePCTFpEEuZQWyjUaiAlvS9JKMJ1KRSsKIjSRkVYRiRmGi5ToBQfhnFVhScnF4KGBDsp/f/Z+/fgS5LrvhP7nMyquvf36tf09PS8MQAGAEGABAiRBCiGSMlaylqJ9krUasMboZAshrWWKf6jsCPWDjliQ2H9YdmxCkeYod2wQ7Jlh7xyyCuJpB67XFKk+IBIkCAI4v2a90z39Ex3/5733qrMc/zHyapb9/7ur7vn0SBmpATm1/feqsrKyszKPN/z+B7PXyWg0a04E/OlsTLl5Ref4YkrDzKtDdk6B8GIacGtW6/wxHuf4ukPv496Z5eUMq0psYDIlI0QaghQNQ2hqaj2zjNJF3jogcvYxSuktqWaNCxOjnl46wGuP/t1DhbHXN7dLhYYB2ipWEZqM9qs/sJEIUdDciGBsMgUSgwVoMtktL0fb1Ali1OmiwXaAowXKJocBDgY84WJ6AK9BWPaW93Ehro1wgS3rrRWNEkGFpy5JpuMNqQSx5RcQ6RBhg2o6wkr1CnGneHMqd61j9vK3geYuwfOi+tjT/seEGaiHr8UHXiLKELERD3Bs0ATHbmouiCbKTkpcEuZu2p7e1Jw19TkqcqZanEd7PvVHDR1JbDVQ6gcEGVl2ETVPC9axtiSilrcCqgSPNbLjC4rtURUYMpSQOve5CL2nbCG9OVMmdEYBM9TZdNFd1Kk3ROoWmpBTwvRZ1Ww/tt6A5bXnQZTvo1lhOPHr/DsC8+Qfuc2X38hUYUKK5Q+mHiqg60tHn700ZW9a8XdSVu+9eo1Xtp/nc+98hLHt27xwMEBF1PHZFrx4o0FP3t0i8cevMLWe56mmU4GgWMMX87smjscXjlm4x/uAETusXjsQx/23evoy2fpn38MiO6hbukFhZ4ZrG/4WrYqGz3FGACtPIKzqC7rKJrinDmeHbPaD4ZqXk6x5VOuNm6l/vtZ3poQ9J2wjkhRUvmYjubGaM6edEI6MIIsY07VoMsOFPLYN2wl5sVWhm8F5Mvy7RksAeDvKy7ELpek4ayVFUGWh4ZiuAXK81GFpctfkfoX5RE8zFY4ev5Fbn/6M7zv0Utc3qkxYLep+edfP6GOc05S5itHmSfPn+dH/ujHiLEa2urtLfHck4ZJFfi3+4mnp8rDVeC1hfE/3PR9JojQpo5P34rsBLgYjQ/unUdCDxPvPmHvvgyffYYM/7obf1Nc/ilbhBa3/NuzJXPvsteXdRzOXUEVxMGUDAPnpd+ruxRo02r8UG8N6+87Hr9FFqdiL+OlhZ79jlY6MWKlSzIec+uWqQzfN/VqD5L6VXFcYoBpHVdiAgWKAt/vOYabY3dEv3+xiJ5a0PtxHn9j9PcdCKj+2l/7a/z8z/88/+bf/Bsee+yx4ferV6/Sti23b99e0Qxdv36dq1evDuf81m/91kp9169fH45tKpPJhMlkcup3JywvA6NGbcJcMmaKpYyZLwiu+ahQ9eR7C/EcDJMQndIbpUv9hKo8RsqUzpRKhGSJFANqShWCLzIBKpIDI3NrQ5c95oYSDxNMkdgvRErACQemMVJJYEpw5jvcjSoTqKrIBAi1gzwFpsigzFFzxryFKdsWOTq6xY1nvsDi4mMcv3aC3PwSD11+kGwz6mD8s3/927w8u8BH3usU5QHPYZUkeMBj9JuYZaLUTJstZPdBrjywy3O3X+TazSMOTk7Q3HHl/CW2L7+H28fHXLr8AI2IE4JQgKRRCMOlf2gagWyBlDxyquspv4NAFCxbsWiVJL7RTdsSHZA2SCGEcCtOCp7TqwEsChL9mBbfc8/p5Wb1BUpIbrnsANGSecp8YVYFkz7nhnrSO+tpREuchBqt0+bhOaJsiOLN0WnKYwG3EvBs8PiYOhMf1BboRKmjjyUYMdgARHcMZhhNDJ7Q2DzJcIj+/LPSPiHSqKHBmI+XaiuskGIFcLv5P+KEHrEQqCzUrbC1GanznF6pzHETQbNTzvfEJ03057Ki3haix5AFY262TJz8JiJ/v1PWkL54b561GFsvObzx8mYF0je9L5yF8u58kxgC7Sc+wj//4u9z8uwxL2Z3Vc1lDWoRZn0vGZym3HaG0u//gR/k87/9Zex97+WadPzcQskzQ2ZHpWWBB85d5r1/+s9RnztXNNK94Lmh7Wfhx7s95ilgtV7e4MCMZKxeIHjTg7R26/Pnr3Ju7+KgbV6NWOgv2fDrIGAbXdty7fqzmKWVU3JO5ELVvgmyrkG3ey93xKibBuL+lO+YdaR4fYh5cr9ByBxAQ3Fj0tE4Wm/JWsYoIboco/E836AzMaDP5yNLbEVPdLA0/MhgTeiP+ZJWru0F6ZHPmIl7l2gBetondi3tzGUfcLd1J3tadAyxheBu76/PlN3oEdNoLjkgl+YYZ6ODWeteQE/9wHfzvmtzXj56jZSN2TyxPw98+nXjWD22fQ4kao5UuJGEh5my5LA9S3V0qvuWQ3d6MDd+W5nJAiKeH7IfYyfo8mO5Z+ZbH7BS2uE1XSo5ltNCVubE0sI0GuSVNtna3x5u6eCNAox0gjaQXPWVDK775l44/ns/yWxF89IDqZ3aLU6bDNv9vBuLBj4HR8yXFFfPsvb3TJhqzuq8qsMcAa9T97pn/4y3VN52QGVm/PRP/zT/5J/8E375l3+Zp556auX4Jz7xCeq65hd/8Rf5iZ/4CQC++tWv8vzzz/OpT30KgE996lP8rb/1t3j11Ve5cuUKAL/wC7/AuXPn+PCHP/yG2pMt0VkiWKASIYsLAZ3AVGpyVlTdWhKiOSBSjyMxMTpxZ6ZY8kv5VOpo1eNsQok36cyHrKliodougrfCXBJShHRByRZKziWnl+6CC/GN1DShguKD7Il7zdlgglCFwJYWt6oy6SLiMTpYYWkLtJrpJ1ebE5//vV/j4PlvofOOqCeEuuHVG6+wReahh67y+1/9Jh/6of8EJTGpave3DYEGoxMnipil5PExJsTJFrcPXueFa6/xpa9/kX22ODmaMTHlm9/4OpcefJAbX/5NunTC+977QfpAHhGI6tTnnbkrZp/m213zgCju9oa71WUocUruHhnFR0BUiluD7zjBPF5IMU80a+LgCgc+USh0+MrC/AVLaHFVcMujqtGVIEdf/CCa0ae2rK24JxYrTY2Aev8rQhsyVRYIwcka8MWgYrTWBJhEz8PVYUQtcUxQzNvOXpiDj+nE+nZn6iKoptqtW5PSszFDEwQItElpopT5JEyCePxe2SwxB40x4PGD6m6HGkEy1BocdOGLfaNO1S54gr0YlhtxtEByKkQwZ6I03H2jZHEjlw06y70vZ99pa8i9NZqRKvUPurxJAZizLxOE+uSAiwe3+ZcoXyDReqKz5XYvEOopj56/sLoZjyoXYGd3h3zS8sfe8zT/+PYB7J6jnSdizk6+QmAXuHLrGo0dcVJv0+6cXxPEz+roux1fO3U47V777CyUJiMB1Nf5U/XJ8Od0c9fPW8MbdV077XoY17DBAXBduBaKQFtcfHuwK8s6+oVhCaA2lbugzzfQ7aevOy0Evh3lO3cdcYKpJvp6KmXehH4MStyrW3pc+TXrfA0fl3GX3WnmGsVbIgTX/g+gv3encnesSSWD1WNdO1BFGbJVyehvPwM90e8qQCg6lcHd9agSOhFenGdu5Ywo7Le+i58XG2K4Lu1OCSEMzJR97slcgN5kZ8pH33+VG4dzrh8f8gVV2pw5VuFm9r7tLTQ/8mDD917Z4vxj5/09OGOa3W32rYKrMyDZ+J1i6bnSg6l+n+zbN43Ls2S4YnSujPpaVm8TxfNvenyde1tpsTpl8/gk7/9+nJb06OOlwozVHJGj9dDoKdp9SjY9S6kwpBXSgSj0NGgKIuxMxFmGdQxzTj9P/0mKVcqkxP4ZHC6cSl1NB8ITY8luuDoKq2+C09ILF7dh1sJJN1or70N52wHVT/3UT/EP/+E/5J/9s3/G3t7e4Gd8/vx5tra2OH/+PD/5kz/JX//rf51Lly5x7tw5fvqnf5pPfepTfPKTnwTgx37sx/jwhz/MX/gLf4G//bf/NteuXeNv/I2/wU/91E/dUYO8uQiVBWeQw/P0ZFH2QuPItxJicPcpKXEsCzM0K1UV3fUKQSvBkg92h5M/TKgIGC1KXeKXEs7GlrFisKickptMxq0rTm1agUamwQFXz7IUJBIlYsFo6uiLQCFIoFhGjpOzA5l4exWftBGKMAyGYglmmjl67Tqf+MATxC3h+Vef54HLFzi4dcSchhePb9LlbS5dvYIkCE2ZsCaYZYJBRSBrxsRYaKaSmtnshOdv3+TGc9/k9mKBHs8AY//mDWZbe8wMXvr9L/DwX/nP2d3ZdnCKW1UsOW16jkbSPMTbTAq1uJiTfwBO+ICTdGQp5AnAlsBcl8ApmufUaDVRBc/Z1BZrS+qJFwpwNlN34xuWxl7g95xYqWiAIyVBLh5n1WGFAtlpzaW0JUkhe8gR02LRCe7OWFFiv8yopc8k5YvAhOBWzBDoYnHPK0BExQpQC567LBshGFOig79+IwPP9YUgKoTa3RRrgaqYLBvz+dGW5LvqzXGyjuCAMUoYmBhj78KBMZNMhV/T55uvKAHBGFVxV/RcaR5nFcQoqdcIvqMO1tN7Kd95a4iXN7wMrwnF91TBRslog5R86vj6hau/3VnevZM4JoO2+uR3f4fps8/xU1sNv35uh79382BlO1ODJ554kh//c3/Wmbk2tLwvqokrF3f5z3/iT/HPP/E9/H9/+dP8seuv8T/74CNESey+9DxPTeaEMOeXv3DEb37kk6dBw53KqgS0+vumruo/bHLbvJcyyJ55BTjdqal2txPG55or+yQvRblTLZWxqFAUHwVMUQRbk96HdziLO47/qf7a0OB1eUbOOij3/hK9Derk77h1RHop2d39m+CkBUGEpopMC/GA4Ux9hwtoKqMOJf463+097ssSoPodff093ygP7/rhkw4Qj+8RIKlyfkt47QQO5uP3zL1JKulTYgyiyDCBzZyae91yauOZavDEhYonnoR/8K1DfmffrXRKAKl4tpjHOiIfeM8VqirgbO8yCPG9gF83NX/0+99HPjnmH/36TX7nUHiwMmJoXBlrDAL3o1Phhy4F8l7Di+OhOPXhjZTlJO+f985KiNVferKIpUfD2jo9Bjz9r+XAEHoQ4MKeJ0Get47A+9j3Npsz9tlyOTOKcjeUXKkDxOpnyOoLZyqkbBy00JamVhKIpQFmuLxguFxa7jLmImwzaDa64Glv/KH6pxrtDEu0ORi6glLi0WGRjVkaW6o8dGGle3t0uN7zpb1bjVtMZ2mzteztKm87oPq7f/fvAvCjP/qjK7///b//9/lLf+kvAfB3/s7fIYTAT/zET6wk0+tLjJGf//mf56/+1b/Kpz71KXZ2dviLf/Ev8jf/5t98w+2pqoZpbIgoWTN1VZFiTSXR6Z4t+0BEJzGoKiFqooqRIMICpVKcLjhCoGIKQMYiiEWm6gnoOrSQUqhTRheLVoCisTXq2FBH59PfCpFaAhNqYnThWs3zQ2Rx9rbKnDo7qk/CXKgtW80+MTRgElAyvctZI67R6SRQBzh/4TKzeUVub5FTy40XX2d7b4eLjzzKaycLLj9+lWp7i5P5nF0qt9CYaz+mTYWQ/b5Fc0bdUMea3a1tfuBjn+BXfuXXuPb8cygdaZG5VR9hJjz12CegruhQavVFOasWrZz/11vXgnjgsJoz9xGEhXksUdUL/2osxOOBuuR5oBRAC0MgxjYV2RRQd0cqhAiLaCxwsABCxEruBeEEz+8h5u5pubgYpOCxb2LqY1aYkiYizPA4M89rptQa3JqHk1hYcKrzztzNoBEH8kGgC+K+0QYajZlCXeK0Ai7vhOwauSjuNoeUNosVunIpubl88ZyI0SJgQlQjBU/Yq+b+2570t1irCnFENNc6GdCZOoAsa3eKbvmKuvRpbsuzM5rPCRfUQig+2cHnJOKsirlYt2xdvXqH8p22hvgDc1fcsVLWzz171z37mlMH7lTBpmN3a/TZNY23+BK/zjQknvj4OT4hkZ3PvM7Xbifa8t61GF/OLSFW1AVMnVV3CBFF+S//3/+Mv/e//19x/uGW5vwFPjLt+MTTF4mTxP6LX4Vf/Aphq0KmDzI46ozAyspjD110l06+W3fci9r/1C2k/P9sTem9lI2jVQSF27eucbD/+uh5/X0+9bjCIID2ta2IfpZHp95DG1cEvrcoiciGL2+oyjfWp9+J64gLprBTwVZdkqsGuLBjPLjns1zVOJjD4Ws2MLmOH30ptMJ6nwxjOrJE9LmNThK8elIAVMmHVHXLKw87SFmGtaq/j+9LxXpS9CsrDgdS4m7X3sX+qxSFTMDYqY3zlfDUAxPO7VbcvN1x+yiRCdzWwHsfOcflC7tO752LNWj0HCqCBSXXgcfPb/O9l7b4yu0Ff+3pB5lUNTMJZIGD1PF///oBL+3P+c1vdHz3gwvCAwUE9H6OZ2pd7jKGa2efPYVt7aTSeT0oLTFsPV4aoMaASJcd6sdt+Fmysdj3MdqtZAjhVfPclovcWxuXiEpxRXCnDuhWV6vVda+Pkep9ndQc2KzDoXUFlPTrjrmMcXuxAeTgD7n8fnpzFISdGqqg1AJ7TVj2gEkxjnicXjeAtaHqlWLAy/u6Rv9/f8p9cfm7W5lOp/zMz/wMP/MzP3PmOU8++ST/4l/8i7fcnqYKaCzkDXVAxIPyEaMxpQEW5oH7RNiKFaJOy2JAyq0TIODWjlhXBDNirkiS0ejWER+sgBLJDqnYGjkeaxT2YijkAU6GEIPnQlqYgSViHcGMUHyoM0Y0o0oOOsxcCN8OgZMozFGq4BOzxhcSE49HimJMqkDKiePDfS4++XGaas7DH9klzfbZrpTtcw9w7dO/yJWnPu45lrJSWSSbYtEIASaN0JnHbG0lsAp2JjXbzS5ZjQ+//0nOX3mcz3zmdxGrOT64ydNPPMDvPX+LT/7Yf8SF7Ypc/F2DGJUGoqi/oAYTcSuPJpDgoKESz8DtsWlLcooYiolb3OXPNVxO/KDZY4la8cEIRXZQUVTc6tWIOP25liS3goPoXqNV9pJJr78xZ060sqJE3Bp1gsdk9RrhgDCzTCVCVdz5Kg10UTERJip0UalxC11Uf8aMb5hNYR9cFBeAWOK3xKzQ/WuxwPmaURWKaiWQsh/rzEkxorklqg/YdGKMUdLhIqBJIaZYxjjrkN+kErf6tRGkWG+RQm2PW6V6hybfZN2Cp0FpVYgISaBRhli0+AZWsu+0NUS4F7nvLQqbpx75DkLs3cDbqZPvJQz7TlUI2s55gMR7Tyqa1w+4GAMPxchRYducyzJXyia3mqEV4vmofugHfogvv/wSwZSjkzk3r7/KP/jMb/Kr//Qmf9YWvHb9Nudue8DF4nsuOEPUSOu+8Qan7jcuo/6UM37feN29lbc4+istOVWh+D6Etisq7FUxZOletLHW4THvNhfG/fFmtAKr7QZ5S1LMmx0P+E5cR9wqEMScEjtS9jDh9gwO5p5jMGXP7TRri1BclH+be3593m5SCHg9MxXmyZWtFT0Nd2lXARmV2MA851fKMs7K1qeljW/hVogNXR5TYme2Tzs7osvwxx4IfORHn+LRD1/gi791nf/uX73EIcK/PFL+0x/9Lj7w2IODUmAAVCWWy8TZmINUbF/Y4YNX9rh5nPnZl27yk++7zNVpYPvBKZNz5/nB77tMp0K6ecJBPuRgntBpLDHpb7SsC/zj/l5/6FWowIZvfZ/a6Nf1f1c/Lck0eovfceey5E4Nfb7H/pXLKh7XNl4vbEk+MehJZHQnW86msWWrv3bWyoBW+nncA6gwPPOyUsNlUUYtH9rY+x2PunUNj5fQC2Grhu0Su6492CsuptlKDtGxemFtibf+doVB+c06IdxLue95qP6gS+4yVjlpwMQqF2LJhKKoywpddre5ioBVkCXQSHRhmxoJHlczqSumdUVWxWIGc8KK1gQLMNGAqdK6lE0WYVI3TGKFCGjOQ56HGD03looVBhfQrNQiDgLMrQOLAIpSx8iiS8XdC1JWd5WLQFC6ooEQ3Bd7bkKN0rYnLG7fYvJUYu/CQ9STKXb5EV5/7os0aswPZ1x9/HGauqYNDaFQfNYxQFKmldC1mWlVoaYsklJJZOfcNoev3Ob560fEapfHPvQDUNdomjGpJ1zdvsYsHRNCJKsxjZAQUlSa5HE6sWwWAlhwcoqgnvcp4Iu+idt9E06gICoobi4r3GJk6+nsCxNdKFSj2GCiFgKxEIlMY2BuSr8E1cE3shonYcA8xqsNYE7PN+SLiAhdNlTc/7yy4qZXXOkyblI3NabBjxGNiUQinvRWhYF4Y2IRQz0XVhlbxYrVTZzREJ9TlTl5xAIQdfr+ykpOqbI6VxTXOzeLDhqqSoWu+MrnvDTNZ/Ng02mhPq8r90HvgMr8eVP0+msM6d0fzYHolPLcZWGtxBdygD4VQDYtcX3vzHJXvLKyK7G+976le95TVes70Rsup4WCZZX+qVXl+ddOOImZ6uIWH6qVB68fcniShnNcCJISq6ObQY654qSpI5PgufLImZMXX+ZbX/4GL+iCr2likpTzwOULF/ng409wSk0/auTbAWa+I4stZ4GMvxaBagymejIc6amhGY+qnZbehjMY/XifJI03M0Ab5/Q7e6R74bMPrO8BArgckss412IQYRF9/4rCoPjqk7Qfpd5mOxLSh79rq4dRGCL9+3admFY2sAL3BABQGN+SjHG7WwQ2TI1xbkF3SbUhV9TyAMSbN0m/+evcOFY+c3OL79paMN0K1JOKK49tc24aSAk8l0hFiMFd1OljeZeWnFTYcYOU5MY4kdaXD+a0ZmyZ0exEJucrJuLugifzAC9d431f2ec5Jhx+10cJO1urffS2lNW6bOiXpYVv/Eb7iIyAwBnVOdgp8s0mhYiUsRAPSZhEuDgt8Ww2HqO+vuIiOFoX+rnVp12xEhulahwnSrxSv8Z73PXlSZGLpFjKRVbmxPKhbNVqZCwR5fAMqxBIpJ+bTnZC8f7pXWG7oqzNGybmxhEdtf8d5fL3nVZyTuScCUHoaIlS2EGCuWBs7tI0VciSUK1cmBQ/ZxIiKZd4FhFyKolYRZgS6FCausRdiSeV3QkVc3G2vyCulcoCKShNFhLBrSiFjCLSywslP1V2LVISWJgywV/MWHkCXwEqi0SBzjIxFStKCVyRgFN1inBr/3UemLY8vDtnRubk5IDz5/a4sF3z8UenPHNxl92tLapoTKK4O14AmTgFdhJB2wxVxXFKbiVrApPtXY5C4GDW8sCVPZ66+hA3X79GaneZt3NkdsjBjX3aJ52tzkUzt760RUPUkzmIGCEvaTyrsljm0QsZRYqhxEp8l3r/9y5seKxSVBB1s34QT7AbcdczcqEqF8XUk9V6fJPTm3r7cIZHxF3mkBKl60nmtOTIwpRWhCCegX1aNESteSyUVWDi41sPlkhX8NTiJBgd5RwpFPLFR12zJ6Q2PEYuiNBooYAPgqj3R7/hxJ6SHzARquC6wwpnSOxdB50e15jUgaRO0x/FQZBRYqPECOV5XbmU6VkPrYC3ykpdVnJzFXBaS2CBeeJgY4ihqgjM4n1cxb5dZZMyslfIjYTf5W8bzt1U58a65YzPb7B9K9evC853rncsv4cgvLZ/zMlUudk0vHqUuN4mFnhKilROlEKO0kvv63fucZGIsP/6Pv/Pf/Mb/MLP/QL26d8inRzTmfFsCdCvxPjk934/3dMfxEPzl3XdqeVvDBaswJLTQ3CPlb2NWPoO9+wlovW7rEkrvbB+t/uMBOZ7uPkfTHnLyoLvpOK+SVpIA2or7LkCiFEXeSEIUNytz0+UvamixXIVRFgkmO/3HgveQStk4GdIjH3MTJedjbgXLoO/kLjVgTXyidLy8tKtvHu9PF7iltrsysYeIlg5tnU0Z5ISR/PI1w4jH91bMH/xVW4cH3F0u6M1dcuJCBqdmqNT76OEcJTci2gn+AZal/ZW04YwqdmdBq7PnWzMktEdJWKYEwqI7OYdi5MWW8x47VYHT32ArQFQ3W01ObucfmuWdRVHGeZZiixCSXbexzqNrh+tM2Pb4AB6SoXjhAcyfLLR6UWWKjHVvYV20KVYAacj0NsDZ8clyxi+IqJ6FIms0jgI7m3URKgLGWOIfY7MsTZnNX2DjP4u16cleB95qQ7PbaoerlD6xsxT7rR5bUmw0fdNw3k/UdSovPsBlZYkd6nPEOWzZKbOklZLdGEcSBqoyFQBQhZabQlUOCMcIEqLB/ZHjCNLRClJdnEBNwZ324sxUgMpJ/c9De4mlUzImjANmGQqCXSW/aULTobRhIoWF7Ij7gK4kEQjQjChDepMcGZoMW9th0AnwpYIObqfsYhwfOtVqt1H6Krz1NM9mqjoyetEiWxvCRcfeZxFPaHrMjMykjqnLDUjdwFpfPEimFNvmzCJE3R7yjfnB5zbukyeH3C7U04ODplevgo17Gw1aHeE56gp7IosSR0yIKZMxRfQVpYvfjDXtgi9W5y7Os7xTSaG4iaYMyHK8MK3ypBg162IUuLJjC67VYyikQuFyjOog52uREOGsvipFarzArgqyvIW3I/bY6KkEEk4eHYg51r3BRAs0pQ33YEKIE6m4ZYzdaKSJORCCBEwojlwbnHLV68+ShgWXTsziX6foAKxJ75w6uoKBo2W1P67Wg8Yy6Yp4hT0JXZMkcLo6KAtWGF1CoUaW0DIBI2YOlNhLPFcakJVO629e7E4yYgEcbdLC9ThTflZfOeV3ll9pZxSv73127zlGt5aOSW/tolM4m9fu82Xnp1xu0vMSx438C6ZXrrE0x/6ABYiakZkHK/Ta1r7uoX2eM579s7z0R/8frRVrv/+55F6ylY9ZZoSUVsuXbiI5eyCSFjVpjOu704dtn7N+kO+0c5+e4b4HsrZNzmF9TYJvPdSRpV4Ny2vNjt1lzuX+9AnNvz5g34j3nrpIY8CB13gJI2FT9/zxq5WZkJKwtHClY2p+DtpYQ8eRFNxgovBAlbmu3s8LAX4vniyW+euRYrWHitkWTCpCtNaaZoUBr5exF8CqiWY8/b5HmzlmDPPASctTavMu0CigxC49vIhzc05xwlONIMKYhGpot+hrCuqeJymwbQueUANJMDlRy/z/v0D7OCA5w+PSJ1xlDt+87O36USQwvxrphwcLFh0mZfUeBpla+VNOUsDxj2uEatkHH3XdAqHLRy1TrDQFIsgMBBnWA9kerghxoUp1EG5PReXF613+Vwijh6c9PntxiUGlr/bcn3OCkcdHKf+/qvPbGUB6cevv1Pfxv7GhrNaX58XY0QUdhtnRN681PbjWSywoQeXfc+PH6rsDv4CkMxIakOurJTZaC09i71xc7l/a8m7HlAFM0IuEUlFsKwCxGAk3DUqIoQQ2DYhkUgorQWQ6Cx6wdnLDI/jqYsr1SRAzxAn2msEXKsQkGLh8ajSibqAmshUGFkTM4HtUDmJai4vR1AHclKhOZFESGpIdPKEWgJNqBBxt7da3JXNCTECCzOi+OzLBF577Tq7l54ibT3AZFpjKdFppJqc4x/9q9+gnT7OldqfKzdLGuwm+zMeq9KmzEWmVMFjwCa10FU1ppF6skVDQmNg74GLnBzfpkkLnjivfP6bLzkgjBWW3XqmGFWGED2vTTJnCKpx9kS3xFCS+coQO6Xqi08I4laPEKhqwURRyhgmoYpO3NBY8Hvg1q5JKKCtvPEiSlsIKiwUP98gIIHKSmxRVcAQ4taWorVRc6uPx0SpJ8Uty5MGYU520g0JBPMkeiH7YuhkI0Dyz42YJ1k2+nhVp5QvFqRQFiKC+pwq5yRzwhITtwi1RYtTlc2tFojB3SEqYMFysetKPxoO2iSAZRuCj4HiZiIsyMQQMDUacRE5hFDom4V5YTRcqCfAbtT7O5oQkr9ji+LC+u4p9yBovpnnHe/v91L3Rk3cna4fHxwJzmsfVi93i+X+p3+D//WT5/jvp5lf/NohbSHc8cxxbiF+4pFH+MjHvpdUbMLjimzt31jVfOgDH+Dv/V//ER/71Mf4ub/zX/BffO6L/MazL1Fn5cdefY0fevHrNPMD4rd+m8mFLX6v2+aVR54aCXRrfbL+7Pe6b47AyFspb/s2vTYf5IzBPQsv3rWsDfyqPpmloH8vbbzLz2+4b09dcD/TcX77ij9D8FgpWXOFKicYSwAz64RZGsc2GWI2JEM13HNhd+pCaj9eijipgBlt7mm0ZWB+W7ntCFSBgxgp6z+uSx3FW/WCP8t56ZpA1l3I+oNf3l/w5WfmvKYNN3LkH71o1C+1RFrfh8Rjz8/vbTGpawbo2QNEep2iDfHYC/E8mVbXqHgczbXjjpThl184YWFgOBWyBKhE6axjP8JTo+deH5k3X0ZvZ6lKDdrOWy8iVI1RxT7hsVvhYygeLMWVTwSuXorsbAnyqrLoimtjif/x8elTH7gs24c79DF6IgyhDj0ztOHzYxLc+6UHae6SX3p5WKRl5ZlEGCjsB5BNqUMZlPsUsovxetVX1V/Xk/2OYdypUkCgmnHUWaE7l5Fb6abe3/zbt3vNeNcDqtYytWRMXYj25LjGVGIhX3QrT4cRxYgSXAgX99OlCqgGYnS2uTpEOvOssqZOXh1CRFWpxM+hCPFSBbZiQy5CbQIHNP0iYYIVfj6CWyX6RCOGIjGyhZFFsWzUIdLUFVLc05rKGdp6BC/B25OylEk+4/D161x670OcnNxCui3i9g5tyjQ7U16+9hof+dQPIdE1Xk3VoG1HrJwVqK4E7YyqqllopptnJpOGGMHE2NvbYXt3h6PFnJ2dmq29c1R756DrmOg5dm9/ja5rmdQRC5DNaclFnEyhV1y09MlwnVTCDCwXTUuJw1GEqQGihCoQgmviMs6+p7ln4gPElxYtZnJfkHyRyWo0wa1elYBFZ8MDSnJaoxW/t0UQLcmEB76bQhVu0BYu0Kq4uPXJbX0sywaGA64Wo8pCUqUOvqyIBRJarKaFEc8CdVC6HKjC0sjfiTP0NOLArzIZWCW1CLWxUJW3HmXmjIHquT18s3U2vn75UZw8IwTX/psJEqFTZ1AUjFzo06eUvF9igx93IpRn8Wejp2jGaEsMWLLM1OJGX+d3TllqazeWDcLfytl3Wtk3gaN7BVZnlbuCqjdQTNiazfjRw30e2RX+zM55PhsPuJEzSXwtnWF8UWdo7sn8VwXzpROQ336RPCfOQ1cf4qVrryEpszOdcFJXzJoJT86P+c/iDR767in2uddJOiOeS7z+ivDKncDk/Zhi97Ar3z995xl3k0HmKGtd34azZukYPNvKnJO1S95QwPZ9fPB38mpxdlmuvSvjMDo+Bi39WxOAS9twdc8pzHurk//na38fkhJDIVwqseFNJVw/9vAGOeXa6YPfpw8JYuxtC+e3I4cz4ZX9QrsfZK2NZdKsKyHGzHFlj4jisdFWB66dwK0k3Ey1t116S4rysfdd5n/74z/I7u7W6nwsf3rnNzXjMAEZzCpel4Z5mzlf1/zSq0e80iU+22XMIkUVSgD2ppFPvP8htpuGybQpTSztXXcHG78TK8v4aOzOKAMQHJRTy3PrythujPnMI6qCCNMITz4gbG9HeprfyaSiqoT3Pa7DGOdkHJ+4HHs4g3kf5zbMBTcNrjS7PEeguBxG4UKE89bLntBl46jNBVz1lkkdzcPlXFzVVS1Bfx2cMTisrP4ynOfGV1nb18a2TmNMve6H/bmaIMzFrVQreO9OC4SMnn9juX+ry7seUClGVqUhIgFaFVIwZ7kpC4WaMQ3ObifBE+wqSggRE6GOwQPvC+9+ws2bQV2IVnFwEAtw6k25KpGEg5tkuVCpOwBKKFuxYpEz01hTxUgnqUyiCjOP+xKLRAvkRphY5SwlAERQwaJbGKbibfQ4GiOGwHPPPYfefIErT+7x1d+9SZzscuWx93CxCvzIRx8jP/cY0wcfoBKhWyhUbhlqCCzUmDaRrvUYmy5lFqljOmnosmCpYmvnAjkJFx54iHPnL7B/OEfnx9TVhLB9GapnaGeJrWnRmFlPs62QYYbTiAecca8nxozF8ic9wQSAKSkKW8Etckn8Ba7FweCcgFROgNAUbU4IgLpFpsKTCgvuPhjEiRei4IQYgJQEwlIsZifi/ZtMB/cXLZtSAJIIlRmKMwk2iidfVMOyg6U+2S14TJyzD/omoj5YJAsONMEtbiLO3thrDr27qIZFp2gmzS2tc2Mg+DD1hXoiwXNtWSZboBFnR1QVmqLlycHBUvTudeIUVST0rn9O4R+KdbAqboVJhd6jW8RBWzaD7LFdvo4HMKUqY+vxfe/UYhs/vpnL73rOOrC607V3AhebyroKdfi5iFQjSt/hLIGjo1scHN3i5Po2dRAejIFF0iGvXCzB0P12aqHMp7GmkrK50jM/+vtGcWHdbzu+/LVnuX3tBrdfvMYXb7/IK9UJ8y+8wPyVm5yrIl/6yPfBk8tHuCe3+PX+ezMg4C7j8EaH4W636ivaMFTDWU577O/6zvbO4Bpsp8Z4FZ0Pf4uwNV8s6FJ337DRWxZd/iDUzPepbAKrq6N0ttqmyzDvXIjtmc6s1OmEDd5R7rLuXi1JjaYkfk3a5x1awjr/z0ZWhOKWHzxMIpU8jlLW/8GlEBww9W1gafnyPaxYW8x5jz/xkYf54cc/wf/hZ7/OzWvdwBBr5XGNwHRrwvm9LQgeYtG7rI2FbLWly19/bGHGA5Oa/8137xAV/u2NE7723D5JE3MNLDQgBC5MpvzJH/4eqt0d5s32cq0aDYCZe3SsKx3Wx2R9hM54RUdH/cvBQjhuXX4M4t4bosakMra3olPCl1i2nHrrpZOYtJ2yf5JJObA/NxYdK5alHgz1qV28Ce7dc2kSqKMsgUZBwoZblrreWiUswTVuOQMb8oEtn2SVxr1k4R3xTIx6ZG0/E4wc1lUGpQ76sTV6oJgK8cT4qfp+PWtpkJW/43nE6cF7m8u7HlBtVRUxOBPfpMS0TKVy8GEByEyl5OkJSrBIG5yOscEGC0BAIESSZVozpkUzlE2YmLunqaoH9oeAVH5tZ8rcElOJhOirUg+SJES2Y8NUArMY2CoWli4r0WpiCfDOmmjMCQMMN3uH6EK/ZXOmPykTOggTPK7o4LXr7ORj8vwGh9df8Liuk2vsvedDPPbQNp/8Q9/N1/KEbLAgE4hkCWgQqoURGlASEiLHXaI1z0UUWyVlmISaw+6E5ihxsDjh2tE+h6/f5MEHHme6mBImFW3XudCVwJfSypn0ohM+xOJrDerZ0SlBnBharCcSoLLARPw1yuK06CqAFVruaMXCR9Hi9T7nQo05EJXyopa4LTP1XFPZfZVNKQGvxkyVmP3+7qqJLxrmbIMLc5O9ibsgKDAvC1sdIBQyh1yADsEJJ6JEKsnMi+vCJARyb4lSpytPWBFUfQPJlQM+zQ5Mgyo5+PhHC+yVxbmVjAR//gVGbYAEzIyuaBOjucYzRxuAWqdA8Pk+QVjknupcyFkRAjOUWp2dMOC7WjaPJxQc9Kqvq8RC1lKJ0SFYVtL9Xsm+HeWeBbt7eNazdgNbO+deBMrx5r/p86a6z2rU2AepfJxPtrg23aLZbWi3gW943GDCY0JbgCLIDXvsmaYOoapqF7YMCMrzn/sML3z+A7z02c/y+ovX+MLnv8rfub7PlrY0MTOJ8OGtwOG5nZUNqxfI7t7bZ0CeNzIl7+HcN4Nvl8IQpxDi+JuBM2iNhEkBqljx9FMfYNJMluePAdlKPav1K8Y3nv0Gr73+6j22+N7LW8VAsvYM755yhycaJsTqOJnB7Tnsz5eAiLVPy8Vi+X3VMhyW4GFowoCAhnvfnMHzN/3afs6logDZ2NZST29xCqEXkP23OiVC2xFTx2Nb8Inv3+b8rnBwbHz2yzMWaryYWj7+3geYNkJnhVRBoA7GPPfita8pYq6s6VOcJIy6CkwnTsb0RyY7/JGnL5Cz8s3XO37rlRbVTJfnfPZffZbv/9Of5NHL1Yh+e9nHbTJuzO/l7V1VUtypjEFILvtt6IkeRCAIN24rB8cZFY+l1+IY16+hZrBIyklymabLkKwAqr5z1trTj3zVp305NX49IHHZoc9TCf7uTYKTTHRqnOTCTHkK1LA5znIARac1Q1LuvamnbDRjrci6mAzrPL1FcdyEtapGLdtwj/6c+yeLvOsBVcrqDxkUS0JXgZh7+UcBsgfHNBI8RkVLTI+CWiYVEdECiCmdtkTP8FsmR3BqcDImFfOUCWZMLKBZETMkguG5gSoCVG6tkRCJInRSYl4kFIHY2el6axeh8oSwlj2fVnDq7UoK4Cqf52SCCh1OTLC7c44XTmq++c0Z3fGcF69d4+ThJ6m2Hucf/8rvcO2513nsUx9E8HxNUSoqg6wZK/5jSZ1WW7vMpPJEwW1SmDYc0rF47RqzOvB7X/0KN26+xqXLj/CtZ75FCBXnd7a41bV88oFPsV3XNO5XRhWFNuN7R+jd1aJblHAf8RCEWLvw3+JA1ZMVF7p1cbfEhTjA8QBGIVhgEXwDCMrAoNiVDcaDeW0Il5fsIJHC/KimtNmZ6bI5e2OjxcNcChlGWRCSCRNzoLQSX1xo3jNGRYRibSIq2XotFGwVkFxZwIJvJDG41qgSoS4oxcCTPpdNrDfhk8s9CsFFTaAKMiy0dYBWrbhoOgMiAjMzYmGM6mOu1Dy+bZbBgvv3Z81OXqHiVr9g1IW2PpgnQQ5W2BqLtcvwjbVCCETqsgnqO9lAtbHcC9K5w6VDWUdQdzv/Drc9G8OccXxVNLPxp5Gg0Zy7wDMf/m7+T1/6HJ//4jV+91hLXryi4EH4wPd9gg9++CPDRVKOnd68DJNIsIyIsbu1DUc3uPHKqxx//Rl45RonN1/lc13roD4Zu9vbND/wgzz0vg8Nbe6VI+Pg+Y19dddy5/6/Z9HpzGrubZ70QuimSgZcbaPg9V6DhgtnIQTWy9kWPG9TZMTKdS/lD0on8hZete+sco8PIeN/bCTHyijfT3/OcoaOxd0eIw1xTf3qbKMbjG82ACj/FgrRdwywVfm/oZgg+lQc7vLVz0cD0eEeqsato8yD159DX3iG5557hct5wl/64T2evCrc3Ff+b6923Jwrtw/nfPx9V2kqISe/TxVcMbk+5WqBuRozg4hytGhpsnLYZi5MaqoAVy5OkabmoSuBT7zf98rj+YLPP3ebajYjzeZorItitQAr3Dq10t93GJvxl565b/2E5ZqkQwJngO1KuDgJSFAeulhTUfH6UabLQxKZod5Qfmmix0vlAqRysRq66OPjMLj2D3W4C2kdluvEuO1mMKkCV7el5K3sjQTeJ0E8Druue+WV1zte0+cZZnkZp7WCeNa6clixz3gNejClvd7I+vkrrFEALp/iHteklX3oPq5j73pAJRJ9AFVJsfJgPVOCCjNTqqpigpu5W/PBFNMS2BeIarRBaQoRRSSi0YPyA+J5VAxqjQRTugpMAy3CtIqFFc8nm7P5eazUTqzc+iXudlYXkoxYXpKeiCFZcLcxMbYIdOqWB4lF21Fcq0I0trJwoh5XkyRzsjji0e/9ozz81JM8sTjBjveZAQ8+9CTPvvxFXj8IXFEQlJQVoUPEiNloDUDZKsmQgwlN07hVKcBOFTi/tcPN1wLJZsyufZ1bX/sS9th7aZoJTb3L6ye36cIOT1x5lA88/T6gsBOZOjV60ZJsm5CDFIuPFbIKZ7szIEiggwFERilAyXrWHGGKkLS4/AU/OZdcOEmFmXqMXKdGpUIUz7uUzQp7opGLZSbgwktlkILRkpmIE2gUpwiCaImtclKIJM4aifSMeA5WohlWXChCcA3TpKDxZB6UGnBLVCrMhhPPuIXg1rl+Q6wjrrFREDFS7WtLMKgKM6OCu+qJuwiGsgh2fdu15DWJDvwIvggMNLUGkoVOlUZA1K1dFeYEIQKdSGEN9IVebekW6SQg7g6ruBUil832nV5WBPe7opc3d/ieyr0KmOu72V0acRZ4mKTE1TTjZu7ousyResLqHlARhPe8/2meeOp97jIqK6LGqbuJRBDPuvOh972ff/ub1/i3Nw/43/3l/4Sf+9Xf5bP/5rO0J8eELkHXcu78Lg99/AcIVT1sun39p4pt/vnNlrtWt2EclteMRdw7XFB+Xgq0S4HID21oxZpw1P+zQZzb3OTCKne6zWeUPygwVYqN/r5Ti4xnxVqHr4m6y99kee14ViyPaTnq2nwXR2y4xwp5xKk5xADirew9/RwS3C2tCoFpbc58TO/RMJgMSjt6UbkIL8NCYsTFHJ13pM5zaUYJpOxnTmqhToHgARio73jDs/m/sqJoMJagAoSHHnqY3/7Gi1x7+WX+zONXPAVJEKqr59l674POYisVl49us/O5yPPPfJOXv/lN5LEnqZ967zCjDPfUGN6NjcBqSdzRXzP8vqFrh8/FDb5/jE7hsPP4LjnwVDTH8546fhmrHfB93oGS9BhlqMvAY9zKPYJ4DkyPsQ9DO84EHeIy7KTq13K/bzZoUy9bFLWYeD09FT3984jSZik51Nx91AoQkrUbD/N+9H3sXiliPn6l8k1rkg/7muLpVJ2bcK/RW37v51L2rgdUSEYEtsyZ0HrJtlNfiGJOKIETFM0GMXoeHjFP6urpWEkhEoiuqQlF4JaAmTJXcEppiFSYKJVUHhwa3SJh4gQAbSEl6NlQxAwk0IrnwhLx733yWAFMiztcUHpLTLUQLPrkixLInQs3sWiNggUWN19nu5owqRr2rjzKtKm4feNZaltw49UbXLj6PU5JrP4WtEnZqStE3cUuZUVCRdt2RKmYxEibE3UdUVHqSsjdnPMPPszUaurOOHnumxypEZoGiTX13lUaq9Dklo0quBWwEmfJU1uaet0n2IX5EIMDrLJ6CNBYIFNin1RoraePp1in3LVtrm7F6n1wrdj3W6AJ0e+mWny53cXO1C08Kr449YmBJ8FN85U4TTj4fauSa6eRMJCOxOjJGScoLZ4oOKoDkFgYmrYq/11KbBLmeaRK8JuTRhQQ0uHMfhGhKhYkBbdmFesSeHs9CXIkqpFRGg3Mgg05q7ASm6aex2EqAdWy8JkUACtU4s9WU96RAnqDQhd9sY3qLIMR12zNrCSkLs9t6trv3u3DcGXFu7vI5pV6be0fvq9KRW/qdiv1r4Ose+zus04bIEtKPPbpX+c/zgf8k4VyPK/546FiIZ74+jXLfD13LNmkBMnpVHesPLqEkcAnHLUtDz90ib/8J/84r9QP8rXmKSbmKS7MlMsnr3k865BOYRk+vfokb3WrXO8NOf3rqXm8SZLaAHbOKgXX9BaFJaBa2/wNt2yLUMV6CAiPVb1kLr3znU493eAuVLruzfTgvWL7N3v9RgHpHVouTmF7uvlJVgVwRi/LWGy302sIsHxbV+DWMLdO9/L64jHUPhzr43djsMGt2wTmSZkNLmBLODI4Y5U93NT3m9m1V3n++iG/tN/ww4/DrW+dcPsZ4aWbrTMAB+OhS1vsndsjs2SFG7dyTNmu5VPJosX2uV12H7jE7KWXSEVpmrIiswV669gV2CEii46cMzG3LA4WNA/Nec+FCQwAAE465bWTNMgbTvjifbqch5vW+bu/Bf3bbBgpGzc7//31k2LVW6l2NOvFhti15drSj++ShU9E2Kt6yvs7g6h+nPrqrKzDPdlIwKjcPQrNwqJzll6xEg89GvetCNXUhkTAItCpcNT5s25F9/haNmitn3rwVZ6rrPp37EsHveNVYfWKTSDMDObJCjvt/SvvekAlCSqrWFimjkITA3NzEFHj2n6LRqWRgLOeaGVAxNSDKqcEugwWcZY2ose5lKx8QdwNS6NAIU2I4m502RyQ1bkXvAuVdoBp8KDuEPy+VnIOdJIGNG24BgNzFyyJwV3KAsP9G1PaMqVCdHrVRZc4OrrNp773cW50h9hJpGuVR3YrLl+6yGWe5Fl7iCCGRUFjJHWZLkRyKlLzQgl15ng+48Jkl0XOdF2irmu6IMRqwrxNXLh4ib/8v/zr/Mqv/gZf/93fJmhGds4xOXeOnYuP8vCTjxVaULdeCDC37Bo1egY6pzi3DKEyKjVPjmye0NCiW0qiurnbM6aXwGwNLCRTmwyMe/2LmoIMCW0bnGZ9EiOKsY2D1i4Ymos1DGcDtODeoO7q5gJgJa5d2sJ9vbMUABwd4ClGJRRGQmfFW9TeZimrjQzxdr6Kh56lrweT2alBt8riVQioCwB0IpVU4sZUYR5hkvOw6LYIMQsnJeBLxYjOactChJQzQhhcFzW7G6UUYg1ynxOsWNdwrdQcitUJn4uljwUHrQmYUFwRte9zVzyYFEvqu6qsbaJ328DWy5uQEjdu22fsU2+tLBumKbEzP8ZC4kcePMf0SPnMfmYWhHmEqB3fzMkVQ2ZIrIpAuFnDODTXSqP7QAbx9azZmnD58iW2ZyectwWNwYNdx97hIRoCuYrMp9MVgUfu9PAbQOuZ4s+pXfnOg7Rex2Syw97exQIYZWAcXW/B2Ao1FtAEG/Kz9EgnIIPgRAhUMbK7s+dCYlGe1XU9XPFGxYUBT62Aqg2g8YzKz+r5vvvOnK9vuK1Lrfs7tWxPAjtNeYYNDz/+abXflp2/CvHv3oPD+7ZhHp4C7WvHekvzED9V9ugaG/63ufWudK6awHNHia8dZG60TqZxeLNj1sELr2XQgBgEiRBHpDZluvWvxnAXk8IWJ8PcEoBKONbMjUWLYDSHJ0wXC+TF14o7nLd0kTONZK6/dkx3dc7H6nI/+vdA2Gnclb2/gRS3wBFGPaOP13p2w9y38gw5LImhktpAhpFW0KS/25NgntNRlsmBy+gswVTZd6fR92qRtXd4bezNlgM6frYlgHOXywC05oy9yfC4phExlojRLLsKBLZrr/Wk89itpqLQ/Y/XOVnee2Ovrr8Jp3t9hThkfVHZsCipOTFclzZW97aVdz2gqmKFBqWuKoIpCwWLkUkwusJ+1m/+OXrun0qKhqVo9ue5UJEWP85ovhDkQl5RheDJfgu9VZczwSpycLwdLJRcCMEnLAHNsAiFflqhVXV3NIEsJdGdlLghUxp1odQyaFSPvVFPMquSnWAjCFVQTBUJiTRXbvMQuxcepDp3EckdN17/JsES+4fHTB7eI1QRzZ5jyFB3cdSWSV2xEKWxCGpoBdYqe5Ma1YxIpBUjS0TqhluHt3jkQ9/H5fd+N91iTjYjNIFnv/UctSwTuXU4qAjiC2wQd5vMRSAzKUloRdw1zorgr1Zik6S40yptkcWq4HT3ijoIMVvSgBcNX0BKwKwvGrEs2r3CsApu6WvNtWZqUJtA8I3D2YX6VTwgwZgUoTAX3tpYtDuGL5AZQzsXA7pCbYLhecLMfHyLNszMyTY6U6J6vikJnjx4LkqDu9Rp8nnpLEFGlaADTN1FwzByFo8ZFMFyQEtclvdbQLRcEz0xryfkC0zMkyi2fcLlMv+t1K9Fk5XF810lcffHGn+HPJbMCKaF3dLdRcWcYfHdVzaJJ28ztrmXet/IDc+W2lYO9PtSu2j5zAuv8l3nGp56cpf3HRufu32LuRXGLXrdjws64zifsxsgyw2xKDvM3C222a7ZaRIf+t1f5W/8iafYvryHXI/IL3+OcDLja1rx33/8j6B1VWp7c7297NO79a5tPGwbjjfNFpcuPbK0wJUbrWA66YWhIuTIUsMcgwsfIfS9tBEPbngWGdqwZCe+m9BtK/++ETB2xylktvn34fhSMr3TyJ2SiwaA++4osvZltU/LiPbW0E2uU2uj3Cu3zhrEewdSa+2RtZlU9kApe3Q/cfq5GoLvpY1AUOP35sLvH3mczcuHmdoMy8LvH3RcnwsLBb00cc+LXkZe0VPJ8uGGfljODhNhUlUcJuW/fekGc1X+462HeM9eTTDoWlicFAIdhMUscdLlQs5k5flKPFEUzjeRw049b9dAZLVc0U572vYxQavgUmQMqmx0erEsW+9i7+RU2aTnzR1qCQChyJfBrYV9BMAKmMLlq7p41ciovacHefnDmWufi2JkE1o1DgqLb+9tMijDRusOuCwXg8uwVbCVloxVAj0L5PqtV/rW1n608aGyP40Wid6tsn/E8XJhrOb5uo946t8FQBWhKpo88xilhUKIAcHoNPjLJf5SxcJi1qqW7LORRjw2x8wTo5l2ECrI7vVbA50oOXtMjCosYkeQQFanFc4mnhjVlLoXInqXK5GSPM8na4OQSpBxlMgEZVFAjEafsHWfZFU8V5AoiBmtZqoQ6OZzOoy0fYW6inSLGaoth90OLz73Is9+8WV+5H1bTnaQnMa9riv/XhJ2VkFIptRVTS2BW2nOdGsL0eBxQymhAQ6OjtmbzHn4gQc57M5RTbY5Pj7g67//28yOj5l3yjRUGE6DHmKJFauMSsFEsShk7WOrPBHtBCkU3kuXg1a8f3o3OwRyhIk5+MilX7dwwT9Lv+AIauqEHyjbxVUv4zmdpPJ8WL0+qy5AzlCMSIuDMI/bcisRvSBESdJnkSCKqLEwN333CYSlxGmFAsRrgW78xptnBe9jrXrwbmbUlHwgKtTiLo4zfMGjkKVA8FinokGqLKCmDoDMc4BlCjFFCW12l8FAZV7vXNxqGM0Z/DrLBST6ppHF3fxITn0aMbJlkiiNVGSB2iAGt+Aq5rFeyDs6se8g2AJn7wDLTeOegNU9rur3C6T1lZ8m9Vu9U1NXBJnQzTqqa/u0B90Qwyd9zIHIhn1vJAz2H1lqRJcOe0ZVVVx/6TqL1PK+S1Ne+o3fYOfr3+LoEw/w0CcvQbPNJBh1DLyiZVs2YLwxv+Vtcq0zxuVeOr/EFgyijIxnzBhkLnX7S0tVf7kMwkAYHRs+CYOCY0WoHJ9T+uWMJzz1SOtxPWMgc8ptaA11nQZTG2+7udwBwZ0CU4yE7XdwydmGfHy9JaGfduP3ZykM9z0x/nXZEesEa+ty7tnlLj251HWscAFghRVvFYuvtdD3Ek9YL/yxH/k+dPpV/sVnn+f/86Ir2yoJtDmwyPChxy7wJz/1IZC4Yv0Y3O5KP/RrR6/k618UAbZV+LEHL7BXBb58MOeffO42D4ToslwVeGo6IUhgAXzl4IhrXeIj62+A+Jg0MRCSbe5DGT3n+D0QSo6v5XX9Oud9OXr3CzBJ6my6rboCuc8l1l8mvaufMSibPU3PGET7CYLLmDF4THmQ0/FL2ZbjdFYZ7zWdBldiGzzQeMy0DUALOrPB0tX/bsBJKrnHquVeOHjn9WvThnf51FyT007dfeuGaV/uqzDQNQ6W2AL+hrEwO0s/8baWdz2g6qyj1ilZM1mMxipCISswyyV/T3btqEXPzyMQKhfEVZQW18YGE+YpMZFIJnmMlbk1IYm7EGZAYnSGviI8u/AqZE1kMf+cDYp/cs6ZyiLzkIr1K6DB6aoxZWYZK8JrTNDFQC1SLB1uyVIUK7E9apCPj9mSCSFWqEVqURbdjJ2dKddeOmQ6OUcVnbCjy24xqaqASmYiSq2CVTVHszk72w0mLVIFaAIkUFOqasLs5IBrz36DeTVjsndMm2vq7SlxUnFpJ9AeGpVlJuJ9RCiLguAul0AqlHtVFZwgIrvlJAe3MNUmYH3aOCcIsWLhiSa0aEnv7vmYJBTWPHW6cQigoNGvq4PXFUsi4WjuQjlJggZDQxlHBSFQiVFLcMAlRhCjCR6lK8VkryosghJU0eyupM6gJ0SVwXqkyODmt6XO8teKW3eawpoXY3EDFEdPCZgI5LLzSnE/DQKmRk1ASqLiLN5vGFTqZBmtOnCygSHROzwn14ZrcJr43hLXUNwKTdxKlt1NMWhZIoODzYz/HnNEQ8nxJYGFJQefWrLZ2wg8vgPLmS3fILyMf9okGL5Ruf+OvWZnnXWHm9jaKRsb2R8S4mRKfupJfu9rX+BfH8545jjzvLgLSJuVa2UtDT2TFDLsjIOAv3KDkl/Flvx873n0KZ758jeIZrz8wnMcfvObPHPjOv/Df/WzPPvfbnE0M57ojG2B2w89XBQIZxBTvMH+XQUZd+iMO17t17TtCa/ffMUtVHL6+Grblq0XiYQQqKrIg5cuUvV0YIwk7eEyGTTfgpA0M5vPXBFXN0ybZkW4vVvrm2bCdLKFYKgqXdfe+RpjndX7zZe19+c+yjnfEWV/LnRlPCeVUVUupAY8trYHWDAWLgtjZg+SS+cPTGhlyjo724hpzc6ezSugeXzgHkCr9U3YgM5NGJIO9+jrsauXeOjBCyzyi1jZ/H2NiJgYTzxymY9/95MDs5y7ZknJbdivIVbATFlXpPcocTB0NG95SIwKpVP4lUP33HGkmgl2AhhbdeS9V84TIuyd26GkWtwINGyld1YBVj//DXfP7wFRL7BHKWRS43oHRUh/P0/VIuIK1AAsyT0G3YpbXsr9grjHE+WsXOQLJ0uD3alw7pysMP2ZQUpwMpcVMLz6vH6DplYaz7WCmoP/roOukwEIDm6K2RXfPaBpSzhAMJbtH8Dd8jan8kIN3VsU3whNtLEebnVMbIDWHheVhUVaum2uPN9wbv9KjDe9+1Pe/YAqK1XuPFhfhDa4ABxSIJakCRIiodBNV+IASdVzrQgBNXe8bIIQS9BcViNSY+IB+kYmkV3wt4CKuwVuh7pYB5xCvRZDLSHFfS9HJYtrdbaJdKEI09ldw07KS2t4oH8dIqoQaiFJoDGhi0ZdgxSidcnC9fkB770yod7/Gl1zken2Ns38iJ1mi489cYnPtwEk0KnQRWUx79hpGkQTXWxou0wtgqSEhC2O5wvO1ROmBTR2bWJvZ5ummXLu8iNcuTjlkcffw1wqVFvybM72+Y5ffPV1YlCYChE3SxuAunueqEDwF9YnowsRsViWehc1Fc/OEG2puQg4c2Lvhhbx8TO83rKkkClJfvEFTNWY0VN7u7Bfq1cgOAhrtYAmg7kZmLvQpaIRklRYesxju9TKilJUNVk9/sFw8FH53T1Bb/DFbSHqY6swKatOEB9vDEL2/qjFGQxrnC5WxNubzagtkCSTkZI42q2tiQKeTJlIYF5IJERK3FaRdhNuMR3E4QCWfcGugjMlSiVU6hbERfAFaiIeBybiLJSpn6fmVr+6bARqhhWX2Hd8WZFQzn6esbCyJlK/PeWeKhuftKGt640847kkVDz+Xe/nDx29wE9+6Safnxfth5XNX2B37zznLlzwasaCx1ptwy1lFLdQXuRJrKlDzZeeeY5udsyttuOXbh3zey/te364ENiNgUfOP4ZWzYruUk592NAFd+iKN15ktcvKt8XiiMX8iH6d8SaMGmGsAKRe8Axhikgkxsil87sQJ6eewdZ/KPc8OZnxpW9+GVXl6uWrvPfxJzeAqdPic6/of+zhx3nkoUcA2D/c52vf/MpIMpFTY7jeD3cC87bW+HWt+eqxzTVvFPzfoSUZdCaFLa/kVDInGlKzwT16LAT24Lm8bhtHpD/eW3hsqHukJFgfKln5Z6jo9CuzNgJiaxfJ2lQzJzuaL7BvvYCczJFnr3E15LITL+fBrSR0qSvseoI64wGLAghWLQr+AFGcTn1HCnAx0NQBSh0iT2zXfP8F4zePjMPct9B75fy5CT/5H/1hzl3YZWvaMGt1IGJwhbWHX/S08AN0kdVe6NuVrXeFs5Jvsiynwb2hNq9LDlY6llboPiyhf8bBLU1gqzK2qwIyKYRWpU+2twLHrbE/t6Ff6yoMyi0rskVK/u/m8V0uS3Ul7Gz7dblcJ4or0PsWVq7onSKctHDSKobHlitCI1BFltbXZUc6xu4n4rA0yOivX6PmivH1NhpLwG62bGfWlVusXLT8/duzgrzrAZWmjpQyfYyLakaItNYhFohEAq5xDQG6zskIpAjJTVV5It7gfH8aAhIrQnbXOlUjiTCJDdnS4B4FSicAmWlJ6jpXJRSGu2SZnaomB6Em0JoTT/qLZITorG5BAg2hWF7KiySxxLG4P+pEjJMk1CU2J6ny8re+zPvjPtefu8krtzrObZ9jeqHhvQ+/jz//R7+Hl259jrlmQqioLTKz1mlLJbJdC0d5jmFsTSeejyBH5lVgW8xjvyRwoZqys71LVcHeuQdYzGfk6Q7tItMdHBMuvpe89QKzrmMbw3KAkn09BRmSwVa4P7FIT8LgzHwZT74sZQXr3fP6xL7+AoaBPr3NbkFS8Zgq8NgrLQFcnqy5Hx//rVYHBvMSVxUKdXgy8y/iMWxtAV+qQgjqlqcMOXhwbYUD4a5sahOJhKCDG14VPa4qFpayGN1lrnXuexbZrUs7CCfm4DCqsVChCdDizGlm0GjoI7JoLRfNoCcSjoUN0MxBqIblgqU4uOmKZTMCjcGi0NjW9IY+IwYlZ2c9zJpBjBzcXSOqM0AGCYjqsFgJ0JKx4uYXS9Bx0jRsUu/UMogx67vrPVyzSeR8w71x5gVvX7+elrmEyoynTg55oql5KEaiU+H4mBfB6KGrD3PpwQeXqsk7jLXL6uoa93KeqmIBkMD3/dgf5l/+g5/l5IbwmUnNJHlC6V2EDzz4EOeefNJTJfSuHW+iM886fW1rXz2w/mVNrlzFo0tCjtVLZeXcpaAogyLGVDa6t8mGT0ZRWGjGVDHLd4VAqzVaic1wMSDGuHKGjSe6LIX7lfpX/M4EW5tBy68bXG42zJU7vSvvdFDVC+gqhfY7L3tzlj3mSEZAgnLUhUnfL2KRAWTsQz2W3Mfzcv3lOAPP9j+vuxAuW1xaMZjQ7NQ5449ZwRYt3UvXYf+Iq/Nj/s8/dAnDOJpnrr+eOJwZ//TmHNU8CMu2ocqxpdfnu0+ZnuQqCDz9XU/xEi0vvPwCf+zRizx9BT79euL2rGOeYN4pCzK3NPPf/MJn+L6PfTdPP/0EshjYosp65vds+ryRo7KpayJuUTFxwqpe0RLE99KBIEL6I15UpCjKGeWO6h9T+taAwLQytmvjqAu0JXdk/yJmxZP8unjLzRM46XAvGko8tUJK6nHeFgZq9fHY9nedJzicFZdk6938zJmxS7s8KXFPplNmpriSGIOtCrYbkLCMI3VlgCyBarEcrb7Xtnz2flmQ1dVES7xZm9xlkoEyfjlKPYAzbMgM0Z8zrMn3Ubn7rgdUU3GzQ58o90RdYx+DM8YkFFImx0hFoip2hSgVIbhw2tQQtHIQIG4HCjG62xtu3VKEWmq3hFguwr+zpy10yR4XQnSXMfGYH38DYSsImqTE0ERadYF1EiJB3NIQS5xXkuIO1se0WKCJHvsSg1DbgtsvP8svPPs1vuuj38ONV17gGzdu8NDDj7E4qvh/ndzkIDzExRyYREFjoI7RkwqbYpUL0nQd1VZDlxLVtEKD0WUjJEMlkBujaiZsb59jWglxMuG112+hrXHl6iO0dL7Rd8mpTBUsOHhSlUIJ7kliwbUwczMs4omVAfAku6nEdYlBI86yhzkrVir9W5VxnoiQk2IWCjON0uFdvTCF4HT3aKDDWIj7t4cAucQ9mcLCjOkwRIGkhqJEBcUp3N0V1EG4GVjRzqiWxYdAaxSGHqHD48a05PLo5Uo1B15HOKGGaMm3gTpBhQRChm2cUKIz750qyEAYkVUIlZUs4yAlTlBN3M0ULUmQ3S20E6dVR6AqgLb3j57KUhMWzS1QQaIvjOKLUs5+kcdqKcEi0dxlVsWJXSQotTHEDrwryhtYjzc99dsHplYPyx1+uXMFGxiXBFCj3j/Afu03uZUTP16d52U54FUyrxVXv3L5SNja3OCVjTGXYIByxHJiPoeD/dv8Ty9e5dd++FP8d6liZu6KSs5ML17gfX/kB5FmQh9TMVR8r/jhjq26Fy3mJgi1+Rq5x28FUgIBtY5XX7tGPVChn752XQyZL+bF9dyWsQpntmb12l6wsPLHmQkDhi4F80EY7AWo0yXGwKSuBmHlbFISGf6aQJsyi67jnt6IdzqaovR3ATltDkVw9mdfpLMfsO//GNxVMA6kJV7XEAc3QmLLmjfNWU4d6b/b+lTZcN5K2TB0VsDCrO2wLlMJPPpExXTX6Loa+ewJMfnz7O5MmNaRbMIiLy0h/TPqSBDvTDhIDn+2gt9JgccefYBs7+WrLz3LZKdhb3uLP/1wSfUxz6TWUFFuL5TXF0pb+9pVxTAAMxhRtksx50j/NP2DjRkBBx3IqX5W67HyyNrUV2HFRS4bqQBoGQGHID0g8qv2W2F/sXSUm2HDPV9fJFRL/JUJs2TYPAEwKaEJyyFyuaYOgS2Bwo82gHVwhuVZGYPOKC5ya+tP7vuhtDkEgjm7XxQn9uhBP0PdnrtsnjxVjfZXj6qW0r8OhkboB4glzZDh8fR9PFgIRh2WbJT9v2rGIhUXR+n7S0f9wH0r73pAtcCos5Qs1UZDwCyTs2vorfji1gWsiAQmjZCzv1fzQkYh5loHCRW5xC1V5a2P4taJDMWf1YXc1MdJxUBnnksqqZX4OWdX2y65rMRCIc9wavU6eE4iIYBkQhHge5fEBmd/6U3VAaWuHCAggWbnAtNqh1e++Q3OnztHdW6baZxCnPK5L7/Ikx99mp1G3IohQlNVqBiTKiAaaKrIbLFgu9qmTR1NXXkC17YjNFUxvQdoKmLTMM8zdlrlyu4ubaw4aluqOrCzd47UpYF0g2BEdaBT4b63SZ3KuxK3Vll2AFMLJbeR0qlS48/eZk841xZBTkoOqVzc5U6SM+JVIdMmqEIg44l4WxTJUFtPJe4L9BRfOoPAQj25cGUlIa6IAzDB7ZlmWHAyktY8QXFtQsJfKMX6sC3MvN0tDqKieSyZ6XLR9fwbS1c/63xeun+1gUkBPlJM5sqkj4nCWARvVxOlMBPhcVX9wmTudhhKzBjmFiTJheQCQJa5oiYIIfvin3MgiVFnt3hJabsFJxDJFCCmbu5XYCLBWR6l31zlTaCIf1/eTBl384q14gysY6esSctrck488yu/xJ95tObV48yvXT/x+YMrETB34TArcVE9I7RP0bsKwb0YUTdTPvvFL/N//H/8Y/7mf/Y/59Hv+hDT1+aeP04VSYmt7Ya6mb6xzfAtb5z3XsG6E2BBIncug8zmSS8sw7Xrz7M2csvTy3rRH+u16mMgfa/4clNjdra2efqp96Oqw68ni0zKHp+7f/tV2rQY2k5RrEyqip2JuymG3nI4/FkHquO1oC2A6t5x8Tu51BU0xQgoLjkWgXoV6i61//13H9msME9LEgXBYxebMKbTHnVvL5eOfxg+2fpP/tXWPth4Vo/mt7EylONqNMCJGV+4dUh9csID04b2OJC7VK51Z34RY2tasTcJJBPamboSTmCr9jipWVu8OEpxL4/VG5oAwV3349UHePhP/CBDQoUXr1FfexUUZrdmdLOOz7/4PF/5wrM8/Sd+kN3z2/TvjeFeLK2VPXFQNC1JlXrlg+IWIrUhomeoY10Fsl56iw3lut6LMghMgzCtpIQo+FwYLFgrqgqXI7XIfynDQeteNjEIWxHqOKhCBoTTRLiyHUtezPFsWYKkPlaqBy69K7+LJ+7iqOXZs1HiyCiszct7nfns678xAlHDvjK63JYhG1rAXB9rVZWcnB6vJSVkQoqCebX+/t/q31uo3nzp524QT6obg2DBXaNiiB6gH8QHLQYkOI14xF2jJlZiRIKSBCoxsgZyVKZURKdVIag6IUAGMUVMmFYVHUpTGO48rsQTtoJvRq04Dbt2ikQr1hPBYpk2JSamC9CYi+tx0KQUEzP0bynRhEhgd3uPj/65/wVZ5+xs70J3RNDA9qWH+PVf+jn2zl2ESjict9RVRVVBzoo0kdwmsmWauiLlTBMjiJE7RQLs1BVd9piw+ckR8+vPcHTUMQ81+3kHqoZ66xw5dywObnCyaDnO7upYqQxC3CL07g8lyW1w60gUoS0LRjS3gHTqLnNiRitKZe4CGCh+wqJU6v2lOFC05NbAzjImTtGKuCVuITrsGX0+MjUIWrKdFAFRitDo4+DA1/BFXXGwpOL5yWJZFII5cKnNF8OIYAkotKfuplPo83uwUaJjKwvOTmjJmSdzKDnNjLklgkQmOdBFX+1C0VxmkZKotxBz0PuFa3ket+o16sBc8bHs1BFVxGOmnAyDkvPKwVwglvPddaASX7C6Es8WccvbTDJVIWkBJ9PoF+JORrvivy9vazlr+/LNfST5rCscz3DNs16KMgfXF/cmvPraMeEk8WSIPEpgIcaxGF+mW1qozN+XGGvMupF0sQo2tLimWbnbw488wuEEjhJkVTrNWEmoTfCYgFDVhcFpsyB4T2WT9Lex3EPld4gHuueyKs+MPtsG9sXlecPyvw7gepW5nAVPNj9XX09T1zx46cHlyJhx82jObJHcVf7wdfylLq0yYXdrSlNHxpByzM4lp/4yTEeXKVc7bR2WLjvhjXbud17ZbZSdxvdNfy3GecgGR6/iUlV+KR2iBrPO3bK8+5cuTUvdha0Js2vKFMZfx8dGaGF94sny4ym4sALUlmQKSKCrA8dtx27qeP/eHvVNRRGSGq8cZvZzcNbZGNZcsPq54/uWSK/QHN9WsMF/xZU7LtwraTZj8dKrSHDyJ7l9jLbZU7+0Ldom2lu3efXZA57qvs/32NHdg/Q5osTTjrCU80/3n40EdR+jLiuxpLtZDsdoVvdLa5kDVbG2B/F1blrBuakMMcdjt2AXFcqcMXF2ZHOX+1mrzHImBqEq1PUD2UVfgziLoedJ7Y+MUzysutjZ8Gep/FoZhx5MllimNhuzpOTh2p6dWWgqqItL8biO00v6GotpAZt15fPncO4pg+og1MFT3PTt1+F+EGsZ2rcEzGWd0/sni7zrARWmnm+AXIgLFHJAoruCTczzL+XgwrKUDN8NSkCJFkmiRIkFs3iK0pB7a4BPbs9TpSWxq1NXaFSqLKgmEr3/a6AJFQo0EgtDigdHWjZMExqNmAMmiWgCRLdiiROaK06TaeqU6VXJnyXZmAic5I5zjfLxhzPPzx7EpjsE3YODF3lwsuDxSzs0240TJIhrjgyoNBFyoMsGXaaZbKGdEqqKTjNdStQ7DZ0aoRJO2owZXN8/4uaiIh+/zsuHM7ZDw7EKly9cYKaB4/mcK+rU3amn+S5xQE756S/ZUdLBbU+LI20qYKYyd3WrzUGtW6YKqbkFcoJWdDANUwR+f4UDAfHrtMQTBRsSLXfq9zB1oGVBqNRzjPW08iFSWO4UJZA6Q4IwwUjRN8PKfHOsALIQYrFwATE6WYgV7a8VQCYFODbZrVi5uKbG4ioYxYFJLMAeEzrRwV014bT/aJ873hMTdqY0AVCngw/m1s2FZaItGXWy4UQUGC1LS5sUopBo0HjgH4qTS6j6vInBk0x34tZX1OP6FuTSt9GhWHCw+84t90+jdc+3P1OeXEFIp45uFK3HG9odqjbgj+ztsWPHxBR4HGEX4YTAHLgdjGAd0+2tUWW2rHUQBpYAH2DeLphU0d9V8TQKIUREhU6VuUDcm0L0NA5BMxbCqkvbaQnnTZTTF55V1T2J82+mHXKHz+vYcUW4PV3s3lo51LHS3JV+HQnbrvplYG9cuz7lQXw6DaNGDV+KSUuxya8d35cBMNraz++GMksgCc/hNEjbAxSiByV96cNlRHqX7jXwObwQvT0GpLiPLuPUhrOHMSv2oRGBTC81j97d/q+NBdwCHqwHEKuj1IMfEU82nVQ56TI5ZXLbQVHE3eqUr8wS+5p54NykKBCW/XBasB4/x/h5iuVEIGV1YqjjBTz7MunWCaHNdLOWnBM5GNplrDPaNvFq6kiyVq+Np/wylrHXeUrpt5X3cEQEgvoe60BGSr6ltYGQIuiXtdLFnCWjYRCh6QGZrF3Xd3LvMgWUbFqksod3RanaBI/xWrreebqdJizfwdNKoXFyh/72tnpsjA1H4L0HccmKHLsyZmUS24ZhHJ7Jz5O18e6p27enRpsVWcC0EupIUSALiJDVyLqCYum/rrtqqt0/WeRdD6hyUd8ki2DFIhKNFKInnxOn8uzptVUznbn7VS2RJNnjn3IghUxb0G0UcbcxNTppPempFtHdXPsf1f1+KwmFqttYmLJNDaYkUbJkT4iGU316cmBjppmIaxPa4oc8k+T29Oh5m5wS2yMSW3PCBTVhvujYP2k5XnScHOxjs2O2ohMlfPTxC+Sjp3itqsiFiSPPZzTSkGNgf96VxaRCsyIh0onRLhIiHltjSSEGukVHEmGvrrj5+nUm08jR4oQsLc988bO8tn2e+tIljg2uPPIoO5MpmsypY9WtNSZLb28VnHI8O3051pMpuDbG3YsCQQMnkqhKzI6JOi25BU92W8Y1l+vdXa9sI9EZ8CjxVQ6yrWhnnC1QpLgWlDdQg9BkQaPQWuvzIQTfuoqKZSuGgfGxG7Q/RlPY+LKBFDDXYWh2IIkVGtLiPgfuCooEtnEGQWcWdFfFGJyStTMjqm/MLtK4i6iDmhJjpQ5yRAIBc+ZDseLDDD0xBWoYShNKIl6gUkXFKePF+jwZ4rmoCilKNi0+3+6vns01kK0Udz/LhU0wEKs/YFDyFsr6vnu3c++7ELgJVNzLve3UhzveQ8X4/127zs6t23zi6Qf4K1cnvHKz4x995Sa3DVo84fn7P/Sh5eZ8WpJba4OA6egH793p9Vd5TwPh2qtUYmxdPk+oamIViBh78xbNigV/N96U18ZdrrnT4TvD1nu8wT2caesnbbjZKYA1lmttLJaswpjNYeCwQU28oSFyqikGnHQL6FgxbJz1COP7rz/DqVtuuP6dXjp1tlZgECCHMsiRNurtpRDanx7GIzsIjEtJNSDsTZWLu1ryXEYmtZNnHR7Bzpa4lw5S9rzTBAzu6m3cOhK2amFSyUBYYQr7C2G/M1KnoznkzK/T2q0ruRNeSMb+LHPpViJUzmirCK8vjBttRuvAx55+0AXzwTpiQxt0bb6utrHAmOLe1eXsy4r6npZTxlJiPm+Ztx1JFNGMJGHRJU7Uhj4dC9vZ4CTJiivf6ZuzPGbLUXS2xhEgNFZejB78LSfA0pYr4rHVdXBV5xK3LQHCOjaz0aHevT6ZyzYifaLfAi6sn1erdfiwLv+OD2+IrD11rTfEG+u5s2RYTtb7bniM8c932S46E45buDWr3cWSZSXj8bG+DUNd47vbCFgKx+nfW6jedNmeTIlSUQXnRRMRqhCYBmcPEMtF0x/ddIzn4ZGCfFE3YSqdM8yIMhHXqiTNTjQhrsm3AMnykiY6BqZBCNHzKkiECe6epigUNzhwrYaokcRfgkkhrzBcsG9NSXiS18oiC1Wa4CBxkTy2pcMciHQti9zwSn6U3StbxJ0duvkJh0cH/OsvPc/XvvwKH/zhxgGTuNvZwpTtuuK4S0xrQevI4WzG9vYWXWvMZyfsbe1CEuaWkCjMj1u2iUy2d+Hlb/CtL3+ZG/sHNCmxuHGdo/OXkJPXufnyy3z8e/8w4UrNRIIL/FJ8X82ta60oMTt46f17DWMRPIZtWraS1ncJplRO316IOZyZzleYYZGKAIEJTjBh4guOiAdgVgF3ETQQcXfQQKBVj9Gy4LmYAkIXPB9IVRIQxgCY0SFMNZAH97hAMs/MXptQWSGjME/wW+HTqjFjYZ6TTIKDLjGnRU24ZsbpzN06ZwK5ct9uKZtNHfrk1LgAnJeWt2glrk8Uk+A0/+aMkXN8TnseLbfImQWntFdPqJyCu1+15vdpCFhUmhLLV7tfIBrKMwKL4qq1LSUPG4aFQDAhx/unFbr/5Y2JdPddCHwDlS9FZ/92L1aMQQmKQAfblrl0TqCKvPrqDMkMhCuIuKu0eG49qSKqqQiG67vkciceXFnEXWT/RDvnP/jNzzC9POFj1Xmeu3qFq2L8+NMPcOWhq+Tf+gz22S+wOJjxby89gV24OPTz2wXV77WuM/DsPZW71X8KuN1Dg3rhp88VM3anHNe1ceyFwTqwlEZ6YX0k7Yz48I3RedYLw5t7ZU2kukP7717e6cDqyrawPXULhceChNGbyWmFx9giOBL8+ysGOgXpIW/JK0jGLAzxLSH5vMjmbllRnUxIevPXyuiVc9VIGbQO7vpmy9gUpCTvbeIQ/yMYVfBciFGMXAUeeOA8KcHvHRf219L6aKEoAW1QmnoNvapPmCeP49VxHoaRmL9IS1c1MSFI46y0Wck5s0gJS5nn9he8cGtGVpikRJWFZ486XiuyXqGfWIIiNRZ52fXjOTdEKNrq+7UORU7PeVtVeqyc1wOrPv5oqQQZ5oZR8pCtvj99+gkxd9mfCoUcDbYrYbcu7tLS12fFS6rv8fXnY+3VX3+nhfGvw5El/efKYw/r/9oxk/UnWatvdGIdYKdekn71DTw9Pj2SHf+y7PT+/TCMWI8Vem9vedcDKkHdzzJ40l6PYxGsWJpcmBbXfJZ4nVYilThFtJQEqphQSe1CO07nrShdobJUTYQQwZyPLklEOkOrSJRIZYHKnBEQCR63E31BC0DO7uYVzGO1CIpZJJn7xQbzxK8S3BJSq7OrRDNyCfoxA8vKvJvRhEhqJqQYCIc36dqO7e1dnn/hOfYPlajZGdwwFrEiLTqsrlHLzNpE0zQY7mt7fHLiQnnuOMmeeHhxeEJWhRjJ1TYf/tgP8kA44pd/+dMcLmZol0nHLXHxGk9+3w9y5eIDVFRO0hCEidMhuoYJpTFIwTfuID2whAa3kngiOaMJzkDjSe4gaUSD0ubIFI/VmRJJhTq0Ki/VRFzoz+q+1ZjHmxmFIZDoeZXoN5rCrEhVrDQOnjoTpmJoR8mhBSkamqyYmIXKglvNzDeEbB564PFcDmzUlNp97ajECMU5MQbhhEzlkg4TC2jwfFFVWYaieULgUDbJ2FviRAhWQKC4lcrJOczHTxz51D1wM4XCDllJJKkOPteVCRUeKwgezJoQYnTXy5B9LuZgaPYUATG6UiLi1kHEWSeD4jm9/h0o336h7053vBfRf3WzHG+aoap48kc/SXj2S3zp5RvoIvPsfkcaYu16Md0GkCQCaDq7KUAznVBJcfnqrZ8hMNEMBovrr2A3b/P955U/+R/+cZq9hLynInzLuHX7kN9VZT7SVL6d5V5B1f0AU5vOv9f7iAhdWnD76OYphXYPlGzkKtRf01QTtic7Z7auFxbHgjxFEB4EGBv/e8aD3O23u3SOvdHO+w4s21HYjn38aaEAHys5RsK2x0jJ0K2DVxQrOGtZRsNyNBeO5n2FS8AkIrBYnu7/rlVWFLz9HDqcw8F8FZiDx4P31rQxAEjZWV4nVcWf/4kf4aWXX+Nv/P1Pc9SVuVfiwzw/ofD6YcvDfSulPDpGtmVMGRsEcJFQ3Nf8uS7u7tJKzXM3T/jG/EVms0TqjOdvdrx82JIyfH1/zkEKhArqvSkxhvJOrM5xKf0wrWxgVrYiKci4QeNhM1eKJoxJWFqIpR/jMt6twU7lFrCj7ORX/ZPWwWOzTYridBg9l03XnCBX+yMID21VBPFY6LqGGGUgiejb3ec6Gz/vAD1Wnmf0iLKqGlufDeMptGI5vUPZgL9GT1bmbenmSTT3Xxy1Yjnz1lo2Mrf2fbcOA4Nu6sG3p7zrAZWWxK+tuouYqqChJYTKBb9sVBXUUogGVOhyZlK09jnCVgE/GgzVQCuJCEwsQPDJWNc1YKhFdw9TRQs9tWWjC8q8U6qqvEC155bKZtS4q5lGoVIlaGBufrwuWqwQhIkEj2+RQkUtOCOfGCYK6hTxi/aEpqkJKaMi5HpKOL5JmNQcHhxR7+5x3Cm1CLHyWKwgMF8saKrAyWwBEqiqhtmiRTURYxzc1oJmZoczzp+/wATIi0Tabrj6ng/wZ37yR4k7ezzzta9Rb2+xODlg9/KT5OCAJQdo1OjJMz3mxwaKTpWS9M6MBmfAE2BRYsbEQIKDHSxSm9GZMhU339QWmYkD6abUh7klJRQgRokn6nVmAc8fNVOjDkqNL2hBq5HroQBOZNGydPfMolhhXorBSNlzdOUCyrLYKGg4UIuSzfNkWTGPO4W+tyNg7LAk54i4hSoJ1MGJLKAHft6eeXBrlmlwuvKyuIsIE3EtzwKjtojgwM/hTaFxJ9BTxefg8VwpuEUvBGdEzOaKgJg9ueKsjF+tgUAYk5LSxy36lqvu+/8uCCr/Ay2blIUbunR1q+g3nDe2gbgA54Qv5x67zPVnWv7qN17gqHXrsBbNaFJow0iT2qvKWbNOrd0+lxjJQctobikPwe/56ks3OPnMb/HQ4w/z9ReeZ89AXz2kvfE6Jy2kP/S+0VYqqxLA5lsOz/UHUe7c+3eWPtav3XhmOUlV6bp2OQYlnmUQVsdXi7+rMValL1d6dHAnMjU0ZywnosSybvWWMEfQckqIgZRGdOh9bM4Y6K3j+DPKu2vVKGK2wXHXx7voKbnU1pbLpbg/6sD140WZ4S7YrhQsPK+DoiMwrmJEfLH24vSzoApCE1kZX0+k6l4QnTo+65d339X9+gcjXGgqzk0nbEmmtUzGPUQ6nHjL08iEIZRsAHkC25W7v82zXzNYJ/B5d34aOD+tnAk5wDTsIFXkazeP+d1vHbE/V44WiW8eb5M1lutqYgj8lT/1MT76wYe5cG57jCwH08nKnBuWtNKJZRxkvN4Y7kpvNlDXLw+V84cfvO9cBinx4JTcVUEAj2HvlbrLkbdhoMdNXkJc2J64V5OUOC5ZG+sBYgzWrlJz78+5VvxR+rtsfhOXj1UU+qx7QQjjOKyzisEoZ/RaNOYG/+7x8yx/XI0BW9+HxqDyfpV3PaDK4vEwdaidgMFAJGBRIEOoIlYpapFW3SQ6qTwexJ3DBaRyDb6BmFOdZymMfebc+haA5LmQNGQ68XimQEkYbEqNklqjC4FpDsyDUhEIMdAFYUvL8hYDU3P3rRjM41OCkMmICpr9ez+hVIuQjlNbdycLHt1LVMfPs9AdFlVE5vuk430+9vAO33rVIxYPTmZsT6d03QIQulZp8EDwRZeZRmX/aMbW1hbaJmxitIuFB5BXNdJUdCLkg1c4zNs88uCT1NPLHB8d8YHv/Tgnt6/x+d/+PZrzD3keJPXkhTkYwSKdJQ9Kh5KKxRPxTjy4iizCXJU6eg6lqk/Wa2AlsHfeA0mMStzq5PQJbnVcqFsTg5V4KVtauII6YEvRyRQmwYXFhSkTKwyCCbcK2thF0TDxRLvReqjkG4yIkUx92vT5tPp5IEIudOcGTGMhzVJvNwIzcrFwOWU/ah7blMFyoPVHxUTdzdQcRGpQ6uAxehUu+ORipUMjTbCBBMSCscBdrfZ6USoIMbrlKkcHc0FLMGcPYHF3RMw364Tv4KrKwkr+L6BPiLxFQEKgrY22vX+L2LuhbNzSNqvxlsfuLIvf4302bFZWNlA1Tn77d+H1W1hUrufEaI9FJVDXU5q69nnCeCs8q3ohZVci9Q9i5ikIYqiQ+REHByd848Zt/un1OVd/5xmmYrRqVJrY290h/+jeqO51LWVf6+lf30R33eey+Z24R6xx+jqzkt/OBfUYo+e0goEhbFyvyDKp72p/FSs9oN0JOj/CVDm3vY1tbQ0ASUQIkymhrkvC0Jpps0XKiW8+85URqFpKhptkmXsbk3fB+mHFxiElvkXGmnbog+e7XAiRysvW6ykM30N6LxmXAJbHJSwBVMQGljwYASr6OpfgZPxe9MRGvrSLe1EMw+fkTH0S12yBLRsBQXwOdvMF8dYtFoc3uXDS8V//6acIIrSzOa8ezPjVr91mv8380rFSlbhdd6NbumZNY2ASAsnykLh2mCfmyu8YKYDK96EY4HsvnedjVy5yOO+4fTTnZ29kDlsHfUeth2M8fGmbyxf20DO9JkoerbT8Xt6GkSBPAV82vgwBUlquhtKfM5wmzAqftyB0eQmEIw5Yj9pxzM9wGeNfemw3fiv6OgYAU9bHJdHDErmvrAR2b/vCcN/h6cYrlfdZUgpAO7uuM9/kvu5xl47x2LgRw7Li917fGjfd6dux9r/rAVVlUEVDY0VEiKYuTCqE2GvcorO4ZSUTiIgL/Zgzghh0IaFWucXLlBp3Iaww5mrUCTpxjU2MAUnOuNeaJyOri1uhIAQynTrLH+J+u2KZQ+v8PDLRAnWIpOyMMJ5MVhGCu8OZW9U8/qZ/u5xcYD6/TXt8hO6/yuGsJk4bHnrgEg/ubPOjH97hH/7aS5gIdV2Ruw5NiXoyoSNx0s7Y2ZlSSc08zQgRVDqn6c4dZoFzO1NEAlgmWOL2qy8xvfo416+/ijZHmAYOD/eZxgUXJ50H9wQBdbAgKHPrMILThqqQomLqrIqdFatMYdTr8wlI0VIpHhdUqfsOa3E/MQlkS0wJJANTCOqumVGcUj2XBSaTPZu3GJMSF9RbrwTIooM7aDZF3RjpVq/gZuO25JgiKnPtQUhxd0PokrEVBMSTNJd4UXdDVKHL7jrRKUgwclK2Q0Vr3pZQrHambr1qxWhScOtRcZWsopGzMwxqMGopMUuiRcMsSKVUYqhGJ1sprIZaXE6jCTPLRI0eNogRo6cKiCJ0ZCoikqENnpS1Eg/+DVFQLQyHgGihZI0OvrYiPqb1u0Ag2lTerPS7qRpbr2xD5W8JFSy30bOrWDpJmCp6a59PXJzwf5ld5b+c32YGZNyK/FVb8NgHP8SjT7xntEmHO97AMHI2rHe3QZwdS5U4rZl/9Pt55Xde4JjAN0PmBr4WiMBO3fD4dMpOjEsstSKQ8rbI3fdSzdsDzjZohTd8vqdHMjiZz3jl+rUi2Cp7O3u8/8n3jSyHp8uqtnYVpa/fP8Y4jFkvWEoVCdGTz8empp5OiCk66+d669eEwjfyoHLnw++I0ltiAsK5WkbE30NvAnDS5bJfCCfJuDD1l+uwE/amxvYEjmaxECDIYIHqrZGCg6coy36TDX1/qk8HAXX57+psWJJZiAj1pvlrcHxywv7zLzH78leZTgJ/+Me+i3pak45OuPFq5NoLt7kmRnXi7LAr7SvP4GCw5FWSHqz1LbORNc5/y6aoZiZbgQ/9jz5C3NmCIPyPD1rSPJHnHTeuH1LtTUl751gUgigLNsQLSemzvXo0JWU5Lr3L3xh8jjuwH0m/ZpRwufxZ6Wtbgsf+BMPHsFcY9+cNiXBHQK43Mi13inVlycrNVkfKRgoWG7sAriKrZX+vleXiOxwV756VOdUfGUI0R8v0OgI6cz01OX3+qedbs4r1aPOMdeV+ug+/6wEVABaJ2YX62Ds7iec6qoLTTZsFKnFNfkZoTGglUSkkDFOIwTNNByqQ7H6+GpgIpNAxkYp5eema4GbmShJmqbhhSVkEasyU5ATodChRI1EzORg1vjgc5UQTIqJuyUCMJvpisjBBNZJDJppbVuaqGB0vvvw83au32dqfQwzs33qNV89fZv+DH+Wrn3+O6aPfxw5CHSIdiUU7p6orpiVXV7CaGANVJ6hEKowuJ0Jo2NvaIncLdra2PRltjEz3LnLl4ce4dG6bycVHWWhgMTtkdnQb3X0KE8/p5bKTk0jU4jE5pjjTnwoTCyTJxRfZE+smyyQNbnExJZsQQ8QyaCw+yuZa7lT8VGoTqiIWpgKhrLjARXw8Y58DSihsgIES0lG05zYIJlmMWqMvdtGADBbcBQa3eDXisUitZCpxh7fa3H20InjC5+ga5ErcFTAOK41r0GIdndZcpYC7iIoSgsdhRaHMD9fJaPEzj6XNGnC/+2Iy9XmhnhfKBDOloljFyprTGVT0+aUAPLg4m280CXdJxMCawLYImAxsiibGJAYm5tuNiDMd1s5a4MAQZfvdCqj68jYJ8/dU2fhQ0e7e+cTTx+8ECGS04V5sE+fec5H3a8XV5w45EOhEWIgRc0eMFTHGgQo6VhMkdZBHCWCHpvhzTZuKqoq02rpmurjKSCVU3/0hqsevolvbfAm3hFamTKqG//DH/xRy7gK6tc1ZuuVx+XZoJO9W3vSUGPXb3fGGFMVcZrY4Gc5tJ1PPxyObe2vcPxsFboPzu7vsTqfL38vUHKZcLDmoRFxBGQLUDe9/z9OeIHgscJrxwkvPMZsfb27Eu7wMjypL0HOmsqRnMZM+n84SPeRe4O7HopeQy+XLPFbLpLCy+mf9zsvPsn6kb5b/NrS5SLljYbd3d2sPjzi4fUCXDLPM9W/cZGunQsjMjhLgoCHSuQdOf4+iMEV6kGhsRWOnKc9mLi8czRNioUcuS088M3Ly8IWqjp7TM2ZC7bLG1m5kujfh5sGM7tYJ+sBF6p3tUrffWwTq2HdncZvtodHgGjcCEeMBZZSLawTD5NT5q0C3j0bL1icU7p/XSKostDjU96/gAPLW1C9FASzi3i8xyMq9+r89KcQAlEdzxMaPiQ3seSv3WXmWURtsWf9ySi6BzcqutgnV9E2Rca228s/KjnbWgri+H97569ta3vWAyhAndpCKpE53Hqy40qGQKlQUtVwEbCNbJAQXFhuULJ5UNqWOKoKYZ5ruTJkEqGRCK2BUxPISKMnzC1GhmOcOUsCEKigdhZozJLeIqQ4bXxCPZZnihARdCSbOASw4s04UQyXT5YxIhSUjlNxBcnTI8fUX2U8zBOXq4++lXRzx0ksv0O3v84HHt1AJzHUGGIdtS2YGlTCJEybZWKQ5UtfMuyOqmTJbzNm6sEMW46RNhO1A0o5Fl9m69Ahh0tDlltnhIfO0QKVi98GHafYuMgmVz2I1kOBmYVxonwCt+sK1wKnAA56Yt5Vi0ZOMlkDCaO6rHApw6JkZa6qS3TuhIQyvvRZXghScaIEAYhmx6HmYsjl1vLn7QSgARYuLYA5QS4Hh2QU/K+PSa5NKXmiSul+42wkTarGQeSiEQlChJYmf+MYo0TeiCFgq+X1FWSBMgpFEaERIxcJWletiMBqcJp4IUmgtuuwuqOKPRdRIMmNeKHK3iaj4PaSQR0gUtivfNjLOGNnIiEVJjBwEKZufqVIXq54UIBmi12XAVnE9SfgYLTDadP+Yde5/efvA4J2AzGlwJBs/br5u0wHb+E1G/9pZZxtYUl4RRfdb6tsLtiVwbO5GHUxc2BOBsm6JiYMpzQNl8CrTk2/tVnKLMPxnCBnE59elpz/M7idbd18zpzuOUZg+9DCTyXQQNnsBaCP8PKMb70f5dqkKg3TSKgABAABJREFU+udcH+rTIrKfOVgARwLeWVTIp0BbkYOmkwk0k7u2a70XLpy7MFTYC8uqyivXX9pcyRmduPK8366O/naUdTm1FAOSCSfdMg/SjTYM71E7M2TmaTTGwrCDWq9BxJVgl5oCq2RthNZuvLFbVyTXDefIht+LoJ+6BYezBTduK9bNOUovs7vdEKtQ4i6NZzr42Ifew+NXLhGBl5+/wZefu8Enf+CDbn1yHR51FajiIN+7N0+Jix6AglDY7CKWM7e/+jxb5/dc1jjoIIKZ0qSOaImj33qRZ19+jfP/wR/mwQ89dWoNNKHEGY3WGZbWv+H9op+ftvJSjtfX8fnjd0ukuC3KEjwZhmnJr0WRKQy6PLpw9Pc0n6AwkH6UmHFhjF3KlasYhdWjq8eVJUOhbDq7P+a39p+W+HJ0yurVsnZ9afrQZ+s4btPclWFPWTbwTIw1+qzrD/42lnc9oMoh0IRAEI9FMYzt4IQCrQaSGDknn9wmdCI0wTnVnKQAIhVYRwJycv9eKZaW1jI5L0penpasigQpcTqCWlcAUyq5o9zlDasKS5wL95W4W2BnisToMQVEz02FC+QdqcRk+etdG4RQBNsIASXEyPlLD9EoBFPyfI5IzYXzF5hceoRXbt8miaFBWeRMMLew5W5OnSZML06YWcskVtQxkDWhbUcVahBjlhLTZkqDMZ8ntuqKKIHJdJeT2y8wmyn11gXOPXDJJ3GsqGJ06laJdJppgtAlJYSldS7H7HFRBgS3Hpm6e5GEjGhV7HnucpZwlzgN4uQeoliG6Ahl0P7ECk9+i1uF3HJSE6ywP5rRSscETyyae1e7ogCr1F0vOvMYpVyW1gAoCQmR2pz8IkXXooVCPBFQxJRAYFFASIXSqSISqQrJySJ7xu9YtGEe3EqZC04fOxUKUURhJDSjLT7dFUanShXdLzFqWJrfxYh43JovVp482QxqMbrSJxXOcDkp+bViiRGUQlcaAcwti12RkEouX6qS420WHRAn883dqdp9c7qPxDp/MOV+LcqbwNG99N0m6fiNltEeZ2osvvE1/tMmsPvAFouDlsuV8HrrMZ1Bli4qY7Hh+vUXmR3ts3PuAuPcb0FcD7u1NR3onBkCma2AME+RYPWUcOlKyfGGAy4BDfWGxp4l8W3oj3s5527nbTh9I6B7q2VFgli9wx3vJcszbBDNluOzPlHWIfeYWW0jytpw91Uh83Rnt12HmZFVC8hbq+/dtjbcqWygv/bfl8xwWxVUuq5o760l4KKzrbx7Q6wUveuaDNaKs8dsWff417E71Z2Woo3LjMDl9z/FfhZ+7/MvcbJouY5wdVupqkhTXBlvJOEH3/MoF/e2UIOD20fcfv2Q7SaUnEqlT8K4PW59kt6qPeo3J9ERRI3ZizdoMOL2hHb/hKYCQiCSoUu8eLjgv3ltxp9NcHlwKbMCIPp+90ZkE7KGAfCcemeswC07/XYMYzImfRj0G84GeL7xHzIeg53NSGV99JgkGwGA06PWN3VwASw/zLPHq9/11TIYN2/l7TQHH2qrxwVbxjZZDz4LUQdLF8qV/WTc6IKGZUBN47VNBgsry9XodOzl+rJhtlLX8pH6VW/penjS/vs8VG++5EyblRgiVXYTQNJACBUEoy5uYgBEoRGKQJiZSsQQgiz8xTUFiWTSIAiIBc/7gHjiWTxBmyDEoCQCEoWt7LFBMZRw0aBUIWLJV4wkiYxbOObJqEJFkjwwzokJPSFQFtf2d+JuVpUEJDgjYKKl7RJ7DzzCE+//ENOd80jVsLj9Cg80xuT4PLHyzE1TiSRtMc3UsUYleUwTgTpWtGnOVCLHlXlSvBDQlGl2G7o2UxOIoaZbLOjaGSfHc849/Bgy2WZ2tM90OiXSYZY8/1NOLogptOK5mLKBkZG8dBHDjFqcNj5IdsLw6IulSSAE33CIhfI8BFQUi5E4EiPA80JNi8qjFiNLSfwbnYExBmGb4ItDdAGvK7FuEZyQAWNqPi+SGLFQnovVA5teZ4mQXavY9dMJBxLJlMrEc23hGb6rqE5yokZliligloBqiX3q6QwNCNlj3sxzYHWiTAfXVW9kVXs7myA0welZvQ1gMRALi18tngMkAFMxZhRht6x/Kp6M2LV0vaZJmJsD+Lb4gy1E2SrPexyMYIa6pIyE6KxHYiXZot1ftdC7rWwUZt/k9Rt+3jQSq1pLf4NevL3PjdwRH57ya7/+PF9vjWMyHcbcpHemXVau8Mq1a+zfeo3v/UNXCyUwS61pET6sV70PyTWNYLl8LzGhfWBIqdtw95PBNafU2wsxa/vpnSW/dfC0oUPe6Gx9M6DKhj+cgSvEY1UHQXr96LL0pDGjmlmKgKuQ6uxnu9sTjASfJdYdHRoLcL6W5pz56je/wry4IqachuP/TgEpGGJrh7LhYxBhq45MkdWXskzufo6vCO7QbwRgS2KK/uJN3bwRosvpY2Ojuaz9sDLbBvAAVVOTJg1fNeOYQJ4Je9mYRuXJCaCZ/Sw0tbPLosZJ1/HB91+hqfzh+nvGfhnoX3AZQZreutOvQuax8XVTYiwVcla6pKjCyUlHq3C7VV7vMgvt35Hl2zGsj+Whit6HuuTY6heM5Tt0mkdu2TQr03yJeAYILO4J018S8Jj4kgHH3fIpHiEjNKFD36+SlfT4RQFMCjEGgwJjGNNhwRxBj97He+Ux1q1yy0NWBqivaoD5d7SEFigmy/moQxct29jqEuDKciBGDILr5ezFfWVejh78ZHGqkretvOsBlZjHzGAdiywEjR7MHxJBcAuTeILVbO44FUiEEJipYhKZ546JVUiJp7EYsGIBSJpKnii3GgSiU2bjjC2IELMDiJ4xRwh0hlOdR0BzcTHLTCwiRJJmj8GpMyFEWqRQa1ohKQju2qYdfb7yiJt5j2aHVMyY7d90v2bp2I7wse96kvdenvMbNxJHx/ts1VP2W3dprAzO7Z6nTYnd7ZqTtqXLBnVFPjpgEmvEMlX05MWLroWgzE6OmWCcHO3TyRTNhu6/zsIyiwM4uHmTS5d2PQ9RAMuKBLcStuZAMWKIQqhA1HM4mVQOKixQi+dryLHELmnAgtInlOzErUeixoxMg7PpVaKIVSwkuzufOSmJivsrB1yLY2WHyoX0NYoRSvJSLZaaqgCKBqGw5ZOKRj2p0GkoOa+KYChgRDSXRIcIIQmtWEkKTEFrJR+ZebB+Lkt8xAkiCJClzK1ihaxxpqVkHiMVxbDikic4BXuTQYKwdA5xGlzBaMzB/0KUaG69dS518WBdA8lKC9QiqMA8OxFBhW9SSTMZYdH3S/CE1c7OCBaFUAgsUjK69tv95v8BlLcCgtbLt1HYXAFT1gsVhky2ODHhS88e8OnukJ/TW4Xu3N+ZhAwgp9cA5tyRUutAYNEiuRvq1qrGtmp6XXDuY0tzdrCl6vmtKPv7SGJQMqFdOE1/MLrarVWnNJebyh3PWYOZY1S2DryGDruXeu9cNoLaUWv6cuHCw2xtnR/dy1bvb8Jiccyt2y+tgGU/vRDhjGI1l3cY/Ts2hYyeqU9rsX5Mxn/H7WI5h8a/ptQ5nfsZ5QxMu1rsXk76zi6D1/MYHI3KquBqq8BpFfOcCspfCsdvW3NPt+uMl21FzC1NuHr5Aj/wwx/hC8/c4Le/9io2XwDGZ8WllR/6wJP88e99EsE9GT73zev8+I98kO2G8r73lpFVynQDjo/nbFUCMl3OHTNyySN57twW89snzGczFvPkzMqmHJ8kFp2x6JKnbiiS03jdW39qQaiDsFd7rDD4Xj5+6jUYsblfCuIZE3uvA5UohWgD2I7BY6YVDrrMVu2WvdtzXyunAc4P1jwbdJZqMM/CTJ21eLD2jKbG8smWQ7pOctEDqqWytTAP9mapEdTya0tKlx78wkB4swLKbBnbtcg4Jf6oH7P2MbWMrl0OTg+q1JxRODMaN1uCQOiB6PiJPDm1VPdvc33XAyo0M1Ulm2JEEp4lvE0JCZ6ILTmdG50FiB1ZhZ0YySrEkAqJgQumiUTMEbPIVAJkRU09ua4ZJ2ZsG5jUmApVAz3kmasSewBRhH2LbiVLRLc04fFdKk6ORw5+jgSa6LFBPWW7ak+O4G5aXciIZXZ2znH1ye9me2vC1vnLWC20R7f4rW9d58u//SXe88n/CYRIO5vTHu8z37+Fbu1x7qIQqkjXJrfWxS0WsyMW3YIoNW2XaKqao/1Ddnd2sCZSxcDxwS3OnT9f6Nvdpa0KDbN2xsHtm1y4+ITToxtUMXgSWITtylhoprZIDi6YZYFKApUJSXVgqErmvyOCFJ/qhkiSjIjbpWIITHHTf8SI4vQN2xq9f1CCKagz6U1DiWMKzsQoOZBCoqF2MgWhkFSE5dIboFI38Tfm+aI0J0SdYt/USMGoc0USB2wtGRWnyK9EqHD2wZbsBO8ZoikZiCFg1vndxOneFXfzTEUJ7U6jbrVSwwFfccPSsmi4JcwKaYbS4ZhJyhyzoEj2uAYrsVRa+QI3NyeosAwn2RMxS3FBWIjRJWFCpPWsaO6qoAX9ibKwjCajKZtIEqVL98/M/p1T7ixp35PgeJ/LqTYMGkw/0oOpypQ//z3fxX/10vN89VevcXRi6LQerEvy/yfvz4Nsy67zPvC39j7n3Hvz5pxvrvdqRFWhCjMIiigIImgQIk1RIylblhUy7WC73TSlYIjuCJoRDk+yLYWiw7KjTUVLarXc7Q4Fw7StwaIsEqAIjiCIGShUoeaqN085Z97hnL336j/WPnfIzFcDiSIB9K6ol/eee4Z99ri+NXwLKAFiw/hgh0KgrhMHm1uUXrnz6qv80Ne/xnf3BUmJO6OGX6TH6F//E6jzqAidXg9VoayUVFTUQ7MEqyopRMpSeOiJi5ztOh4/vMEf/+3fZG084g5dfuOPfC9aFjOq199DQ+TxOX8Mjt+03dCPPGgOqJxUjkKkE06c4QQ+aXw4X1GUvSN1m6+Wiw2tw83kHtklswkR9SfVTGfeqz0yK7jYByduQr0+U+kT3nUqKJocnDnsNM3U+cjbHQt4f6PyB6hleLvKDCix/pKZb+05c8NiRtDNV8xh3Ndpw3stNveaM0eA8MRd8C01u93k9Fqfv/ix9/Dshasc3tkxsCOJUR2oQ2Sl9PQ7RX4HSwicYiJFsnsoxGSWpdSORgVNyhefvsL7HzvPudPLc8ogTUpslDhoGOyMefm1fZrkGOEYiZJwJDyHIZl1CLFcoZO6z4AkmWkQgTpmYR9yrPAJa8SRciJg1hkgNWOtmYVZSe2dC2lBpaWamLcU6sSlswUdTnKKlmTgbKHEPI7aZepEEH5yUZ1a/VqSd82D0n6bR6CqR61Z7feZwdzWX6AqBF96Wm6V6f3sm4NpTq/2ciVbvc2zKapyGFvPhxk7o05bc+axuccym/PbVL7jAZUSCTneyXmLExlrolCz8iAOp2nCaiXZlarO8SSSPGU+LqKZ6tznOCZj5fNJSKkhiaecBANGFIcEIUiiEqPZTmo5oEQtvqaIfoL6vZDZ6mwwOWfC/jhFelLQYO5ghUqO0RGCcxSYayDJ0QRzvfJll2JxHdIQ3dsjJs/dpub2QLiojm63Y/ffi9zdvM3qhic0gZWqQxToFYWZyzXRjA4Z1YnFhR5FWbG8skoshJgskDzhGDQNd7fvcnv7NlQ9qv4K3U7J4uoGqXTgJIvf1sKRCAJJHY1LM7miNPs7m9UlqfnUBmfZ072aW6CqacTFOzooMZMjYEYfOpYtCtVMGuGhjELE49RikjQZcI05D1TKlppGLe6IhPlwq9KSCvmcIyS2uTGCxQUYvb6QROhoQj0EbcA5KrWEu6hSAA1mJfIS0IwOvTPSiYZoQlJmx/PJku+a46Mn5ED/YdIp0BOLNSOBF0t4XFsz4tSUBpkP0ABPpu33bcyaWHp7DbaQt9ZTVSOWCMHAW4GnSZbgs1GlIdHJTIQpueylJYQMLpvsgCkpg//vpPIW0dEfvCg4v5m8hUvwCTb2h9xeXOeJ//g/5gOpoN79Bn/uieeAaLGNMZKiUAVP7+7TFAeRl373Np/86osM+8u8+vTzfFAidxYUQuLmMPEN3+Xqp36Fw8EhH/n4x9g4s5EVB0Lz0FlGrw2oEsStTdLlV4ndklNPPcJTy47/i7/FwoeXGV/uMHxllLdcXr9hNQsR4uZPnJdI804dj7ivzd6mhSvzRZzDu5blbu6Gr1Mp24NSMte3WeNQ+5xZZ5oYapp6dDKgIrObNiNSCkdiboTR4IBnn//aTNxSG7PG7D/5Y5p8mzmd1eU1HnvkMVNk3aux8+H2uuFoyKtXXjEwJULdjN+gTf7/qcwL4rPfJp/nsNX8oJyNlTqpHIfvJwC2/HUKmt58fY89ZPZwvqGg+MEB5fXrvCse8N9+//0TYfbrz29y9e4Bv/Taba7e2eUdl05jabUSMSTqxiwwKZlCMKacWy1XIakyHNeENJ0npuQRUnJsDiO7VwYcDAIv3N1nmDyD5DlUoCjwRUEtsLzcp9OpEJjEbE2F8kzgMkUrDJPJC7MKh1bgb4GxQmY7PYqI59vcPk9/nwc82X4fZ6eoeY5odusVsaTQm+N0QlfoBADtNzo/HmYBGfMWsqlCrZ3M09Vh9r+5l5krgneOpYKJK6M1XwahCfZru2lZwLmFDqfXe3S7BVK2uTlngZfmfm0JjPJaN47cvjWgCYmVrrAwdtmqlftQp0Qao6g0aabW7TnHe+abVt52QPU3/+bf5Gd/9mf5qZ/6Kf67/+6/A2A0GvEf/Uf/ET//8z/PeDzmB3/wB/k7f+fvcPbs2cl1ly9f5id+4if41V/9VRYXF/mxH/sx/sbf+BsUxVurcsAmZOkdSSOeAofRmqtoJgcQnE9EMUa0EsWJt33YJaIUFMkCFMWbe5xGo4R1ydFgCVEFR4Vp5MdKZhKskWSxKQ5BY6BJRjzgaei6aEI9jgYjwcg5bi0ZXgTvPMYLmAVWJOeiEpxGxrTajISEQOVKqsLTiWNGqoRa2b9zhdArqUoTAjQJ3hfUBG5ffpFzpx8gNg17+3t0F/sQIqPRkO2DHW7euMaZlbOUFx+k7C4QKyEQWQCGTaC/cZqr117hta99mXJxkbXzF9Giw8ryEjsHd2nKHnUYU/rS2BCz1kWSAQzDQQY8CycGHJP9jnOEZEKIw6OSqFPCi2cMkCKNGjiISAZhKSvWFKMPd2hKRn+vBuhUJVtnYjbdmDiTJFHkBMsqtqqlHJQqhVKmTOAQE40YEA8pWWJnjFgkZtfCwnmaZO6kpXiCU8AhamTuEVCNFGLxWV5ddnmyRvJi7IQpOXzMjH6SGAvGaGR2TYu1U28xduIIFnUHSTjQSEetziMShQjRmfZPoyXxbaIBUAmawa75cHtpXRttYRurWbY0m+mTmsts0EhyQid4GhHw0EkeiAwzq+HvJ4TqD3sNObG8iff5/YCot4jX5ou+0ZUzQlYG+kLr0668sxT2C+F/S1CEAknwzrNLfPeHThsNsyRa94rt60Nefv4mj53e4PTt2/x4gitnCwZRGA8TV7RhoUiU5zwf3HQ8crjHM7v7rG7d5LG10hRHSVkaBVwwBU7Y3yHsbZL24fP/9JcY9Bf4UbnJahqx/cwBB0sbc774rch3zOAhgi8WKcolTBCZ1Qe3oqoSw5jQbIHGmR33KCCd700F+t1l1tbuY5oytRWt5k+f1T4D7B1ssr+/daR/s0Cjw8kLCcre7nX2dm/MvdNE4MiPVDKDQRsZn99NE4xG4YigclSUmn0jJmOnvbcl572HAH+PAR5iw87e1gTIvZ4ufLZHThq1R4XF30/5w19HZpBq7ic4LqbmrSQzpx3R+R8Z5G0/HbUMzD7rpFZrz7EQ8pP7R2fOO/oKx/qrHT4xMTg4YPDyVfyVKxQeyo5Dc2x2jFl0j4lUBwgNUtu8+7UvX+XUao9er0en30OjUteR7WHNwoLlOrt7YxvqIfV4bGyh7aNTIpL48n7D//7iISEpUTtoMqClIlA7lMR7HzrNf/YXnqJaXkSKCWYCyTGaMm3FCSGDM/c6R5uNarYxj7ffPFidrjWTXw19zY2D9oyZ5WdCMtFacKZzfnp+S6SRmP19Os/nYN/szScdKPN/8/tPcmmJTtbbnIlsHoxla1anEi6sespCcIW51qkzy+NgFHjpmuXd3FisOL3So9epKCqHdJzlrWuBrSqaov2dvFBCk7kdSnYZVHX0Sj9pD51pK1WoQmKviYSkVIUwbHS+cd+G8rYCqs997nP83b/7d3nve987d/yv/bW/xi/+4i/yC7/wC6ysrPBX/spf4Ud+5Ef4rd/6LcC0nz/8wz/MuXPn+O3f/m1u3LjBv/Pv/DuUZcl/89/8N2+pDqpC15srlBOlTsqiN//7GqWDMHI22DRr7Z03NzoTyI1ZTvGIi/hg7ldRYJws/miBgkIKxqLUyTawyplWNCWh0YgXjxPLX2Ual9bFwpmLXOuuJVAlo7aOkozYIGtfbF4bo5vzLlsQjO5dvdGuFx7e8eA5PvSA8MK1bRb6p1hYucD5jXWawU10/xR93+CLCvEFRRjT7G2i9YBzp1cpvdCMI8krXj0sL/H85mV+59f+GZ3uX+HJD3yIWpPRJieIYUwKi4y377D90pfQqovubVEtLBC6HW6//HX88jne9a7v5vSpszbxXcJjSXEjgiSL4ynEgKZLQsLjXMpA1ARypw4lmlZYs1XJEjcQ1Nzr8ELQRBRz1YNksWpJSFHtN2TCjKcOyhQJXpCogCcKeILFy8V2YVGKBtO4Es2dD7POVYVHk1J5IahZy1J0IJ5OJrXIXY1qpFRnLqIUNgGT4ByMCVTZsmacRK2VyCj3tWiXuRznpI5GIg6X5WIl5HivIObqV+Hxmgh5fI1TxKvHwptaF1ShzlY5IxqwSMImBQrxhJSzsDtF1JPEQF9XFRXLmaXJKOYLTUhSogtIdJSqljT492ig+lZYQ978Anxc6D5+9MgPs7c+Kii91fKGQOpoafWHeZtUeHCpT0qBz46GDEf7HL70KnVM9Do3+fKZq5SFp/BCWdrfp79+yD/7xZv83/5Pj7P17G/x0V7B+h9/nCujMY9eFs4d7uGKffShmqd+a40b3SU+21/micvP8ZG9lxA166iPkWtJCCnSbN8l3r1ORNjZusPnfMG/f9Dwb2xu0nhP8689BNn9GdWpQHhCW4rzONeZkW6m6mBpBROJqLhsUWFOQJ3y1k1hUQubxDmcL6e/zfTrPLCbXAEKTgpUjGCmrcfsndu+bN9vKlPL9BmzwKe96gQXRJXjx2eF77mimOA541vUCjWzcvyJo2xORpM5oH6v0fym4t9mq/r70FB8K6wjTYRRbaLuRI4+Onaw+NjzGwVlYb+3rk4pKaMRjOvZC+av16M3m7RZO7Z07hswARGzRfJJc8DgOK6aKylEtq7d5LP/5Dd5+e6BSU1i8lJ+E8pMxtAEx//4T36bxQVP0zi+dH1MdCU/9IHzLBQFVbmAektrMhomlpYqnCQ++6ufZ3U4YLzkie++hOaUDSlGCidc7Dj+rfsXEXHEKLy6M+JXNy1muisN3gnnVyvuP98Fr6ScH9NlUo8meSimCXzHI6VNp+bzvng0rlDnEe18O06IM2bav6XVm6xBcx016ZNp183+dqQzZrq/vc/cOnJ0LWLat9NemRkZMv17XNmhM1cwCacaR+UwmmVse+RwXuh1PasrJeKEw/2GW1sNSYWVpZJzZ/p0+xW+8kY2JvZ/u8bEmLh69ZC6sXCaNs8oGBA/ODTOgYMm4kVZqhyVk4kMJLkBTSFs33ulYxTi1EL/NpW3DVAdHBzwl/7SX+Lv//2/z3/1X/1Xk+O7u7v8g3/wD/hH/+gf8fGPfxyAf/gP/yFPPPEEv/M7v8OHP/xhfvmXf5lnnnmGT33qU5w9e5b3v//9/PW//tf5mZ/5Gf7z//w/p6qqN10PLx6SOeAVmOA+CmNQT3JQODMja1RIlkQVUSQ6cz9TR60R5yM+Wx/qBLS+4eIZ+UgZA0F8zkPkiDEY+MH8WEeppnAmwEYx64SfAVERY0qTBkYuGoDLhgYRRTUiooyC0BVLQluI8QumrOVtBpuk4W3OP/AIL9y6ST3ch7hLHFbZ4ua578GLxNEtW5SbRNi6SZVG3H75qyx1lcXlVfq9Hpr9W6sUWD2zwUujXa68/DwPP/k+kkYcsJsSzXhMt19x6dKj3No4w+7WXbZe+zpNCPiiixPl0n0fYG1pmUiDx+EyFXkSyVaaZCZ8ZyQImnPShCzcx6wmCpKAhKpQZFczr9m6Q9awJ4vdadRo0qOYhdJl6vRSLGYoieVO0pSIYnVKviFE89iuREjSghvLfZHUIJRmAC7RYqJCzJqYYEBDvfWl5TSDgoiIo0zmVpicZDKM3PeiFOoMrCCIRqI0OApQQd0Y50qzfIljTMSTSE4tb4WakS2QkCjUmMtgkbUxDYmQzOwuXlAN1gYx4RQj7UiO4Aw0FZnsI6bsXummhB3qZKI1bcSI7BVbzFwmto8quJQYE+g5Tw/hUAJvtXyrrCFvurxVge+bubL/Hu5lwyMzL6nwyPlThNeu82VVQoy8+sv/jLtXXwaUl4l80tWIMwHJ54SxSYWOCv/POwf8qb2alxY6PPPqFneGYw63hVN7B1RxSNhWPn3nLpvdATcS7OuQw9sNqrBYdoiibPW6fDAGXBjSaWoUs9A3EniGwD/2gX0CD6fIA0y1yrNvNCuctKJFC0zI2tbpy8uMxJjd9maofI/GtxwXayx/4PG2nxG5Zv1s8rwxyng3+T69fKqRncVQMvP7bNVfR45j8spYao0iJ+Cdv+cMQGvbrgWZWfDw3k/i5iZi2lyzHHn53OAOR5qJTpkt9wJSR/ULJ93391K+VdaR/ToRfbBk9kferZ2LAKUXLp4tmNw6g9oQLKeftkxo+WKF4x5mcgTMyvTzUXw0Cfo/Ft81efwJ46wFB9PPN194hWf/1Rfpry3y0T/2PrMa5dAGiwvK4DAqa3d2uPn8y+hu4Oq+cnO/ZHXREUMkNoEwMhfWpg40TSDFCCR+4+Yhhzt7fOLMGZ4KkeRM6ZhCoEC52IUPrC1my4jy1WrM13Z2aIALZcFGp8M7JVJvHiIrC9A1hUjM75FE0RjRZPtfmmnrhLn5HW8LnW+wI00029YnXXbs9NlrVOZ+k7l/52fMbBzlCb04X0Fp+/XImjIPF6fvPVdne67mf5uk7NdGqrU5sDm/0I2oVwrv2Nlr2DkwxVfhhU7P4zsOV0zXo9mKxQgvvHLI4biZqReIMzDuJ2QblqKmdMZVIDNj8SAEduvAOPff6DC7jzJDDvM2lLcNUP3kT/4kP/zDP8wnPvGJuUXsC1/4Ak3T8IlPfGJy7J3vfCf3338/n/nMZ/jwhz/MZz7zGd7znvfMmd1/8Ad/kJ/4iZ/g61//Oh/4wAeOPW88HjMeT/kQ9/b2ABDN1ikVYrTcQyk5Y5gSizkqvIAk1DtiirjgGYrFChQu4TILXsLIC5IknBfLZZQgOm9uXyKWG0g8LkXqaG5+aMI7o+8UTMPvnaDqqWWME0eDs2eICbqFM+E8igV1q0JHlA4lI4xsIOZYncL8zQjA5z/7G/T0tyjXVmH7Gk0IxCay1O1Tp4ad7W1b2JJYkmAJ7N+6jBsfEA9usdDrI50OVVEi4mhiw/b11yg7FfuHhyTnLHYAI1coxDEa3Kasujz1I/8hRX+Z0e4W+7t3Obhzg4O9bR750Ceg6mYLiuVVEmcTMTnJlO9CqY4GC07SzNjjPOZfm7B2cEKBabKds3c2C5ZCztMkSRFnVigfjbZe0RydVKASIDpqTXR9QSqSWRGTmZ473hGTAVaVRHQOkiOJo/JKg7nXiTdSi8IZmAneWO1ELZg7ZrIJi/mChgZRT1BjHQzJ3AJJCZxSOBsrIpn9z5llqUMHkWSudxIpklCJp0nGppZUGRDpimOS78U5YzJUS/KHgmqklzyIxY0l50hJ6UqBeCMZKMUEIVXLT+UcdLRAMWDlVbOrpM0bS2wsmfK6sFVaE04sl1qhNo5/L8Q63yprSCvLHVn3v/nlmFD0Br+/8Q8nlFkxy8CUE899pdJ59WW+4fsmQKcIMaF1yOfGLHS0VhxTGlwsSj5RLfGBVw+4k+C/v7XHc/94C0XoqMPHQJGMi2nbmVXHC/xyWVF6KL3nLz58lrP1AXcjfE9M/LQr+XeLgkFR8Hcfej8vdXqkFAl94dHlBVZPnZoXFjmhf7KwEptDUhgzsfgcbQ3XYenM44hcZIpQhJOpylvhI7ueiGPcJjVGpwApB2in2LB76xtoGs9UTkgpklKciimzbl2S3vzQel0EMi2F96wvLR9x7TqiEccUQFNQBSKeXn+V29t36FZd+t2FOUA1jXqYgZ6q1E2N3gNM3ev5b2f5VllHXAGFJ2dvt98mLn0z/egEXr1e59Na6Tqzm2Hjq0XF+dOkLwSycsvSZ3jf5q+yPnIcnTVM7jXj75bvmYX5OSvpzLWzugJgPApUp5f52I98hEc+9Li5ZombvybPsa2XXuPp//EW0ii/cq3hizuJ4TjyDz71AlXH47yxgaakjEOi1+3gHVzeDhwOSj717A0u/0//R47fVYbDEaeGQzqn+vQWuhSdEk3K+4sO/+nKCqOgHCZ44NQS3ZVFXFJ2twP1Qjllr8uKxEmolEyJFmZj10TdBJ8et07NrhtHlQ2zedpmT7kH8pohV5hTZEwedeR+M4tguz4edYxuHyezE33a4fni6bmte3/r1je9bBq3FNWsr7O33B9Ennl5ysHXRrF2uh4pmaw1s4oAWzMjzbAxy9QJ7eqJrFWFEWWJyR6ddlDPKA0WyuxXFkwBn5Qc8gHRvZX98q2VtwVQ/fzP/zxf/OIX+dznPnfst5s3b1JVFaurq3PHz549y82bNyfnzC5g7e/tbyeVv/E3/gb/xX/xXxw7XnqxXFNOCWR2aKcGsvJkaBeoJInSG1Ap1DrMksJa0iONDYonZd/d0nkSkdQYsEja+rIHLI4y0WTBUzKF+lCb7C7nSdK6eKWJWTykSCGekRp7XRE1c2maRUej4ly2qgA+CMkFUmi4fecGz3/hNxlu3aHq9ugtLrOwvMzZjXVu7e+wePoBipUO6+cvIgm2b7zC9t2rHOzssrJ8mmZvm/29nUxGESAFNDZsb+3w0JPfx2Mf/j5AIFmdI5FYjwkxUXQCUkVi7LKytMLZC/exc/YCX/3Mp+h1KlCj2fYohZjWU71NW5fM+lOLmdVDsr6xSWBTxMKPzIXPJ5vEmsy64zE2wJiMDTFoJAWzuFiOq5ahxlmcFh4RYSFbJ51AIWaxLFUMFKF4cag6oiZKkTx+hAplnJMCu9QuNC4zQSYcFlflMOBYZ9kiip8k+nUa6eEZa5s81+KzRmIMRMlNafBBSU5ZwDMSc10dE0g4nNg5JZbDbKyRKmujg5qOWJK5J3bUGcDCgFIX43+PmcrW4wiaEG8BsAveSCyM2loJziiuHeBdYeQcKREkUqinJpo2EgOSRfKMs4AY3+Ia9q20hryt5fWE4mMoYfaHt1ZO0qtaVIPjwUKpB4d8WUsDzTgudAJ//r3r7J47h6gplFzydBXkIBCf3eaUJD7yvod5x1bgt7d3+G/HO7wcE6Oc32UiUmZBBRW6ZcGp06u8+7s+yvmLDxgY39/mzzzzedZ7JUmgT+Ihpxw6ZX1hkauLq4By9twilzb68xvtTBtNtbbTb6oB1XBctsmXiRPK7hLiq2m7vl6bz2zas8dnD7sWkISaqIEU67nzZsTYox3SirAzn4/39eQeJyLEk+qea6rMGCFmQ/Czdjv/rjlOqxWoDgYDtra2GQ0PJtaquecdQbLTc/L9Z4WnPzgcBXxrrSMrXjjVdTMgyADVrKBqZWYMtzRo+U/KYF+zhC1i8SpMErebkOmd0CmFTscxGjQMRoGigLIUxrUp0qZPm5XEdVKn+bGtkzrI3LlT0Ld4YQN99mWuPf0am6/eyaHJNu/tNUxB6Zxjb2efr90YUiTYPFCgYtQIn35mM4PDFi1K3jONjCHiUFfy4Pkz/Ok/+qQRLzlhd++Qpz/563QK4dTjD7JwegM0sn1lm/s7wqgJvPDqbS5cWuNgLyAxkVKiCKZwbQHVBHTQ5rzLPSEzCpP8xrMxS9MTZ1tutrSuaMcOH+tzOfpb64Z7BPe0/HvHPL2P3mCGJk9nf2+7Pc/7WdfjdkwmNS+bdj0IWRxVNZY9JxauULh2fTG5rVGZxHaJwFLHUXmhW+UkyVFBM7MXrbufsLtb86Wn7zI6ZkYyMOQEnCaKnI/UlNX2TJ/fTTAr1lLl6Zcuvwfsj5Ummiz1dpVvOqC6cuUKP/VTP8UnP/lJut3uN/v29yw/+7M/y0//9E9Pvu/t7XHp0iVQo+JWTdln3ROdgSQjfrAGVxFqxcgaxGipi+QQ34A4DlKgwNF15g6YYiCoo1EBTdRi/p54b9ajGMF5AkqRhJCEQmx0OZzRDKsasYEGRCPiCgocDQ0Z+1PjcerwmfoaTagWhDAGX2V3xYbdnW1W1s/zzo/8CV793KcYbu/gEe689iJ3L5sArM98jdFwSCMeHxvT+obAxqUP8v4/8x+ysbGBFAWFwv5gn8HwkDvXn+fGJ/8JZx79IMVyn7C/i+v2cIVDUqIZDdCFZaJXVlfO0lk/QxwdsLl1l+HuLkXVxTlP6TyikaBKo5aImCjZrU8mm25So5GPeTEIE+Y6R0EyVz6XiFFxzijSk7aZloSgEefaHA6CtJpSNfc9BKJ3FqmklmchpIijxIvNyqCWlNaJEVeUIjgsZitENUKQ5IguToIuBYg5Ea+YitCyneMonLl0esn07C6DlLwYiJgFtc1tJiQKMSsY3qw9ooXFm6nFzPnsHtmIgo+UUpgXao4tEey+GqfCWeENTJVOiM7ishJCKYW9r8uLUnLGJujIgNFi0ooIzhWWJiAqI0w54JKYQkCTkaiIPd/aLb/7W4jv+ZZbQ/4wy+9RCD0u8h+9n1ACj60tcPulV7jcXcR1qpxIEh4/l/jTf2ydztI60iugYyQjEuHmv7jDN/7bQx76/vtY/u6HePqfvszP3xzwoiso1voUe4dICHyvOvoqjFC+7gK3HSz0epw6d4kz5y+wtLwMCDo6oHEx555zU3QiGM2/85Okv0cbQ+b+6swLzkoNHAOuktvArphx95s5acq6Z+fOApxpt+SjOq12e8b0zBmBRo7WTI680lG0+BaKHP+qQIiR7f2DmZ/zCjEreKkJx24UWLrvEt1ezxLPqxoBT6gZ12Pa+M1jTIkzdc1y8FxQvpxQv9nyxm/61oWgb7V1pOscq73OjLWjLXL89eQES8exsWXnFSvgiukNnHiq0lS1DtAUGI1sj7LY65YQaQqpNZ/bKhNnu2o6NXS+r2dAv4aIr0rGvR7/yz/5AlcPR/mXqcQ+pT9XYoBXm5xzE/uLwPpSRVk6xAmCz+B+QtzN3qBm1Iy4eHqRdz90PitZYXt7n2cKl/M1OqTw4BxaFDkHiFL5RMc3HIaEawIFHRarkjluEZl5sRZg+fY7kImoJnM/W/VkooRQ5gf7LCqb7/MWjLVWoPlyj4VfZwDtpA6zT5oSSJDbemYFeoMyzWeVlwRCUoZNovSeEOEgJJZK83DZr2GpoyyWMGoSTVKqwlFHZXvkp0pUhY6Dygm7uw0HB2miFGitR6ogTlhe7rJfx5zAOCtiZLou1yrcrRVpIoLgnPXrWsezUExp5FvWbs3v0+a3sur8HjbUN1m+6YDqC1/4Ardv3+aDH/zg5FiMkV//9V/nf/gf/gd+6Zd+ibqu2dnZmdMM3bp1i3PnzgFw7tw5fvd3f3fuvrdu3Zr8dlLpdDp0Op1jxwexph+6qMv5mlKkUIsJGanSy/t3k4yhrXSgEhhnrnsXzUpSiOUwatRjWZQgaKBIzvJM5Q1EsuandC77niqNGhsb2uZCSCSxAMcSqDOBRa2WhjUmNXeypBSYtaAhs8bRuk956pRw2nC4t0Ovs0jHV9z32AdY7hU8fGaDG1tDdja3eODi/Zy/cJb7lpRf/vSv8fRzLzLc36Lb6UNnlZVH3g+dCjodak2EGOhvnKU53KcfhjzwgT9O5/QGK8srxKamHhwwcIKEiERl48I76Lp9hF36xSnqqsvqmfu58ODjXLv+Cr4qiGoulHWeKD4LSF6MzS9gFqwqbxojLDaszEGgsY3iyeBUSER1lhMqt7UlVrbgXRRwiYaI1wIvQuELVBJF1mo1YNSn6gkpoClOZmNMniSRIrUiUXb/S0phsIMUo1ml8jUpJRxKLZGIuV0UZDDWEm44aNRiyFQljyuzgQZNeJ9ZntKEYwdVSw5sG7FDfZp4UnRUUGO7IIizuiUDQx6HK1vtjUOd4LPCoNG8jeb12GOuowEj8ChSYiiRyjmaBBJBnGn1xnkjdupADGg2GuwdxRIjA9S0vvOT7fpNlW+1NQR+T5hmUo5tjb+v9fytCZYToZ1ZTabQc54n1he4/vwVLi+s4Es/BScCL45O8XNfWiY9/dsUl5+h0UhVFFRJ6W8LT/1bT/Lgf/pRfvWnf41/+I1rfL0Rls5e4GN//k/w8pe/yotfepr3HgYuJCP/2RFhi8SZc+f4Y5/4IUT8TB2zqw3mhoyQNcJKS9etIrT5T+YIvGVeSJm88UltfPTYZIPVGeFS55pYJ9fp3DVTyDaFXHMgq2USOFIvONqDs+fA1Izze9OiHr1SAE2JcRrf44q2DoruDzj7wlXk4kNUnSUWe112dzYZDg9p6vHkviqtOCi07KjHKvEmy8ktdPKbvdUW+VZbRywG5IQ8UjMli+d2jm9H+mzUCja8wkTchKFmltn8jqo0LkyeU0rB+lpOYYFSLQtt6J8mpW4S++OUmVhnVurZuXVkmAITtzFNiVeffYXnvvQiDz3+MP377+d/+Z9+lTqCVUyYcONp60aXeLCXuK/ruHwIgwYWuwV//ce/i9Mby0RxlIXHFZn2OBk9+pXre3z9uZu865FT+DKvFe27qCMmIYVEbAK4nIS+gRAScazUhw3NMLCztcd+mehcOIuJZpLXndwnudqtXFdEi2EHY/ub7blWOXOvcd8qOOcw1gSlMsnvdOKFRz8e2UhUNSewNVlmohxiOl5SNI+s9vI5QDHzjKTKMCbq2AIRS1VTK/icfD2ostcYCEwiHDYwim2smTAMxjMQ1RSp7RK4MzbPKkYJ1RolJ+dN0ERbf733PKAt8J6O9Vk1QoIJSQii5g0gwu3h8Rht0em6YtH39t6D5s3LIm+1fNMB1fd///fzta99be7Yv/fv/Xu8853v5Gd+5me4dOkSZVnyK7/yK/zoj/4oAM899xyXL1/mqaeeAuCpp57iv/6v/2tu377NmTNnAPjkJz/J8vIyTz755Fuqj6gSJUAyWvEkUNNQiBFWaI6J8i4CnjoI6oz9RTFXPqfmghYFihQJovScsbDVEsw9MDqCmHa+QwFExmI5hzoKmqN9ShWLexFFNFKjJEs8hYih+uSFEjcVWLFg1JgiXoUyZuuERg539+hVPbrdLsOchPehs2d5/5P3U9xQLjxacGm1R6eA9z28zDPPP8t49XFKHaEkiv5ZFE+KDfvDAf1OD9fpcjDYQ1LE+S4b5y+iseHgcI/1xXX2fE1HPEGHRC90FpZZ7gg63uXO5iYrK2dZXllhOB7RqUqcLxjlCemiMHaBSkA1GqgRc8tMwEATC2qLVsT6oY6J6daSyRxaBj+MTtNptnaJ4LOmuYggrrA4M1GSN3ZBwU0CMoMoaMTyjAkxmEuoT0Zt15AoU15cxOLvnCjBWb70qEpUR4kJfxEhhZai2bQvUaBJBrIbNZcMFXsnxYB5dNbnSS0PVqlmRfK2hlNLosqMkA5b5YuoBMQSHmMU8AEDmymalW4YLDBUVXDR3jdqdmdwShMtZqt0gteYf7c2CiGQvAH/sSSqJPZ7sncQp+Yy4Ux1UEYTLktx1HnOeGesg/VbAFTfcmvIvX44Qch4M/c6tn3+3uXnY+X4bWSipcyiGovdLmeBL75yk3ppkcK1cUBTTXQSGPqS3js/zIVHP0R47TmaV57lYw+uUsV9+u9bIe2/wv7zl7lYCT+w3uE3/8gH6ffW+K4PP8VaucD9n/0SF5tATMoFp9ysCh5+7N1MhI9JZY2M2JS9LruK2GZZBqUfzRe/HA1xI4GqgsIfE0Ylz8HXK3OPFSA1DDeft7jFo2cejTma0zwfv/NU5DcwlVID2kw8dtq2nZeJjkhZCtxLwHrdl5nWbHLHI8Lv/F1nL7bPh8MRB9t3WBHLSSjdSF2PODzYy81xFDjNqArm/7ypcvQt5R7H73Xsjcq34jrSyoezYzepsjk8JKRIx5esFD2kI/RO+5wjaUrUrTnnTnMnmKZXFK3nhWQBgsTs2mTu7joZAFlYVcmuUhasH1OiTffUwp+plVEmOgJmzgGoR2O27m7zld99loff+QDveN8j7I8b/vIPf5BhnVnVkk5y1z3//GWePLPG1v4hTxYj3rvS49evD3jpoMZ3Pb1OH6RnMczq6PnC+FuiMh7XPHRhmdcu36RwFs7R7sHEmN9D2Lq+S7kdqDoVo50BdQHDGNjZHnJjHNgKkaev34LlFZ762HfhO9VUgMfacmKRIyExcnZzjyLLIdPz2rOn307q9BZUHJ8b+rpf5y46Mn9VIcTEMLRAuFWLMOmkwjSzjDLWqCaKkJlnTZYA89iJKc3kdZLJdZBDI3ILTMZFe7mb1ksUuqIcBkvBgsJegKRx8vyZiL/8mkKIkeev7U6UWMdUDe3yyMxftUS/hRd6xTxNxwSLHbHS+d9LQPebLN90QLW0tMS73/3uuWP9fp+NjY3J8R//8R/np3/6p1lfX2d5eZm/+lf/Kk899RQf/vCHAfiBH/gBnnzySf7yX/7L/K2/9be4efMm/8l/8p/wkz/5k/fUIN+rSIrmfmeh8XgsriNqJGWLwCiFbMXIhAAkJJq7U3QJ74WYKaiTM1eqmoCKUDlPUMtO7SSaEJ4aY1ZKRipRQyYcAM2U3t7EeorkctLbQFK7P+rwAfDZZ1hTZtTSHKdjwZqHg23El/T6i7YINOaT+sLtQ/S6UFUdOp0FbtYj9GDEb/7Pn+Pu5pjlCz0ubJzjzp27lGtr1IMh+2FM3xeoRFxjpAd7B7t0XQmLfcpOSVlU7I4GVEUFIbVk8nQ7CdGGheXzjNMyMY5xoyEkc+Pp+C5FtOS2yZm5o1GhQ4HLAnxSjFnHWSJb8xUz61zBVJshzuKUokSyJ6BZraL5ZieJBLVA7OQcZQFdlzOyp2z+daYRiZpI4inUkivXUdHkJhteSmZZQiyOKqRkwIyU82KZy2GhECVS4amTUDhHNH07KJmdL+XEzkKV+1AkkzrkGL4GsxRFlEDIKcDFCFUkcYjl7RIUCd7GsDOzvMvSsFBQCDR5EXEYXby5cinjCNE1eBHKVBitdIIQzc0RrF8iijpHIY6Q/dhJniiW082kXrH5o4lCcz4sbLwntVhEl9vgreiEvtXWkGNFj3xod4CZP69XjouyRw4eRWozcuubqtaRW80eXywc55Y6fO2VW/heZwKm5us2pfONJB7Yu8HipQX6972fznM3iRcHVB/sE16peGrU8KF+yfj+M7z42LsYCKRYsNBfgqUFmhggJlZjwcXVZR598n2gmUO/dZPJz1IxRrqYlK8NxrziEj9eXmX9E6dxy6uUhwPi51/g88MeLzzyjiNg5OR2PqE159tMA8Pdq8xu8cfPPtIBk82+VfHIFIyiU839ibVqn9P2bSttzYoJJz715PIWgMzRNzr663AwoAmKZHIbAfq9HmdOnaYJgZ29nXvf/HWw7L2A072+f7PKt+Q6crRT1UZEnfYJKeClC9qFRhjfaiaCq8xeD1lSbY/No2rF1vPNQWMhAS0SOlKJdt6lrMxk5lkWv5sZXWfR+MyC1YzGXH7+RZ750nM88d3v4+HHHsRVBT0nfPT9jxjQaSd4gjAas1TvIYMhZ6oxpxrl7uYeZyqh6SfOXFxibXkBKQsIidKblUpJRAcuZNdygaLITKOlUWYvjbogFgaw9uAaTkrG+xEKj6s8Ppoy8jAogwiqlojWDWv8bMvkNmiTyqIJlyKa0nw7v1E5Mr0n64GeoJfRowdmfphcL5Pvmm8cknI4sjxLmf94SgUjsFh5uoXk3430qhCTWcRN001I7nURoXdSTWYOTKs6P+FnSSpSUg7rxDAaSZfmSvccmQXbbqJAk5SQZsk1TtzFTjhmslFbt5Wu5/ximQlYjlw902aKcjB464zDb7a87Yl9Typ/+2//bZxz/OiP/uhcMr22eO/55//8n/MTP/ETPPXUU/T7fX7sx36M//K//C/f8rPa9SvhidqYtanwSDIK6hAjfWcU4SEbG33Lr+OUSoz4oOc8onY8iZjFKwlIJiyQLEiHZOQG4ggeupRAk/FBIip4cVQ4EjELumJxMimZi5hAI0pQpSOW10hcQZUipUSiRA4OD/HBs7SybPFCMdA0kX7ZZywFjVSUrg+qjDbvcO3GJinB4f4W95WPU8eazsIyMQVUYKmoiKqEKNSxwRdK9J6mHkG1AM5cHQvncU6oxw37ezugQjMe0vVCv9/nzqED8VRhhxWNRoNeQEEi4DKYzHFrGk0wzxTpiNLBNE5F8JRkRkaXLVFCTroLQqJwBaSEBDVXNTX3wE7hKMvCLHyq1DFk6GMWGhcM4BaZhKHVYBgDpPW7REF8IsWIqjEbumQWs0LcZDJPGAYxkoZSLNltxuVZO51AC9uknBqpBo6QGst3lmONyNYncWZNLcRcnYxVKKAqjHP8lJOGRhSPt1ivLACJmP9xEqWUIgM7QIWgtmiWydFxZqsrs0VMMEtSgxJcwiejhG+SkUwU4qm1wRuHOkhevFWokqdJAXJ+NtFk8VvJ+tWpxXF8M8sf5BpyvNxroX/zouHrQ4ET7nl0Y32dGs3u++3mJcBaTrD5mWdfYX19be6q2fpMLCrAICmiibVOh/Gnvsro2ibDP+G47/4z7H7xOnviGBQ9PvnOjzOgxBEQcVx64lFeeeRBXiGToDTCE04QXxp74MxzW3cYY/V0fGkU+J8PanYWhB96vOD8k110eRXRHm73Ls99ZdSGLsy3+D2a/9jhY82nJ5w3X8PZZp8aZqbOfpNYEZ2HUq0wAcLK8AAXE9sL/azsmApw6JF8Wm/A4PCWQcjcsGkBoEx1AgrbN29xX6cHOa5YBE6tr3N6fYPDwSFf+fqXJ1aMkyowJ2++TgVfD+D+QZc/7HWkFfSKsoYUcNieJZogyCQe5njTymQMnrQiOIHl0ud4mGyVmunv+Vrkv4Z7qLO1KsZZdUE+M/d/Mxry7Oe+wuVrt3n0fe/koUcvUVYFCpSF4/zqIpPErEkZD8b8wj/9Zd69tMLnd/bppoT0CtR1ufjBB7ny1Zc598g6p88s5rrYfLB8r0YixVKJE+HRBzdYWqgoK0e1UOFLR7/umKdEUlordwxG2+4pSCrcRthWobe4xB996v0srC5T7eyge0JrjpuCi9y2avPUt+a6Ix1xonLspBGu09V8VtA/WuaN063CZnqyZvCran282PVoVhSHDLJsuRFKgUFIDHMIREgWTtYtYKUsJq6LJ/97j8n8Omtuu2dElM1Um7fO5DShcBa60K4TCojLaV/mwKNO7quTE1sINlOv7G68VAqrHU9ZuKleCo6M3KxEAMpiFkJ/c8sfCKD69Kc/Pfe92+3ycz/3c/zcz/3cPa954IEH+Bf/4l/8vp/t8BRSEiVS+pIykxskcZQ5rqRJRmpQFA6Xk6BWzmxBglmqzP3LGPhSdnmqnOXcCVjunhiNyECxZLylEVATsHxLUUyQtdxReeJm+nXT9nvGGrL7oVAZBzgeoZNdxBIlw8N9tE70V9fx3mKvUgqMtaEoPb7wlOLNpa4O7B8Gzpw9z92tK9x95SU+8rE/xc2716mWz1CIx0mFFAUu1GiKVGWHejRgsazYj5HxcERHSoqkOE10y5JOf4Hx2NEMdrl1/RrjasxgWHMwEsoCDp2yML7DaGeTouhQYwmSSYlSvIFLh71jsjZkQjQBipFLNJIoUXwWVIKhBkq8JT0WJXlH35U4J0YC4U271qRAqdZX4xgoBMTZwmNxS4GaDGbE+tkmvEdFSdHAdRLLV7XSHLJXLpDEgbZuiDm2S5UR0BFHoWqkFZIyu6MBQEWJ0RIOewGRwtxFXXa3EMGLt9+dbYA58xWCpxTjECzyeuPU8pBJ1jqZG6nFK/mkRIkUuOxKGanE5xxTyjg1RAVRZ3GDyVG7HL+XMNO/tDTwapnMcwBp4czahprdt8ksgqoJl6ZBzRFF1GIGY/j9Aao/zDXk7SrH9tMTsdJJkGt+m7jX2bOfT/d63NnZZKQF6+urk19P1IvmC8sEjxWRjUtn2P6nn+Z8M+CVs453fLzL/gs3OPwn3+DMSPjF9TWuV12GhyNW+55OZQogyTleguuwkDq4WJuANom7sU1ONGVqZkHKDi9o4ppGGDf88j97lo89vY2rOgyj4mrl9iPvt81Sj5M8vKGQ/voI9liRE9zaTr6Nzuz+cGF/k8XxkOdO3UfbT8txAOPITq8HON61eZ2bC0vcWVgGEZbGQ5qiZOyLyb2mopmc+Py3BEoMRc1flLtBVFndusv5UxepxeV8O1O65rIsuXTf/aQUubt5l1E9ev1nz7TFSe3X/vpm6//NAl9/mOtI6WSCladRIsq4FDZlkRCNXAgPG8F+a+nSZ0HsvNB+8pLhROh5f+Jwb6+fkoJPj9v6H83jQzDrQQuM1NhbYz3mS5/+Hbb3DnnwHQ/yzvc/gfMCs+Ol9UlQhcGA57/8NDdubVHvR3xs+Og7zvPEw/exuHGavcdW+MpL11Fp/S9mrMUKuKn74WSuq2auCmnJ7hAsBclw1KAoo2FgWEcaAoPGrFMLBawsdDn/wDnUWfxz8kwsUi2gal0iWy+UKc347Pw5vmDPtMKRMusSfPSKuY655+9trOk4ZquUzoOYEUo9IeESUnCMVRklzZKstWpXYaU0eWMypjLenq3E6825o9boVgFjY8/i6irBZIsM6N1s/+UPHugV06eJTtQ9c+3RZFmj9QJAp+NhrVew3PXTOuVBOF/Fo/d/e8ofioXqD7IkjGZaxJNSIjmhpLDcPN6051KY5QMnCKXRbxdCzPl+JAMg58QC6CRhUTfmEqatq1TOmSTq8bnjncOIANSIFVzWtgjJyC5wFnyqEIl0vcv5hjyFdySX8MmydScnjOsh9TiwtraOOAsAdN5R1zVVWVA6T10PGO7cxPUXOdje5cyZs/QWKkLY5xN/4f9M8pGit0J3ZYODwz2SQqdTEgMs9zskEoMmUHQWKKnpdHsULliOrm6HYWroFh1rO6kouz3WT6+zdPZhysOGph6x4JVu7ajDMzRqQpOSWMCDGk16SomxM41LgSAeajHLkWo0hj3nCFgcmcNAYqHOzPVqVhQKo8kku+NpFIIEXEqMRAjBNo/kkjHYqdComY86kGnIlRJPUrN2aTJLVMxJjJNGNkeBqjR/dmNEchYZJ7YAdxVzDXCOhkBSwamndBZ3VFhSLdQpThIJMatW3kRwDnVKkdqF0Z6VJGVCFbGxbPDJGPbIFPKYpieoUqeaTo6qbdQSAHug1kASsxBGp5QJRBJ1UtCGFI0XqhQTsJwaXIxqdP4CJBLDZL+DsRZ6cfgkWXFgQMsS0Mdcvylr43dEmV2P76HIO1pmhcfff0uc7E42q/lrv3uBparixctX6SwvU3beWDsnAp6SR2XIw3ev8Wt3G/6kROJ6xdJDyvKHL+K6H6Xov8w1X7H15Huo1hcZH1rg9rzmU/EaUV+A1mQGF8BNKpqyW6mKw5WesRMOBFxKfPm1bc5tjSnFcWvcsFwIO/e/a/KeLZvxRBY4Ip9MBbA33bhHGjU/5FjnngRpsuApyrnNm1w62OOF9fMtuTHn5IDLRT8LA8rZ/R2Kesyd3hKi8NiNl7m6cR+3l1ZPrMbcI4/09T0wy5HBdlS9PP09hIg7HNE/ZXT3RlvdkoBAp6q4/z5jvBwMDhjVwyNPO1EbMCP8y1T7/gbyzMli6rd/6Zc29ybzM/+z2etybe1xwFxex4MBazf28DPvfa+me10ZfHZetMd1OjOP39nmbsd522GS4rCk8K0LaGpqPvPLv83OzgF/9E99L6fPrOXLp3NkymIohHHgS//Hr3Hj9jaPryxSO8fH/sz3875HzlKeP0V9YYl/+HP/gtP3XeTdTzzKsE7EBHVjSkhTMiZ6pdVtHGDvsKZfVYQm4usIpXkGCfDa7gH/n3/0q+xHR1RhmJSDZDkfkzh+8kf/CJceOk+qMhjpKn4pm3iSokXO09go6RBKp0hwyLjMr9guODLBV9PWzHBK7qEsm+m9OYCcT5aTp9AMFLK/TUqMYqRlJU1qISm1Wpqe9h4xMxu77AEjairgAgHxcxNNZsdCHiMi94CAJ0xHye8h+XldjFV4lhvVTQhZbP+Kqpmh2e4gYpZAcwuUmQU8A8J2MIujtZx6gYXSWd/MuS1M6Yvm587bK4d8xwMqxJLt+szQkpxjTKJQE1oLKXDJfC9dMrc/Y78WRIqskRcqEYJEeq5k5IxgQgGXDGUbBaRSSJHjpjIDXFKzcEhC1OHEmVsW0JGCkC0xRdv9qc1BBCSLUSrU0QBNHFAPDjm1fprkPM6bMOwx1zQpCgOC9YDD/Zs02561jdMULlAlz8b6OdZXV7l5/TX6/WUK5+lLycAFtE4UvZJaIhqVTlESQ2Mg01cURUEKgQUSYzHw44gU3T7nH3iC5u5X+caXf5NxZ4PO0ml2kxKjo7uwTq+s6IgnqhF3JIl49YgKPlN3h6xnkZauSKEST53ZAaMaqQSYUK9qjIyZIJGahItmlRExYGMJaK0PVIz22zKLMXG9HBEpKCyOLQfji6bMKmYJgi0qFuqkLLSEEuJJWNJnTW4SJGQA3oEamYM4q7tkM1jlzQIUnC01RfYx9tlSKupRJ0Z3jhitfgy0FLIp0zMZW78BlTILPlEjRCVFcwfUsmPjTLPFipgp2BNFTsTXuEhKasyRmSglJhOqOhTZ7cKCVX2yxXiMxalJzkPSpJBZK23RdljsoargSJNkzd8ZZV5zNi/hnCDRc/Khk277Bmfc89dZYXsKpizf232nV3j2hSt0VlfNJWJmBzWihKztm9EKdl3BI/GQ3v4+vzg+zVPyJfrnOxze2ad6/zLSO8vwU/+KSiNfePQhLt930YhhPBlMzTeLo6FMWyQRovRQc2ya1HssBZ/2y/Qj/LmqZLss2C08SYTfVeXaaEQjgld4SgvGLl/dIqnXwTu/3+3zZNjUHpneXSeITek1DSOEhJ/ErxQJlmvHegrc1oRzHqdKFdMkz06VxrQUyidpV49V6k3U+573mJxkgkuKET+uWRoN2FYjaJo9b/Z+nU6Pfq8xamsRRqMRIdRHbn20BjPOY/eYJifVciIQyUm/fpuVmbE6B5CzmxrO6MJ90JNf9XXa7Q2fe9LnuXtPR3WRJep2W3OaLSAHhzz9W18CEZ78nnexsbFy5JatxdjCFjZfvsY3vv4SqRHWFhZYOxhSbvR48s9+hNgv2JOCwzpxSGTRC1IYNXcTE4NxC84U78BjFtPNg8DhoEZXlVEdadKI/lJJCgEvynqvw2NJeG1gVimnyuZhTUzgS88Lz1/H15FKCnyngwyVKjpTXSZMA+XEqOQaIThFYzRijekIptLSUptwgiVEdbLd3auPZteVNzOqbfgbMFooCjq+ZU+0uyVVc8/PwEKZm942dLIC1ouli8m3pCpNkdw0mZ4+ZfIN87ecm8sZMjK7CrYLxBTHC6c6Bc67SSbpSWza5CIjQoltW+n02iYph425hRtmnMZh6cxTwEjA9sbKsIkmq3hhsXLGWUArpf/BrRzf8YDKOUvAWzrT1jtVMpMBFR5E6AjUYj7DhbfkrikvDNElapSueISSVDpLdGm6m8wZZ91WO3ND82LWJ5HM3AYWBIkQXMR7Ydw0dHxhHS9kVy4lFm3yW0flCkI2l0pTM94/4OzaWRpv1jFNQtdZbJiqo1OWBrLUsbdf88D9j9BZ2+DwYIs4GLN6/hKjdEhUpSr7VK5g4KCKSlV1SGJm9LppKDsVaTw2kg7nUSkoKs9eCIw0csqVjEdDKl8wGO7w7AsvsVcnOrqJX7rFeDjg1MYqurhsCXy9JZUlRUJyFGK5lupk9K4+uUwQQaYfT4yIJOfpiKLicjyRWQgrVZJavFCh5kKXspvemJAHtuKJOPUEsUS3nRy7JuKz1sZ81jVTsZfeUZOZg8Tincw6o4xTbY57asGUC85ilDQvDpZcUWwT0Jae3KyZJYKoWa0KsYmecjJcj1mXHFjiZoSIGrkJtiiNY0MpBUEhSECj4CShzhYVkr1LJOHqhoYG8RU+GaFFgy0qSRPqDMw3GLFHgUA0tsAEjCXSMZhOAzgN2S3TrLFB22TEBjQLTUQXLPYteRpRi8tSpUHMsvg2a4b+0MrR1zqq+G0/n6S1PHrdGzTRcRFVJoLQ0d8WOhWpifz6557nwsUNvG/JJ2RSR4uVyluimOJgrSh5YHiXm0N4rulzvrvHe90BzdcPqS52ac4sk7SEWzu8NC740uopiqqDJqEqbCMzN7kZ6S9rdoWcH6a1yaaAqnJQVPw96bLaE/7E0gJ7Fy9xcOEhVIUBwh2EsvC8+8JZri4v0l/boJy5/bHNcqYxZvNIvbVyr5sfPUePWL+UD195mYvdhtB3nO5GdgbKxu4B7zrleHSww+6u52NPPcjCC4GxJnwWFnqHNe/ffpZPffApkrgTHn0SvJvW5US5uQUiLSiabbfp8CEejHivwDsG21x75RV2zpxhODzg1OoK68v9mWcoD116iIkEpfD8yy9wd+vO/IMzmcHUlejNO9rcaxp8m8Mp4AiQAhBzU0ecNZRzFJn4iixMHruee7TFvdaQe02QLN0evaRlc4v5YtXE1q3bXH3pGvt1wwOPXeId73lkBl7MP8qhNHtDvvTMy2wcDuhqYExg7+wKy0+9l8sI3ZC4O6pJoYduN1w4f25i4fAC3SJbp4yzy8ZQUkJIXDy3zvpq35SLQWlGQmgs7+cDp9d49+MG9EIdGDXKp5+5yXAc2RkHDr52ha+/dJt3bJxi5d2ncEWk7GXuOgHEQG1LsoBm0o46EvfiZNi7FgXopBknLSBwZE24R5HZ6Xi8Z+XIByUDIG+OiPPPhWllmACQOUXE7NyfGQIhxKlCSMF942XKoqR+/GEm6h2dBfk6d4+jg0BT4s7OLqvLi/R6ndwW86uwilB4Sxt0ZPlEJBGj5FxpUEdl3Nh+10bfplylKXTMFq5CWKgslr19ogM2KqFXtuk3eNvKdzygKsThvSPkWBcvRkU6JlHiiAhDsktZRRasjd2m9EKhJgwaE44J6AhoUjquopGAdxCd0E0laEKc0tOCKJFGa3AOr44Co50uxePLHFeF0BHJgrlQOM842jOaFFGEEAP72zssrZ0mFrbwNkRK8VTiGYwPKTAa0Z29Tfb3dqjWNnjumc/S6a+wvLrBAw89TtUtuHNnG99ZQjod6hTwKRK9R0pPGEek4xmnQEWPbqfHYLSJ73YoqpKkSqcqSFHYPtxnfzAEYP/mi1x59iv4hT77MeJ9xcGtWxysrbO9eYtzZy7w2Pu+x1wZUQqEYYoUWL4myWx+pXhqEo1GChXzCgqRIeY6WalRhuA8tWDsO4BIAPUQjeI+YJYbn7zFbgmWiDlv8BWAJGpsuonAIAW63qMEIy7RYkKkFFDQRBqNCQh1ChQODnO+J83JfnvJxopRubvstqfmVpc10qVzRCeQBBcs3im5iCPhnbekuTm/QoW5ANrCmf3hvVmFSgeoN7J0tXitQqCDZ2c4wIvSXfBQmF98cpbvql186qiIF7xTvDrqnGS4dhYQndrAdExZB+amOEoWV1VlDVDKq5NLZvWrSUbtDxiNvOn1ThIPvy3LGy3Gb0Yl+U2pxlRTNx+2LKz3OxxsNmyOBly8dConyTzy/CPStVfHAy7R397ks3QYEpHS8XAxpnPxPbjP/y7hT5asP1AwulwjD66x023w5x+0TTi7hyRMITRXJrKHIs5RdrpojKQ65u1QaWJD6vbQqiI88Bg8eWDxh2DWtqrg/nfeT6/0RngyIzy4rNmf1YCeCC5OeP22BeZrPM3lctKVk0+ajFhn8ovl1zs12GP9fffB/iZ/4Xs8n/61Qw4GA7orPao7tzg17HBxsWQQIs6b8ggRnPMMF5c4OWfbSZYrKIoS5/x8nWf8kCZCj86/o7VfFkdS4rOf+zx/Moy4P8BHfvV/5X/72J9hsH6Gfq8H9GdaQCyecvIoZWGhz1KdHQVnBlprQDQXd6NFPhzsM3HNOfEt7/39214lM4emshitFludWncoISdBz7FT2ZXuJKz0JnQwb6ViGSy0z2USW3zt+nW+8bWX2Ns+4Mmn3sX9j1zMz595l4mgLuhoxLWvfIUwOCB2Kp6+tcO7Fj1PvOdh1v/Sx3l6P+KDY3E4ZOef/gr+cES/vzCJI3YC3dLWFOdy9E/2ykOU+86ss1C5nH9KGR02bL52B5cM4q1/8GF6q4vmHdQE7vvoExzsDnjphSucW+tx9/YBC4M9CjXXZqnbpCzkNczmRYrmkiaAREt70r6y6Iw2ou0IbcM/jvTxHNPEzAqkR/pQp21qAC+jgvzeczNGjs8gbQ+qTgHi3DUzz54BVi2YEiz8Ynd1mTIJC3k0aAu8NeW4JbNMT6nlZ14AoQmBX/nSN/je9z3OpV5nBtRNz5WZ+kx+UdMrlOIpe35yy5iUMENk1MaNNcHYBNu8VQpohPEoMWiVOZgho59MlnfFrGXvm1++4wFVWViAv7jCZiVqcUvq8c5RZTWdJXk1y1TjDOGGZCQJQYy2W9RY1Qo8iciYmDWyNg2cNJgDnlGoOwKC5SAy+4ejK0YkME6ABops+VJiDv60AUACFQ+pZn93i/7qCkVlAnHhLMDVaMOTsdh5z+7uJtdf+QZd5zjc36Hra648/2We+K4/Tm95iZhqwv6YtLzMQlFQNzV1SCwuLoBzhDgwkFYVDOOYyhfEssI4EoWhJioNLHV7HKbIzt4W3mHxUMNDdm5chpCMOVATYbyNpi5Vt89eHFMqBiAUvLPkb5JJEFRglBqkcJTJxO8oJmhUIkRprR2WgcqYYYRKHE3KeaWyi59hMQNnkQBqtOdRDBy1yZVz9huzOIrgFGqFUj2NSziFkSiFCDEqIYxzAltwyWWGv4Ti6La5PpIgmfDCck05VAxQOzEKdZdAnOIL7MUlAz8chWhm7ytovD2bvOmKt3csEdS7nNfBGqOHJ0oiaGQwGhBlTE/OELG21gzsJHrLveWNsCOo0fKDECSRRKnEISnQwVEnJZpBF0XoICRxE+ugihFRRDWCFQvkxQSElPsXyRS637lFT/h04rJ9lEXhdU++17OmGsfpVmi3eHi5z9W7A+6MByytdGiFMTttfkNVtbG14DyPu8S1nV2+6rqIJIoEj6zAh27fpvrnL7P/1CpLj1SkU+uw1WXrf9/k1c5FOkuLhBTxvT7NeEQdI+UR3/n29aSNO2AGHmRhQ0WMjSsq45jA+RynaG/nxFPbgoFM7mf/Ly6cwntjp2NGzpnUQo7WxCqhmcwnaZg2i2vvDuJK2vxU891j94jNXTTuz8nJThNlijjvcH2hWih5R7jLy8Mt6DzG3rDG1Y3VLESE0PowIOIYdbst8ekUQEnb58q8WCX0F89SVQsnjh9t+3wyTqZAdGIxVmHz5i2uvXqNYiFSaKI5HDIaRzptDWbxz7RBJ18vXbjIpfP3zT9bps8wuUvY3Nni+Ze+YaM1a7xnZ8vJAOHe4Ovbr0xRbRtcPypLttcWJ+NWBUK3Q/ADqnS8NWbuxHSkTo8dW1uOS91HvuoJjd5Sp8P+7j5XXrzMlcu3+cif+AiX7j87ndsyvUtL5LBzZ4fnP/MV1ta7LJWey69c51TpoeqiCwv0gNNOcKo0o8TBKzdZ7JfmEi9QeguPCCG7fM0QYijZOiNT9ztN0ITA8OomHQXx5nWU8honTljoFkjo0F8oWF/qkA5M5UodIJq7v8UgW0M4Z5aM0bimDuEEjYzJDG26E2gBVjtX8rPnMM3MOJ6df9j6NunPfNh7z/qldeKwYbQ7nO+i15sOOn+CoDNMovM30AmwssHXKUvEeXYevMheVBbU3jMvlgxjQFAKb2zPZacg1uGIogCubu7x//30s1zZCfxf//xHLQHzSdqAo19bkJdlb++cuXs6oSqmbd3eKsXEQjUJf5sA4XY/bOwgglAn2BklCq8Tt/S3o3zHAyrvXCYzSDYJnCPiqMS0+pY8NuJdgQalkoKE0nFkmm+zCBR5pCcw7byYq1U7hwpniVMbCXTEkRKUvsCh9PLEE8204ZJYEEG8J6CoM2uZ4nImdYdIYhwb9va2WV4+RblQ5DgkpSHRzWxAdWxoYkO9vUfV6fLYo0/yzO5v4kdb7Ny5hoQuFy7eR79bcbh9g/rgkO7qBRu0MdJfWMQVnhQD/bIgNIGy7AKBQhxaViSUxqsxJIoHCrpVlzgeEOsDRvUiH/3+P8Xu7pg7116gqQf0Cs/+9k1OveP7uO8d76RyjkGKJqxnwCgKFr4kaFBwMEoGfgtnvtuFK4mYf7RZnFLWDKvFQMVAk6biRpFzqAQs31SRChqBOkGFkYOImh9xXRobUZOi5eNJCZ9jo0qxChRq/uNehI4melFoChMEk0SLl3JuGrDqUo6tMm28IMb6RyY2ARqBKk616Qr01NlmqnnDcJbM1FOQMuufqoGdmkiRDOTWEgxsIZmRyLFz+zrBN5y7+JhlEnc5YZcK4m3RcfnhBVZPMmOSk4YYjVVwJCYElwrBYS6zecx7tbaL4hGn9lkNtI2TWqJgn/DOQGf5HRNDdbLYN1dOkEPfsLQnv+6tZ+42IwcpZqX5rsUeL1zb5Q6R5eXO/PnSCrY6wTGC43RRcl8a8vxBza2yb0qnZL7o777yAhtXrzIoEjzloX+K288vcH5Uslmd5YV3vgPLVq+Euplrnzl7Sq6oaELT0BRMWf6YAAcB9YmxJsYaKZcXICZctBhC7wWkTf57NI1pYe4Fk2j4aUPOwdu59lVal7QJAGvdErOpQFwBk+8z92kFCPFzgli+hVkVnKKlBymoUkOnHiOVI1UROYgIkTAa8+CjJWvvCzz3ck0RzbVZpn5yR8bQ8dEk2bI1laPa956hDJZ5YKk6zZVFgtcuX+PG5ib/94Fy/3hIsbCMX+hNEavMgPITBrUcPSefNtHMq7J3sMf27hatVaxtq4kQdezNpsdPts19+xcFXj21zJ3SlFoCxKDcXepTjRsevbPPGzbQzL3mylFgda+F5djhVogGDZEvfvrz3N055Af//MdZXlvKSelnHpEBuyDs3t7m4OUrdMs+d0YDgi/4s+9/CCUxPr2M/LmPIl3P9X3Hu/sNN27e5cubd4ml4wNZcF7olGiM7IdocdOma6C13Cx226Q27TEDAxICpSgL79ggFYHNK9dxKuzfHaERYkzUBw07bsDu4Qjf6bLR62RXaDejrhAWV7q40rO1ecDB/qE9SZjOqPZPBlGTpm6Fwbm1x9Cg6kza70xs0S5HE287na5rTqDTr2gERrvD4915Qj8eGyKCPecoZp6tf/veInSqimqhx1rdcGvYoKGZPDGhjKKRXkkIeEmUjYVCLLZ05blPYgwcjhu2d3Zxcw+Xe1R0tm5muNgcJVY7zpL1tkQg01NAwXnB+/LY/VRapm1FW0K3PEYLL9RNw9tVvuMBFZpJHlIJGUA5SYyx/ASVmNXC4WkKE2KDmhtU64pV4ZAcb9WgNClaUrkkJElG3BBtE9Nsvo9eEOfxKaEuTyoU9dCopygdpTjKlBDnQcz9LWFCs1PY299mYWGFqlMYWYFaYtlGlaDG/OZDYHjnLq7ocu7CRcbjfXpLq2ycOcUDj7yH1XMPs3H6NEJiZ/MG+/WIJV9wUI/odjs0o4Ex5CUoehVhlHBi9Ysh4bynWxW4BJQOdQ6RQKfyxOEBve4K1PsUXjh19izr9z+IL7q48V2uPPsFFs+eo1+Z2Xc5ucz7Zq5iXhyNBkR81hKVLJgN2vIqiceLUFDQSMJHR6UABbUmfAE+KZWqxfgkY+jz4ildwiUFb6QUVZkDMb2D7C5pfSuIy4ksxeNEcd4bEFGbnHhw9Rgv5nroJFM9U+BzwGQgGoEZDidG4lAlZxpugaiRRnVKpJH8hFyjI9760wm1h0o9mgFTkGiW0xaQqV3vxRL2ls5AdhClysyJu1dfhBLk/WJMkGDEFTm3VYklnHaqlEAQwXmQpET1pBxHGGRqPQwkKjW3lGg1J3lz9XNOSDk5n89uiikpqiaMxuwu+51TpmLeXGk3xhmh5C3LgbOBLXO3ndfOTf+aZeNC1eGrV7fZLoSlXjVXVclC/9QqoUjyPFEokPjSKFEt9eiOlcHYQMW7FpV3Xd4n7df4f/9huN8xHCZWqgH+Xz7PvjxMkhz064QkloAzS9LzTTV5EUUk53VrsVZWPLYic1JlOBiZlaZ0+Mrx0PoiG7FhdecmUYW6t4AsLiJka2gcWyqD1mdq0jJMQdRRaT/XR1MDGlu5LMdqWpsl9Ufu2boGZcdeDfPMimruWs4JEEhFXlNCTW9ngHaV3ihxbm+fhKMejthYKrj/nYlqb0BTx5nYqak16l4zR7D8gzE20/PmMffMyYL4nOBcZEJGoqKkNKRPzXBcMFhwLHd6VL4i5eD1Y0N4rj1l5t+Zdm+P5S9bW1vcuXP7+Escx93Hfp5/0rd3mYwkVRon7Dtn8bcIcRTQJiErXYZFcWzc3uv95zDTLPI9OiDmTr73MY8SQuQ3PvlZlh88y8MbK6ydWmVqcplqf7Lqge2bd7lx7SajrS1e3RnxQ3/2e7h/qWTn174K4nHnL3CnWqCioowHjEcjws6ITnKoK7hwapmlxS7GAWXjLiWlzbbhhAmV/3R9yX8TkKLFJntwLiJhbLJfM0brRHNYsxojhzd3+d0rW3RGynvPrpr3RgvytQUZAklZWVlkcXlhsqQJrSIqz0udaWayciYmYghGYpF0Qsc+SxQx526rauyCmQPd5xAEEWFw94DU6ExLt/01A0pm95zZNplWLB+V4/PsCLASJxTes1RG9mswIoBpf2ve51GLMW+CKaL7s09VuHpzC0JgNB5QNyM6vg8ydWa0f2dXieP7XZNameEe+6hM3upYaY8lgW5hXl2t26IINM3bJ4t8xwMqV3gKn3MzqVkP1BnDnKQaRCwXE5akFRG6FHQk006KCUdNCjZkncXpJFHwFjdSqkm6FWVm9VNiTBMShUIdTrLFIQlNakjOk1yBaMrsaIlCPbWaEH2wt01V9PDdLqKYW4pzaHJUzgZLSg1XbrzGwsIyS2urljhWPIurG6ydv0Sv22W5v0JvocdguMV495BBbcnuFqsK7529UwwUpWl4lztKoKHjFxg0A/COoiyhqUlRcVXHhA0X0Rg58+DjLCxFhjevcf+7vovoSvYOD5DqQUavXuZMf40kDkeidkKlDucw0oIMSkUw4V5zfipvVp1SspbBeUQ9uJznSw10eAF1BlQKB2W0hM1F9tlXL7ik9L3SSMzuc67NYAXiaZKB4EosX20tiS6KS8rIefpxSLcOHFIZYYZYLi3NTIzd5oBB0TGBJVudgmYQ5DJVvpr9yEua5I8Q1JLgtiQPOKPpR7MboVI4R8om9yC2s5Tq0WT9Fkj2vjl/ltPEqBly5+oLFIUn1Acs9JaRZDFZzpuro2S3wyBqygYHEFEpLLAzJirnLBOgV2Im84hlJEUQPB3xRgIiiVEKODyVt0TJHosNrDVlynmhJW/89ixvpB7OucAcOTfIhMPuiEwkzOxrrwMxp5vMifLPjBDvnePx9SVeeeEGuwsdepWfedRxgVxRSl/wxHKXa9duc7O7wPL6MptbQ8tBg7BSeT709G9QXb9C/Lc/Qr28y2B7jwc+epZyAeq7G1z/zCqWttHe2/mOjZfsvgYT5fWkDhbofRThmABjVhOzPNcHA+qt26xduo/7Ty/x13/wER7cu4v/X/8VzeY+v1Cc4dXH30V21KGp72AkczkCZGaPnhPIj1hJRY6eAdOIqPlz9egxmcqX0/5QygB6X5+Sa6gUpLqmHO3y6pe/wal/JMTtu9y5tsvw6++g3jkgjXsoia6Aj4Fi4ublpq/RWhU5WpSD/VscHmSxdub9dPKP1dX7ilNnH8oJ2nUS0B1D5Ma1yzxRen5oocP3PXyeSxun+Htf+DS/VVVc+FP/5kx/zdxw9gFy8jidGqgkuxVPzzrSE99R6pZ7FVHN6Sba762C0RKzD/eGuCSUXW/KuaxcmVgb5ejcmW3ReWQ/B2pnTzza0G0/tjK6KPVoxLPPvoQsdnnfR99DVzw7O0Nmk7S2qgWnsL8/4MqXn2Wsns39hh//iR/i7KVT7L9wxci9BMpH72NpUdgfJLpeYDjmhSs3ecepZW41YzY2eiz2u9Qj2/vWNvrEmLh1cxfnhDP3reO9xSgfbg8RTVS9kqJw7N/dJe4NKPGI5LjjZMzHmiIpGfECTSTGxLgOjOuaejCCUUCbyNzobJu5xW4i+E5BtWxuxVNdgsw1ewKISr09JtYhgxzNxF7TfptEvWYAloIlJBYB7x1Vr4vzjlAHc6mbHUOTO8x35sn0IEdGgc59s/vMXBaiMqxrUoosZlxpVmSTL9a7JTp72zxmXAaIiLK7f8j46Wf4iyuOhb0tPvnrX+CHf+BjR55/rCLTGuX5EU5wd509/eivc2+bseS+T/TUHXvPt1M18x0PqIpeRa/XndAnepxRg6tS7w6pqj7d7gJRTGgcqgkplXpqbSzPEOC1NMuUWJB+VJctHB5BaDQSJOHEEcSEVonWkQ2JRsFyByUEE35Daux+CpKEJBGScDDYQ8XT6S+QxLJbB2yQTTKoa+TK1dfodXosLPYJIoyTWeCCCL7os7SwjPhEWXnGt3ehrEjpkE5ZERRIkZgiop5O6RmMhpSug69K6mTvEpuGpBW+6KDjEcRkiY2ToqFhsV/RhBEL5x/n+pVXWV1eZ23jHON6RD0c4fs9QmqyXUqpk1JhNN5JTYBJqsZomCIqiSKZBUXUmPAkJXx2U0nJWPPEGTOiYpTzHRzJQ1E4i2HKoEScWRF98niEhpQZ7pSUMpNQvp8mi2PqjA9ZiYfc6p5lfzTk4PCAzupp7quMiOKBsMmVYp3kEqOdm+jaBVRKkksTbY8TUDEqFKceyZm0lEBHQSVNspsnMfe5cV6UOjlmbJRJSQrMX1snm6XlZfAKwQcTvUSpI9y58jyHmzcIouzevEz3/ifwPrdHZh5Ul3OK5DY2N0ulIFGAsSJqovDGQpgwrb1PFsc1igEym5/m+ZEI1MlR5GfEZPmvUjJhwae3bxF7u4ve60OrKRTH973vfh68sMKoUX7lcy9xa3cwJQS41z2PKudmhK35S6fEE+3OoFiy1Qudgueu3ma81KVTuPnNkpmtQ4SkiQ7CY2sLPHvtLsP+Mv1+l8PBONPtWiqBdwx2uP/ObZoffAK5ADdfu8LFP/Ygvlrnzt/8HPvPKdcfemKmpuaWIQKFLxGZuorMioCtECAT0gXNyuBEGI0p3QpNEwj7u+w+9yxVGLGjD/G3/8nX+OntV3nf3V1CwmJTXdYWzyGHqaByrBGFqWveBAjNiCfThsp1nRdcZ9+VqYh7BDCaFBJXexS9fdLYIZpYHQQuiCM9f40zjy3Tp8vtv/+PCeNEatYRSXg17VyvDvhqEXJ8pmggpfH0JWaFESW7PxtYPGotm315JwkRl90Dc0+kxDjW3L19kwul5x/HEQ8n5WFg7bUX2Fo5Qx3TCS1xZGAfaefZLxYDMytMHilvZVl4vQn1bVCcc3OEHj5rYJLmdkpm2U/JFF3dlYJUB+qRsrDWyyk8TpJC858Z9KStK57MAyBmx/rM3/baF595jZeefo2Du7v8yM/8efpLPW4+e9OUnvmkwhtBQ4qJ/adfZhdLBCxO+ON/7iOcPX/KXOcTuKIAcRSrnnI44u7uEt2u49prmxxsDdCgNDk2x2XLlCIsLHYtncfNbbzzrJ9epuya0lfCFhoji2s9fFWys7vHMzdvQdTJe4ZRjYbEzRu73L09IiQjkEkFvPtf/2OsPXSeYm2VcHsbHTQ2f2WmLYGY51bbOM3B2Nz4Xau8mFeQIaAJRsOGkAHVdE0/urZbPUVkBifbh9VTK5TdksPNPcJof6arZjlLZ5QZEx3SUYXSGysqpO1/YDwOHNbJck+6NoQgj6f81xyI2sXHnm1sfCZDhahUIXKmcnRJHBy0+2DbSvOryRQaZgtbPrdp17WZut7rXWaH82xrB6czGrLZ57995TseUHUKY9TrICAFjSgLWhBSYj8GnAZ85TNVtVApaIZfvo21irYpeF/gcHiJjGfQuVMo8agYu1sXgYLMlucRkuWmihYTIx5Ssp6eWCEcFAqHwx1Q6C0tUmtNaXxppqkS20DHYczWjdv0V1ZIKVBrQ0861BrxUrBQdimrCpXAYrdPGB9SHwxxVYWTIaHw+AiaIsNmRH9hjSZGYmyM5l27hDCmW5Q0o+GEllxLz6geUxUlRROQJpFEqEdjOtUCqxceYjDYIR1uWxxGVMreAiRH0jAJBgzRrH1mOTH3ykBDypt+RKlTxHQzkQKyg6ZAcqhLuGicNAWOoNAA6hVSxKsl4tWcP6nIFpKQMokFZkEpvenYSQ6NlhunI8JgNGJ3d4vq0hn27t7i4PZN3r2+yv39hmdS5Bu377B83zqNKi+99hIX+2dwvQ5elZjMshRznIemzOYoDYWa9cA7nxMNGnmGVxgTzMqhZDZJlxMnK01SCueNJl0VSZYLK4lAMqr5IEqoB7z4+d/ExwHjJvHi5z7N+rkHkU7flmIxIS0ls/y1pEUlikRHo2pEIM5isUIMjJ3SxTYKh1DHSEpGo+LyamU5vSyXhSUZjJQCLnkCgeQgylT3/+1YThKv2x+6Tc3Ka1c4v+GgW7Hcrbi9Mzjh2rwJTST62TOOfpp9xFRSzriHsizYGI64cueAsLSE9ye7P0y2K4WF7gIXxPGNqzuMOws4J3Q6JVvbAyOIAR5OB/yxl7+K+553cmNF+fJXn+fP/Nh9vPzlMWcuXaD7OfjKwLP3qAnmkl3CnCiIo1NVcMRHvX1Vs1ZGfNkDDTaoAI2B0eEuf+TH/ir/j//9l/jKr36atL/Hnae/RhyNuVFUVHdf47HxIVWvx+ZjFy39RXvzuXbO/6rONfFkUz9y8CS97tH7zjemXbzoahbKOBU11PYPCZ7DqgtqCde5vc3CRfjof/ZOuPQgRdexduUm46cPiM/t4n0EHSNNxEdlRSLvPdvl6S1zK04BJNVMHYZmFONz7z4DW4/+CKQU2Nm6ngmUTBKKMfDlLz3D4M4WH19ZYaAjNqqKWML9Cxv0T9/HuB6ze7Cfu0qnSp0JUJpvrtl5IhnEqirjejQH7ufFyjcp5nx74ynWHlplabGfBWlTaC00sDWRuzOUz11YbXRJ+zUpBZbPL2XCBSZAaa6PZ4AAc3FO0/5ux6/MrkEzd3n5a5fZvbnDeBg49/A5tG4gdZlYZbIlvlt4vCqj4Yjnbt/h1JllNseBD777ft71yDn8aIzWns2nL7PfKVi47yzjxXX2xp7lcsDt4Zibv/kMtz5/mR/++ON84I8+zmKvg4jQX++hislkMXHhgdOIOFJINOMGV3gjsGgVSzHS1DXOJU73erz69A26V7cZ7g8gwo2tIZv7zdTluef5vo99gPWzG6hC0e+ipZuZXVYsiridbwaeJAswbdu3ZGTTOWHXLix3SdHaPE1crXU6NVXNnBWnBDt2PwOt491D4sBDiJTdYvKMUAc0tcogq4cvClxV2TkpkRojBCOlGaD1OiWf43NS9aJToZLTwMREHDXmvk92QGgvyq+UMlmVJii8MlbH/+tlYXuvpOMi3zdqEyK3FZE5z4VWeSUtMsQUw5f3B4yawPtPLb0hqmqx6CyYUlXLIXbUbfH12uKbUL7jAZXTrAVylVk6MIpoIRGdor4ghExZDYgmghpKbwd7IOJEqSjQZIlmS5LFnoij0Zg3ZzMcO/Xme+4dMUHhPJqUbuks15Uz4TaoMspWrqiBwWhMCMra8orlt3LmCjeESeLVcTPg6q07nD13no4odQgU6ukWHUYYnXbhhK43QNjpddjavIU42D/cp6oqNDYkX5CanGmicITBECm6jEJND480Y5x4E5azDcL7kno8pBFh2BzgvFDHmlE9ZmNxnY4r8csbNON9tndvMkxK0enhUkNEaCIkIj3niWJU9ZogukhMgs9uIbb2m7UNzAUwRUuQ7DQaAErm8tZowouARGgSAaUQc0Ui5hgLtUlaerNKqRjZhCUH9gQiRWHWlADcefWrnB/eprj0CFsvfoGNnau8913n+czv/ibv+tgSn33+swxXz9AH/Dd+h+HaOZYfeZcxk0l2S8SC+4WcLBiyH3ZBVOYsj0NNdKQdPQa6NNk9WuCTJNFgQpYXR3LJNjiUBockJextMn7pC6zpIRtlIr76Berhn6OoehS0WjelidY+BUYuEfNi5rAEw0ETjdi9F5JlkaolkpKlHHACqp4qv0fX26YdUVQzUYeS+8JcMJN8W/v8WZnZnWYh0F4q+dqVfZ449Rq1X+DOjV1j6ITswjClkJ5cfWRlPxFI6dHfbUPoL/RY3R9w/fCQuLw0ATX3up93juXg6O0Mec4lqApMbeS4c3c/b5iKE+X89jX6Tz7CzZUhP/+lV3j/UwuIBlRqNA0o1LHfW8iEEpqFN8kKJ0cIIdM+5yab0ZrbGhkZDnepijJr3EGjxWpu3H8fL7x4mb06gvfEpuHus8+AKD/fjKmc50//8Mc4f+H8bNpZJhLmRCqawMjpbgtUztZx04Fbe44p8nlGBsPcLbIkIBwJ7FY+tHaTD52+hWRaZ7DcKb/0yqM0HpBEKiL+pa9TPBopFwrSmRKpRxRnSqqnVqFTUWuD7gyoWGCQhDWgHGzxlWHOL5fraVU5GcCc3OszRSzea3Bwl9mxV4+HfOPzv8bpcMAfOX2Kbdejf7qPXxae2FngsaV1rt64ys6muSRZU7TE2m/wzCPHWxAxf+StlePw99urdJZ79BZ7tOMqoZS7Icdfk7s5C+kCWhVIFcFZYnRpG/E4jjpSEqNx4uXdEcMgnOk6Lq118/l5PE9RGQq8+pXLXP7Sa9y9c4eLD5/nIz/yYVMIqMXsFs5Yar1zdIuCL33haQ5eu0OShs+9NuLf/g9/hIvnVnMOJ5OcuqfXqTceYOkHvosrh7A9aLjkaz6/E7ny/BbX7mxSVJ6NtWWa2hJDV51yAgYT0Fvq2ecYbU8VncTsgqJNJIwaLvS7nC06/L+//BqbKbGfBNSS0aQIZSn8lb/wCe4/d4pSoNk/pOxUlkynzdGnisYW/uiUNCcL+jIBFPcqU68Al9lCJwQzohMFEirZxa9dhfLVYiCtGY7Muu0E54yGvB0TrZtyy87unOTQDVCXY5xDNC3nZKRNy6zlfVbBIQhlr8Qt2TjRcUOMkWETctqUI3CkBeMu7wPe7rPc69JdWebm7RGFg/e8+1FWLpzKKXAst0qKCY2JZjRGJ406XbPrRhmJIivGeOrusdrNlrmwYzH69+CMtbv1tpwqv94+WPUdD6hQy0XVaD0RcING9gd3eOnFL7O0fJ4nH30/CjSKJQTLWgBjUctdqo6RWI4dJ2ZFcGqBk2YanSbCqyXbuNRoH2MKNmAT1CKgQqNQiKcjEBTqOjCuG9ZX13LslcOTcGLOYqhQD/cZbO7w8PlLFKVn/+CQquogIaLiLTGwExbXTlFVBQuLfVKoqQ92ObPYsHk7MMYj2Y8xNA1lp0OTIqOmZmVhmaHWhBipXUGhCXGOUX1omgscZdUhxobRYJfxaI968zJSj7h95euICpV4Uqq5dv0lqIdUVYcGAzXWJkIdapL3GGec5SdRgSI5mgykXHI4sfxO0jh8glg0JPVoiEY7rkaTHrIJuhI1NrmkqAvE6FGvFF5yArnE2ALS6ORYgqgR49zyQEJ0zNrmK/xb95X8mo5Zd8JjSxWD61/jlVe+zuPnT/NvdLb4nZ3rdFdP80RPuTveN1eOvCC2gk8lBYi560yS4GJJnwvnUCIxQUegFCOU0Aygohi9Z8jjzWkG7s4SEZcYnb/LgpZD6PiKTulYLSoG9ZhOtzDyk0Iooy2aUa2NokuoWI4HzeMUhbFqZleEwnvTspFImhMeiqeTY8gKZyQt1m4QsBg+pxY35TRS4u3aP7gZ/7aUk5VkeYvxSrlcUHz3JUa9h2he+U0YhTkBuL3uzbTDSeKqCVzCmeU+g5vbvBpr3NIizp1smWrr573jfFC2m8BNlxBvfeHE1rrDxqCVauKBZp8PLXX4Sh1Z/tD7Wers8EM/mKgWEo9/d8nw6ue5fHmTuw+voZlspS1OE01oEBJdh4GTGQnaZqj9m1JEyUH35KB8BzjPuOySzt8P9RgGh3D7Nm48ot+rWOj16Pb7OD9ltZvhzqIQ+O71G6x3Rry6v8TX9zbyT4mOhz//0POsdQaT/DoxFvzTa49ybdA7oQ1bBxpbs+ySaSB54QPdsm7FXyChzlFJtN29qHGhQc8lkreYTG0c0uTY2o4iDxZUdYLhgKLoErrLvHL5Bt3DAO95Ly1vvLyOAHCiqHFULd0qAbLKuig7CMr27TvEUeD+qmCp8qz2u2ysLRMESrfPe+qGp7XJyp0WVOqxQSzHH3S8NeXNjf2T3u/t1ir/QZXLQXn3rPIj6cTyl8XvFr9bjHRmvmvzeB1twXupUVTh+Wv7/L1feRUVz7vv6/Mf/MBDRgc+ucvUNnCwc8izv/11NAgf/JMf5sEnLpjSLJ9dlZ7VxZKFzFH9v/3ib7OyP2bsYfvMGv/un/zXOH12dT6GL4FUXTi7wQjhtb3IA+WQg6iUW9d59elXWHJFJkvSHPcwW7PWAtS617aKAJ2cQVKuvnyV5z77VTpFwdpih7NLHbZ3BoTGEqTkZqYZKf/Hv/wi/8Gffoq7X/oG3ZVF7v/ud+F6XVJMlqYmJA53ds3sMqPLOKnMrmyzXpgpJWKa9sO88kwn17Z9NwVV87MomCMdosK17X0WugUrC92ZCuQQiCaiaZjvYSRQFust4B3i59fpFrbIhHVQ2yuRosj1znHc+T1ag7Kbu4cVL/N71OGo4eb2CDBSH9ft0D+zhBTZJTlBrFMe10fWkrxfHg4bepvbdFY7pIEydVLmzS0IeZ1K2QOpTb/xByGEfMcDqhgDJCMxCBKJMeIksrN1k62Xnqazug8PP476BQpntNrOZ7/+LPArxjpSqKORRIHQJGhVFkYlmojJhORSLRanxjSDiJCwuJiUc1tJEsgWllTXyGDIxuqGAZ0cvBqTbeIex97BXUb7I86eP2+sdFEnwb7JQSMNSWERz+LZM0iM9KqKvf071KPEYPU82htTDpMxWyUTyCUVEGoKcaQYcFLShESnqDiIkX5RUqtSRocvPQc6onKOva1tFqpTLJ19CH94jc7GA8RODxVHMx7S29uk0x3iCoeqqeBUzcJC9r9WiTin2dqk2XXMNB6NWqCo5N+SS8QIpZoLX1Ijc3BixwKWVNYhlMmsYeoCEiNNMvBkft3G2qjRKJqdd3hRUsi5mJKyQ49tv0inPmDncJevHezx7Cv/iqt7NZ/67U/zYx/9CFXhceMBNxcvUDeBbop0vLMEzQq4HJekbR4bh8uWnALrWxVH4ZSOeho1C5w4iESMOt/RUTEadpfoJdNal86AUSHmdmdZ04XB/jZ3BwOG2lDXgeWFSGzGLIiAV5qUEO8pxCjwoxjDZFLTgJbJIy6QoqNyNh5wjkatXkYcIMb0iOUFU4FaTblQiOZ4K4v1K5ylbi5SoCq/fS1Uk21edWZLtBV6MA6Wr06Ndj82I2LI8Xs6I0j+Hhb0dqNuY2QuXThFeOEyd0ZjOmvLx0gWju4zKwLLTeJqCNRuGgMhQL9T8p5HV/j0F3eIQekT+Z7hdX5DCr64tM6fKwcUZYdxvUcar7H13C4r5xf5X/fvcK3zDlbFTUQd274iEx1g1qRPNaDzLyXO6MZdhigpRfCQfE5wXhYWA1IUiHdU9Zg/9a99P6v9LlU53bImQKPVlqI8sbrJA/09kjIFVIAjcbp7wEpnNLkgaUnH60SQnbWAlKI8tLiTKXtnu09BlLXuEJE0A+hsTHinJIfNgTJruZOgxRJx8X2w83mc2zer9XkHsUMKEWGElDA+2Od6apVzGaxNBtCbLHr8iynZlarqcd+lR/FeuPmrn6OslZWFDl2XWFgrcQ8W3PrNK7z4/A3Olac59cCDfPnGmFEyZsDZqsi9xvOxjn9j29LJ0OD1z/l2K7dqeBIL8CfP6VnXvNbSLAjR5RQrmAW4LXM6mpMaRAERqqJgcWmZaqlP4ZpWip+X7xHGhyP+5d//FMtnVtl4YIOH3nPJ+jWm6bgXwTvHcBz4nd99hmUv7FcFL91/gXf96+9ibXkFp5oFb6tUvbdPvHKT6mOPsTsO7IwjF2XMK0Pl7PY+UiceX4ssxTGHu4eQUo63GtHS8GsGJ4JY2gSgaSL1uMGJeZvcfPU6d559hUc2Vjj3wCl+9t98is3nrnP3uRuMYmD/cMzWrT2uDGu21VIVFB1HHFdoSDhf4HwGtj7hC4c2M5y0c2tM23jTNAQzlCETZUuMcXoJtu56b2p3Iy1K077U2ftgmkzEUkbktCvROVzpKCpTxO8P49TKEhUJBlb63tMpsi+K9yw/fIai3zGlaNOYzIVO1gKSTgxnsQloNIr1CUPHLIoRsxTNulJbCIq9eXvP167fYWd/j6yG5TNffIXve/9DlJURhiyeWmJhrT9BadP1ZDoqC1UQZ+RZYve1vfRE9dH813yKydv5VTJWn7AZvo0ryXc8oErAgIiKbW5V9nvdCzX7RRcdBx6vlU5h1phx1ggW6okxTRL7Ws4SG/1RhcJ5S6ibtaQRu38ZS8YS86IpjHGUeVMVtWMxKQ1K1wnjccPB4ZC1lTUz2SZz8yODKkTY3LtLGI04ffYs0ZkrWGjGxlkdhdJ3CTFy5/JV2DjFypLQ7S3ShCHj3Vvs7mzi18+zvrLGHXYJoaFGKF2XlIbU45qy2yPEQOGENFZiRyhGkbosiMA4BBa8I6YI3S7D/W06S6v0V5eJaZe9Zki/qBiPBogvceUS3ZWEFgVjNe1xF2dEC8kINHpi8WMpa06TBgyKagaSkvNOOVKwXFCNpmy1SUYln6IFxJMFWhESgbEqPji6riCJubGZW5NF/jhvKsA2TsnisCJuNKTcvMr5911A3SbXmy3OdGo+O65Zc4oe7rFRNazs3+D8qRUO9q9wq9ujFONrckHBl0YyQqJOll28QhilROExggZVamfB6EMaPDkGIwmlU3tPBBcwDTdmxUKEoEogWF4tcWimb7979zZ7g0OiA6+enZ1tBjubLG5cygxCtrgXyU2ClhsijRPKpCDRCDoERBJaWKyfx4MoXsVSBGAaVCXh8wYTHBSpAmloAApPqZJz4Bghwrd30SPfbJOx2EPT+lOUiDYUreAp0ytntwI54djJT7FSeMdyt+LWK6+w5zzV2gqzUv6sArT9vLbYwV3d4pV+Cc4f20TqOvDK1W2W+h2WXOKxZz7La92CL65eRDVSVJFe3xP9Av0ysXb/AuNv1MQ6cTBq6NYN3Y757rduMfbOgm29WWiQk/Y7N3ckZktz4x3NcITUI4hKubzEwsY661VBd6FHUfo5IV7n7mngTAVTZmSFhPkSCIgpJQw85St0xo3qSMP3XM0P3/cy/XKcBbwWwOnM02bfYip4pSy8aoDmcjT3n1Me7l9FUyBVHo0AEXUJiRFSQ1MIEpJZ+XWqyZ5SIr9BeR3MlZ2Q8UVBWVYUAv07BzxZCN975hSrC8raJx7DPX6aOCw4d3OPC/cFytWarRf2eb6/PPegidVgrgcmkHpGxHzrwsvx1/h2h1JWYpoKka1MC1nAc0rVL9FGjY3VBVI7T441yL2Q1PRjBHynpOyUljdzZqEQIARl88Y2v/YLv4HvFLzvE+/lzENnEKAWh9MGn1rgBwcHQ26+eIPRzpjFhS5fOlTu+/h34btigmpbpfxyzZ1digunKFccd+oxj/QTO0NluB/58le2GY7HnO2WcO0Kt19cp1rs0l/pc7g3MGHaCXWTGIwTpXcs9itC3RAaA3r9xQrtekQtDrtc6tJ/z0N0z63T6VacuW+NUAf2tgccDiPvVyVGZefWLjeu3GTlwhke+J734rI/mwDqhMUza2j2FGnGY2JT229JqYdNlslmyG9mpoEiE+WXUbxbu5RlQXd5Ad+rqPeHjPayRWlmfwDAORbvO0VyMLy5ydJSDxyslomVboelXkm94Lj7/NZkReiVJRvrS4hAZ3WRTrdNmaH4bmlrV1JG+4empGlBde5bFEhKqAPhoDbwlTJLYqZzFxGKqsAXU0drVajrhqa2ICVR5XA45r//hc9yOBgjYkqxX/nCq/zFj9/i0uk1S40ToT6sJ/GV7SSwvcM+D0PMhgdPb1nQJlhsdrBwG9K00eccISZKA4udr2OOB2+Ve/lE7+Ydxr+Z5TseUGlIlNGC7Uv1JJSbN5/ntc/9Gp3BAcoht7/+OR764EdJarE9knMTSE5DknELglCoz4xYxoKnThH1+BQsTsQJnfwcJ45CHZoJKDTn9HECHRStA6PBkPW1VcQL4xDxGGNdkEiDsrd1B1Xl1JlzBEn4PJZCSBSupEkNrkxsbV5j+8oLPHh+nSI6lnoLDAabbN59jVdffInY69MrHRdXe+w1AV92Ca6xYPQo9H3BoEmkArRIdASGGuhKRfKOuqmJrkPlKgoVmtGQxe4iB3v71IcDvnHtRZZXz7LSXaa7vMLuaEhnbZ1SoYtYAuWsZZBCkWggVwRStFgerwI5fi2IZNYe+01VEG+fE0blTVRcATELJ2W2MJpDUcJJJCgoDtQysDsFL0pI2dUou0qKpMki5cMY10l0O8rja4s8mBJnTp8jlYkiCmvhGg91FtlYOMWLpy9R9yrqpAzCmLB7SLm8YcDXmSbJizJU00xqEBpybiwxa07CFgDnTGBsklA4cwd0zpn1QyGKMSwmIiWFMf95hTgm1IGrL36N5YUOjXqapkESXHvpWc5eegJXFDSughhpkqMozdI3SMZ6aDZUIwipxdq7SiUNivjMSEjEO49LZhmVHHArCAUJkWhB9A6qBOKaDB69sZh9p5UsFTnn6fUV3IiqqumUwkE4wrLXnj8ju7cuNW3w8OyJkw2z22Gt3+HmrVvs1dBd6MyIr/P3jjGy2HG86/wiL13b5/ZiZ96Kld2NFRiNG/buDHh80XP2ma/y/Kjk8rmHrfOInFlv+Mt/uk9HTlGE27gysfMbN3i5qfmlp1/m0fIU3/u+R/ImlWvkwPkSmBJOTF+cSTC8997cj7LFrx6PiYXna08/x2tf/Cpy7SqCY+ncGU5fuMBKVTAUWJxps6mu8TjQFVHOLx3yvRdu4NTWgZ4b03PhBFlUJn8mLjptD0iboHtWXatzl84zWMlEcSdtgvFtU6BIAJccuvEkSg2pga0X0ExCpCpsJyU0ytlBzTdefYX04AM58ejss18fXMzCGcOKOSZTjPCmbhLXb1zhFBUPS8E7Omu8s7dC2d3BjQZInegOhlw8tUQZRpTXr7Ecq0lgubSWiEn7n/Tk4zV6s2X+bOFoe387l1ZbPkuXMutC6Rc8PhUUhScRsjVDZodoLnq0ZezojGaljccBpSp1ThGREjz7uW/w6X/5BULR4wOfeJK1h87QklncRlgRx6KpiQkkXvjaC/g+1KMhzwzhwk/9WTQFS3UgR7pGoH71FvUpS81yReDRKvHyYWCx2ea7Bzf5+IdXOddXFnpGaV60gny7pySmuZycWaNSFsANA+RjOX9TsdGjc+kU4kvo9XAbUMRIVRRwMCIGSE3i9qt3uHt9i8ZXjHcGE2WKiOaEsLkhEwwOhoQmTPouKmhMGSydAIimr09ZehZPL+O7JURFD2t0HKYyP+C6Jd31ZQY3twGhf34F3ymIIbJ/2OCjkaU9/9oelzb6dDd6jPYSZ8pisveU/Q5rj5xhOKq5s7nNgxsXjg4GFKXZGrC/M2CGIuNYxYsZBsppImKb4+vvOE9npT+nBdx69TY7VzchM/L9i88+zfNXb1DgKdX4ibd2hP/5U1/jr/0bH8WXnjhoMnNo7sv/H3v/HaRZlp73gb9j7r2fTZ9ZvqurTbU34y0wmMFwAJBD0EIilxC5JIMSl7vc3VgjhWKdViEFVxuKDUpcBkVoBTLoRAIgCUeYwWAwwAzGt5v23WWzqjKz0n/+mnPOu3+c+32ZWd0gSC5HUk/siajKzM/ce+65557zmud9nmP3dBoRLKZMl2jm7lsAwFeewUYP74XuSjsyZNZ2OMT7UhyMUUl01EaJRjwsPLBGJ0niEyNxLOzwiDDq33b7vneonALnodB2BlsKWHQeON+aQyTQCR6hLrpUiuAk0nerWJ8T63Vi5KGss0YeTSoBFep6F+qHHI8YDQGMBEoCSY1rFe0wdTahdIFef8DCwnwktvCaTIGoqBDuXOBgd5tG2mRuZQFqSmrlo0NhvSNJMnwo2bj5Om/87pd55OH3004MttFCVKAc9xge7JBUExr926wurPL5T7+Pf/C7myhrEQIjl5M2kwj/MzZCIrUmwZLbFC/Q0hZvPCKBFCAE8smIhZVlrt94k6LyDA8HZEnGjY3brJ45Q393k4X50zjvwETol5cadhSERkgQUUxUwGhPKQqrwHiFMpZEIiRQalHfIJDWK3dQtRFf15oFCaTKUoWAV5GiPlZExWifr1XoBUPAU3rIDGRMwXIqUqZrIRcH1mA7lkdWrpPNVSxKm/c9s4Y5m4BNkEHB6WpC7q6wlvYYmyXGXsjLnP29O6wtLlAFaISadNRFAggUVHWOPdWaIIKXWP9klZ2Z0ZHoJEbepux4Fok1gFpIfIzqT6Mx4hybV19h843v0LQppReszUACV1/8Kpce/wALpx5EB0+lIpnFVNzOiMerqMEmCKI9aTARrkqkfhWv4mgqFdkJAwhRhJQQIakGO6PsD4RYWyUqYqaJRC/fD226Gc4MGoH5bsqHfuz9sDhHptq8/4MJv/HVF07Uvsxi+ScDycf+Pzry9COptay1FDc3Nhl6TaPVOhn5nxlaiktnu7TTwIPnmjz38hb7ldQUze901YKPrHzl/gH+1oDXslPcOX8WoRb19CXWOAw5V1/Y5sFHLNXLfcKLI37INvnSzjV6NzuEpx6oi69BhzpSSR01uue6T/TAC1J/T0QoqopHPv/D9MqCG996CaoIkyYEcu8wlfBc75AnkoT7V49gfLO9XaZXVr+u4f7OARc7h7XT/86+TA0bPbWMZvcq3ocgxz40/aY6ev/EnzC7ZpH4fBkP3gmoWDCuJEKOk0t/HGVTEEf56n8THaoAWM1fe+MlVu+O+YudnI3fWmfh3/l3ac21/9X9iBPR8ulLunaE6rXTe4bDHgujwIJRlGmDfHmO7v/+T6EXWtBskp37IMo7VDDotMXluzkvfPPKDEkwPcORO/Wv5zT9q7cj5/l7dYb/IVuogydHi0AMYx3NYyEvKhIgMxECH43fkzPg2C04yjhw/EWYEiEIRJrvaR+88PzX3uA3f+3b0F4ge/Yy11ZWedDB2Swer3LMMhiuLHj922+xNxrRDA2ylUU+8sc+wRuJxpXH746aeRjF7T38Tp/Gp97P2FtGCC0V2PYlZV7woO3x2DlDCIpKeY4D5GbXcTzwJLXdfIy/IARBfIgkYURo5GhzmyL3FMMJ5aiiHFYEAt3V7kxk14kQ0hRnEspRfuyEdXZ7OpgS6x4THQMaQqw39kSysGmPZ87kNMutYhDUppbmYgfbauDyknxYQlnX4ye13mOrQTLXQjb28S5wuNFDmQHjwvM764c8c76LNbBZlOhxSiPTfPvWIR85PUeDSKJjAog25M6ztXfIpQtnTzjWCFAFVAUqnFwcTtC6K8CYo5oupUhaaayr0grTTGM9Vt3y3oh8MI6wPwXXb+7wz37zOR7xI348AzGWRRQ/HRp841sv8MYH7ueJR++nMZexeOFoDT9ypSIjIiEwGOeEO9t4rUnujwREvqzwaYYAzbnIoiqVwx8M43wwsZRkVouXgio0upViW60YLKgvNfkeej3f9w6VxWC1ARUjC14p0iylaDQ5EMOgf8C5zjwYRaihX6mOC0UloAxoHx8khYqQQVUX86vI6BehJlFo1iuwQTBE9rhUAUooUWgf06ClVAz7fRa6C1HXQDRGokEvRFaXg7t3mZ+fJ2m3ooVQR0+0gA1Q6bhRJ9oy2d9F2yaPPP0UEhxznQ5FOWZ4uM/h1i6NRsapU+fAFzz/0hXEzONNIAmgxJNkTbSPRXyaSASRB48yUYS4EIsyFud9hM14j+Q5aZYxuXmbYT7g1rU3GNxaoBxMGN+eZ+Pmm8wt3M/lpz9MMj8HXuNUJFOwGCot4AOJKKoQIxqpEgod63GoHdjIxnycFUehXUAZat2vWEM2lDJmVVAkQWNMoFQK5SNRgg+xMF2hqQyomrrc6ugAxGCe0FUwlwrLFzuk1SHDyYTu4jLmyUeRlTZKWag89nCH5t0dHjYle1rTVwafF5T9XXQIpEoRxJMYjQ6R7tYYiRkmK9gQCKJIxEaaUlWrwdeOSyYWrwUVhERFXShVF6KWBKwWtAesUEx6bD3/CzywJqTaUDRhudFgLm3hy5LqlV9CL/8lQtqNDIEqUqho7anEoCVKHTsVNb+sCtHBVgbrA07rWGQcQu14RY0pRYS+qtoxDAoKKpp1JsSi8dpjQ2T8e8+3dxiskRXxvjNLzC89CiZBa82TT3R44dVr7O4fcvzT8bd3N49njHT1iTKtOL/U5DuvXydrz9FoJO/oyux3JXS7GYPDA7747QG9URRxfmfnp7aCp0PF++7e5s2nP852FRm2ps6HVoEkjRtpOXaIJJgW6AXNKZ2RupxqsE+QWgz9mHNHiNEMCcezR/eYxPd6NiLMLy6wsLICU6NTAv1XX2Xw1ltkWYP5RgP1+OV3XPvxF45H82cb9ZGdczxvEzuhAl3jmLM1rfIxQ6Oty7o+8d3au71aO8NTJ7fytZaDntUeRf4zg8LWBlgU6TbeMJkE1g8GXC0qDoKjSpuY4ZBmtzVz6n5f7P8JQ4kI6z1mIM3sb1GYw33OzDfRTUXaahLWztG7tcn8guX2XkVIm6ykGe32IqwVwNsn59zxE/5+7d+SR/Sv7Fj+T7Udd87fxVlSwPpz1+gstGk9scrIQws4Yva799NHx3mHS6WOngFdP1POed566Tpf+hffZe/UBdoL84z6Hq0y3jysOH06i2G1IASEa3fucuX5q4zv3mW+bSnTNk9/6n2Uq3MkeU4ZD87x51+UwlcVrm2RpmbXedYqzaQS8lJjvnqD2y/02FIBLx7b0nz2k6djXY140iDomh4+KTzV/pgktbTmWwQfGf3yUU7aSDHNBq7ee6wCn08o7g4QVRF6JZPrI5zR9CcVpfPkpefupOKH/8IfYn5pjla7ET01dRTcERfwhYvr2NSRIzpjwYM3/ugWqnfOSaVqEeBGSrk7oLQjGmeXaV1amy1Endl4KfK9PgRQPlCEgLKGg7HjpfVD7j/bwGjFzgTmFg03hwXX9sacXcxIyoSDouTj7RbDN7cYVyX9/QFVfwIiKKtRzbQmohGyi8sksni0NogQ8jwyPYf4t0nTaI9SU7g3UtLl7vTCTsy8YjChHJegFYe9gv/HP/oCo+1tfjRtkqaW+S68PBA+nw54YVLw97/4HP/X+87SWZnHJPZkZLFeo0XHcR4OhpSVw5We8TCn2UwxWcLc/ascH3Hxgmm3ZntI49IplNagNPnBDuHKBt5aaDaZrp8CKHdSLPnfZvu+d6hCbcppqKtzoBSP2BTbWoTCoU0DV291DQyVkVpINkYqjdERV6slZkTQZDqSQiiISlHK4CgxIUMpj1KBTBS5BDyGRAlOgxfPcDSgMd/FJJpYKQRKeUoJqCqwt73NwvwizW4bHyUFsAQmwWOMofIFWEsQT1CGEDSPPP4MjY4h0SmpVfR7h/R27qKyOfKy5OqdETbsc/1OTvfyWq2vVaIxZCplHHJ0aqm8IVE6wuAwVPVkT7Wmch405PmIUBR4l7PSSTlcv0lrMsJNRriq4qDYRwXNw09/jHariwRF0Dpi844xV0lNTp+gscrgg8cS9QMCivnWHFXl8VWO1QEvgUoFjNFoI1AptGiUCJmOkXFHhOhUIWYNtarhhrV6eqWjs6uDxILzEIVzlQFEoUNAV/DWz77GvFFcaLZZWGgSehUqTCBroILghwr31iHGJsy3LXcQKMeUo4Oa4l7jjSIVQzASWXdqan4tEb4Xld81BF+Pd20EoZgp0tU1YZHCPqA0ZEqjQiAYBQQWWiV//f/yJKfnHuaf/syL/Pakz/s/OcePPXSRM9kat7csv3x9TK66eDRVHcmxKn4/VaDEolVkPXQoMtGEEGu5lAhKhzqjFtABkqBRWvA13XR0SjVZMIiuKfGnOCGt3uuanMRV/7hTEK9tbSXlc58+g8gBVRn11dqNJp//Ax/kH/zTL1G5I4z+sS+fPMyx3wU4u9Jlb+eQb716i87CYqz3O9mT2W9KwVzT8rsv3Ilw4czOPq+O/Tc9TydL6YwGPNixfOPh9+NqzahptJVAhPIwBjxrD6XojhCWLKwmKO9pKItpNNDGHnNUpjZfAEmJ3sTvMZLHor5xNGJBusAMqiSAm0zQRcGF+y7w4cceY6HdnF2PUpDqQGaOYpxGBYwJs/rAY6N0Tw+iKauV43Nn36hJa5hlkuJ7npb1Rx//vaz5E/NazeDg1HsDdTBI6vlTbb6F6i5jOx2kHKO9RTtDqAJlmfOTzTn++NIK/8n+HlVV3nuC37sLJ+0TBsMBNmnQbiXv7LwCxPHawTZv7+2yOt7gwptv843/9L/mM2cW+WsvvMnmqOCvJAkf/1M/yvDzPxaJz97FgPyXtqkj9a/x7E+PLyf++td04P4n2oKKUh+69rormT4FR2QUMnG41OElsCGeBSVI1E+BYzbHDC6M1PP9mFslNWt2CFEGZpSzt77FP/mlr7EoTUhTFh5/gCS1aJNgTMJ+qSmDItUKL5reYY/r33mL4RDmLy7DWPHRP/QJ2ksdrodQEwcQl0UlSE0x48Ylu996i959CzS0cBvNA3j6hadJYLi5z3gslOJZaGmyLGF+tUtjoYPPq4jAyOKc9S5gU0uSJXSXuiCQ98eI83SWu7SWu9wajXltv8dHYnwEYJZJ8S4wGue88OY2AxcYuAo6DX641STLUnx1lPaajpsrPcW4qpkHj824GooYjmXJuOd5EBStpo3svEVZryc2ZgjvqduJy4QQhiXNViSO2DocMFGBnjhGuWNkSnInbI4dq8FzbWOHvcMJPZ2R5wkHPUdzqY2ymnJnws7+hGrzIJartDOSM4vxZFajTMrRKkfU78pLVPAn2PxOihZPo0PTnxwNiJ6SpWiub+zz+u1dnOry//ELlIOEbOwpAlhdoJlgXl3nK8+/wo92P4xzUXMz0dP1vj6dVoQEXr29i/Ka4cGI9Td3OH9plfnlBidrb0EZhek2Zn2a1cOiUD1LCIIPvgYgHNsTv4ft+96hsrr2hnWMpkagGxiTMcoHiHckChIiq45TEKeeR5t4IzwmMtIBaEFLAIlZjSkhiq0N5khxbqLKPUKmLZ5YP6OAYjhisTkPWRrZX+oN2CiLq0p293bprp5irhnpzNE61tVIwCYWB1ROYdIGyjnS1NKeW+aphy5BOaazukTlciTv0VUDwrxF2RTVEAZ7ntOrlpRAFaAoS7JWg0oHgo7Cw40aagM+UpvXE1ErUErjvWc86FOGwNypM3Qy4YH3fxYXKvb3d5n0ekyqCVvXrvDkJz6HshHulyjBGEPpAl6H6C7U9QFGQRIiXAwjJMFgbYP33TfPrf6YK1slSXDomhZdIYRqGn0WtIoEDkarmg40gAokKNCR1EKJAhNZBitxKGNIqelJlUKL4FQgNQqlFS+8vc2HTs3TWOiivUdeeAMRiwSHYNjb6aM9zLfbdDNDajTloEdxsIOizhAohfceFcnDoxMXNEbHc7kQUEQ4o9GaUqJBnikIouv+x3qroDyoQCVCgq7JHixGPBfmhnSWLzDMB0h7hV4YsbWYIa01bPsxmqN92nLAWE5FqIF2eBOzsV6gVIIh1lwpoyh9LQ2gfaRlZ4oZj5kt0eCJjH+RcXa6IMcyau0tXlcYBTrERVf0e9sYmjY58b8wHBzSTe8QhrcYDVNSM0S1H0RNCsT5d4Yxj0HQjo6pyMsQ2TVTw5X1HZzzdBbn66zldDOod3GJTkmnmdDa6bHvE1oNe6K25R1NxfOcdTnlpOBrlYFGFt+qHbkIWc75yLOQmoqDjQI/cIR5xeTGmOFzIxKgowzrW5ts3l7n/IX7Z5vY9GCBGDGeGdP32vN1ndZ0KAP1Opek6IceRCoXr9VoPnL6LI+vrdFM7cl6MFE8vbjDD57eYEqXpZXQMsU7nBxOjMtRJlABDVvS4GQ7qTl1fDzvMevl5KeiDVbXxIkwE45R9UG9o/rGP0ffdxnz1KegKlFeo4LGe4cT6GrDuVSRaU+qhSOKqnfc0eNnPtlPga2tLRaXVmm12ycTRPUvd4oxf/+N77JXFfwf73+cZqdDKygSVzEvQlg9xeU/+xMkh3dicPHY16fHU+9yb9+1W79/j9/lve8fqN+0Xb+zxy/cTSJ8W+I2O/Axbxl3AiEUgWJYMLw94m0j3A2OalzRGgyxJhbYz6b01CETQOrsaA1t2tovqapApgJvvLHPzvP73D5sMVhYwJxP8Yee9hNL6HYDZQ0DJ/QrYTFTjA76XPniSyQKVi+vsvXGDp/70z9INt+OTkUtU8LMGD4KYFTDCWUhZJdXaGpFUXqs87x2mFOMxzyUFrx9OuFX3xryX/yJD/HoEw/R7DbrTMrUQ4sXZ61mcXU+Zkym9VTB14x5EHzAVx4XFJs3DhgNhNGowImjyh3V0FG4wPakpLCWsw+eo7XQouwXHOZHYEuZMXnGALrzUyfrWOALZuN+tB5z9JfUDL5LbdqLnfiOUrX9dg/huByFeBpnFmI2LAReeHODftPR0Qk+F4ZmgkkVlx4s0e09GE5ITKA0FUNRlE4w7RRjNcWu4+03rsGTD8e5NSqRcYlqJHWk7vi1xEycVJ7gAhLCsXEnQue0Qhld1/cKwXny3rhmlxaKQT6bg/3bh/zHz5xh0onEWv/4ecftPnzq0ZSPPTQHUjJnclYnexSVozj0GKM4dbqNSUwdbBUqJ4zHjjP3zbG/N6FjDfc/vkazlc7CB+++t03fPU6QEo0bPyUdORmp+Z6173uHSikQrcl0hF6ID/R372Jcn+JwhHYKlw/xKtAwCdOYhVYaCUJeDhj0eywtnyHVMXJSGI8NsTDQ6ki5qakhI76kkWZ1fFdhRQEGnKOcDGlkGe2sRSDUC2CgBEI+ZrTfZ3X1FDbL8AGchYZE3SFXM5WYEBiYQCszVOJJbcrlRx7BpiXKtWg2E/LhkK4uuTnYY2sfUtugvXDAmZVlPvr+x7hyUNFXhhEBnSaooEmSFHxFI8uQsqRU0aFsWIuIB5XSSBVVUeHGhyzNr7DUbaFbZ9n3YMVy+twl7INzXH37BbqHA0wWIy9WG1wQghJsvcA4BKuFhIjrRyckhlrPSxOU58vPv4EXTXNujqAiYUNCzRqX1ppN6MjaIgEXFEYpFLqu2dGgYy2bRpEo0CHKFEutc2Xrtc6gMVpF2m9fsZRqzs1ZTFeTdAR9sYMyIIcl6sCx7Cz52HOn1yNXJUVwjAaHuGoCrqTSmkybiAvWkVpbKfCqwoqpndZIsYyKYrui6+vz02Uj4EJ0XjIUIUQnSymFUx6rKnDC1/7F1/nVv/MthrtDCgd2XlCDJl87e5WvTV7n7q0J/aWPkj79IIkxOF9jwzVI8FG4Os4uRAIGIVWRUTEohRGNq5ixpCll4vyV6NwaHee6rqN4ogSrDBaNkkAuVcTCvldb7Rjca5SKCDL0qN95G9Xp0BiUGKkg2SNdvRCNn9qwltlmIOSFI0mO8OqCsDcsSJXm6QdW2O/n7I6KY9kfqW0WxVon4YMPNkhtitvq8WuHNso7HAsiHnX5aMwzq3n8cIedIKw3OmibHDmHdT9DgPWtDf7DP5/SUhPaZztYYPcXNrjy1+5gexW9TDEeW/Lx+EivRR0ZF0fDc8wcPuF4CMbW8EWJtMjD/Qldm+CUJiwvxs2eKMK+srxKmqbHjgVT+HOqHPN2UBeTH7EMHm27xzVijgyGo76+OwBTTrx45Ezdmwk6dknHPjM1sKiD36o2cutMb1mAr0A8ygu6rnYvx1FAs0IoxPODq11aN95iY3mZfrt1rBe/9/mPVZExGg7JstY7vjH1cUtjZ5DNVpJgshatLMWkmiWjGXpPa28f04gF3bMjT/3E6fnqRMV03O8dtd9zqH7P99/D68Tv01780gZp2ooGtaiYcSLWa0/vXVlWKOPo7VRRsB4gxoNnbJO6DiCEY6RAx0WpJYD3QjbXQiQw1hlDtYLMK7aDQnY85cYByf1LtDvxTlY+sDMukVHFxjff5DB4Tp1e5OAbt/j8X/k0aq4zE7qNTyd1/VdtzCogCNV+j2KlSWO5zR1p0BZFrgKDkNAthKyIYjSlj3pDeeHphOhSBh9iIM9P6bmPZr02muBiVsUYRTGYcLjTp+yP+NSnHual20P+2S++zASDr+G7MZ4RZ9SjD5/j//QXPovVNiaQj0F8pwuYzDIgx7JJ08yf4sQ65iTu3TFWEu+HBIW2BpUcY1VVKlLQA+8QlA31k6VAtCJoReE9zSxw5umCPXNAahRzq7EDi6eEdleQVkWVBnwR7QtVefr7Q157a5OyimUM4h35rT2wKtaaHXe+65mirIpaaNM9ysWJppPoTMXsevxuNSw4vLGLc7FmLUzHT8H8muX0vqFsBS4/AK9sGW73PR98OOEnP9Xm+esZT59t8cr1hBkphgiHw4JpQZoCKhcovbDTK0ESKhHKsqQoioiGOHYPjg+lQmi321hrj2JKEhkFfQjvWHS+lyvM971DZTJNZnRNoxuNeK8gXTnDwgPzNFRAJQ6tPGIaVDhSidF/pwtuvvpt1N4+cx/6EZLlOZTSJBINX0ysk1LWUYnj6ou/A/0RZy9/lM7iUtSRsgarPJPJgOAKDrbX2S1zkmaXsxcfAaOoxkOqXsHqmbPUNcR4KzSwmACOQFKrYFN42raFQZiEik7SYqGdMjg4YHnlPMF7qskQ5QM+eNJsnpWVVTrdFs889BAfe+IS1evXeXnf0TQJ2iqoSlpJi1wqssRQBhMzZ0qTJAnDMicYg1WaRFvG/UMWlpfxIZCKJsvaONF4Kcm0Z3iwx/z8CmlicUpACWmItWbKRDIJOyUpCAqxkfkuMSpqeBkQAnu9G6R2jtbCEt4oUCHWDaHwSmOVQgfBBUVpAsZEBfVUJyhRtTCyJogm1CJyjaBBh1rnSpNi8EFq7S9FxyieWZnjvPPMLzWRS13UhRaEHCqH6gjYQKI1yWrCo3oN4xf4rq/YvvYq/e1b9Pe2aa9eRGwA0QTvMQKlMogYKk103PAQdCQ8mUFBojaUDhE2FHBYIr271tHBiXTvtUmjodnM+It/+c/y7a98lV/64kssSMK/+wd/kvsuP8PN57/CT//O32X+3BweG53XoHDO4cZ9km4XqzReIkW6ro3CaCvH/hQwc5pSraicxMyZ8iijSZTC1HWGg8mIRpbSIKXQHlvDQVJr3vX5fM+1aUBYYFw4kqBxBxVlPkAOBjAZUc2tkndTfH2Pj5uaPgjrGwecP7NIltmjSLMPfOzxVf70n/g4dw8n/J2f/SpF6U+cWiNcvrTEs88sc/WNHr/21iaumdzbvXv+FkyrgfWe9TywNzd/gv6WOqMiwO7+gG4nwVjD4b5n9UKMXvrcEfKUptF8yDZ53PbYcOUs+xENagPaYhNLqGuyTjhVHBn8moopzXqRC4dvCWdtg+DCjMhDoTASSHxO4jSiTZyEanrco59Tg/7kdR//+yjq/W6fOe4GHsWfT37lHY7AbEc/ijrHSFwMTUgA/BS+OHM/4L5HMcvnCMGjQmQzC5Xnyy9s0Vlc4lyry3hS8ScvL3JwfZffvdRj0G6fPNeJa5hewbFxFsEfblMmCnhgZggf/7Y2mjmb0NYJXZuitWZhuYHc1+F9hyucwrPQyTHzrRm1NLVRNj3WCZazExbOsRkv94zrPdbMv+yKvt+yVOfPztFqdd7x+lGoBbR3PHLRsL4lFE5OjsasHu5YlnD6Qn2k6b0oK8fdw5zJYcHaxfkorxETIeTjiq2r+7hx7bTUEYRx6fjO87eodoZ0zjTZ2Rnyh/+3P0KiLZWazuEaZogihjP97PXghfI711h5+iJpp8HGRHNKQz8v6ao+3/2Hv81XXr3NYeXpKnj1t95m7/k7/MBf7mIaGdWopNmwJJmlKh0qtWijcaWj1W2S9ycUwwJjNd4HinGBFDnnznXpzjf58utD9gsfUTComkRCKFDkouvssTpyBurBl9kkOzlXj7hW6+dHjp7j4BVFFWV1jIrweO8C7aIijPJ3vf9uXCGFBzUlwDhySCEG+wslHAbIlrocHMZykIgOioRpJtPsji2+ziCFShAnfOG3XyUvKnCeoCIhjg9H4vKzGaIVYjWq8viN3izjJAhFajHdBtlDpwAo+3kNiwSRmNE6Pmuns7OZpSgrmJCTJAmdVnw3iEIbwWYRzh3ZK0O0fQIcHBYR3TJdT7QiSRIyiQHANEmYjHPu7gxBhdo5OoqKqXrqaxQPPXCBTtfOEvoicsyZCpxceL53K8r3vUOlJMKpYlbEMxbPuL9HORqzW01IC4HFM6x6Q2IgwdalyIEmhpXVZcQmzM+1QRscCmsStEAioLCIjgX4S/MLjPo9Xn/+C1iTkJkOSTujHI8QUbS6Hfqb10iVx7bXOHv+YSb5BFVUrJ1bxagUJfGBgPggGQGLRXQgCYZhNSJrNEBDp9VmrmEJkx6JSmk1M0b5iH5vm929Q66v79FebtAf7nNnc4eVU+f5R7/xTYZ0CGlKM02jsKuVKGpMgtWawoKUKhIUGE1XWVJjGXshSRP6vX1W77tMiwnGRop2hcH7jDZ96N9m4eLHMEl0BKoQQEMiGq0j615QU7UaicyHRHiUr8MeLjjy8ZDQ7rC81GF7OMa5EgMoI/gQoydWC0pZmpKgEEoVcbNS33uvat2qmk6hUoHEHcEsMJGZTBnBS7xmRGilCarbwO0UGGtQKylis+hU+RypNPiAKx17wTFs9DjY28CPRhxs36a7dj4ux0rQQdVU5LG/MQwXF6RUW6o6gxZbHa1TEbpoNNGJFE1FrNdzKsYGrSg0hovnl3nqo5/GBeE3fucV3vfBB3nyY58DnfL4D/0R7v/NL7EbKSJQmKgDEAp2925yvnWZYCM+Wdu4OTa0RvtpVtTGzJMRkijyg61ZWzMUjgiXLbQnCQHp78HSMipJSXTULUsNFFOA+3u0HUX3phEyYb8/Yk57Jsun0BaYP4O4Ej+Y0L50GfXC9tH6fyxyVhSOECKhCsQIm0GYDyV2+yrLcwvMZ5ad8gjfrxWcmU+ZL3b463/zOvulIV0wdbT6uAswdQ8iVDRrpJze2eZm0mK0uHgCNjczylQ0tLa2+/zo5wytRsVeP9LeHn5rwuDX+txNKvJS0fRV1CATIc+L2rqro9yVxxqNOUGb/s7NS1PE2s8Yl+SyyREavP6tl2A4wbZbnD6zxucfuMQn8tuc/9Vf4Gb7Ai88+ZHaWD/mqNQe3cmk0j1k6vdC845d/8n2brHL6Sgdc5zqg5TO4LyuHVKFBEMQAyOh6KVT/yoSdChBm0Dzo38UKbfwWy9AUcR6TO/5+hub4CwtZRjlE7rOofIKNcpPOOQnr+ueX+tMaKOo+N+MhvRai7waPGLuDWYIzbTBX7n4GOMSznYW0CtneOB/9yfh1DI/vHEN5SaoC0+h8cjNaJAcF/WcJl9jhP0el1SOz8mjc077+C8d7uMO7PdZsspojZ0FBU42paJD8sh9GZ/7A2f5Rz9zAz+qMz/HqdNnhvjxL8cfx8x/MmVZ6maMcwfNLIrK17prqiYZmvRy5nwXrRSh8Lz05VfJX15nZDQ/eP/DfPyPPol027hJeeTYqbqWSMFUomD6Vr6+jeQl/tEzDCXjZuV4nza8PpjQqITtu4fsjz1aCQ92Mi51G2gFPq8iE7DzeK8wThGcR5tY8y4+RIp05/F1Teo0IxaCp3l2kY9/8nE+/ic/yfoLW7z4d1+g8MI4d0zw3PFAWfFbv/BN7r98P0uXzsawoRwftZNrxAn1t5nzpY4cMKNhuUvDGJI0RQ1GhLxAj8ZUk/HR2jT9ngLaLVTToCqPquprItSINQHROA/VRDOhhbZx/Zhm2ZSKkM+J1aROsCIUk4Ableztj7mxdchwkjO/2EKpQJiE452P15UkmLkWUjicHc6IIERFB817we8OQYGbVDVTaXyetVbMne1gs4TDuwPKcYXUUj4hybl4XwwYqqREmXhcJcIH7hMoQZt7gCo1yVYcHpnRtgeJjp9W0cG6cK7LYJyzuzeaLeUasEkSWVpDnZGaOcIKVzkkeMpJye6tHRSa9lKbtNmYOYLfi/Z971BpncRCftEYHSiHY3bu3oWixB+MGDvBBUEO97Bz98XMjK7p0kVhbIKYlKA11iha9cOhTdzmDFFgtkTIGvPQ7tCZDCmqEYP+HmpP011YRFlFM1lAL62hFNjWMuPJAKUNC6trJDpGI7xEVjrwWIlLp9b1gyygsgQSgy8rmklKUzmG+YDu/GkEjyn67GzexNhFzp9aoXvqPEppOt3AZm9EYhPEeNJUgdUYBGMzrGgSC4FASxnGiUa8I7WWka0QCbSU4AP4fISlYrC3Q5W0kd71SC5hDf2qT/9gwKX3rUSl76DxWrD4mAlCQEEaIgwwcoRJNMB0oCDWCKngadgUbSxnFjSH4zoKJB5VqkiSgKLykU1PicLUUYyo52YplZCYCDsrRWMVEQqopyrc8fNRJFiT1VpJC6nQST10PObcAmplHvQYnTaQUBIGHt1wyNhj85yF0tHfvI0aDwHLcOMmPPFRghgsQqHBakWqdNyQgqYikGhIFRFqeIyOTKlIQh6wBDy6hoYkdaTZSNTbEu0xQEWIMMB8RIliMKwi1lxHaEJVViityHRCGXn+SXWCLUvGk12SuTNRb8eYukDVoLMU4wW8Q3SFU6HWVAs1IELjAogWquCj4agC48E+i2srpFrwQKpNNJ7V90774Xvd3n35jYawhEDS3ya9exdvm5iqIl1aZpwlM0rxEwa8Erx3fOp84H0PRNJ+54SbO5ZWO0HybZLlRT730XO8+sYtJk4xKQNnVtqcX4Of/9IGeZqQttRJCIQ63jOQEHgcT7bQ5NV9jba69j2mG/1ROXw0lAXwNMmoCkezHQ9oRyWLVYNGVaBLYZw4nrQNvjke8uK3vsqZ8xdiTUMdMAjlKDqK6t046e7NXAjiK1Alo1Bx+/W3qV59g+bjl2m3LvHpZ5+kzeOc/vKXUHf3ePGJaIxqiBIY0xDl7PDHxvt4RkbF7PMsEl3HNGb35J7fTt74eCB17LU4voZbO4ts9hoz4zKIZleanPc9fKlh5jCDCgF1cBvKR1C7L6OufRU1yuMwhEDqHVKUhKqN9xLZt2RKaDGzaY717fisPO5QQ6OqeJ/WjCdD3qw8lTaza5/+tMYwZw39EAl7wriHXVhFicHtFdAbIsUG6vFnETsGNo+d4SjqLSf6cmz8Z5Hxk317pxc4/c7R62r6/zuu+R136D3XZgLY90QBIoucp9vM6G/3GQwqhGQWrKD+zvHxjy+pk4Ge2cuKdjMh+DLOoxP7i2ASKCcV3TRF+cCrP/9lzoQxupHw+J/5MBcee4Chg1EVyx/mVbR1Yq1WTUigpuRDdUbicIh64hLpQkpPaVIV4Xd7XnhAJ/wvLi+xcF+C1gGNYaGZ4ERIvIt6UlD3dbY8zF6jTk6ceC8I+IDRmixNWKgCjQc7nP5zTxByz403d1k+2wUU5SSwuz3GTIbMJTJdAo8FX+rIDNOAwPF7M/tttoY7o9h2AatSBnlFxzMTQpb6fpyoPJSa+MqAquXwQgiUZRljT0pwXvBKx0enZtFtpI7EBvLSTjuMMA3+Qj7Kyfs5lIG8LMlDxUI7gSTgRtWsPyIBnVqkCLAzABHCfLMW15pmqSLssBpMZnNtyvo3fRyn2qCq1v/SwMTBL76Zw23DpJrw2h3Q2vCLz+/x+m1hrqNpp3DudJNz6shBm81HiY7VKAQGUvDKjR1Mo4vP4KVX9rhwRkeR3imUAlDG8MD5U6TW0h+M4uGm9ckijIZFHHkfWSDTzOBKj83C93QZ+b53qEzN4jYxcRe1jYzl8/ex39sjyzvoKpA1MryBalocHQLBV0yqHE3AK8fdzWsgQhY07VPnaDdTCl9hRVMoQdsQ4VRYFhbP46VgWE6gFNqteUQHsmaHfLyHEk3hClJtmV9ejIudrqFwQSLxgNLx5mhqSmqNEk+qE0QbBEcjtfi8jxZDp9um9DnFaJeD3T1aKwvsj4WFZpO9QUAlluWGJWt2OBweorVBG4sXhbGK0sUQgtR1R4hHKYVXQrA2ZlCMpiwGUDkaC6tYJrTOXsb7EqsseVWxszFkXCmy7jziY2bCKMGHaLDFuhtNpTxBeUQpUqLjVYUASlOKYMRT9rZxeclLL7dIGqsopcjQVCogAayK2kllKLHKICHWe4lRaBxOJEaxxEeInLZopahEoUIsVAooEh11nUQcTWN46OwiLe+R+SZ6uQPtNgQHnQY4QesUUo0aJihS2nstsrvQWTxFyBqkSYJVnlIbdM2GFMWFo8MsOqBrWukiigKRaChFMwVUxJkUYsZU+5gaD3WEUNXSNRhEhK2b23zrt3+dr33py6TZIt/99tv8i5/5aR593yd4+1u/y8uvb3Hhgqlp1+NcE3E0kgDeo7XFSGSgFGWotOLDl9ocjDRvbhwgAZK6sNaYuODneKy22KDABEoVWQCL4AhljqQd9MyckmMZuPdou2cVLkof8eRJIHnw6RgEeeQZtFHoN1/BaF3XUFEv9syMTC9CwylWbRNlFLqZcff2PqgJsh/w5RYXl5s8/MOXEKWZjA74+jdv8t//Yh/VWYiC48C0EP3I2I9RujnleHgVNq9NuFOW6LoG56SLcwxOVfcza8AH3z8Gl2MkABXKB6zVpEAJtLXiTzW6/OJglzJ4psxL79ykfu9tq3alcC5QDIcE6yhtnNSh8oRrV9j1BV/sH3Jq+xpvf/c6ebfBHzv3Kp1WjNoaIywkw2OXc6/E7/T1+OrtvZwbd0d88OF5GompR+Do/6O+nTRQEZiMLcNh1M2TEKU3XND0xhofZCaP44hwclXXR0ZHLNbH6FChBluIK2HzdZiU8d4FONgXgheUE7SLhpYfVxGaFAJ4wQQhJOZEHYac7HgcV4n9WK8cbSVxnXuX5q2lyhISyeN61l6C+UsoY0jOfIRIuqQJkzE0tmf3TMnUuzzuKNWemoTaRq2N0xM+0dHn73Wdjl+JiDAejTk8OOD0ufN1UELV33tve1RSC5YC+JpcQStFCLEeWPmKRx5f5rnvbDIZV6jUROYzqYV6dVxIhKh1JAhT2jmROkqgNcELrgrYRBMEhuOCNLWY1MRbpSFtGbTzbL5wBcYF/nDM+OkHufCRDuWZhCHw2mEkEUiM5gcWFpmbJmyOPTJG1f6Oc5SvbVL+0P145XhlnLMC3NgpcaWw8d0bZP0xCy1IG4bBWKgqx6QKMClonVrBWEOSWqzVYA06sWgbIRo6tZgswZYem9gIIwshOgrO43pDhncOkNKRtDReBbKOoruQQNCU1tHfA6MFeyyrNnVQjgd7Tviw9d/3ZgZv9kb8oy9/l9WFBe7e7fP0pWU+cCbl/nQZLfqYptXRYIXDyQx+i8T5EOubYt1x8I5goqZWM6uwBi6f79PJKl65uUhexaB7ZKuO2ayyKvnqy2/yW6+8QlE6vvHqDT5/bjkSWcnRohDrJZk5T7MHU9c30E8Lt6MjF45lmWc1kyIMtoZMyTt0PUjDUnhl3ZOpqAt2UFlOt1KKYSCRQKuvGIljsqhOwoSJzlR0+ISvv3SFzWLM6zdKfuhTj3P6zBz3Xejw27/6Fo8+OU/SULP4gXjP1vY+Wmuc8ywag3OO3f0B8wsdDg/H0V7MEuaX5tDaEFzAFQ7x37t15PveoXrr+d+m0WpQBqHRbOCCY7x1i2J/F8Y5o909htawt75OozNPUY1weYk3wniU88wT76Pdgm//xs8xGU7wwZGYjCRLKSvP4twKw1GfwpU8/OiznDm/zMadLcqijCLA4mllbVbPnY/GPtDLJyy2V1mYW0SUxovHSDRMHAGrNUapKJGg46OuBVyo8EbRBBKT0jCOIu/TnltCGcHkI3q7m4yqktH2dowmTHKSfMxiZ55O1iCksL95l7nF+3EKrEBqEsauwiYG4wOliZCB3FcQDI0aRmeCJR8c0O0uMjffYTx0jPZ2UEmGt2Bsh3JckXXmoZURCBhRKDwioDFICDNaZKUMGVLD/ITURAPFoHBVQWftIl5pJoMdKt1GpW2EKI4rIWo0ee2xomoYnIuGbPCUKmAwVN7jdWQvNCqgBcrZ56baYx4thqDA4LE6EPZz/O097EPnUCaFEJD+IaoYAi3Y3kfOnoEK9IGQj0cEEawEqskQvMck4EJ0fIyKdOQQhYgnSuhgMVoog2CxpESad0eEVDigCo5Em5h9E0EwpAioKAhgpaJRBf7uf/a3ccHQeOAZNrY3+Zv/9d+j3fhZqsphkwZFUZB4T9AKQkLwnsSA9WMY7NGd75ImNfFEqHj1lbfI5pfpJorSRyigr/wMm54iICWVj2yW3hdMevu0g8PYJGpooTDKzCJu7912b98Vw7wkd45gheAqlI2sUwSHCQ49zdpMvz7NEIgQJOCGgvSjBpqQs3MIi/MW2YMXbmxzMNfk6Q8+hZaSL379Gs+/Msa2FrDHNvd7o/ciwpo+5EP3r/LanT53mik6iVDYIzAER87HzK4QLpyfcOGBBs3GBJ2OCC6hzAPFQGO7TR5arHh10GffK+5IzkAFTOWiNp2dSj9Mj8YJ8oJ3jmB8td8bcfk73+GPyz5/6x//Q9zNHfTogGq7z96bb/DTX/wiUUDB8FTi+IvzG7Ratl4UZyY+Jwfi6BRTQ14Efu5rm/zUr97g1/7TD3NxpVl36vgYvguwTiJN9WCUcHerNcuOjYKiUCbWM6owG1lBzTSnojMlMzIKvEcGA7j9bRgOosMShDIP/Jc/f4uiH6ICvfOIgvXDnKUAwXnO3l7nI7sb3PjoR3ihMswq7pGTWbm67Qv8R5s7/FUvhKpEmlEIM0KGDChFaLZ4czzAlWPuG7UZ/tOfI0sGNDtCMBbGHhcs2raohlF/L4RAmZckSYKxmrQsosOXJJwe7HB6/W32Tp3n6umLcUTrifCvRDQhR8/KndvrfPXLv8X/7C/8JbI0/f2/+x5pzgveeZwP9AcT5roZiTXsHxwQfOC+lQbtdmBjL6e7ULCxo0lTy2A8IU0tzWZKnlexpmiuhfeesjdEm5qaIktJ2g3KsacYe7rzCc57xoOStJWSmWZEZqAQFfCTgp3rN5lbbvPon/gYpx46x2RxD60VhZIj4flp5qWe2FNtI3QMtCnxuFt76EaKum+FiUrZ8RWrStgWYTGD8pXX2d08QKWG4AMTF/e6SRCefH/JuXMriI81SSoycDBjEaxbY77NZHeAyRLS+QbDvT7iPeogZ7y+j+tPGA8dVRkIlTAeOA62hiCKsggUhSevhKGrj1/XDknNUxufoWPrZP2zpQ3JPWvtXvCk8/N85BOP8ItfeI2Hnz7PpLceNbHqdcXMtVDGnFxzZ5n7+L/NSyb7gzrrFvBBY1E0U1fXZ0V0odbHVrq6L/k4Z+/OFuP9fQYHI7Rp8au/+xo/8PQl0qRRr18cC8LUDMjTa9WQppYydzNC0ilL5NGlTveO6Yj4Y1nW2IwIP9Zs8VgwDET4G87xYKeD9oE/fVbzzJJhv/S83WlGZ7AuAvQuBpJCiIHv3d0eQxMoKw8SsNZgkhTvFCJ1uULdtyCB/V5vdl39YYQp5oXQbDdwlUNrsFZTFSUqKEa7Y9KmRdrfu3ru73uH6tf//n9JotNYw6IUSmLEzqPQgPMOpYRbN19HiKK8AZAQSG2bZx55moXVUwz622zf3cEYjXeeBEWBYsNcRaoSqxKeuPwsi/NdfvdLv8De9iFlNUEFRZokLC6tQrNBYjIoKz7wA8vk3pGQxcxQrcLtVYQbJqJxhFk9nRDZdRo6o8LTSUC5MUaE7nwHgqcoRuxt79C2hqA9B66iv3sXZWC00+ew57n81GUaSYbSCheERmJrHK0mMYZyiutFoZXFEPW3ggro4NnZ22BhcQWro3bM9uEOrWyOpN0m8SN6g0NWT9/PnKkLJ330CqdZIKsTIFDWJAy6VvwWLRivccrjQ4VlwKmFBhWK4Cs8JcY08QjGgzIWcVHctqwjvcFHZkIDNVwy3nMjdXzeR7FmpwJKe0Q0VRAyPYU8KRIlpK0Gpm2xnQYkKWIVkIA0oCzAtBCnUGkKyuPKMfn+PnayiyuEHp5yOCDNGiRaoxUUoggKktpEbCsTFxeBTFPDpAxViJnBhEi7nutaL0oUVkNJRahhF0nQKJVgkwaricXZlMF8l8P5RUzRxweDNRFyR9ZCaYNBYUxFMtpBZIKxc6hmk4lPqXwUSQ7jHuPdW3QbXZRKESxePJi42Iuu9anQaFPFiGleMNjfoNFMkXKMbc0RtMIojwmKoN67S83JDabeWOoIXhCF947gIbz+HKYYQzfCTI6+Ew8idaYqBhcCiXFRtFoU2oKxFaMs5W99eZ2vvX6dxbnfYrXV4P5Ta3S63RPs5EctvmDQXOgaPvPsCm+9ss3rhw2aTXvMmXq379ZGfwg88uCIH/rQBd648lzEwVPy6n/1BvtfGXP+UkpPHL1g8F5xsdPix0eL/He313nj9Vd4+pkP8PtTex8f0PjDBVgpSz4+HPLff/mbBIHEhxpDX+uuYfj006v82c+cotGYOlPTi1H3HvJdrg/WdwrWvz3hry49QPHNDjsfNKytTTWe7rGUpr8FIR9FZs1ioiiOrcNeapiKrqGE9eoR6vuraghlRGoHzFyKPdWEtRVkvIOeDGM2zgvjOzmbm0OeUpY7YcJcqplPmjil6DHhNzev8seKJR7Me4xSiypryMosin7PlQtMyoKt8ZiD4ZDBrXWyx58AwOiE+YW1iAJowc9MRjxaHPKx1qNkH3iS5uY30cN19FoDITC6CsmP/yQH13uot3bAeQ739knQrFxY4/TuDVb2b7FoLcUTzzKXneeQBtNS+6ljPbsRHD0/x+/P8SsQFKPBMBpT2jB1iOHkc/hebCGEmrzA4yqHdzHYkecTrFZ8+rMX2dqsKCrP2XMpt+8K3gdc5WPtsQ8456mcMCk94qPzYG1dA6MCOgu4MtJhe18LyYeA8wFTOowEqt6YMB5ghoJNLK0Lqzz4oYukyrAewoyFl5mRHc2Qaa7TH3uvo6LQu3/lKurcHFVmWC8d9ycpjeDZHg/I3ryJ7I1JAqjaiC58zBb5ENcfhYrwMkWdjaN2qI6lNDSRXMzEz+aTgnx3jL19wLAs0cbwxnOH7O8X+BAYFSVeQx4CoZnyyR/+AAtnlsksx2YozHIt0+J16kUaFdkMJVC6I8dEROGTlCyJNehKKdpzLaS0UfPSCwRF2swwmeVojXlnEEwbTX4wrLO7qv7IkW6jkhiLPB6YikyLcPfabb7421/FlPB/OH2edtOSDiZ846e/wPv++A/T7NwrCAHHj6S1prGQUm17lJs6TMeCNHLv3hHH5HjoSQG5hxcKzbqHCYFBgCv9IVoU/90dYWnPoIJmJRvzRPDoJI7Ji7fvcrrTRWuhDDDKS6RlUUQovNIKYxQ2JY6P17WUETMijbiA1G6iTFkJPUVZkmhFkhrKMiYspHKohkHk3bP2/zbae9fK+VdtOhITxN3Qo4Ii6Bg19KgIuQkaI5G1zGmFkgoIOKmogiDiCaEEKvAaqy1eYjbDVwGrPEKCSSBrNEmNZTLuYXUk/51Ujupwl05YIu/dIVQVWzdu8egnIwuK1Cn9UNf+KOroEIJRGhUsWiqcGBKjCcFjjMeP+jTb83hrCPmEw+07HAzHtBqWrN1hks9TYZnvNjnsj7BJidMpKxfOIiZmcrRJSURH9rY62trERgFdHTWeElGUxlL4itHeLpdOX2R8eJfrdw/Y6/VYXjoL+zssLy9iTMr8xYsEG2m0lY0boiXWQKE8PkStrwphogLKBxJlCEaz2vB84ozh/oWzZE3LIPfcubvP1cOU13oOJUmMrEigUIFKKdJ6vJSNxo4H8iA0DLGgVQloTSWCNVNq9ShG2zJRnUzXrxiRSKbRSKBpwRpIEkjmYnF3BpQallqItiglFOMexfYNRCqU06jBPgd3b3F+YY3KxM0uUZq8dkKaGjwmziGtSRA8mkIgVTEq5QhYDC1TR4WCJgRoaB03HhGMiYZ5Y3EF3dAMxTJKWygvjPOSVMdNtttdpbWwhFKKuUxxsTHi7niI7rbw2QIuyahEgbLE5czh04ygEiqgJbE61iqFE4kOUm1MIgZUILMtTp15kNFkl9Gkh0lS2t1lUAZnQ2RXeQ+3E0bfDKtdb27KwDMfJ00baKsQrSLDUv09OXaQIxhGwFeB/bxE6YQyOPIAd8VzezSkKHvs7ggL952n3emccIzkRKcEXwU+/qziA4+U/PIvO17f1LRXstknj0c14zdm4WYU0M7yyIClA2ktRGtJOH9+F98ydHsZg7HHB0USFI/Nz3Hfbo/gBjh3BPPS6qgua5pykGPnPp4BUkDpPXuP3M9r5S6rkyGPe8Wh0mw0WogGKSYg8IlH2/yJD3fATKE0J/NeJw3y45t99IB2tsesjOCPnFuluqOYPD414/W7fg9AguZwJ8N7GOZJhOoe+4gmMvRN7293ErCFoloFJR6jo5M87AWC9ix1GlTjAl32oifphH6vQDYqmoXjqQr2AzznCp5ZWEANcvri2T7YwzRSUh0DL1NH/ujG3tNEePWlVzjvA4/bFs31LV65/BjB6EiSYaKmi1cerzVBaWySodtzqGYKOag0JbQUKhNUliHWoLRFKU3lBVeMCUEYtTqcHTXZXD3N6fOn8H6esDGciZ/GDO09N/+ePh/3Caez9eBgn8WlFbpzi7FGI5/gffV7XPB7p42GY1wlOO+pnGMwHEdShkoxv6A5f67B17++x7AoKfKMcT5CJhrnHT54qqrCuyjEGvouQsZcIITaUK8cVTnGlQEJiuGBj9AvL5RVjhtMSKSi6k8IyhGWM7IipV8MeH3wNolJyJoaTcrx3K9CUaA5DI7NMqdfs6cZEVKAPMeFivK+Dl5rNkYlD6Saw0mJmYw5uLHDV97aQ6oJiVFRPD4Ii+2MP/e599E5s0AxGCISSFOLTgxVEdBWRUjXlO00CL5y6CzCHSdVyauHjte/vk2SKozWjHsRih2Txx5jNZjA6eUOZ9//MFo0pSPWMsWI61EAQNUEVUfLY6wV4lhgoIbMXVnf5aBX8OWvvs6V6we8/MYGDy/kDGRAohbAQKhcdAw55hjWz4QCfOkIeRWzZPWDoORojVczx+GkA6hEYh2cFuYSx24RGHmwlWC9ZWdYzp6ro73iaL2fZspQR04swObeAaeWFo4KTKdNEbW6pn+qYw4f8NB9qxwsLfON2wfENTUwmTgIiu2xgKpotDL+5GInkhZZjQuKOwdj2mkDY+HOZMygKkiCQkTPCFSMViSZoRjCeBuWLhJrdY+v1/qIDbPynkmes3cw5vRaiwrFazc2WdMN2kQ2Y/L/v0P1b9xEIiEAQdDGEFQkkdAKvA81pjVGQiPYTDA6I+BRdR2TaINWhkxbFLYW7QXQGA2GZDYJvA94V5FqjWiNEU3a7NDuLNLrbVK6CiPCW699mw/d/XEWHzgX4X46GvheC4RImpBoE0WEVRSbS4zCK2grSMoBKpS057rRqCl6bO/eIsssnWaKURUJlvsfehAXchrNBu3uMqfbbbor82zljv4wOhdOeYISUqWptGeaBo8bYswuaaPolwNCf0A45Xj7+k16IWHUO2DBJBTiMMUhd69eJZ+MePD8eYzN6mUgMurZuobHqrjQow1R+SmmYBcbgR99IOX0nKYcDUlsi8QM6BjHw8sary1X9it0klG4HDCkEovqNVEgOBCpORNtCSKRJQddS8Koelxj7ZYPkAVNsNF5TcQw6R0Q0hKTBcQqlE4Qm+G3N8CD37+F7p6huLpPe/Uc3gkvPfcSut9nNbH0fKCpCvZf/zar910mnVvASUBpRVtrRDxeGZw4dM105ol6WKIE70qSoGnYjBApwvBKaCqNNzFb5epIeKjHdmV5lZA18DTApJz78GfYeeWb4MagLN0zp2hnTTq25MlTQhocH3roSQ77Jd+6ukfVCmQ6IMHgQ8H+YY9qeEgiDqPSKMorEWpppkEIpdAh1AXJmkRpuotLiEzIRxMGB5voRNNsLmHRVPLepU0/XiA9XbpnjoJShGtvErZu41wtJOktN+wqeW0IzIx1OSoq9yIcDnL+n1+7w844kjh88olVumsdHj2zxsHeGyzOT1hbGs2gGNNjcGxzG00Kbt/Z5WDU5EsvKlpZm2SxBUrX8dVj13HvdRHrudqNMY+vFuy8ucHqyirWdJjcHdH77QZ6I9BY8CRVnHAmBMadgp1EwURRi7pA8BhFLWjL72n7HndKinJM8rHLcPsN/oOe4ycRrnQW+M9/8CdYywr+nebvgi959oE0MpMdO+xxR21GzHHPuYLAV962/L9+ZovP/sgP8VNbm+x/903+8z/4VG1EqZNpFDne7SMDZEp8fvwEqnZKhZhFOHXomM/HNJMuCxu7mAdBJZbnv7ZDmVg+99gah//w23QeatF6tkF1IPyNf3iDP5N1+ejYMxc0f+nyg6TnuzSTlOJqSVnGQIxyAdXJONsUFvuBfcysDmPaG1VzmfsQWL9+nX/PNnikmWB3t7nWH9Bb6GIkyjVMfUltIiGFUoJYkBqeJKIJiYpBkNqRUrUB5gXC3U3MQpPtxQV2G49Dq0Hj+gbn76yTLJ5GOjU1uLwbVfo9IXp5xwdwlWN17fQJRsr3ujMFMMkrfC0fgkCRO6j1/B5/5BTNVovvvvoqt7YqbtwqCejZGDgXM1tTJ8eVtTCtjgFEVQdppPBMZ60rp3TRglQeNRlTKiEYE+to2wbv471vt1OMngkrzaL/MfEsjCXQ84GtoiQINIymrcGWJZNr68hgSLHYoNKKvhgaqbC9X5EZz96kZCv3GO9paTDK03eevGlZPL9MmiiGOztxbZtvkjQyBjsT0oYhzQy93VgPo0y8Li8ONIx7Y9b7BbcG45g1g9lzrVQkb/rk46v8xOc/xsLaHNIy4ISO0vQM3MoMRhQNL5waVaACqdXkWnG3oTEinB8FbJAT63/hPXdHFQ9fPsdTl7q8efUuzz52mtHWXkRy1FN1sjUAxZEYszq2pugodu/rmh41g9GpWYKsLgGvIZZMOxA/IopxgJ5JecmP+MrBgIbSfPLJC5ya7/CHkqP99mjdnDp1kQSivtUoDXlR8F/93Bf5j//M5+l0moCa6Xhx/LvRu4r2ocSk3qWz8zx5vs1bt3cQ4Mc+dY6lbsbP/NK1md21en6JT/7Ag8zNZ5AKg8Ma4YzQMAnzWUJnYQ7dNLTSHBWi3IiyGpNGEhXdAE/AKTfLkk4XbQWIh7JyBIkYq9QmOB91MlsNQztJMKmmdO7f/CH+fdr3vUOFUlQh4Gvq2EpFOvRKAsraWBukdCQuwEaYnTIErfHK4F2F+LiIOOLkjun3WGjvdaBC07QQgqPVbOCsUKoompi050nbHXp7G1ShjIueMhz07/DV3/gl/vD//N9HWRO1hRBcrR0g9b4XlKAl4L1HJQlWBZTkuGpIlrUJqUWqCTLa5dyC4rHza5xaXMT5wJ2bN7h0uoWIZms/ELxjqZXx4UdXeXtzi9+5UhcgBiFYTQzcaKzWaAcjSgKBQjQGzXCwh/aBleUFtm+9zOHNdfp7B4zTJmPvaLcbTPZ3mV9YBhSi4wOQiJpRmHsUTkXnJcVHgTxgzgpPrkAVKq5swbjX45m5ORTCbq9ApTmLJrCQNjisXDx+beD7EGKUn4Cua7S0CrXjEdMIIjGRbFWMgJSh3oQMaIk6WE4cv/u13+IPPzrmwn1tOLeIjHchS9FzpwlqDpqnUVLgTw+g8uy8uc233thhTkCVnknlON1u0C/2yMd90vm5WEQvEuu0dMyFWRGUCiQ1ljsoSJTizvpNrFGs3n8Zq2KkLVWGUjlszTyZ1otcpT1NSVjKUpYfvp/vnP0A7dZZeq+9gHJDgjhKAojDJJpLS4q1VmCus8pg7NkbR42OYaFBNE40c8aw1M7oVSuM8yFZc5GpOFopUXgxVQortXaXNijlcVJGmz9N6cyvMR4csvH2a3TmFlk4fV/M4rxH23Rzm/1NHTkUhRPNIB9zdS+nEcZQKH4jtCiyLpW2M6M7fu8oEhmCpyodg8qx0S8ZjAoKV/DGZo+Xru1y4VzO089O6CYTHl07i6sUpVPcuHPA7v4gGhgIw0GPz/1Ii858ilKe3sGY/t0EcIzzZm3435N/kbovQFUFrmyWNBD27+SsnFvEJsIknyBvdQiTIXZZkSSW1BekRtFpWX7k9Dx/q3/A7tYmU4r0WWxVnTjbyYEjBgG2N3a5eOMmob+N7lUYLbSUolpZo3nfRZ7pbvBnHljAUiEEZEa7r44ONL05996sqeEicKO/yHfWHf+r/+SzPPf88+x8+22MMhwZCEdHdV6xt59FOF7QDHNLCFB4wz379+yCvFf8+reu8VfHCatzLd7/za+xPCfoB07hg8aEwNndijv/4Apmc0LpodipSFTCbk+o5hWfWZmntdBi+UcfRT+6gDrwqP0hXVeQ7WwhVYm+fIHl195iTi2xv7TCNG591P/oaPf7Q8ajIak2aGvYGxxgn38B+aEfQETwgxxfltztHXK4fQs/P1dnJ+VYgXqEYYk2oJM4/72gfMDkI6r+kHBji0MFg6IkSSecpWDNOazzhHqMGvhIHCTCRJlj903RaDbIx5PZdaj63okoqsqxsnoqZmIIJ7Ny7+HW6jRoNtsxACpCkiq09uSjCR96/zLXr+zRGyW02g2UMRgLWitKF2HgWRJ1dsrKYRNNYhWVi2RASWpQSuNdIHii1pwGglD0R4RJifiAXWxCrQdkGgmhXx1lH9TRJD++YgQRXhscICi0REN6UQnPZk3MzXW4fRN9LuGgZdjpO05ry3hYsbs+ZrRV8Nq3bvN0M+HHFho8dCpjLtX8yp0B36oKrr1whabNWD2/hrIm7ifGRJSINTHoqqMDorRGvCc4ob+9DwcDfuLDD5CL4erLNykrHwOUSjj0sFUqhrnm8iP3oVspBZCoGETIreFuGkWr2y6wOKrivqwChTbkSsjwFMR67dlwiLBR5gys4YIxeNFUolHGooyhCGWsoxSZKUd4pag4co4sikai0WnEr6l6XzjSBKshxDIVUZ6CimsHV6Jws8kUH//Ew9x4/hrqoI/ODH/5z3+UzZtDtJlm3+WeuIVixvSqaip9FC9dXedbb9zhzfUtPvDY/TMkwPR7M3mEev9SM9rQ+JIx0/pcuHi+y+piIzqQEgPaWauNhCgPc/dmDzEtCCbC361GScYDjz1KXg4Z1CiuEOIxtVHkFSTdkhEOXwf7jZ5mF4W7WxUGYXN3SGN+nrysSLKM0sX67yxRWOOxVpOX3zsJl+97h8qLxhnAexbmVnnsg8/yja9+EVUGtLiYFRCNImavIiXltHAv8I1v/CqNlzNGBz10XbtC0LGgmADGkGmNaTW48sa3GO7fYHh3F02C7S5gGymHu3diMbpSGElqe6Pgu899gUfe/zEe+cCzkRBBFKmK9JgFHqtsdHgIlAhda+nqgPgROlQ0uqdQQTDFkFdfvUKroVhoCD4UjEYTxkWPfDRgXDoqp9nZ2WXxYskrV+9w8yDHqDmCiZtlWxkQRTAx2zN0Q/pb2xSdFiZt0ZmfZ7C3zdLSKmfOrDG38Dlab92kd/M6VT4hdwUHhzssP/IhPvSDfwjSDEdk13MqFuKjomFiMQQVRWQNYGxgranIc8XNAgpX0HIxkuWDMCgNOmmztpBSSsVwT3BiSNE1aUNCUIpGUHhT16BhI+mRxPuojcUFh1cBow1GhKAVocZpWxF8WXLlxltcbadcuO8M6EmE9dR0sroBdq4N45L5S4vI5JC71zewOmG5kTC0BWoMq60mSIXKhwixHkppNaup0ErQ2NkCZ5VQ6KhLceetl2llCRfuvxxVo5QmVbH2agbCqI3LFhqrAo3Ti8iFP8b9do5nUs8/ee4WOrFYLFUV8KJZ7VrSTHOQK3ZGFQ64O7RIcDhfYZOUvBjT9Nuca0xYvq/FgavY7N3lzkHBmQv30QJe/fbXWZrrcvbhx0AcojKsh7xybN26zvJcC6MVS815bt24ysgPkcc/Srp88X/4h//fUksbGWmWEuoosPOBvHSUZYk+tcrXlu5nvOgYHYyQBA4rhVIa6k1oRlkMiNJkjYTv7hb4tEmrM48c7OON4tXNCa9t5fhQsXxeYRPP8pLjD37mLEZnSMj4ez/3Ai+8sB4LlVVg9bTlRz/boNGMEYLKw8bNAc99M6EomnETv8cHmTbv4ZnHUp6+aJjrVix8uAkNxWRoKD2gpRbmZiaG6QOYSugEgxUVA04SOKLGOpHGmbXjcU4Bdq+u8x9tv825beFwVJADQWnurJyBLOVSa4wx/shfUvcY1MeNwHpXnwVxQzREBQU6w0zZ0USw6LgOnehZNNi9N9y53cS5OjQ/NTyOn3JW0BMtm+CFN24eMpGM9iinHI7YkyZvffWAK0Fw/YqfuLhGv/IsXppneyPn7SsFc82MQaFwKE4vdtErbVQrIYhGq1jHeipJ+HONORaI9VbeF8xlZTTWZoMqs4i1QnF40KPIJ6TtDkFBIRC29wneY6sxy9du0t9a52vXXmA82If5+RNZTwmBg1s93t4ccJlzaF/ghgOKYZ+kmKCuv4RUGdIv2XnrOjuFI8lSHlxp0WlorI9rtiXwebfH+TPz3N3t87N6LWrQ1EZllmWMR+P61iquv/02VVly+vx93N28w6NPv59JEYM04XiE/j3copEsHOyNCD5w+nwXmyjaWcbqfMKXvnwVVzkmpVAUmsUVjbWawajCB+HMakZVeXb3KhYXUxqNhP39MfnEceq+FtrA8KCiyD3LpzskiSFUFXIwimUFCZhUR31BayJToFb4mv3MtOIuIyrUTtZRxVtk6Z1mNqKIbWIdMhoz8Z6quUhlltgdCBdWUg4OYNBQrPX2+CtnAk1p0FDCyqUurcUWP/nUGv+egvWNIVe+9E0mTz3MI5/+ONoKNjPMrXTQ7SZIoFUpsqUWyhqGGwdkK13+6X/xD5lH+NHPf4hGarh+/yL5KMd5z3C3z63+hNtjoTVnuDnsYxrz0GqwXHjaourgeFwjAkTpAAWVgcnUcQhQicxovafXX44Lets9tlML5SEH/ZIXXr/BXDoh2MAp7TBTOLEoch+4XQWqeg3qKs2FYFCVO5rb6miOR8erXl9CLAU5DsEUFeHSz7+9zlsvDulPJrREkZQFf+dnv8lT5y+gHpjOuKO5p4ymNd/CJPoo6BSic3I4LMgrz+2dHh947MS3jn6Tk8eLv9SOXn250/6FIxcQlMJYgw8axHB4UJJ2EkxdVzzWFTfz6DZubexRBseZtS5FniMSEK05TCfRWSlczMS7uLF12lFWaJwHijFs78Z9eXt/QiPT9IZjensj+gMYhHgvR+PJv+kj/Pu273uHSllFZ26JzsoyF9Ye4rGnnmBz8w7l4JDdjU1OnT6PSRRbm7fpNhaYm1tgb2+LoAxLC0v0hofsbt4lSTqsrCxSTsYM+yOWVpdxVUF/UtBdXkZXBRt3b3Przjpow+KZ+0gzzfbtdQRFq9OBoJjkI7SvqNAo1+Mrv/KPufDQQzQX2lQ6Ri8QRSOCqxDiw29MUusQFfhyQmYsSdomhIr+3iZXb93l0pl51nXFcFJx++4h6A53J4HFuXmadsL9D9yPryZcP7CRVrLdxWgVqdO1wfkIZbx75zoH69cZDYc4iZmg5ZWzDLdu8vQTz9JVE0Yh4fKj78c+9kEqF1hcVPzKL/xz7r/4QbL5BYISrIAJBgPk2kWtJOKCnGjwYjG6Yll7Sg97uaEQONMyLLQyRnnObq+sMeeK0aEmSVLmspxyUqGNQWnBOkFMxNUqBVqiXHCGwakSTawLMkmMiBjxWAXYpE61a7SGg/42k2rM+tgyuTOkqQ3ygYuR4e/a67CwgEoUklcwGeIncHM/6nTMKc2cTTlQngebCUnaxDUtqhgjaYboJBasEinxg0Sa/KpmHTECRenobdxk0jQE70hsgkGghqQadUT5OikmDF1FI1HMn8m4kOY8kd9mPH+KdpIgwVBoR0gUCyun0NayNzZshxyfa7qdjIM8shtGqkIP+YDhxvNkTz5Ed2mFB5sG5Sb8ztsVE+tRwXDntReo7j/P8HDEYLTNBz79+Vpbo6SlKxDH1RefI4SSyeE+OuT09zZRxe+RtXgPtLTZIG00EcD7ilF/wM316ziv+OwPPER3vsNDK0v81mtvszMa1FH5qk6WGFRt7AIorVg7vcw3r29xO7RJ0hYh7B8VRKto8IsCpQOFP2R79EWayRKGU/yBH1H84Gcuo7VDmVhLmaZlHVHWpDYwv6o5dWlCUEN2dprcK1I1lWcNPmB0yZm5MekwR4qCYWfCzp1dGGmCEvoharfFWaoolTAeCpnTzFkox0P2d++yurp2jF74ZJv5IPXvzntaUtFONCmBHoptH6OX2wsrdJXnQb1LhB0fy05MU0R1X2LdpKCdiw5TEHwlKN2ARCEYrNUo5ZEyJ5+Mj6AvU5avAM5FDamyjOT+Zgp5QtVGV2zWwOpyiVLCwaFlPNYED06BvrjI3KUVPnU45ttv7PGFtye8ReDJzND68Cm68y3UrR53b03427t9bqlApTz90tOz0MkMmfOoOwNk5CAI7cTymaUlboyHVN6jH2nyzJ0er/hTM4HMeCfjH8PBiKtvXyE4T4YG52OQqTdgvL3LQ6bF2VHK8OYVdjavolWE+FktaKmz1CPhtRcP+W+/doW//tk5kjsv0NoZYoqA9hWHkwkqGArlmQSNFoXVlolJca4kHU7w7TKuVfmExuaARr9ELa0iJo75JC85uHab+blWpAUPgZdf/BbbmxukWYPDvU1+5wu/wM1rj/FDn/3RetK+d9ePWZvhuCLZVJSx8Hzs/W2yLLC+OSJttCkDSB6zddG4DrFeSog/g5/BkCWE+A8iEiMItSJIdHyqQI7CZprGoo31JkUJWIKPAZ7JjmPn1UPOf3hlFvGQe8dbjpwrFTydOxv0t3bQ4wHXn30K/+CjaBdQakDphZu7B6Te42/vUpYVikCpBN0rGdUseFoUfuJxo5y8P4p15D4QXHQutNYEJ9gk0sfHpbHWoMwLnnn2fpYfWkMJPNpRhKKEynHw5h0e3B0w8cLIC7vjAUHatI2mE5UdI9nV1FlQ4DQMjGazkSJoFl0MXMxyGVNILULflzTTjNWlLg+ca9NtrfP45Xl29nY5PBySM6FlWvW4xbH0tW5TTOdQs4EeowGfBUujvVW5yO63c5hwODSx7ovoRAQR9jb3GfR7+MGIzzmhtQAug1/59sv0Nnb4sfc9RrvbipphxxyjclKicjW7p8FFohSDZjlZIM/DMSTB9NLlJFxx+oscuVwydQohIp7C0fxRxADXpPRc3e+zbwXrxrSXDCNdMSwVo6Fje3dCf39AplI+9LFHeOXVa/QOB1SVZyHVbG+U7B6OcYzZuDrioafn+fKv3KS70OTDH3uAQQ9u3xL4kGbz9iGtZsr17REHuzlhrcEUNB5+DymJfxvt+96hspnl9NqDfPjTP0Qz6bC7e43PffJHePP6d9ne2OaxJz+OXszY+Rf/hJXzj/LE+5/ld37z52nbeT76Bz7LS9/+La6/esjSwhl+8Ed/nJde+V2qV97imU/8QSaTHb77nW/z/mc+yqllw8/94s+jCmH5zEN87GMf5u0br7G5fo1WY54PfvrzLC+0+KV/8tMIkKARL2yuf5fnv/xFPvFH/ihGxwc48eCqCowmJAZfxUXFpODGAxI3Ri+cxhhQkwFvvn2Vkddc2xtyNmQ0um063Tbd+QUWltZoNxJyZ9kb5lw81aE7l2J1YMcLLiisimx3WimGO3e58+br5OMhxiZoLYQStrc20YNDjPUcDAYUyVmUeLzSpInH9m8R+gcsnVojjVBlJKhonKiYi9LiUTpqg3kDBEcqDi8K5xUTrekkQtt4hiNHv1dQVEIhCl85nMkoClhsWJCSuxNHalOwUtcUKQxR6NcoheAZjA4xPhpc3ZVTKOcZTw5IEZLuCmiDJ37eD/q0U8NzeyWfMV3OZQa5cp29w5y5boO0HamTq80hPhd+6Z+/xk+9sMfHLl4glyoSeGjhgYUWhWqyEzxXX36B+5/+KCqL+6iaZiy0UBCwStcaTYJUBdXBDmlusb4Em9QQVEUTjavG9HsHDDbXuXHlCmU15GMfusziwiLz119nUOSMHkpwWjMuc6y2rJ49h0paDPNIOBDGI/YGY07ZCxRiI8lFbcAvtDMyrSknBZtDw+s3D5gfvMgf/NgneXFXcf1QWJprcabbZK834PDuTYrhPmXwhBCzXKITdu/cgOEWxldUpefWq68gjTf+x1wG/n9qv/zFr6G0YnCwj0kS8I7JaMTC4gJPPfgQnVbG//vv/iKysMRr371COS5othJ6B4eIDzQ7XcR7hoM+nVaL+cUl7qxv8tyrV7j00AUmztCbeNLEALp2pqJR4aSi57YYyl0Ub0QtmkaMWCa6Q2IXj6Vm4o/FuYTHnppw9sIWLzy/xNb1xfqtGW6FEODihTmW5keMdhSrixYkoEXTMIrOfIeDBLoqoLWnDNCXkrs+UK17fvAjD/J35gx/9e2rfOlXfp4/8ZN/ntRajgjaj51uelYRgii+8eWv8vH1a6ydtkgQ/mnvkK8OK6w1nHvxS/wv3U0Wezc4+ESDpafnqaV8ZwesXZ3osAYVI6cRH4MKGnEJlAbRHZ5++BJpAgfbu+xtH7I3KenvDOiuOUBTVYa3r81RVao2UKeGQ3SqVM10VdtBzDXjZjzQ0XB1tVPWz4W9wwne5WyIsKdgQMAFIe9VhGrE3rUhLx9UXPMV+0BbCWNgyzlOD3NaxmIrh/K+zmzWDqXShNJhX9zANVewi4KWI8JnEfBoymLCrbeukmJ4ywmvDXM2xLNXjLj9lS8jjSbtQlGNxjw9v8RNHWuEO1KgfI8wKhi+YpjsQFV4tANZWiLhgKQq8N7z3c0tLrbPY1pDUjJSlbLcTtmVlIOdA85N7jC/scfCuVXOvm8Z9dWXybpzmGJCmWYIiiIvGA+HLHQbIBowzM8vU+ae+x96kq//9s9z6fIHeeiRh45Novd+iipOUyFpROie0uAKx5OPLfLyyzvsHIAYgzFCoxbuFomOvFaqJq+CNNMYE9cAY8GmU9SCQtmATWMd9Hi/z3h/QMDgVU1XLaC0IQTwVSA0FvGTIdW4to6JrLyeKYy37sTUBgesK1m7eRM9ySmCR5pLdGzKQTFhHBTKC+rWPma/h7p6h4PcYyTKfBzsFZixwweFD4qyqBh5KNF4pRjsV8hhRaOdspSUlIMCYwziAniQKuAmJUYp0rbBBE81mjDZ2CRMHOIDaTswv9akt+8YrZd4IkTNoRgaxV2lOTRH9ayRwVBRaU1JhAPH5TdMEXgzJPGd8Yi3JttoOhijSRNN1DH3NFuG3oGjX41p6hbUrozUa8SMj2jmsMgsa1kr16H0tGbe4IOw329Ex1sdhU56+31+9599HZ3nfEYLTxlPdrbBdRX4v6VL/ObOHj/1sz/Pn/+TP87cXGdKWIhAJPiYdgTwLqCVYmt/xLDU7OwXs/eUIup4IpgaQhgd+/rvI7+sRhDW4MQghHAMBi6CaIPznr7OaSwbbh4MaKwmvPjiLV59cwNRDe7cOWDtTIeFxNDutvnt33qev/3f3Obxxx7gM2cepxj1+bt/4zcje6VXPPeNJutX+zRalltvb5IttDn3wMNoZXBliLDi6hDlZbaDHHXqe9O+7x0qBPLxPrduvcX7P/CDfO07b9GfX2Z/cIDSsLW7QbNMcSEwmozY620TvKeUgsP9XXweMcZBCsbDA8rRJELYkgTxGeRjivGEcr6N1Q2aK8tUriDNUlSakCnIlOHs8n1gd0kCOGKmBKMQVfDcV36B+x55jLOX7qNSgb3hHi9+4wscbNxg7fRFzt7/Ps6du498oum4AVpnSHceVEXlFSOxNHRgTieszLW5uDaPc571OzskScqwGLA/MrRai2wPRjQaCc/ct8BLmyN2qgxrLaUEVIBe/5B+XuJ9oGkEyT2ZJgrAGkNqNRNpE7SlmhSkqWdYCeu3B7Tbp2gszBEIWLFUGqp6cbJKIUrTEMErwXqFCiXaaCYorCjaVrHcFDb6Ob4MtBtjjG1SeJCqpHRR28pqzUKqCJVnWJWoJCNIwGhQQWjYhDJERsfDjWsk+ZBWM6NamscNRtx9+2XOr6QknUW0sgQVo6Tj3g7KlRw6yyR37F8bMUozrt7pc/nSHKfWMlAVb/7mNfRKxkvrI8oqZ1A69itHMxNMM2Wl1WR7r8fNnTtceekbLD/4APPZOVKl8AQmRR/vhNRaSBsYnRCI9PCVKxEfiSoaOhqnWikSCextrLP+rd9g0O+RO8fZSxcYHO4yuj4gdbu0rGHrYIDNWjQbCYurpzDtFt5P8CEw9sJkWNBIDMPSUwwGLGQjchIKH7hvXvHkD32Ifh54cSTsbe9wdnUZFQIPzHl627v86c8+QUMZrm4POegsc+vtlyl9g0RKVs4skmUNFtbOszkccWo+Yb/fY+KFxGb/Iy8E/+at8IL2gf29Q07ffwlcRbl/gJHAgxfPcdgf8/zL6zzwVIvhMGfcn5C1l5hMKnwZSJoRVjMZ5SQ2oXKeSV5QVZ48zym8ZTAq6DYNWgfuf2zI2ftKsjSp4YK1m6JCvRfGmGYIfapqQitZQs9o6WON4EKnRat1SG80IZ90OLybztjXYi2X50PvW+bigiFcKRDnUC4gZdw49VxF53+9xoV/kdLc62PxVF7xS0nOR8j4rBGWJQqUehfx7jNYyD1pqmkRPhJZOId7+yyMJxRlk7HX3Bo7kipwVgx/paF5+HCDGzcPObjQZuXpuSNGp3rnVqIY5RlXDlYogkF70BKj9mvpIWfatVZOEMJgm6LM+Wc/9fe51htxTgLbtyd0l1NcYlHa4J3BuWMcijXN15HJFaE+rjRcv9plkleIjknFygljUfzNK1uUbwo97dnXikJp9ivHOSu88mu32Z447pSe12v8v53C9jS0lxI6n3sIeewsYX0H9odIwyAm1nN1zy3gLq+Q3N3j4uOOv5Bci8b52EEp7OxMeOHtQ8QZ7gosZy2cEr7dH/OKd2BTOr0ho8GAl8RQaEvbpLRNQiKGhgooP0BXBar0BO9j8AcNqeN0O+WZc9DvTxCiBlirKJivKp6wis/0hvw9p2k9colHJgfcemWf5rlF7MGE4Y1DWj90jo988+tIu0tpDC80u+xklj/85Dzh6h1Km/KKKlk7s8TplXlezRp8+vJ5irXTR5NIMcvyvlebD7HeqdXNascGum3F4oLlt7/Wp5Q2BMEmiiSNQRUJMN9p1DWTkCaaU2st0BDwzC9bRGvEVgQVaK0GpBLGuz2qfo54D80mThsmhZ89mq4okdxhm3MElTA+dEx6FUk3Csu6+oGNUDOpsxHx2fCuT1+NKVSB1yk2bRMCjMsCV004GCoka1CqEb9yc59FSh7IPFcnwvVbh4iCkfeIBNZalv/gww/RWmjF+ieJGQ6ROhtVB1J8P8eNS6rhkOFEqIoSnQSGO30G65uMrl3HlR6tFbpjyX3KaBLqPsVgcQXcTVI2k5Spl6SI5E6FhlIb/Iz5c3r9tXKNin06qEbohNq51RhjCBIrnZRWiFUclCNWsiU00yBShEz6Osrk9dTRihmvaTlIEKGaeKriiFE01FlJfNStwweywnGhMvR1yo62/HriGax78lBwLa3YsIq1jW1evbHOx55+/NjVHMsu1U1p+PqLt/mtl9YZOXj5xi537h5w7vQiiOL2zV1+9jee4099/oOcP7vMK1e2+Oe/8yb/4U9+nFbzmEacmq6WUWw5hOkZp+fUVKVnfz8naBhNKvbujHjp5S1efPFu/KwWtrcOeOKh0yjReDK+89JN5lYWCQ4ajYTJqGTYL9DK0N+foA2MhvD6y9ssnu5y4eFL+BAHN2mk5GXAO8H5EO8HMhvb70X7vneosvlVmkurJO0lWg1Fb3/A3MIZbHOFpDlHp9MlaSg688t0u02KqqK9ssRoZ8hw1CPoisQ0yLKEb375CwwO92l0ljGTXeZtQaOreeHrXyLtLHD29P1sb93AYrhx7Qr5eISyCR5opoG9cR8STaZanHr4EWyo2Lj9NqPROj/3U/9nHnn/J/CJY/P2a9y5c40wGGCzJlnrlzh36mH+wGf+MCxZSua4dNrhygHDytKfCOMSbBajLKNRwc7BPjdu3qVzfpfJaJszpy+wd/cG4caE5oOP8PVtyyRbYVCMWZrrkgiIVjhrWG6miPTx2lJkGYPxkKTocemRR7hwbpHtfkWY7FP5FCOB4XifjY07BJNx5+ZNzj/wAJUKJAHKOnKmJeKRDQErAedyrBLEa4I2dFJDy0K/gIORI7OBcjyhSiyJsoz7PXbdhG4rYySaYtCjYaHTXGXockRZDvs9xAsrS8uR/tsG/KiPvv0mZ1aafOfuXZphyObNdc4++zDeVzhjUUETgmPn5mtQBULl+Mr6Ab/81jYLawu8fXObP1dd5E+f71D1+nz3zpDenZw3Cs9Qp1wZDvDOoceKcVXxU29s8FZvyLj3VYb9PQ42btNevoDTjjQI++u3ONjZpNFuc9+jT2EbFlGazatvstJOsL4g37hG68FnUFqRKQhFTihLQjFBdMLq2VWUr7j+9h1u522evlRhxZKPHc25Bc5efABrUgpXoKVguHuX7vlFJk5oNizj0vGFX/hHfOSpi6xceowbt67RXvK8efttzj34EN+9fZ03vvlFfv1wm1NrK1x+5v0YZXjtO89x4/o1fuRTH+L0uYd4463rjLI5KudYubCKSQxJkiFJhs/aVJmHqmI+Tf7HXgr+jVvlHa4o0FrFOZNHxfulpXm2Nu5w8842VTVm+84G5XiE1YpyMkG8x1iDBI+vKrSGyleUbsLKmXkGvTG31rdodBaQquJwcAChz8d/2LC2mrKw2CYf+HeQYjDbbH0M9lCLHtbGgCIymA4mY86dg/PnW3zl1xW7m4q80JENMwhalSiqyJolDlUoBkPHd6+O+MSTQvMxQ3ZpifBNi35zizmb4RmyP3EM1g95EMNHG01+Zn+bm9ev8vDlR5mJdh8fwLoewAd4+Y1bpFsHHB4M+L8PegzRvOkCpVa0jYZGYKsq+EJ/xMfa88cwJdNoLigSBsUcr44eZBwUkhfgPQ740Jzh3NwhAPpAcfOLz+HHBZ/vD/jl4RCvMvybFXeY47Cd0mw38Aqm5B0n0n3HCq8RQUkgBI2raxoCgXEVte1ECdtKyFFUIZI8lEHYCfCcC2yKpzDgxXDJpBy4QE8VLJ7OuPgTjxLuO09pu2Q/9mHk2nVkf4B+9n6YjFjMPTQbkOQ0ssApM45adCagE8GUI7Ir65zRGR9JhI/Pz3NLCUs2pZxUbEtMBCVGM0IotWboA0EZMhSp0ejDIapfYaCW7wCsRnUbrJyyPJWV7Ny+i64LxROJIuZSaX6tX3CQVBQXHiHJlrjsLOahBXQT9GNnMMsdHlqzdEyFVwVr55bZ7mY8daFFduWQsHiW/9ZN+Pc//iDfvvYGpzLFHzvj+Fl3zCD7Pmj52KFCpH8PvkS88IEPLeDKius3xzhvwUfWv6jF5CNLrYo1mWlmgIB3kaERFfDBR4ifiSA2VyZ4J/x/2fvzYMuy+64X/Ky19nTmO9+8OWfWrKrSXJIsybNBxtazAT+DeO5oN9FhvwAMAf7DPBPwCBy0AQf9wpgI22G6ceAXmOb5YfwsbAvLkqyxVCpVqYasysp5uJl55zPvs4c19R/r3JtZMtAWLfeTXvSquHXzDPfsffZe67d+w/f3/RYHBTLyNLoxPoaiBK1tYHck2AeYU+DbmuENzxvDexx/J7SW22QnlgPp0GFgIQ5rKB7rdnm2t8sszWmmy7yn2+TKvWscDPaoTcnNveu4fok9EEyt4Gys+FOdhImpeGOm+e4zPS4MK6YV9JoRj5xaIeu1QlIRf9T3KaR8gCjFgdF85vef51OfeZWVhiQVnhc+9RV2LmzSwlNoR2FcSHhLcBKQEvVwTnvOZhmCHDis9nigEoJr7Qbez0Fh89e9Dyx0gTfRU1jH7ekQkUicB11rhtMp4/GUza0BCwsOkXhmRUltNVmIvELg5AMMzotQkdIWDBbtLYlQbE5rKudJ58LLKlJzSOi8POYtvtQIr4mE40MbDc51gqzA527NyDPL+77lJLtbB3Sv3SWXiuRQkPloBoq5SXtzsuizr97gy9f6eDK+eH3MZ1/b5iMbi4BgmFd8/MJV/vS3Ps7pjSXu7Y/5w1fv8NeKilYzuY8W4D6GQHjw9vDA88BKCibaYfIKqQTXb+zzb//NVzD2gXPzHmOh0iW1djz2xCmUkHjjMXOW2ePdNief2SDLQjAnJOja8cILd0kTRSOVaB3WQhxLSmO5udPHzWY4IEsiTjb/5HyRP5GA6u7du/ztv/23+b3f+z1msxkPP/wwv/qrv8q73/1uIETtf//v/33+xb/4FwyHQz7wgQ/wS7/0SzzyyCNHn9Hv9/nrf/2v89GPfhQpJT/0Qz/EP/tn/4z2ISXrH3NkjZRed4OHzr6VfDZGWFg9cZJZPiJOU5ZPnKLVyLh05RKrqyc59dCjTIspJt/j5ENPkdczioHhoUfeSlnNuHX5IlmjR6vTRepdGkqSHn+EjUcfQ1VDBv07ONqsn3iErNhm8+JForTBOx49wb2bO/yBlMRRk3e9/R3s3HmFq7dyfKQReoftzZcZDO4xHg7nWQnwaGblFtfzEf/L8CZLrQa5T3nbk+9DqoreypPs3HqZ8f6AVG1w6dIWxWCZExtLdJph06v6JbfGl1g8cRrjQcUt2sstUi3Y2drBRAqLwCuJ8hA1Gqx3Fkhjyeu70FzqEh1MePT8MQaDPtdv3+P5L32Gt73t21k99xiLepfnbl8hyVbZe+GL3Ll5FYcjazWpZgWxdoyrCVGtkaminTQodInTmiRr8MSTjyM7DYooZTzNsbqgrqY0FxWNhQYqiRlv3WU08yS9FuNSMdi9R6/VoHu6jSRGehjeucysciwvvy/0okkwxjC4d4skF1y5M+Dxc6sMdraZTTaCKKEIelhKWPLRlNxqpiTs+oiximhFglY3Y9fH7F0dMtrc5XObM14tHDNrGVaGapLjtMUIQT4r2ascs2JGPDM004Q7rz3P0rENGsdOYPMJmy99lvG9yyTdHuceeYJIgMDgBnucWkpZSVJ6dkpbBYag1JTcvXEBl9c4CYtLC9Ta058UjEcD1KkU7w1CW6ZFRXNhhYODfcaTEd5VpFlGtX+P1vp59Fxc8iuf/TS3XvsyD53qcDzJuPbip3n0W95KLprc3dzhE7/5MRrNlLyoyPfGHDz7HIudLo3lRRbqMxSTihdev8Tr17cgUvSWj5Em8ZyZSYCCrYN9oliy0GtznNk3rQ2RsaTOA9V/Pp0FDbAkpTCOv/ZT/3fy2iKTFgfbW9T5jONnTjIZ5zhTs7K+iMcynk5YXFkkz6c4X9FuNynyEhVLyvEBdVWTtiSNVkKkKlQUk6SSemb5I1o+AOKQGQ2c10gZPxAKCCLRZLFxBmM1XtR89/ceMB4KPv4HNfU0ZlY0cL7E2CkWDcbia8ukiNjs11yvI1QUqIrFmQ7bx3MaWxMa1rEnPJ/enPADKy1yPNZ4vvzsF8jHE97xzDPzrPIDgck8Lerx3Ll5h9XplNI6PmkFMyHRSdiY7wF/8YVrIBxTBD/JW9jdXJ4HlCHz6QFhBSpZZEZMJTxDLSjqAKV9uj2n/nZQFJY9bUOWn0CUoICH8oqdiUd5i294DvlDDi/vg+7GYf+ZB/JaYI1nNHEIr/ECtp3EesXTWcxpAdrB2HjGOEa+phVHvG2lydtSRZkbkljyW7s5Lw4LWlLSeO/DjCvFpV/5AkmvwTv+xyeQp07gsxi51oIB+MShrEMtJtj9GgeoXgKz0O+w2G3yPY9uYEYVq50EjODbehkvDyq2as++EExwNGToFY2B1EMiJTECKT3qc69DXjAdOEYjgxMSkIgoIbIe88Wb+Ou7CCNoRJJECd692KTnBAd4ai+pmwuIH/geHv7wDugCISKyH8hAKhrf/ShyLlOytLyG8BXi7jaM9yn6BdPxjObqMeR+jhIJ16tFTOSCwPkhacZ/RWT1jWRH6qlBaA14dDGByvP04+fYPSjZ3ilQ3UBXXY1DRVomkDQ9phYIoWiuepwZkt9bImka0pZhejemGMP627ZJGpbJ5ROUMxsYhrOY1nIDZ6AuNOXEYJwDZRGNGoTAVAOUT4lFh2JaUY8gSxTWhF4t6TUCiynuoG0VgpzygMo7Su+JVUQsI6p8ijYl3paY2U2srKkQKOUohWBTW7yCx1YyPvz0Kj+UxNQ2VH8m4zETC9mkjyYKvVTezzWSBM569nf3yacjDg5GzIYFwyjhxWt7XL7b5/b+BIWgNKEK5AAnLN2NFqeeOIVabwfyLfxRtftoKs3XvZkD7+eTgplRVF4wE45IhWRLbkqipsV5hTOOWlsqKxn0J2zvj+n0HFHmmeWerULTSkIPnPGCJIKAtvPU3rJbW4wPQWqq4NJgyrA2tFoJkRJEkQjEQwTyIe8FlXfUpcLUMC0dD5+SpFHE63cqFrox/+0PnGdwbYEvHUy4WTtMpanLikPZGickQgV2vLBFC3COrnA82Q4wz74JlRzhA/TxVn/CoLL08xovoHIGYyuMMUcBqpsHQxxe2cPM1wPDIxlIwZ6pkaXn+Ze20ebwtTlXn5cBuipq6qpkdblHq91GRYr9vT750LKYNXjPM8f4yqsDvNN8+PufJhJw7doWT7/9BOudiO17oyAKHEfgQtJhWtWh1urB/gmCZb7uAdVgMOADH/gA3/md38nv/d7vsbq6ypUrV1hcXDx6z8/93M/xC7/wC/yrf/WvOHfuHH/v7/09PvShD/H666+TZUHd+Ud+5EfY2tri4x//OFpr/vJf/sv8+I//OL/+67/+NZ3PamcpZNVExP5kQtRos3dnE10V9LqLHGzvMI4jOnGXMp9ysH0PUTnaWcxkexdZRiz01jnY34NI0lpepNVaoipzqGp6C8fwyRJuOsbWFYvLJ6iMQFsPtFleO8Vq9zgnujGFKFjuHUNFKUsNR9VISLyjVoapteS3LyKNJ2u0qIsS6wXCK6qyRtYTdsoZ1XKPSHZpZ47Pv/h5Rtv/gUI4Hj/zGDdvvsbWndsIp/jwd30bjaxF1FvizOoyymoWlhbpDw8YTEYkmeLp0y1ee/0an/iDjzOuBIutdRYalm5rmX2vUFrSW1LockxpDTNjuXLjMl984cvcu36ZG5de48mnnuHxtzxG2uhgvMCVUzZvDRHes9DrUtua2aTEO03aaNImZX9aUJsaJeHk0gKtdpsKiY9TxtWQzMOtW1ucbW3Q395kdWWVrdu3GJaOy1/cJBMwzXMeO36ccV6wtHGavXHO1qVXqbTFPPokrt0L2R5dkirBE2dW2Ti3Qqeb0o4lV+8OWHKWTDgaBLr68bRgIYvodhqcPbnM9x/r0mokIE/S7aRMB32uDRzPDXN8q0UjjVlNFdNc02i2cDIYSKskWSPDWkMnajG5/iqzYxu01zaQjRaRipjlBVokRwxDaI/TBYmKGY7GPNlr0Y48MQKtNbf3NolUwsLKMpOJZlbmiGJM0b9Hvx9jVyJKUzP0YJUkL6bMZjOiRLB7Z5N0WlKdfAQMXL98iS998jepzYRyPKSRKt721OPIyHHi9BmuXLxIXeYksUDnJTNkgKZVBc1pl2anxcLKKj1tudIYMPISoggVBeFpU2ukE0TeQGVQOCaj3W9aG1JOJrha45zDGY3wHl2UTMclkVSMh0OitiBSCmc9+XgWqJGlpK7qQHygNUZrnDbUZY3VnrqsUVGErxx4R9SM6a1Dq2NopJClkiJz3Nrb4/z62lzP5P5GdZgdLPWEpkyRh3Tg8yBAoZAqwmOJU2ge8/zwDzuuXpuyszVFdvfYdVPyTsU+llppbt4t6WuPWmmTxIEgQx6XdH4qZv/nbvH0rsEMYS/zpK0mfyXt8HE/ZefePXoLi7zzmfd8FTTrfmA1GE7Z292hEQuuoJjEisornPB4JDKOEe0mURLTyzJenBzjyvUeAndUofIEeN+xjsKKAuMls5lB20DnbB2h6m3gpVcGfO7yDoL7emAeR15orHbI0lIXFqvmEdXcu3IEqPKDzWDeSd4YKoZ1YNdcI2gCjW3odTrWjDg7hyzdqB3/cVYwc452BMdTgUliokZEoxMx3JpivQLvEAuWht7mkUcVUnlENcBrg7cakQmccMhTG4i7faoLY+xmjmwoWE+QY4O0oAtNU3tUoujEklx7OkJwICVjKdFAPXd6lPUUQlDYwDoGEucVotL42mIrNxdSlUQyxTx7lb3ffZ3dl6+Rm9B7txQJIuHoxRHVqCT3Ch9DaTwiSuDGFcRsBEmCUgnuoXejhlPExatgJfatj8O5DUgayCVH/6V7jCYj7MWL7F2+TS4VX6olxOJ+lvs+guiPPb7R7IiIwg/z5MDxkwnHNhb55CevoY1HCcGRdtd86Qgp7uuAecBHqIaHGBQJSkUoIWi6JTJv2POhorV8qhtEbQV44Y4Y2pwP1EhChD49ROg51hQ46xj1c+LGGG+foNy9zUI6odlO2M2vMBxv4yyMJg5nPVKEKSkAAQAASURBVM4HeRjnPX6+/gRzPRLlUYlnoWnZzR2/0a95x6ke/91Tx4gjMEKTxlBPHcZaDJZyssO0cwwnQMQxQgZ7pquKFz7xOXx5wJmHVlk5+QSfeu0e/+A/vEgmPMZB5QRjC9IrjieLOGs5dWyNR//8+zAuxs6lSwSeNyvaHY75c3O2D+PmtuSBObedj8jainricMaBFyRxQiQEaSSOYH85gpszw+JcOy+WgjNNy92ZZGbBxYaDyuMQGAtCGvq2pLcQ+ucOtb8E0O5EpGmE8Jax8NBRxGspk2ttrm5rpPDMjCPyEkYGU8DdGja6it/4g2cxN2+z2IgobZB/8EjGBi7kmuUsIUsk8vYO//StbVQs+MU3ppTDKXfv7BMryWhvCNbRPxgz2R8x2O3jdM3Wdp9eI56TysBkOmfOm+v9+CPInw/EGN4HGZei4sLzN7h2cW9+1Q/XeAggu0sNNjYWcc7Q6TXRuiSqNAu64MZruyy0myTK8/kvXMEj+d7vfzwEvAp+9P/8DG9czvnFX3yeb/22VYSMiUrHmY0WkQp9VULfF3P/kxhf94Dqn/yTf8KpU6f41V/91aPnzp07d/Rv7z0///M/z9/9u3+XH/zBHwTg137t11hfX+e3fuu3+MhHPsLFixf52Mc+xvPPP3+USfrn//yf833f933803/6Tzl+/Pgf+3wyW+KKPVYakr0bt2jpIdPbBzgbsRgr9N4tfCRZbkr8bIfBtR1iL2k1DdsXPsesqknSBsK36KY9OvRYWmgRDTZRpmCt1cUnhmk5whhHNxFkKx1Gt14hbiWcP3OGR8+8hS/dvsdnn7vNw2fPk0aOz372MxzkfeJuwmx3SpYFXLUBymKCdQ5vakw159t3kjTLcL6m0YHh9AYH/TvMtMVWlsuXvkItHKkQuMrxxYtXWFk+Ta/fp5vGLCx2iSKFryoiEhpxxqxUtBtt9jdfY3t/h60oIZKwsriBBEajEYmIQ0bRVnzlK1/m1vY97l6/xiyfUlYVX3nx89y8fZvHnvkziLqk6u+QqQSlFK0so5Us0+tUyFgRxwmJIDBxRbDUVqwfO0nSWWKytcnN115h52BIr624ef02T5xcBgztDUlZzkijBmY0ZOPkCpf3RtTxaaaznJ0Lz7O3t8tsNILKMtq7R1SM2Ny+yfb1l3mkKXnrmRVmmWNvmDOeapSqKe9eorO2QTkZsrd5jZVMs5i0ebiV8P7zTV4cFCx0W4zynElRc3BQkZcKFbdQKuOdjy8gveYzL+3ggF7aoRnFGCdIZHDjlIRxZdgvctZqjUMhk4S01SRrZAhX4a1jvH2b6d4tVjLJYjPl8V7KWttQCcGW1TSrMYWxoINekRM1j/UkfpxAXSKyRZxto70k8SrAkmyB1hEpllOp4qXPfJR7JmK8swl1TiojxtMhmTK868knePnLn+bRd5xhmE+RCoQ3xI0EQ4lyLUalozY53SzmRCui7STFSsqrgzFJOyVRERjLscUmyZ0pj2clk6Lg9mjAdDr4prUheX9CFMUkaQNdVuAsVVFwcmOVX/hH/5i/8j/8U166fJPaQdRoMp4WqEgSpxmTaQXeESeKfBroi8ejHD/X+rEzi6lKJA5bTPFaIISj3UpIU8nKaor2JkC8cKij+MTjRQgyFILKVkgMiWoeBTReeIwrqM2ISLWIZEqWRjz5ljZPPGGYFlOkUPg24CPacYP0+hg5M9wd5KwttOk0JE7AifdvsPTrS6zu7DEZaO48V7D32yWfk4ZKBIHuqqgYjaZ0221kdL9KdXjKeVFy9qmaRjNj6iNWJ45iBk5LjE1ZWFxnY/2tZHEHIYJgaX8welPmeL5Fsz84qiHdP46DYVSzt2cYDeHOrmVvpgnCUh7rBZEA7wLbqLWefr9kOBe0PcRWaicYicBOeqgdY7yh9p4mBCKd+SlVXqKdZM8LEgKblwEeizIuURIj6OeeUX/GQlOy1y9pOcf7UslVB+w71FKH7jGFX14AqfD1DJ/X2Jc3wXvcyYewty+jDmZ4a4icYHxtSquhqLXFVJZEgFeKvDJ0ZMKLk5rbZY0WHg2UxqHFXFzdeQ50Ta5NIPEpHHiLwJHMYWQIhagEe//hGrsX93g4idmjDE6jF8yAcQ23q8C+ZrynMB4vI6RzUMxwCxuIaoJnhjixBm/cwM9q7MuXEM+9hPQeYT2Nh5cQX1a0n3qa8dVt1rOEE8ttro1rjFUkkhAcHAr7/DHHN5odsblHazfvhTSc3OiQZg3euDYKjfZzYpXDhn6cwFowJlRNy1rgyoxy7ImagkgJjHZYL5iMEqpZTJm7INZ7CJG1YU5aZwOBiQSR6kBQQXBovXQ4CqwT7O+MyRZzjCkQqkZJjRIeJUIvr3Ge6bQOgZ+CtoDYerQZo+sR3hcI6QJUMfYstg3TMlRYI+HQ7RqNwNtwbNsBESUIJdgZ3aHuSoSSeNfkYJKh59DpteMLtCpYfHSFZjPlzniKvjvku5oJAkfuBZ8tPHu9iHf84AZOaJqLTcp6GyEXEKKH85777vSh9tPhOKyyHCZW/FHgGx5aRtWI9UWB8w4zv65KSBTqCJYphCRKHHfuFOznZt6z5rkmHMYJauvmzMrBPmsb7vWsNshIIeZVGzGv6mtniCOBd45iaogiT6xgZ2mBj71xm7LUGByNWtH/5VdQ3mImhmfOxAzfKNi+u097oRGIN5zAO8mosLx8b8IzWcLQG0pvsL0uiQrdc3/wxRf57edf5HsXG6RC8t5Oiy9+6lWiV26wYiz/zUKDX/rXn+I7llq8MquJgZWZ51QEtzXgQ1XxQS0zT0hUXb5wh1efuzvv5w3BlJSCMw+1Odgd811/5mFiY9B1hSDG1IamqXh4VvKpz13nfX/hDMobBCVCpWE/lKAiQRwrZJySz2ra3RSHYjK1TIYeJ4I+3lLyNWZlvsbxdQ+ofvu3f5sPfehD/PAP/zCf/vSnOXHiBH/1r/5VfuzHfgyAGzdusL29zfd8z/cc/U2v1+O9730vzz77LB/5yEd49tlnWVhYODJgAN/zPd+DlJLnnnuOP/fn/twfOW5VVVRVdfR4PB4DodFwZfkEjaU2l69fpCVK/tKHHuYLL17k2niFt661iIXhwp6hudgjjRJmVU0kHTMVMdra5uTSOsurC8RJhjElk/4OzUQQpzEzM2N99TwqOc7MVOzvbXJv8wYfes8T3BtX1DLixPF1nN5hqWXwXtNIYyI3ZjDeCmx+kUSXmnbWwDuHtgI7czSaXY6tbCCTiMFoC9kWjAYTilnFYO+AYjxFJgpdV8y0Imk0oSFAplzfuspoPEWkMDjY5s9834+ihaAykkYz5oVXPs8bWcJnnvsU2/v30OWYSVURy4ThaJ8614Fdx8Hdres0my1ev/k6eVWhJzNcbfDCgpUM+lf4yme2UAhqD63WMo3mIqNhg6WNhzl79mHiRgupYoSDSMV0Eui2UkSSUJYFk8mQqxdeoLI1ycoyeI1XktPLC5w/sUgzi2lmDc6dWuTJjSW+bynhY7t9dmcV1htiHM1UUfqaqy//IfeuvU4+GdDqtumeXuG9bz/O1FW88oWKv/iW07RbCR0u0KivUuRjpplj5Xyb2wclSklWTnRZqUoePdPl//XRW1yZxHz0zpDRtKSsa5qZ5OFjLVJqvvCSBiFJMoHPIY48GQ4rFFkiGdYp4/09Ln/6d6mQ5PubLC13kNrx+u/+a1xzGaEiEkqyRpO3rmQ8/dgy8ckedpLTv3aHrtR0XM6dvOKg36cucmadiAUEaZYgV5ZJjUdvFdgooZMJhInx1Yyzp46xGCvKi29wuT/k2LF1HjvdI00kvdiSCcu49rQzaCpBJBRn1rvEGES6wHA8IbcpIoJuU/H046ucW+kxGGg6nQXc/oRWmtKUEZXx1FqQCMH50xvsj2dQavrT1jetDXn63e9HxfG8qdxRFzNG2zd56m1P0e20WVo/xresHCPwEM83Eu8xxgSafqUIRRaP9R5tDdZ5tDYM9vbYunWdrJPx2NsO6CwZkjRiPC5IEugtJlhvuL5/j5XOAsutJs4H8e+8mgKSpU6XrcEmVV3z0MZTKBkj/GELrkO7CfddCYEUgfMoiiTGWJSMEEIhheKh8wusrreYVR5PGvTbTBA/j2LoLSV0FyOkyvg9NWa4e5zvm66ineHCS4r/8Adf4ge+9xk6vc7cKRFHTNEWwcppOPuwxLqYu/cEe1sRQrTp5xLDDOvqQGsrmFNE39dfAeaO4ldj9u9DIjcHgg3vECWUBup5g7J2QV8wwmOEwHhH7YNMg3SB7GPPxey4iFjASVWEHiEn6PuETZtwXNR0fI0kkAsIApwnF57PV5auFDRFcF4HTuOx9EvLF6cVFk97InHGETvNGSQ3nEFfHlJHEq88YqUkOjNACIP0CmU0Xir8rXvIgzEqUah26EftZgHiGcUyJDK8RUjFYhIzq+Du2JB7QUN4tBc0ZYA0RSIIi8dCEsuItThifSPDtx1MNbW3HBiDMwI9qdm5M6K3ZChKyeY0dOtNRMqNQnMlgalQeBVRY8nLAkTEcM+T9DV9V7OclORXd1CJwLVX6E/GLEwN8Wcv01qIGS432FeWqNNk+Vu/hfHvf46za44zpzu8+qVt4iQhySK8O2x0/+OPbzQ74nQgMhESvLKcObtMWVX0+yXeibn5mMPSQrMN1gpsHZZSWUhskaFnHqEsJhVYE9ZJMZGhR68OQYB1jtlIMxjWQHjsvUfG3Pf6xCG89bDXxmNqiS5K5OBzdNJQIZoVYF2FkgprNQd7JViIM0VvzdMfT5iOXmaSbwe2OmHx0uNTwfiJNuup5/qFIV9eKyjOTHFGMJvWSOWJIsVDJ9aQSuAYkEYFUgi2CsknLn8BozXeC1pdy2MioyNFoOUWMJae11zo0fZe0sk8SU/RORdhhSKKBUW9g2SPKFrDs0oSdZE+kFKIuYUU/gHImr/P7HlYsfLeM7EDXFyDiDHeYJyaJx5CoBkCKoWUnrQBIrZkCwG+F4YiEYLmPFY7NGh5DUnsWaRxvxr2AMx4cWGZLE7YORhz+nSbRiPQBZ88fZ5Xrv4Ox4ZDei3Plb6hJxO6TUkVR/zG5X1kmnLPCKJC8JntAePa8N3LS0yNp19q7qVQu5pbuWd5GpGlcEt7JtqQa8drE8mxVsxUWK7mjl4EG5Fg7Bw3cst5mfNCv8QC72wm1CJU5JzzWHs/4SUAGTm01uzdG4Z5Pn+11YgxRvDIE6uUxZSkEVEcaGb5jMXFDkma4WuQtaB9rMvCsqAUgu//bx5BKIVUBuegEUmkkKRpghAxnU4b7yXSCLIkOrrf3Uzgvf7jmpCveXzdA6rr16/zS7/0S/zkT/4kf+fv/B2ef/55/sbf+BskScKP/uiPsr29DcD6+vqb/m59ff3ote3tbdbW1t58olHE0tLS0Xu+evyjf/SP+Af/4B/8kefL2YSVlQ3wM3RRsrHQ4dsf7zIbpLzw6S0ee8e7WEvh5a1NktYpFtZXqLY2OZE0Of7ow/yOFaTdZeLOIkJPSOIWi8ceYa0pOBaVPHfzADqrWCkZDq6xPRyzvrLOX/zOt/Jvn73MjX0BzQZPry5TT8/zwqu3ybIerbUO5naJ1hZTWPCOKovRwqGNgbkKdElNXvSJTnYY391GjwtUFKOcxyuBiCVisY0vDbqsqb0EoYMAXT3i0sUvI2LNpz77b+j01pmM75JEHbZ3bjEYDKl0QRS5INJZ1ThV04mb1A1FWRkyYKYrZtOCJAY/0zjtiNIIg2OqK+LCMN7ZBynBQLEwJl3oo03QyqmmWxQomtKzfuxRlo+fQhFR1DM2b15iNtynGOxw7eY13vnE4+z1d0mjDlIpIiXpNDKW2k28FYhU0CyGrC726NzdBuuQ2rK6skihPHUWY8sRnUYDUefEkSKWEiMUg50pzU4Lm2jaDUE7VXRSQXelQXNoOaGbFBU4WyBaKWvrXQYHE/Zzz0o7Ra11SToNBluCbjPi6bNLvHzlLnGjiXAJnVaHWWXothKEdigVsdRRxE2L8EMmmwMKEZEpkNYyMpaV/IA7l16hu7zCW44tEAtHUXv89g1YyODqNbZffZ7rwwnLMai6oNfpcKKT8kQvw3dGtLtdRBwhfYGpK+LIsdJZpJ4NaXSadBsZT3VSRicX2JWOXg8ePbFIbTRLS12sKXASoqzBtKo4fqzDemMDq0s6C8s8//INaqlYWlrBFwU3Lt/k+5ZbtIRkFml+4KkVVs73qBpwp/aIap8rO7dQLPFQbwHrXHC2vkltCN7j7fy3c1hTEyn49ve8C+ccg9EU7RxxlITNY975XNdBpd3KkOU0zmOcw1mDtR5tNFobVCxIUkGz7ckyQSQlRVkzKyJ6iwHwbbzGCYiidnCY0LSyBCHknBXLYb3mTv8qUirWu2dIowZKpVjvGYzvBhdBSFa6J4lVRiRiZqZECkGkUrzzRCLi+OICadwJ30VImomn0gXjIsfNATNrpz2djTb2bsQZ43ACHnpfTD6WnD//BmlDYa3A2whbR3zmU23uHpScOCOQXuK8QziBzi2xLGlWllhp6mIMOjQN31fvehPS8fCZo+fFfbeQK5XjIQFt6Zg5T0VwUqt55SjxHiMFxntuScGuV6QmAIHu+pRNn9LF0LKGiKAFtO8SdkSDyIMGhD+k4RVMSZBRyDwfOM8Qz3atuVmXlEJw3RqqumQwh12tWHilmtK3jgjJhZdusSeDYHw7a/DWMy/SXM+ItMVeGEOsEDsl1dU9xLjEVgFq6JxHKkEcRRQ6kP/0WpJJXlIbEQR2rQ+07hzq1wWKeekFsZCkUtFJFL23ncK3FNz8IqkylM5itWWyN0LKioffFXP7UsJkpkgbbe5lGc/dvknPS7K0A67gmGsxyQNs7PU/uMzStudXbvw6P/7hd/HS9mVWuxHn3/9uLl28wRNPnkB5RVIp/rc/3OViZYjXmvjasj+acK6q6b92k0baJYojjsR6vsbxjWZHvJ/rmjlotT2PPrzOi1/ZZW/HBR20yTw4mNsaV0m0E7g6PC62Q9ORd2BmgpkBW4cLU07nVQ0XjjMeGrQO8E3jQ7+UlAop3NFaOrqkh7BWwOoOs4HHVgcUlWdswjyy3s4DMBko3KWnqi2X37jF3Ru/iLFjPIFEQ0qQCGKleM93rBAJuH6nQMQxlhgnPKQxFhP0iYzFa4giRewCbM44T2Fn1FYHWvFUMeokVHhSAyIRlF3BlXlWxTmH8Z44MiGRrCRxHAUNKyGIom3qekC7cRJnWxw62JEMep/iEGrpw5qvA0QD7UucM+zmW2hTUTmojcN7dYgOBObBci2wtcRoEF7TaTVIk0OiIM+R+u38GYCGjkgSG/qH/P1Xgq0WPP7EKZaXFnjpwi1On15nsddBCIk1jo/9+pf4zmMxT59M+J8+u89/+57jLHYixsMZ//ELBTe8411PrPBdDx/nlY++yMGe4UN//mEoPL/9/3ie73r0GFns+J9f2+HH/9L76DWbvPbP/gN5XfF4lrBfw++OZ7ytExFheWlS8dS5Bl8qDLmVfHFUYQUUzjPWjtpFIYXnHmihEmFmlZM+X3luxN2bozCPvEBJwZ/+7lO8enGH7sYia2emoCQylpR5werJY4F8wkIqBX/+B89xTU6prOXRx1aRKmKcl0gkaSYQONIkIo487WY7BHZaz6thIUhWRzP9T2Z83QMq5xzvfve7+dmf/VkA3vGOd3DhwgV++Zd/mR/90R/9eh/uaPz0T/80P/mTP3n0eDwec+rUKe5tXeftVvPajVfY7N8h8av81V9+BWM9iYBf+9xXIAJlGojpFlv7t4iVYH9hg9HuiG6ny9bBFne3b3GsF9NdPEncyhjne8yqnHa2SCoF+4MbXLp6gZZLaawt8GufvcqzVy8wqSXRzTVev7zDwd4ud/u7jKoBdw/u4bVGOYmPBTJJMLZGENHtdLEa4sxxMN6m0U5pOoNqNRlOc+JYUecF3nt0pYmbDZKGorIVTjviOMIogU4KjM9RLmZvcIutwSZ1WVDNSoRyGJUQCdC5YVYGBQYZR4xFBU6SCIn1wcgbLDovaXa6JLENPQsGbF4FPHEiUc0EXxuKcoIdS9Y3TuNRVOUMXRbkxPTdRarRPSwFk8kUW1ZkkeDqzWu0Gm1cJJlMxxw7cQylJDMToE2xgiSKiNtdmlHBTEScXO6yDqy2l7FFRby+yv6sZKgdJ84t8/mtZV7f3cd7wbP/8RVGpSFKBEWtmShJQ0paWQy1ZibBjmpWDBxbXcSXcLbb5ODGDv+Xt6+hREqilvjSzoh/vNuntoI/eGGbm3szEAorCY6zdSgkhde0ZELTKw6KIb1em2Ya4WNPVylKrWm2FEu1hdUl4kbCgtAU3rEfp1x+9ll4+SUqn1Ipi0wdD7VjxjVMD/Z5x9IClTEsdzo0AV9a0AbpHZYAW/KmIGn1iKTl/FoLUa1x4lseJu5K7mzv4Z1kUoPyFb3OMk+89528dmOft7/9EfY2FXhNp9fm5MYCV167xrd/y2km+3tcvtznZNMgdYVJoLWa8Njb1vjUVLE5swwnOfsHezw7HvB6oPwhS7M/9lr+RrMh1y5eJGm0aDQaYDWmynH5iLWlFoPRlJs37lAWOYtLiwyHI5IIOu02UZLhPExGYyaTHKkC051wFqlibFUAjuPnxywdGzMd14yGiuMbgjTzGGPJc027Hc1hJwGPLkRCJGIiCeCD7pqMQMCsGiMQ1K3VeXY0NBk7Z8KmjqQ/uRc2Pm+xrkZKReI12list3Q9xKoZMrhiDlGSGhWDMjCtPNOyxhlDK4OGV9TOcvLcbI78L9EehAIQyFTw2NsnnHm8RlBTFYJ87JmNHUVeU7gS7wVZWuD9DPwi97mjOMrY3s93zh0UgvN42GMjEDQxFFgOSsdu5anm5GS59lTG0YwtOIOtBdYqXm4soufyBI7QYN33CQMfHx0yQPwFm6LJJnPBTsS8ed4h04Td6YwEaHnFgoxYlhE71tMUEatxQorFOUfTS3pJxsholHMsNGM6BBaw7mqE0iWMPC6R+Ee6iEQRJVBfBDKFU4ReG23RCNRcq8o5jzAWaktRGYZOsGUdey40vwfgYwimlkSEdRaDIzee+mBGpj261lQOShcc2nxWsFl4Lv1+zah0bJeGJGmxvLLMrbt3UUKyvXObRrvLWm+JcV7hhSBaaLFz9TYzb7h2fYtboxlp2cEPDarb5I5s80KywqKDe42ag3LAqXPnSBdXGOcVsnbs39ohObNIHL+ZxvprGd9odsRYhzAOIaHd9PQWumzdOwgMZkJi8rDXHvY2CcBVngB+dTg9n+sCtBHoEpjDfu0cg3ooMTSbWpz3GFfTH99ASMmT70o4fiIlzeaaQkdneAikDTZBJgbrbCBQ0AZrPNY5Ku0pShu08ACsJ88LirycV2lAKUGWBJ0sKUJPlZCS4+dboT8IUApajYiVhR5SCKz2GHNIJR6YNJ1wJBkU2oaqhxLUC56LesBkV7P07S0+/J2PM9MabR17uzMuXxshW4rt3X0EnqyVEiUKBHRai3SbMYXYoqwOu6gEjSibJ2TEUe8STlB6GeytdzhjyesJVjjGM0eeQ104qspQ1RrnLNNRTZVnGO2pikDTXRWBke9+Wsjet2Ui3CyFw1VmbsfmEMxAF4EQkjt37jAaDhkNJ9yTnvFghJxX6SpTcjMvsdKQV5ovXd6jFQvquuK1O/vsOsOvfuEW/+tzt+jXFd5H/Nyvv4iRUAnLb16+RxoL6go+84UrdKImk8LwaKvFD60t8nI+4/LdPt+/vsyLQ03fOr7r+CKv9/vcFAUf2ejx6YOcG6Xlh9tNfmMCB8Zg7RxeeJQH8dx85c58rsojCw6Kut3i/FuPIzsZzYUuJlYsHmtTVRWtVoM0jqi1wWhB5CRX92N2pvMgSVh6XcFDx1P+0p97G92GZHEhotkyNNIMa1zo7Ts84nxp/Unypn/dA6qNjQ3e8pa3vOm5J554gn/37/4dAMeOBW2JnZ0dNjY2jt6zs7PD29/+9qP37O6+uYndGEO/3z/6+68eaZqSpn+UviOvYPnUab7y+u+QHwy5YwXH1zdwKNLlNZI05tbmDYRyDA40cdzkeG+NE6dO0kxjaqEpihJHhNGOVizJEgl5jbGGmdSUxYjnr77I1uY93nL+aQo34zOXr3N3fxtt4dnnPsp0uMdsPENXlt5Ki6quaK2tkrabTIdDZuMZUZQwORijFhuki0uMDm7jKk2SKfbGOaqo8Z0exng0hqyT4ZUkbWZEzYTewgITXdNpNMhtiZmUeJFi4ohJmWNqiGqHUw6rLZEtcMLh8WRe4GJJEJEWmKpCSUHSbjOpStLKob3CFBVGWBKlmBY6qJMLSRIleO1p9jooFdPrHiNt9igqja9LnIOTy4sURY4Snv3dHYzz9HoLbO3eZTorOLm6Rl5oqtqwsriMjCKk9UghKeqaTtZEZ02m+RRlxxClLBVTjknJLJIkpmDsHIvOcrLbZHWSkk27LMaaZ5YEiJisqfAyRdcl3gqS5QYy91gZ8fsvT9kvDRSepN2i3Nsn6fWIUouXEqUcS1ULVxjG2vOx526jCY5upCTlJEcIyPMcIRV1VeIXOrzz4Q2iKKGTRiw2FVEjJZ/UTKylhcFdvMfbz/fopgnNXptOFhrLXdbGeM/qQsy3ra3Q85p4ucGJezGRzPDGs4wkVYr+TkF/XHBrIlCtY2xPphzMDN2OYvveAZxfpddu8vqlbWy3xUGeUhQF2lR0TsxYPrXOzf2aSCr2Rp5rX7nCcOcWi902q+cfYmg6/NYnLkCtqcea7PvX6RSG2O0SrbcQrRVkKcnLAl0L2rFkp6zY1SVWGBac+aa1Ibvb2yyuHyNrNdH5DG8qHju/Qa/X4BPPvkJ/MKIRBedhf2uLlaUu3eUmXlQUWpKPR4xHOYtLHZTXTMZT2gsLHLrwcezJGpb+WJJPYJ4Mpigq9vcNjWwZGQsmxZRa30ZIyWJ7kU7aDSd4tFMcOv+e/dFtlAzUu86b+WvBIatNwSGEXYo5BFAIkjgCFMZP6c+K+ceGv1FKksaSNIIsjugkCk/Qd1FSYJ0nLw8dM46yvuC5d5Czn9R4DM7C1h3Lqy+G9XekaOkdbt4zEHlLIA9+gCyCw2rUVw0PEZbjcobyEHvNVaf47dsTxqMRg7pGek9pLMZZht5wRU/J9sYkicFuLKOPNCrFAx/7gONz/1BH4zDc84DIEm7ORngELTzfKjPWo5hPFSOkkqyIiLYQxMIxI2LBW24LCxaWGxGPNGOitYj2Ix1UDAzH1NMZ1bNTZBqRrme4NKbzwZOQeVCC7ZHnX15K+NDOHZaqAqxl38dcsZa7pWbLeqbWYjzUXqBx1HOtLoujcJ7aORpnVyERuP0B+cixmTuGdi6Ubh0rWN4Y1uxqw641iGguRO4hjSJ0rYm9Q1tLPimw1rCwtoJr7nJidYXF8w+z9aU3eES1WWn1KN75Tj67O+JzSycxk5y7+S4TK/mROQPtpKi5GSXUkwlL4s09Lv+Ju/9fHN9oduTCay8hlaTRkHzg/WeIleKlF6/yylduzYOJ+eoRghMnVlhcCtUIgTzSobp/OR585I/WfeirdOG3MOAqrK4QEfRWHKfPxTSyUCGYF6aOfHzvoT+u6Y8KplOFkoK8NGhtKErHfr8OgbsQIAW+8sx2xAMJj1CE2TgDMg5Q31mhiZTg/Nt6GG3RNpCQHzLNpbFCpuKoeGNs6OVDOLpdxXAaePmckDghmGU16nSonMdCYQoQxqGaUegrywRSuKOq22GgqE1NURXz8+eo+u60CQ53wA6HyqALrHrOWLzzWGsDkkBJRnnFy18WVKVjOKkYjgq08RSlp64irBUYa8nzAq3TeaB7v8L6YGoo/LY8mCgyRjCdBXgmHvqDbZQE6yQHezsIEXqunHNMizEfvTGEGx7pHP/zc2MifHDqZYNeLOkKeCyJUVnYnwye2ntOL8bMtGE00wyt55985nIg43GhT/fLxTY1DhT8880BxgYyjx/93Jip9pQO/sXdksIJjJf83wZjKpchpcJYjzaH6/V+r1qaKLSBWEpiHxHHKbqR0T29gBCSU08ew8/J862paTZTWq2MvVHJzXsTTAyFqZnNDIdhUhJBkVuWlgXTac5Cd412Cq1WgjEW71y4sg/GsV+jHflaxtc9oPrABz7ApUuX3vTc5cuXOXPmDBCaQo8dO8YnPvGJI6M1Ho957rnn+Ct/5a8A8C3f8i0Mh0NeeOEF3vWudwHwyU9+Eucc733ve7+m81lMV1k5tsTN37uCxuGs5WDSx8aSyd0ReEtdVVgZ05ERS6snaK52sd5wrAUXTR1YbBAooTHasLHY4y3nWly+eYM/vN7n6q1X2Lp1BznTXHjjRWQaU1YVSIgqQTUcQSzQtkY4j5aholPnU2bjKeWsBgUWC85RDYeUoxHeW+I4oRiX1BNLw0tEEmFqQ2upSdJQWA0uazIa5NRIkk6DSVkhVaBCb7caTEdDqrzGR4o4SUgXmvhSk3rJ2BnSVoRtFMQOhBVYpXCNCDOpcJMckQh0EmFrTVWURGlMJQzCB/xBomISJD6GuvScOH0GL8CYHAiwg43VdcrpANlpsn3vDkpKZrmm03Ds7Q5ZbHSwxtLIYnRR01tYJlGKJA59SKasyOUUKSOqYsZSUtCLljh+vMNi09JKusS6pCWbOG1ZWFjkLcJyb2ZQ7SU2C49ShnbSoMYQk+ClQBQxttY4FdFe73G+6Vhbydh9/SrTmcHLCFvUpFkDGUn0qE9bWKYuCrSw0gXxROERygV6VOdoSxF0h2YlriiwcYRPFUkUobFMSo1FYZJAP7xWlbhC08hzomYLE7WI8wkNa9kcT3ltf5enji1xe2/IrjE8ffIsTzYkCwn82tU7XHi1Zjw94MRb3s5Z4zB1wXBUUC4XeG3YvHybJI6RK2e4cHOfO7tbCJmQAGcP9nnLU08yqNvsXPoi21NFWUGGoxyPeP1zn2Pt/Gme+Z7vZNrfpX+wR9brYvI9pKgoqoxyWDFwAuMMxIqbwwlxGqPiiLoq2R8dfNPaEJj3PumQjVRS8uf/9AexzvArv/5REB4nJNoYVBQjVehTcU5TlgbrHVIpDrt/JEGd3gt55EAJwRzXdj8LDWCM487mmFOnu5SiZFbNcDgQkmbSQiJw8/9qG+BgcSTRtsYGgaU53ISjfdt6KGpHrRULrYg0jh4E1xH+wh09VkIhvJz3ZUGiIMlk6IuygeULJN1UPCDCe+gghqDRWEtdh16OWnuclfdhfPO9d1wnTPVlIm4RxV1W208Riejo1A8/+H7wExzJhjC8uznDOM8fDjMOTEyj06HX3+dPRZJGb5kNGfOdDcX7z57hbCfhYGK4PZ1x1Of11Q4rD7o5/6kZAYf9clIK5LzKVeP5DAVCeEyqGHvBLVuT4jlpQTrDMoo0icFabKyIm4L2+xLEeorvCRBNpKkQnz+AXFPsz9DWMf3ELb7c7nEji5kYz2vGcLmxSJz1iObB6n5xwI6Zknsb2P2charAeHDOYgnVqgCSjLjTH+DuDvn05h4X+5ph7bhl50KjwGoiMa2M3WGOdgZPivdhfjfTCCFgdLBDtXKMoqyp64pmu82B1SjvsLMZ46qkcppIwEJnlTPdLtHAMNo+4GZtEU5y/MQJZlXFrKhwCwnGHzqab7riX9P4RrMj+SxHoIhjxbd94DFuXj/gY797mb39/M0TTQhazYRmK0ZKRRwlSCG/ao7Oe39CuIEX/qgPykvHyScmLCxApTWbWx4pPb2uIFKHh5qvowcTMQiM8dS1I00VwnuMcdTGo+esfocitd4KjBHo2ZvhmEIBPgRLeM/OwQQpBadOdGk0IvoHhrIMGaNipkPiRcHqcpNmFnHj4hRbe0491sJ4i5Chj9F4yyAvUAIiFeylA8rKBjbkxLNyIg7BnhNM9hx6DFJaGhsw8xOc80RRhDyydn6uayc41ItirheFD6LlIaBygURIOqraMZnGpKmjqjSTPIiaV7Wi1jEQkB1CSA72AunOkaET963rkZMvuJ82ch7jPLUG70LAa73D+sN7O7+/PkB+e2ttWo0Q4B5f6rK80iaOBJETbL4xpMg1As/YGZS3RM4QW0NmHS3rwQV2xke95aWSgAaaa9C1YkEmIHGCllMseU9DhIqdSTxTbxg6x8QKBhouI3FKoDxUWqCi+/uJBxZbkr/8Hcf59IUJTx1vsCxPUKZNdhah1g4RwWxUUlU1WTMCZ8iyhPX1RV596Sb/w8deoa4F1qtQzRNuHhQH2Ycohe/9/oqP/MXjGJ3Q7aZYbeeojvvbnxT/NZbkjz++7gHV3/pbf4v3v//9/OzP/ix/4S/8Bb70pS/xK7/yK/zKr/wKEDKef/Nv/k3+4T/8hzzyyCNHVKXHjx/nz/7ZPwuELNL3fu/38mM/9mP88i//MlprfuInfoKPfOQjXxOrDsCx0w8R+ZLxnbso4xjmY4qyotZlEIDzjoSITrtBp7nItBqzt3WH4+sL3DwQWKMZHdzBipisnaC95dbePptXbrM7PGBcOOpZhYpj6pZHGE09NjSbCWVdBorkKBg/YUIzZTGeoVDYWY0ToPMKpRJMPJ/k3qDSFOk8JGGzj+ogVucrTdpqUo5nlINQjladGrShEAJtND5WoECoCF3U2KLGTgqcFMgOMIRIRUFTx3kqV1KZOtBeewKuxzi0dyg8iY8CbMQEQg2kRNeaKIlIezFRkmBNjZIZ6+tnaSQJSRqRTyaMBmPOPfR0gKM0O4z6B3gU93b2Offw49y+fYUsUqyuLDHYH3Dm7HmazQ69VoI3lnihSRwputKyJBS+0yLaMnQFfMuyYu2DpxDrMdRjiDagHsFYwIkTLFw2fOnqNgtNePpda8j2FLG6BNYGQo1ZiVhYBl+BSHjojS3uPLvF0ok2nWdaiDgBlUBdgYohabJ41dD+rYIqaVJ5HZziWtNIO6w0WyzZIZdKgSsKRJpxPEl4TDmst7x7ZZHjCxGzouK13RmRkiwsNNloCFZXYkysMFOIsja1i1G2wtc1n7qwyZd2hlzbGXJpktNYPc3WjVt88Lse5aXLd/iDO0O2BxNqk7P2iAjN9AhW2i0eWhJIA1fuDVg++Qi7U8lgUrOy8TA2ikniCJG0aaWKnVnBnVdeo3XiJJNGm/6NAC9dWlllePsuty9cZDQr8bu3Ed//NNHxBv7qkPFuhVwrMK3Qi5K2e+BAuhoXZ1B5qkNMyjehDWmmEbHT6Ok4UDsIaLfblNoEnbtei2leMJrkNBZ6OCXDJixCz1WkBGkWByYvGzSsrK5DM4R3YcvxD+TgpTgqxwgv0GYuLSkg0CoL+pM+k1nOemcD7y2TXPPR39lndTnmW791KbB4HW0k4sjZgtA/NJiC0ZZGIlFSz7O2IVN8iIhQUtJuNJHivgsS4j+Hto6isnM2JwLFsRdHnwOBTveNW7tsD3IqbRmNLVp7tu64OQ10yBYfHi80h2uM10gfUVcDZLKEEOqrKkhBpDPsjA7nIfcK7Ty1VFQqoZPWNBqeH+oscqwd01IRT/mac+fXyRotlvolN6YWI7+KRveBzP+bgqn7HeP3n0IcZV8FcyeS0KslAKEkA+CC0tTWg/JICU6IEKDiEZEgihRCRYhYBIEoCWopBQnO+DnlsKPOLW9IyQu+OQ9cQ377XJmzZGpeyBZxGydZWT/BigxEINVkyvs2bzKTksp7Ku+4oA0nasN1D9oJpoXmd29OuTYy9GLJyEFbSrptRU9YtozjYl3Rlg6vBAaPd4YsDmLBrd4KDqhqG+Dkccx2XbM501w4GLA5yrl2MObueIbrNrl76xqjzT3G9Yz0ZAezOWVleZHZLAh6xkrNIW9fDfP72lyhbzQ74sKtJU0UrXbG1u6E4bAgrMw3pw3u3t1je/uAbrfFE0+cD3pwR2l2ceRgH12VQ4d7PgdPnNWcPg/aGJqbMeBZWo6JojfN6sPa1gOfFOZbKNYIDoY105l+4PM9w13NbDgvbYXSWFgHh7mgeYLosBI0fwdKzoMhQqKo1CFpIyT0upY0VUSpABl6tqwLPVkQZE22BmOSWLLQTkOlRsDd/Rwz7ydM0jBjnPOoWELp0bkgWwOvQJuSSXkQ7JmYX8+5FEXsG0QuIQRZoQnImcCeYE2omPsy4t71iknfUmdj8mXFbJbhrOXu5hhhJWpe7ba1QKtQcXqgQPVVl/pQBH1u7/2DlXGPt56qssxqcz+YPQxovWDt+DKnFpZQQvDQ2TXW17rgQVeWwd4lSgocnsk8kRd6m0IAjgfhxDyItHSspe1C4MicAt8ZuN0vMMYj/Vx22c8TacQYQt9aqcK5Se9wwlFbT/TAdi+ASntevjlld1Lz/G2LEreYOM8TDz/ElRfu8PgzJ/nKx2+wvTnku77zODxzHoHj4XMn6O9MWVlucuPWkFluEZIjxIQQgqp2pEnCw2cfQ0WwsNJkZbmD1iawNL5plosHC6pf9/F1D6ieeeYZ/v2///f89E//ND/zMz/DuXPn+Pmf/3l+5Ed+5Og9P/VTP0We5/z4j/84w+GQD37wg3zsYx870n0A+Nf/+l/zEz/xE3z3d3/3kZjeL/zCL3zN53P2oce5tXeNyXCIrz2m9GgxI0oSkjjF+pokAj2bMvI164srPPrkYzz6+OOUIuH63g75dI9elDJVi+hYsTfoMx1M6CaQAaacETVjjHYkNsb7iumkCFz8XmJKjZqFiaWyFDezOAUyipF1RZYm1Fi0CrhdgyeR4J2hGBuiOCaSEkMwcjqvEEqhq6BrI2clEkGNx5SWuNMka2Xk+yO0dyRpjJEKqQRZV4GxTEcF0nsQijSVSCupSo2VAmUEIoPMxjhtcDLGlhq0pTY2NN8bi2plqGYCpiZSTdZOPYTLS8o8Zzr1VLMpZx5+gkm+Syo7RColjSL2+7usrG4wmQ6YDKesLfaoa42WCeMihyjlYDBhdbFLp5ESxzGZdLSMhrjL2EhkFNGKagRxUJ/3BkyJm8yQowJWVqmnOTYO2g6qrnHTJrAHaQJ6hqgkLsrBTRG1YHhjyN7E06kclGWAB0Tgaw2iROCZTTyFSmg2IqqZwomIaazpRSnLjSYfWsvYvjGmLiU+yVhptVlJauqZYaEVky4K8BHNWJJkEd00IcocclEhVBvrFGnDI8o8MGMlERU1UyGZVYbW2hk6MqKcVXzstbv8/qVtZiamzEck7Q75NA+U3apBriWj8ZT3PL7MYjXjYtZhd7ciW1zBqxhnPSYS5HVFqsL8aWysku/v0Vp/nKrRxOkZ5WjE0uIyo+1tiuYK8dpx9LEniRsJ9uUrXNouubZT0jgbYcoKIWFh/Ti6HKLrOsA49B8f8veNZkMajVAJ0lWFszXtrEmaNqnKkv7+HtZoGkkEeKJUEQkxN+Rg6ppIChqJwgGJVMhmM1AF4zFWIzgIwcXcOc9zhxeOLJEsLao5HMbDPEsNQTumqAp+41OXSGPJu96ZMRo4ssRjNPQnGomg146ojWFzqyBLBatrCUki6GQerQJFdl4eVrFCgOPmMDwl1Zz9ah6cHVWUHMb5ebOvxNh5YEQg4hCANp6DYc3uQcHOvZqyDMFEkga68iC5M4+mhJ8X5/xRWUj7AXvTlzjWez9xFJrI4b6DdvTAw4SIj896eC8wUaig6ahFHjf5zb1bNMaCv7Z6nD8sJ+T7A55uWr4wttxuLOLkodfn/8sb7VHh8AHH97BhhQecSO4XGsNLnoZUaG8D46A8DGslUgpetJKmhs5tR2Zqji+0kUC8EePTAEny8yqaQCD9Yfg2z7jiWXWaDVtywTukVBx5dd5jheeFNA7EJXNHrI6h8gI9z36Pipq9UpM4w9moycvGsIAgUaHhfGRCgmZNhIqJdQ7jHFVdY5whsoaqKjDWkOcaJPybO9t8YnvIZ+/tQaT4zU3P1hff4D1PPcq//c0/5NWbm8TveITk6XP4/QMWel3yWY62HiUDBHXOYv9mdNvXML7R7Ei48YIPPnOcXqvJhb0tjDPMCyPAYVAS+ieNsUwnBffu7SKFZHVtmTQJTr/gzY76Yeh5/JGc1ROGxUXmkLqI0yc6OO9JYoWUglkRqir3A7HDmeopKo2xDm0sXgQo7+HnQ5hWhyxuUSxYWg4lL3GYDRKCKOa+zeI+i6CUsLySsbzimUxr7t2dPXDywek/djbFzRlRvfFHC0owt03eU9SBdMs7gdGAOjz78FtIT/uYx5aC8c0YkAjhsdZQFgVJmiClvG9MPCifYK1D6yBYKyD0hhOgr1IEog3hJMZC4gVGG7TWGOOoagvCESWKNFG0Ox5jFe2WvG9fDg/n7/8crusjoXYIyaL5Am85yE007+cKNtfOWUnF1LLSCLTjo70Bo71+6PmyjiT1dLoRjsAa6Z1nNDFHFZuj0pggsOFFc/KMOcOh8BJbw/5+Qe0CzsA/YCD9nLzDc0hA4Y7OuTaOxM2N4DxTWNSeT74+Cvdi4MHnxGnEI5VjNipxpcVojzMeXYfgzeiat731UV740hXe+rbjnDi5yJWbQ5Ik4uSpZc6dWmIwnHLr1pid7YpZbYlUzf/pI+d49OEV9vZnHMoHHA3h8fJPrkb1dQ+oAD784Q/z4Q9/+D/7uhCCn/mZn+FnfuZn/rPvWVpa+pqF8/5T4+xDj3Lp9U9gxzmoGC8FUayIoxg9neAlTKRDOklXtHDFhC987tNcuXyDD37HDxGrlOW1s7SaEZNpzeCgT9bKSNOIarLP3cmQWg8o8gpdHeoKBFYlbUI5NmqkMG/I1EUJxoFQyCQmihIa3TY2zwPb1pKgGFdU0xlW6NBnIAV1rPDG4WtHnEbU1mKLImSwPcg0RfTagdJXV+T9GqEdWbeJcTWimdBspTSimNmsxOFDVlSCVkArIZqa4CzFEtVIkUJQHYyJZjNEJBA2LA4rdDCAswpTauKowcLJszjjcQpmRY6ta86dfYLJeB+ra3rHlxnvjOgfHFBbwcmzi1y58BKR87Q6Le7t7LDUW2E6zmk1WwyG+0i5TiOOkXFMiqXwGl9VdJOEZmqpZhNatoK+DmDayCOqNs5WyLqiLqAczuidXMHIoJGk/DG8mSJ8FO6JifGVwss2EzmBrqVSCeSCe89fQzZaHDu3hlAetGM2tkSxovYWg8BaQyZC78eoNnxmK6fCsJR5Kmkp6xKZCCqpMVITL3eI4wS5P8OriNwCrqYb9ZjNFIW1RBrK3CIWUu5t7rFXK1KlqGSTRTxv7Uh2Jp7/7eIWQwsUOc2sRVHVVPWMLElRcQLestYNVLN3lze4E7UgmuBVTBKlxLVFR4JCa4S0NBptrFgAMSNtZcQPPUY53MZqw8QYukbz+OOn+eRnv8K//Ee/yPc9vcGv/d5LfEks8vgHDI95Q1VMiXG0khijFtit9nEi6Kt9LeMbyYZ0FpYQKqKua/Y2dzj76DKtVsJ4krPcbWLn9Oh4zyG8zviAw1eNFo00OBT2MAMcNfBxihAV0lV4JNNxCGR6y56bN0qW1wWdJGFlSc6dLEk76zAtxkfK9A5Pnmu2Rpo7WxOMgYN9y8f/YMBoaHAevu2DK8QpvHpxyupKxOKKQlpFHEGsxNx5uF998gSbFc7UMSnywys+f09wbA5Z2K2BovSMJiWLi02qSjOeVBQzizaBE3BtVWCc5JVXa+7e9FT5fU/m0BE8JJl4kNHNe0tlCrxXxFGGnMPQHtSSOfx//UCoJYQAFZN0emzfrMgLzbVsxoW6YmU64/G4xQtxm4vt3puDKH//M9/0nQ8feY4EUueX4sgTTgQsCkEhZXBgfHguk5LSWyIh8TbMCSEEbS94TAleMpLFQhC/WLKw7dh4Mjg6002PlgrhNR74jGpxJ47ZERGpDVAWMw/i9mVEFWXUQiAPHTfnUc6TIimTBlYbDIaRDjTHV2KJc4LbecUvv3ab7aLAGssL4wmTqsYIx3bl+Lm9ksu1ZdpI+aKzRCrCOIsTimtbB9QWiuEEWzvcuXNMpgULacbqQpfm2PHM2TVWWzH9KuUvnj3JMx98lIuX38k108ZHGX5qkUC312K8cxfnAumBF/fnyJswO1/j+EayI34eHT752CpJq8Nv/rvfmwc2h1/ufsUznByUZcW1q3cQUpCmEb1eO4RTQpKkIbgK8XaAY61sWB5/q0MIFWBRAtqNNEACETjveePmHnlRzQtM/oG8gDhqbxgUJcAR/fX8G8A8sEF4VAIrpyVKzfsl75uR+XnNKzB+rijhQMhwDSIlQ9LJi/sL+tD5nfcyHf1b+CMb4ZwnLx2zkacYg5CCbOE/vWaFmtsx6fFSgPMYa4md/6qlHRBEznqK3BBFMlCizys7GEiVwEuJ9wrnLM4HkhlrLM5q4lTQXQyQ/kRFCDllNAx9dFJFR9XrwwrgYY/UoQES82A02ONwQYwVzGYaJ+fX48FADICQ2HoQwogLBCJrJyJWnDp6v7OOm3cqan0/8PEuyD84d5i8mCe25gmcigB1d/Ng95Ba3h9dmTf/F15x1MbxJkDK4RKeB16hvy+sPW88VnusuX8PqzokcOqy4PxDJwIrrA1VzbvXStpLEU8+mfLEExt84bmrlIUOvnMcUVUlC52YNI7QlQEZGFmlDLptUoGLJX9S408koPpGGisbS3z8919HWfDY+c0VlLMcJ2yoxliLSmPyyYzrs5Io7XNne5Mnnvwg165fZn9nj+WlNm465PWtm7hGQhxrVjsp/WGfeiYwBZiqQkqJyBRKSmRVEmcZcaIAh9UOKRI0GpzEW4M3gqosSFOF1hpdWWQq8M6jbGB1ssbgygD7EToQJKRKouMEayxJHOOjGKpQ4kxchBcOmcYkwiMsxM0m5XhCMfKoRkrSzOZ/26DWFZT1fH3HpF5QFRUmFmSdjHpSUh/qTpnQ+yDjBIQkayasb5zFeYEpZwjviKzn+ImHMa6m7A/pdZbId7aY5TNG05zHHn0Lw/4udWlZ6C3iUCgUrd4Cyjl6q6voyZimiGllKVIldOKAhhkjaTVSFloG0YyRx9oBlpfOIE6haWEQ4deWWTxbsdC4yLIsUMtrkACLx5Amx3UWoO5DHCFdDy8kJ42nl27ReWQZjrdxexVlv0As9iCLQSkWT1qUqejbCKsNwno0FkzN1nDM5fGYOI7om0Bf/nQ34ZHFHgcTR2spDjC5fJ/jkceKigawuNwmObWIur1PN1PIpS7pqIkwfdZ7KT/+tnOwvsxzr97ks3s1qi54OLb0Y0lqam7EHkjQByMSAYkUYGp6aQzjEsUqV3LPQT5m++YNDoZT0qwBwOlT65w+30E5zepil+aJc0gZKLqT9TPEiSTyAiMFURIxKC1rZ07y2y++wm9+8XVK5zj+2DGc9AgZUc40tfZMZjO6Wcx6b4FYOgYH+19zUPWNMrQNENiyLMHD+9/3Nh5/+1P8k1/8N0xm1Rxz/+CWEpwJ5x3O+rlQp0DbkFnMOgc00xFKzJBoHBXbm4ok86wd9+j6EAYij0ghrIFm1iFLMhyOWZWz1w9i4saE5A1eUFWOrXsVUgYc+4XXR6QpREJQVZ7bmzUb6ymtRlCmP0r/+/u/nBPMpo5WK0B0DqsdHkF/XFPPWam885j594uTCGeh1UhI4ohbkxHehc0siRyJgLc+GXP+FAyHnrKA2zcN68dCBXmWGy5frpg3NcydBs2d/eegznj07Hfg5/1UD57v4ThCAM6/j/ACLxS1FFTWs1/VRM7xdLeBq0tm8dK8sfl+t9iDnxmKCQ8+4WnXNd852qXhLSMv2LUO62FUlgyk4lTk8TLhLhA5Sy1CA7b0CushlqEiFEvFk0g+FMOnxGEfQPgNMtBi+yau08X2C4QQLMzFhM+WQ5qzkGn+eKtHP07YjGKEiFDWsGACPEs4T6kdibXItI0QFq1LhNGkXlAKR5qFDPbLgzEegZU+NKUTEgIH2rJpDIPDDPWcSMA4g5SKtNElafUY9ftUZQ3Ck08L1joZC5mkEaXUTmCFhLqmbYLD8ejpFc7f3uLileuMvnSPxXaTdrvJ3SsTvHdBgulNt8PzJ4rT+f/ROHRH0ywln3le/MrevB8E3uzhP5DgOFx+zvPGxZtIGSo+q2uLPP7EwxxWgERUB/0nYTgsld4nWwifeVjXNDYI04Yg69BuPRjUzR1k/0BV+vDsxQOnKI8ONa8k3X/J+/tSBni4tzeew/fmrr91cwKKQBe+dzBjOBU0WhJrPMM9h9Z+XiHzmNqxsKrmUGGO6OOZO+aHlZCjKziv/DjvmA0FaWMOb3MCV5rAOCiDqHGkBFJqhAXvNEYLjHOBTVOAkhGNNEOKGKEKyrxE155yPcU4i3cVk0nNbOKxqYfU4YDheEglKzZWT5GkGcKH5EEIXsT83opD84o/vJeHt9+AGZkjxMBRQOU8Qkocjqm2oXp2OFGcC0LO1h3dLD+vRi6tR3O7KPDC4ZxD+tA35bzHCQfe4wgJm1Hf4C97hDysiR8G4IH+P+wJbh5wHRbiLNpWSNFAyiBIfz9c9/N5Mf/e3mFKg9Waugj9agB1FQSRdZWzvrFErBTa2KBV5iom/RJdGbI05t6dMaNBSRo3SZSgrirSJEYpRVnVkFQ4a0mymIVeAoXHJfH/p6X6Xz3+Dx9Q1aJg6/ZdbDKH4UiJcMFBEl5gEchIgFJYo7F1jRfQkAlKzol0pUfriMgDdka/v4/3UJdt+sMSpx2mqEFbaMY4H4NxeJFgnCdzNbPZDFuD9IrDXDU6wgiBLwxiLhIXRQotJE5WQIzIYqwuwHi8VyA9ta1QQiCSiFgm1GWJrzUqUkgRUQmQjRipFK6sUQRBP2cNToNNDJlM0LaktmEBVrMZUkUoJbCuRlgLrZTKmIBHzmv8HKpjncFjkSpiVklub2+y2FvCF45GlLKyfhIXw2D3HiQRU2koRwP6oxELqw+Rdprc3byC9J72QovBwR5SJKyvrHDv7k3OLS+xc+c6JJIsSxFSEqWCFSExyjMTis1+yfG1iKQpEUkPRBxK/60crARpmR1sQZRxakXhmxWi00M0wFVAt42wVcgauzpQUfcMC70hYv1xRLfFyTNN6oUYFpcQaZgjUWeIsDUq6uKkIGk0MJM+qYDFZsJ6lHIzNyQiIo0US0lCIxIsS+ilHpYWEEtbJI0CVUXE7RW0h4YuEYsJfjxGVBpXa3YujXipjEglfM/SlOzcAseaBWebU944aHOpv833PLLEr1ybMRpuY43GOwsJNIXkA4+u8t5Vz+9cHvHCjiOOp1y68CL37t05crgXeBcPPbNOZAuWuz0eOn+c5vIQqxIGyTHkgcHWNdprtHEYPePEQsT05Cpf6g9YiQztRoYgQqLQusZFBpzBWAGxotVeZXjQ/9/PCPx/OXbu3gkbmPMkStHqhCrjG5dus78zmm8y7n7mkSM3h8Mu8AcAKUTZFEy4Hg6PtQEiJ+cBlzNz5j0PxoKSnt29PuNpzlsePk+rkREpRZlb1tcFi71DYIc7OhdjbdhYvUUbyBqhGl1WnnY7njNhPcB3JKDShmluSOKYZjNi3spy9LrHkyWKYmbw1h9BTyBsgnt7I9IkQkXRA9nMw+shaDUUzQzixBFFUOSKM+ci0gQGfcnVK9WRE33oN6nI4muL9XM2rvnPm7pO/ohDCsZotrbvskio1BwXoKxhZiy3c8NdRmzPaqI4pt1uBQjQ0Z2bZ2vFfWcA74nrisenuzSt44tOkmiD9Z5H65obSqJUhJKKk16yBryMYxXwUlJ7D0IywbMgFZmMGMjQP5cSTJfyoW9BSo+9dIfieh8lJV7BB+IKQXl0LjmCzwuNNp7H8hnNiKOg3gEF8EJu2JnVoWfUBsFXKYJchHEh8yzFfcpoKcW878+QC88nC8PAHjrb7oFra4/mBNZS5jlpFCCv00lB+60n+fY/9V62n7/M869cZ2uk6EWSN/Zv86R/C9/39jOMxxV3Dqb0b18jW+jQamYMRtNwGPGgg3boF95fW9+0w8PZ5ZQzJ9tMJgVVdfQtHxiCNz37wPcP1z1cA+MsXkDarZCJ5h3fOqLVVjQaD1aKjlbT/cf+ftJnnjX4qkTCm8/pcC0EIgTmCRTmAdthZeWBs37A1lnjcRZk7PFflU3zc8jwYZWkqA1CedaTBF3B7VsGPBw7kWINHNwzdJcVcl5R9/OShz8i5njgq87PtSrACcfglZjveN9JugstWu0GkQoJb7yirDTddkYcz5kHCXDG0bRmYamHwCGFRyrJwaBm1fd4fNnjUXS6GYtLTZr/3VN02y3Onu3S60bkZUm7s8zduwO09vRaU7LMMCstC70WXhzq2Cm8E0xmhm47Qcj5OhRhXTrvWeq2WVlqzStXh1bvsJK1At6zO5ywutiaU9f7o/sphEQC/WHBYq85D+BCRct5GIw1rVYUejrn/VHeSWptKIpwjt/6/Wb+uRHOOUaTgk4zQ87XqHOOuq4pioosjbDe0GpEJFHE+75jnaKyoRLlPPms5g8/eZNpXockoxeMbu/TTiPuvnaXhrIcP9Yki+MA365LFpeO8dAjDWw9RVrD2joUlSdOgohvOatoNxXLyw2i2KFrTRpFCKlothLWjy1jTYi+HR46ktp+Ewn7fqONnZ0bzMoKmShsHVj0wmJUeBGam2MVI1GotElVDnFVRd1OuHXvdeq6ohE36bQ6jGdbaOPQpSaNUwb9IdZYZBKTCoWeSQQxLi8QWQORAd4zHdc4G6FkuOFCRPNKt0M1MqJYUlU1IHB5FajLjcWJQPkrXDBokhDsOScRWgQ2sSwBWxPN+xGM0zgPcSTwxobGxlrTiCMaix2qSUk1nDCdaWQs8WkMzZioqtC1xnuJFkEJoZrVoRIVe2QrwVeAAlfUeKdCZtrXIYPhYyIlcE4yLUsGt+9gPKTdBUajbabjITKKUGbG7t1rFGVJnEjG4wOm5YwkbtBaaDC7nHPtyqtMphMSKbly4xYvvPQVfv8Lr7HSXsO2O2xfu8KJ5S7dnQNWXttDqoyslREzo5zlFIXl1FvexY2rd/jCqxd54qHv4Pf/5fO0VrrErR5KKGT7Bg2ZUJX7eD1DRin1dEaxs09n83Va3Qw/nrC1ecDKo1NarQZSSPp7fbYLw1AOQEhqWzM1MyhgOJ5wYilif3uAr0q67Q6XRymf3oamqdi5K2le2EXs1AzGGqKEnd2S1VHFujdIleCHBVnPUJY1o4VlXn55l8V4xNuHDRrdJqepWX3kJG989jLj8ZjVtUdZunWLq3XJ6bVVMiFAG84uxDy60iIh4WxD8wWTU4mQ/W21myRpirGOG/f2GU8nUI1YPXaMG0WNvXkHhyFeFxR7+5jBLuNCU2vLpNakKyvcunGHQsDFSUFUSNacQ3iNrQtcJMHCdJrTbqU0khZLvUVmd/73tQX/tcOUY4RQOOc5fuo4rXaGMZbB1ibjrVsAc2dv3tAdngl/PMfqexeSM3hwE0F6JkYCRXFIMeuJk/Ande2C4GXluHKp4PxDKbE3TI1lNM6ptabdTji+scDGhxcOvR4gBDh5UWMtJOlcSwU3h86E7HMxK3AWIglxdD8e8d4zHNXEStDaUHgHVhzmtT3WwySvGY5q8IJmUwHcpzP3MB6XWBeqXPd39uAICB9YALVxGCs4fV6QF4YLFzTlbH4Sh84zhAp4A8pSMywu0Gs/iqL95mDq8FI/mJ1GEMUxqtNmc8dzAo/1jkuTnJ969nX+/qlTlN0F8lKTOIgiTaSieQAFb/bbDwMqR18b/q1sEDnLbQGjKApvbiY47+gLT4rnIW/oKjjm4f2RoCs9BbBvPS84yTkHOxg+YT1/3tWcsTZQ5W8bbv76dTrrDeJBRTtTpIKwTx3WEeYQHBCs2prMVHxQzjghgpPsfIDXVkJyrdK8NKsfLDMggdyFQNA4Q1fGZA9UDoyz5FVJ2W6wHwve3lK8kBuKefnVe6jrGu8M1jlwgTnXyRDIjwdTGic2+FP//V9Anf5DPvOVW1w5qJmO92mdO80Pnn+Y5cdjFq/tIJ2DSNJZaJJlMf3RiNDHd/Rtw629H9N+cw/h+ba3LfH2d57kM8/epiwfdOz+CxW4+fy+L2EkGA6mvPzKZd7/Q57zj8HyeptGKh9YFGFoY0OMOm/kZx6AvDnU+uqzeHO/j64EQgqGu5bbL1lk5mit3D+X+/mMYGMOP2PWFxRD6J1yxOlXHW9OaLFzu6aYOtYfjlBzOGywl+E9QgmEBTeHHvpDTKTyiBimQ8Nw39HdkLSWxSFaEGMcg3tQjwVl7rl+q6TbheUlQRzHROJQ6Bhmk9n9YEZKpAcroDJ5qP4IR9ZocfvGDKwjiiVKWmw9Y7A3Y2UpJoo0+3u7HBzAcKxZXEhIkpgkiqkqj65r8sLgjAlJ/Tkc0jo4GMxYXlT3kzrziW6tZ7+fMxomSBk/UAkM5xrNA8Dt/oy6aKHkPNnk3Zz6PVzD4bBk1EvC6yJcI208/bFlZUkiheKwVuk9VJWl1J52I0bKed+uEIGG3GvwyRFdXuj3ssjIkDYb8+MbSm1wVDgsrWYGzlMbQ6+bkGZzMXobYJbLixneQ7sRvmOWRJTaYY2m3W3wzndtsL9zAIsxp0+doNaOE+cWWV5p8N3fdWyefBRYvYWulmg3OggZMx6XXLqyiYqjEBh7z/HjS6jo/w/5+68et65dRJcVadagEiVWW5RKES7QlEdpglAR1tWYInQ4OhHY/a5cv4CZTVjqnaKZKqoswlaeqJZEylNVjsh5dFnhWxmR0AgNMoowyqCExFaaqJD4KBgFiaDRzNBFID2QhIkTpQkeC7VEGB0yLxa81yiliLLQh1UWJVEcI5MYpzxmMkN6h0eBDyxMWZRircEbh4si4iRGKEGcNTBKIosCU9VIGlhrUEbQarbJ6zG2DsdTwiOExHmHiCIacUptKuJYBngHDiklBkucJMz8AD2znDvxODvb9zCFJmk3cZMJejpmsd2ldp4kjqn6d6hHI0oF1rWJUSQqxRUF44N73Ll9hROr6yTS8MnPf55/87/8BqY2rGwc5+zZ01y8eQ171c4Nw4xYJDxz7iymHvPKnT6VMHR//woIyXA85qf/1UdZWVplf+clOkvHsFXBQneBPB/T6S2wc/cmdRWcRCMhEW8g5xk84xxCvYiaE3jU3qE9WKvnm4Oklo6B99zdUhz6rk447u1GXLlxg18TDokjVjLsbPMy+GH/ikcGaFASml5jAa3FHlFrgbo2NITno9f6jKZjohS8TOnvbEEU8z9+5g3u3t1mUsyYzqZUHq7f/TXqyYT/VWpSK5l5Q7qwTK3GOG/JWk0W2gsoBZGQPH/xJsfPneX9j7yD9mIHcXyduCrodVJm2UPk0iHqmvGoIJ8VXLy5xeZ+n7GuscYjG220dcgoppoNiBotytkU4UpcvIAz0zns7Ztz1MPdkO2Tkve/+8/wjrc+RlVrRrt3KA6251lR8UA558HxQP507hlGUYwQS3g/r/K4wz89rOYEXoFmD6Jono2cf/YbV26RJilvf/oMMg6HjY6IFQTCe5rz6rRSzB3UOSueEGjjuXs3p6otEk07c0dZ6NoYvLNBMPJ2NSeOmH+LeZbaGD/fqGE28/PKR9hYJRJtBCIKxwt+gccYENLTPwhVy1s3azqdiFZbcrBvuXvHgJnDSo6y6/d9tFpbhtMBC00XHJ8Hru3Rvx7wEI9qhF5inAznN9e5GnkYe4vIMrpZGyFEoCV2lkgq+CMu5v3DGA87QmKEY8x9qOChw4GHGGhh6TjHW4A172k6hwV6XtDzlo53bBiYSHjIOZbKCi8klGAnUN2b0WxFqIg5DCYEUcLPSeg9RN7zZ/2Ul7xiQfij++MOE9TeYb07qkoczkQH6Psd8WhrSVQgbq60pT+eUhuDRrJvoLaHlYTwIUWRM9i9i3eOhnJoZwB7RFQx6Ac9LqkUT/SW+Z/+zHsYTwrGoz69Eyv8q//nb1Jqy8U37tJUhqzR4thim1ZqGQyHKIID5w+rEP4QBvVfCDi+SUYkBY8/ukLlEv7xz30RYw47Ar+27+bxZN2aZGlEnCWkaTKHjb05mrLO8fqtXWZljZCec8dXWO62jpI/4bP+88d280qP1kEWwFYhuaGAlj+0Cf6+7XkgGSJE6Js6ZKc7bFvyhGApVLwERgeBYmfmSRIn5zBp5pWmYCOtc3P/KdThkSBj0LVj2nekPUXWEwgZ1kGt4caXPWYscN5w5/YdpPKsrzZQUiLmwsOhwUYhZUgwSSGwHtIsC+ybwoM3tFsNrl2fMBtXBMcsVJelAKEUUSTnP4IoarDQS8P1EYdafQ4pYlTyAFZhfu3ySpBm9bzP6j5ywPuQcFNKI5Dz/WMOJ3fMdf4ETki67QeSZx6OCCQ8SJmSJip82aPkl0fTJpajo6rXYQrDOglKIJzGI496q6w1REmE1pq5ajuCgE6wQBJL6toe9YcF3TERju0941HN5asWZ+SbEo/B1odzkMKzvNykLEqsDZWsT3z+Ns8/fznsY14QRxHLq1v8+996ic3NbbQWIByPPbzMf/9/fR9JGoMQ3Nva5Xd+5xOh8CDC/fre7/0OTp7+T+vHfT3G/+EDqrtX30A6R6OzhmrVTHf2QHhUlqBkg7jVQE/GdLuLaF3Ns2YxvaVVnnrynVz8yhcZbt8mzyIqM2Na1vhIUJUlttEAoYjzAjso0N4RRSHY8daACT1SVnhUHCMSiS1CD4JQMSLy2FLjpENUCpVEGONByEC3jADrcFJS1zVSKSQhSDN5gYwCexM6COERKWQc4TNJo7GAKR34oD3i2xn5dELkFSJKkY04ROrW46ZjShWTdtpU0xysQyOgrBEiInESozXeV9g6QsUp2tTgHFKl6OkMlOfcQ2/j6ac+yDtaCwwORuxff5nB8IC142c5dvoR1k4/Rj4d8soXfpsnTr6FyTRnef0k3ZNPoAQ06bNy+lHMzUtIqfCSYHScRyYpve4qjz3+Hs48+h5efeMSLh8zPLhNHClOPPQYjYZkU1+mtbxGNe6j0ozGusOlTdbXzrL2aMFwa5POYod6lrN49jHS1jLHn3wf05sXmBQ1K60Mn2TUaY92Irh6+TKVLiFr0l06Qa/7/2bvv6Nsy+77Tuyz9z7p5spVr+rlfp1zsxEagUiEmEXJChyZkkaikmdky5bH8rLl0XjNjMf2skZaHs9YI9GyhgrUSBRFCowSCJIgQgMNdECjw+t+OVauurduPGEH/7HPvXXrvdcADLIJAWv26n517z3n7HPOjr/vL3x/c8jYsX7+6/T7XaLqDM3ZZYJ6hUa9wq23z9Mf9Wg1FpC1BrVqhTCQbF67hE5HLCwuEiZzyDDAYti+9hb5aEA8v8LizByNasja0hzdgx431ndZWFohjiuk0iEO2vQ7bbo7O9SbS8weW0OLgOMiQW/eIAgUqt5ChgmNSp16OuStWzcYmZRjzXnPKOUMcbVCb3RAXKYN2N6bo723QRRXmK3HmNkFknybQg05EHPs9TNGeZ+9/QHrnR4Xbm2yu7dPJqFaqTLXmkFaA0iyzFCpWAKl0FZg84zcFRTD/nd6Kfi2y5ixzzlJvV7j1MllPv2ZL7C9u1fGIRwFREeunfosyhOzoWHrQhupIJqtl9q+MjAYh4x8/pdGM/RWZ+0IQ2+BlmiKwvK11y4hA8Xi/BzH12Z8sHdZLN61yyexdKWFY8xC52g2JcIptrdH7LXzKbe+iTQ+CUafaC7tIWgReGtIllqEVYAr3VQMee5QWA/m8HECN29rspHkwtsjhkNXPpf3AfLxZ2JS7xgMjankHV4YGxYabSwyCEqQYA8tF7jJk4IgzzX77X32O20yFWBVwrVQoasVjFX8TFpw4ByxElOCursDD7ujli8HgYp4JAhJneUld5g8VOCQzqEEhM5R4EglrJQ4KxeeIj0SgmUJVjqOIVgUkhtOsS4dqhxD1glqIuAUIU5YnDp0miyRr28TPIXyww4Mii6U1iswzpEhyLEI9AQUy8m7iInwnTmBLSzOOtIspzfKESpkPXds7wx8nK+xOKtxxlCkI7JhDxmE3Ly16V22jMWU7d7t9DwrmhJUuwPec3yeT799A9Go8RP/4SfoZpb/69/+Z3z2tRucPrHKar3CYjUiDB2ddpdAgijdnfyAPeTxvztT2HdXUQHMrtYxokJ3kL8jmLnnr4dR/QCsPWa5/4MFp4/XmZ9JkMphnfFzREqU9BZ1pCNMfDvach7fa50qb8LYec8B+zuabOAYtP1cy3KLiDTChVgxbeeCCbWluPP5BaNdRR5CUDWoyLG3YchHfl7nmcUFjt3bBicdezsajCAb+QCtaxdTT0iQCS6/lXmhWjJZL/OBd+XqbOT09gHh3aUrYcx991VxGpz183xxrs5P//EnieIYKRVKSYT0FBCHSivBhWtbHFucJQjU5C0Gac6Fax2WZytEoSSQoKQgCCRKOgLlUNLb685f3eeRc3NHXaad5MrtfZaXaySJt9bLUhFz8fqA+9bqntJeqInF3wp4+0aPk8sNT/whxpYtvxf4EBbL5ds9HjhRJ5AlOLfjhdGDwys39lhdqhGHAV7p5teOK+sZD56qHnFtdk7Q7ucMMsv8jM/rNY7nzQvNzt6AEyv1kpjIH0uznL39PqfW5kqSFb+mD1PN1u4Bx5abSGc56Gf8zD+6SL+vmaTyGOt2sJProlDR72VYZ3Am56d/+of5/g89SKC8UjMIFZVqjSAIsNYDOKMhHRygpCAKfa68973vBP/gv/uLpVVOYI3lrStd+qN3T7n7PQ+oNtdvoa1md+s242zjzjgKl+GkxeC1LL3OPoXRKOljHgb9AafXzlGMUkQQEkQhmVYIVcEOekinUA6i+RpEjtF2gcoFttBopRBCoUcanEVWEpJ6lTTNEM5hlKOxMEPa7eNSg6z6JGShFkSNCkIE6CxHDwYEtQpkBTKKiJREjyxEAYU1PpdNGVguLajCekd8JKN0RCgj7MBibE4yA5mTZAWoqIIrCsxwSBjHuCAgTUdEauxHrxC5RsUh1hZQRJAVKAIfYG20X6gUOKO9dWIgCZxhY/MKqCaN5hzLJ+6nuXqGjSvnMc6wcesSgQ1YOfNe5ufn6La3EEnE9puvcO6J95AXAQ89+V46G1dQAuaSiFiAEIpKkFBrLTLqdWgPFMVwyMHWDR+/E0T81utvct/DzzBz/BRX3n6VEyfvZ+vWdebmWgw7feSixORDHv/gR7h18SKNpRlS4+Mnuu0t3vvBD/PK+YvM1+pUpWCnm9I/6CHiBrNzS2gLsYoRUQQ2Y/nck8wVBViDSJpU51qY3h7zy6eZl45+t8fC3DKRkGRZxvzSOYQZksQJycwclaU1Nq9f4sQTH8T1e6TG0Fxc4sSJE3S3dihqTdYePIYpLM35ZSpJlY2N67hWh+7cEklcpb58iqA+z+bF1zk9u0Q9VgxSw9mHH8FRx11/i2GtxUFvn1hJKvVZDvb2AUmlGqG7+xQYtHD0egdQtvOoLwj39tH5Fq4ecvnqDqFtc4Cimw7IhMEIwUxUZW5mgaWFYzxwaoEg8NYAF8YszC7RWlmjNrNE3tlmb+cqO9cvfEfXgt9LGbtbCBEQRSH/6l/8It2D6YSchwLFXaXc31RFkcxVvEBQAp1JLpfyujwVDHuG3U3N6rGYKBKE0dH4Hpx343V5wc10i82tfU6enGN+robDMUiHdNo5TmRIWVL/WkccKaSSbG8PPauSuwMIOsAdIQafbHqlp8rk9QQQx97yM8lrgsAJQ5Y7RtoLgBY4aFuuXM4ocofP1+p9+CfGk/H7i2lMd0i3bI2lt15gFw0nTs5Sr1WoJhHNWkytGqOkxBpDqKBZr5Dmhl/79PO8/5Fj1KsRSaXCrTjgD1diAhWQJBHX1nd56rFzJHHok2iWWlUf0zGFo8aqYjwgCSVgLe/V2rtxOg9GZElMIvD5WKRzqCnd7xgcTFyLlESWGlkpxHjZxgmBVZJtKQ9jIsSYsKLUPIvAM45JiUAicSWduu8Z47yG/49nmh9KC25ubHP52jo/9slnkUqVfV4yCkw0xQJrHYXWvHnpJhev3fZsXdqitUYXBbooyHPNaDRid3uXzt4B8wuz2DJ+sN3r09nc94xuSmGs5FfeusX/96tv88efe4Tw2Glm0oxr166ydesGp1fmCbSmhWTY6TPsHPAn7j/FH3ryUcIzDxO952lPnoC3hvT7A/7uO87Qf//LqYWIUw+u8PaFbbIs8z/esV68M8RyR87Y3zHcumQ5uejQ1rLbGSCEYKczYL5VZ2nOu8Y6Jw5rdWWOpTvvKUqlCd4S6V12wRR+3uepz0+krfXyRjlfjhrE7qjUCcJY4GolDLZeSSKkK61IFluyu3k3M4cMQMbWE3aV606Re+ASVtQk4a6UYyWWIIhkSa7jyvg7EIHnqerrnKIrKDIASzrM+Te/+XXCUBEGikY9IVIeFEkpkdJ7Bux1Bqxv7BAoxZj9Pddw4armdeNQgUVJJgm9x+x8WIuSil46pDPsE8ppYg7BYJhze7tDFEiEkBPw1+sX7O90CAPprWflNiJEQHdQ0O/0JoofT+xQWvicRSpJu6/pdTqTHF/j/vAWLEl3ULDbHnjAVc55ZwXdoaU/aI/PnowRY32uwq3tMkdiuV5Y6+gPM3b39o5YjJ1x9Ic5WzsDxruHtd7tcmdvyKuv74GDNNVcvdJmOLST2Lfxu7jSXd05RxhK9tpdtDZkWUqrNcOb57e9okYKlJKEQYiUPqk9pVKuXoOTq6sEYYgTkvXNA15+5QoIUYJdiaNOXrx7ipnveUA17AxQQiCtQTuBUN5XNx8OkKGPqfIu5AJUiNUOwgBRFPQO9pFRjDWSoRN0igFu1MfkBSJSiDSj2G2j8L6+MlboXFOTNeozLXZGNxBhgK1F6AR0WhDUIiphxGDQxzmNDAV6mBHO1qguzNDd2oMCqjN1+qO+dy2repO+NjlaeVZCRICgKE3jpfuJkgRxjO0X2IrChAWiFWL3M/ZvbyPCYBxqgcsKpBIgJUEYYrSGKEJaiwoUpq7AhWA0I2WJZ+soY7BOYbtdAqcIpEIbg8VSGM1u54CHnvsR3njheYT2yWM765dZPXaClXMP8fpXPoPrFZx59MMcDPZpJA0ax1ZZf/UF0vU60cIK/W4XY3KcqBEkAiscxhbkLmaYDqmEktevvIhxklprkWLUQwmDIuBgc4tub58oUrQaMdf0AJITNBPJla//DssnTuOEI80HRNXjhMUety5c5eFnP8wbN29Sb61wtZeR7l5nsHuLE488hRgNKApHc36Vg43z7G9f5un3foAbV64hREKyuEp/+wrpaI+l42cZHnit7rFTD9LZvsSgMNTn19DDIa3WIkm1wc7629wXplgUemSotuaZay7Qb19me0NhA0WYVKhjscWA9be/ysrJM6S9PeYWjlOfWyQbpOytXyaqbCGKfR555n2Ygx02ejk3L55ntjnLrf029eUzNKVCFn36/QMMlnqzxcLiSa6++RUil1GVAS1hcU4zN9+ivbzATLJAI+9hrODcgw+ze/VrKCUYWsmChr2dPvVqlR//wHPU4oDtgz6ra4JjJ+7jxELM/Z/8IL/zla9TWZynkw155r0f5aXP/sZ3cCX4vRdZavJUKRQfkSHeYY2eMnDgjMVkKVGzQlSJQIyZnpggiSKFYU9Qb7jSf3/iTTYppaHCAx1jyHPDxmYHbTTDoSbLHTdvDFlZg0rFu4sVud/kBJTxCWNzkzusdYyrnBfcnRPkuRewhgNLa2YKUZWKKGPsJN7BAcYKDg6g25FEiaHIHUUKrYZkMHQM+mbqPbxw5WGB1zgX2rsKTRerHfrA8MZLL3Pt7QuEShIGiihUNOoNVo8do1qJfOxXNcYZy7VLV9jZ7eBMQRSFzCzMEkYhUvg8Md1eH5fnhGE8lsPAgi0hkCitYHYiEnnLmi1jmOwRi1EZ1zRuUzeOX7ATrKikRCmfe0oKSoFMTvrTW6DkuFUYe1IdDjM3EUDGAMsLZYdgH1dq3CchApIs17z4tbcwVvDZ579earH9ywphx4+Lzy1m0IVmZ++Ajd0OOtcYbUrykdL1D4F1gqIoiKsVFleOYazGWssoNdy8scGVT30W0R/RvbrBF89f58Z+jyI3mNEQbR3zx9Z4TCdUowhnDNe+8BJ/48f+Krf3BvzZv/ZTPPfh9/Pl16/wta98ifW9LuDfK8/evWDyP4jy6IkKx8+u8Pf/yy/Q7ZVsfPdcOMYA6s5jh8Cqf2DYvGnpP2oZNh03Nvo+n6a2tGqltQEvoLqS6MNYz/A3seiW69n02pKllv0t48e6AQxY4Sh0QXvdopUmrhi6ewH7fcWJ+xwqFIePN/WhviAmOaW8YO7H3rFTQUlRnvPSr1oONhOEENSPFZz9UIYZwrWXY3QhOfGE5f73RkjlQNpDa/v4Vm6crLacIaVixOqCzGSMlGb7fAgGwHDtlicDUnHIA0+fY211gTMnFpFIGkoxIx312JXJc8f5r/x68MQD8Pf+4Ytcu3p7itafiRlKCMfKao3HHj/Gww8uEMkANZ6gzlGp+3Y/9Lj0bzJX8W1ESS0/ntQOCELDdmoo9TVM679qAupKMRMJKMAW43YYgy//txaWm4gdd7v/fabmoBjHq6qJAscEigzH0Jqx/b18HoFJHH1z6NY3XgNt4Oim4ztKhHPk3ZSDg5Cf/+dfIc88oYodKxDvGC7TYzAMAnq91Cd/TkeoIOErL97g6qW2H5MC4iRgZiZka2OIcJKF5Tof/uAxJCWgcoKdtuX8pdSDZeGB2vG1GbR99/iGv/cBlc0hAJE7sI5KHGKsRQaxD6wdjYiCKjNra6R6RGdzE1GkKBUh6g0UI4a7u+hun3y/g/HRgDhn0BJcT3uNjdFgHMJK4qBKFEQYW6BsCIOMQhgkPoO0zgc4IQmrEUHFYg4sujeinxuEKShsTtqzOCUhd1hbYEvNohISMNg8QyCJggDjcRFWOLTOPYnFyMdjBfUQO1vBDVMCFSOrFfRBDwJL1KijtfZuNArIclykyNPUaz9CsHlBIBVWW3SWeU1TJNCpxhUGAs/vrwcZdjRCdLu8/+HHqIohFzbfohFGnDt9gr20TzVq0XY7GN1GSIlIaqSDA6qtBapzs3TaG7xx4VKZ3NHhs2wUKKmoSMNMaDm2UOXMqSW2NvZpzJ+lNtykHoXopEpkh9TOPEwqJM4N2T52klprhjjvkCaWUOTs3LjJ3NwS6bAHvS1a9Tob1y+ztLLE7RvrLFYqHEhLUWkwyjRxpQFa097eoBA1pEzpDR1ZWGUuCBjs76O1o5EY9tubFDonCasMux0azWUGvT0khtZMjUA5jM6Ikyq3tjq0ZuaZabbQOqdaEci8jh3tMDu7RlSt0O13WDu5CAm0tzeZn1vDSEkiLdHMHPt7bXZvXuTcfQ+TDgZUQkVzpkXR3uHCG19l/tSj5IMuSWBIM4vLBhTDfWwtIet1CIBABTRqIYPRCFPkJDMzJK05gnAR1w+oDQqWTqxx+9p5gjigmllWZme5IG+TGcvzt7Z55OR7KPb3WLSSLDtgfzRLburIyjyX3/gqSyceZJB+9wpDAket2eTkA48yNz9TCvQ+fcBU+pWpclSbDBDEgnjGxzLKI3TljnrNsXYqBOED/DGlUC8A4XzfWahWDq1H4/gGUdbR6fTpHPTZ31Ncfzug2TS0twPmjmmaDUFS9QHA1gikOkqcMRbIx0aO/kDQ3vM7eF6UeU2WlLcuTYR1h9EWYxxFIegfCGo16PU97W4QCrJUkA5iKqGkspQzGuXshF6B5awjCARrqxFYSBJBVsBbFwo6baZMVb5EjRXCWgWjPCtV7gSDHFwRc661jHQODfRy3x7nHn6S00bzwhc/x/buAWtnzqCU5MvPv8wf+vj7efLxR3zcT1ayIVpLnmuyvCiZ7w7B40RumLIoifH/QJrlvP72ZYwxTBAPYtLHUgjqtQor87MEYeBdt0s3T0phTUlRAiwxRT4A1o1jbKZNev5SJ8bCno+dM9Z40O8c7YM+WV4w16ywtrKIsY6r17ZpNWvkhUZbx8JMHWOtj7ERlq++fJ680CgpGQ563kqhC7TxDIvpKMU6gVIh+ajH7NIqtza7dHbWyYddPvEDH+fW9Wv8J/+Xv0MgBc449qxkIYkZjQqyzgAbBzx57lEeOR1wfuM6r1nLg5/8II8/cIrz/+RXSZYW6ScRn3rhNTZN1QNRKVEqpNMdfivT9d/bMtuKyLTj+rX9w/k/pXLxc3nq91LonrjTTYMs5wX43d2UILYc9FOCwGKdZdFUcWUszjAtSPMCENjigN1wQJZrxmPpiJEJUCHUWj6/nLUOk0H3wCFDQd5JyIMRWjsGHYfpSXRxOORdKawf0TONF5epZLVSgpCCIFLowpIPPI11NDKYXGAyy/DAk2FkA28FUmFp2aLMlVS2j4+PHFs7SiBiHUioz4FFsnMZnDCEcV5alwKSWhUrJUFSoTY7ixKS5TjmVKgmFrspG4yPrQJOntng2tXNqX4rX0v4mM1arcb9p4/xffedJVBy6pxSUTL+PgGB43c5NItPCI6APWPAehe96UBRieCYgCUlGROBjNv6iOuyOFTCjG8wptMft+UEUpfXbRjPpGftIc05HlahsJMwDHBH8vId6W/jKGSPICx5CcYgZkqHcLSNDz8Z4xgOC5/cOktZXGzyxBNNdm4P6A+8ImBlbZaz99XZ2byKdXD6XIOVVe++qAIv48/Ntnj0kbNTg9yPHz38n1j+vu2igDCpkuseKlQYKciNRkhHRIAWFlFx1OKIWj0gdJosS1FBnaef+D7+3Wd/iXQwQLsRQRRijMFZi8kdcQSZLiBOcHGEMBabW9r9DTpdg7AGa4T3Qe9qyDVF1RseBZKim1FgcBKkcTitCcMA5yy6SImCCkJZzwYky3iIUGEECBVic4t1Bhl4xj1UuW6JkuNfG+wgRYUBRgSYUUYUx1QWZ2nf3kBmBdrkWB0SxhXQBUVviHB4EGUzgtAzsDhjUEZ7oaqWeOtRWhCEAQiLsI7EaVpBxuLMKnpgmQtTKknIQ8fneevmBqzM0pAHqO5FVpuLzM96EoPZ+1c5vqTYk4oHn3sIna9SrzSoVxIeu/8sP/bJj4ARyGqd3mDEqeOrNMIQqzS2uYKxhmw0oBGFdIdddgdDkmqLlYV50v4G3UGf2dkFsoMOSbBNXqkQ6i4m7SKF9QGjWYVY77Nz84AnH36Qy1dvsNfeIIwbpIMdiuEQKQVrqyfYvXmZSqVKXY24ffM20gieefojvPD6GwgDo8EuO7v7LC8dQyUt9ve3CaOArLPv80TUGizOzHGwv4MeDohlTre9jVQxzeYi27duUKtH9A8OeGz1aa70DrC1JrduvsVMdYZBJBmlm1RiQ3X1DLvtWxz092lUGwwLzUKj4Lk/9H387otXKQhpthrM1ZvYRoPt9i7WZez193DKC7XDvGA0zNFFQRDGdAeWjcttRH+fGwcF+4v30zEJvb0+RVqwlw1QsSKXksJCpjOazVmWEvgPP/E0v3thh/PrW+SjA1ozx+jvXENE3+mV4NsvzglUGDEzv8gnP/J9/MK//nVeevm1UpH4Ttrko0WFispinaO7nS9hJJibF+SZoN8vNzt7eN7+nkFYQbI63uxhNPIU20kyHVPgqNctJ8/l6FwyGGouvQXLK5YTZyTDgaWzD8dPevrhSRC7mMIvThIqwdwMIBxb25o8h34X9jPDyopPjiiAPHdsrMOobymM88yiTpYxFmCtwVhDvWFAWmZalrVVL2RY68hSyHPNMBW8cdFRFN7Fxzf6WMQsNdtRnShJDpmwSq1vEEUk1QbOGMADUmc1Ah/3IcuHLYoMKRMf4yolSZJ4927GQfOONNNkWV663YzvPe6FsRZ6rB8XE2EoTjRrq6seDJenji1IQngAXa9WOLF2DFMUPi7JWawTWBTOOWYrinoEW8OSCOdI7hf/rgKQShGGQRl/cSgiOefK+BlHrkGGFdJRSqPq4yCsdaggolZNCAoNCBbmWpPxmGYFJ08OyfOc9VubFKMc50zpzleSgbgyJtgYsJp80KVvHTr1SYGdhXPH1/hLP/IsywszUGTs3djmK+tDLhSOmze2yMKAFy7fZL7epD/KwFne+/3fx8c++BR//3/8NGl/m+3zbaSKObV2pmTHLLsiTL7hHPv3vawem6MzgitX20f7FpjYIcvxthw6Yim4kR6Og8kyMyUgXr86oFeMkHEOgaceHxUFWer7rdCWovBt2M69UDt2KZtYPCeP4JASai3pcws5yEcOsZ4jHTgboLfmvCIZUJFj+5qhWvPzJKrD7IqP03HOsb+doTM/v2QAcysRQgi2r+ekA4vOLc6WCgMBg+2IN37Z5+z06dR8ot2N6wWjoWXtvphaq2wIx2TsOndI9OAowQ0OFQjCCFTs3XilcojAuxYGsfREF+V7iomWyk1nDp80ugOUEMw3EihjeUTpSmaMd0MMA8V8q0qzmkxcBY+aY+6OmhuPgvGpbgI8vaKlLgSnJsalksJKgMKPDymPViZwR2/guGvLGdvcJ1j3jmeakaAiMbGK+XPHZylS69hM77byiKl/J3eZxJreq9wNpzxudIxGhrwosKZgdr7BiWPL1Op7GKFxVtCaiZmdrVFvBBjraDYUUeLfVQURxrqJi+hhze9++Z4HVDEKa/wGYi2YACpxTC4MUobUw1IzqARnTp5GHV9ja3cbZIO4XmPY65BmI6zVJXOVQxYGk2kyAj9F0gIRB4ggwOkCm2sProSa5J2SIsJKMKMcV4kwRYHKNEY4ZOQpe7XWJU26QqoQLSxBqEBrTK5xQUCgJHEYYiKD6wzwFOzlUJYli4t0hGFEno1woyHGxlg0tjCoLMIGAqeh0CkyCXyclBGoUOFG4JzFSIGsVCjw5tUiG2HyAqwgzAtUVAZICoeNAnCG3mDA7v4eYtTDKkmjMY+UIReu3MBYz1SzeuwcsSioxTVOzD7IrrxObVGwunqMh0/P0Gm/RRgrluYXcarJ8twC3//eZ1GiQRC2SPObVGoN0rUH6JuCbLBFnubUGu9nZ/8SdZOyJENmZh5g/fbXcMxSmIDZmfvY230D7QyVZJm49iDd7jr5aMDKysPs97ZYXlzl+Mn7icJVjp9tkXR3iIhYfPg9XLv9Os4aKmGT1eUa7bQNKuHRJ54jG+zx+tWL1CoB9x87zcH6TeaadZwMcKGgEcdElYBo8SyhcwiT+sV++ST1egOpJLrfpd5cpN/bJ5o/g7CG5qNP0U97nFpdJg5DojMnEKFFOYMoNN1hHwHMzR7HqYgkEChbECQBjz36FOdOXwMKWo05bF6QDdp89IOP0h5p9ChjmKcgHMdW1mg1Y7S1hJWYTnWezvJDVJr7LD+2TL9t4YECvX6d3ArqOue+2nFsUdCUIWFukNWAfgpf/syXUMfW6G9ewOU9RlaT1APSzuZ3bA34vRZRaigDqajGIa+/9ja7u+3yqLt7R7pXOVTQ+q9isseW2kUfj9Nsxuxt56UW0aednWlJBNDZ0zRmvHUjDoW3vItpgQLCwDE77wBL3BNkNxW9ruD6VUt/YFk55t0h0sKRZY5KxW+aRSawRhKEgt0tQ6MeEoUWY/16ctAz5JkAZ8twIEmRC4ZDw9KSd5RTarydH7L8pUNNkozZuryGMM2g39dcuWzZbktwntlLCDwFLuOcK6UO0xmKnbfZ3fRa98N7wA6Sy6+8SKVS5cknH+bmzQ3Wb28hAxDYiWb0la+8VFqdJL/zO1/kS1/8KnElpjW/hHHQqFZZXlpAyrH1iYlH1rRQ4WDCruXjoST1esLjD5y8t2a+/CJVQG1mHlMU3L5+A609S6hEkRUFH6l3eE+zy39+cY6t0fjeJWQTJZgSkvm5FssLM55iGg5FI+GQYtwPDkyB1pr9g2ICTB2CYTFE4GjWE6+MK58xDiXf9/hZsqzg2oWrDNptiiItW9qTHh3qx33P9Dsj6Gx4QU8IPv/Zf8sPP/d+Kp/8BCvPPIjZvkL/F1/g9d1NLnX3+L//03+Hdjm/+YUvlNpvg9WGKIjoD1J2Rzn/t3/7ErWZOooFHgvtlKDlmHPvHt3xH0RZmG8yHGry/FBDflQI9cXh+OCsZiWS/Pc3p0U0wTQCEpQJXfExMcL6/fi11/f4N7/bxxjLmfc6Vs4e0qlPC65HyuFQBfAuuCXA8pNhMusmwM5ZGHU9yAYwTjGz7Bc2ax39jiZLLdaCCiWNOZDKsr9d0GtrhHEIlRDEvp+ddKUl5lChtHVZsHfDsXDOsXzKgy0xRYgx7AqGPUmtZUvLV+mi3HeoyLF8ImZpSbF1Q3PttQI7CtjbC+nGBeGj+YRwSAoYGcd1o1kMFdXwaCON3/6P/eAJvvDiGwxH3nWy0VC0dzSNmYS5uYgf+9g53vP4mZIAZqxycR4giaMY62j731vgj4QgmvCylPWMu2TqHq60dN+pADr6yR35c9cjlH9rAqpBuc6Jo8cdgq5xbKYcsXCKO2sSfhzbQ//Ge+6T7uhVk99GI02ep56cLVTMz82ytFRhHtBGc+7cPI8+NMPGjTq5tszOBYTKN4oKQqylVHD9wQCpcfmeB1THVk8zNEMkkkE6whSGxtwS/YM97j/xICfOrrG/12Zh/gRPf+hjVMKUy5cuUmvMs7SyQjNO2M+G2CDA5QVhFGEDQ2ACrJAI6bDa4PrGazYcIAXOlc6eQnrWP2ER9QCRWoTFZ6iOgpJb1CCi0GuBSlTvbICwBbnOfR1SIoTDZgUmEmgMhMonFJYCGcoy94tnUDHDIU4JZBLgrEZqi0DispxCKmS9Agd9bGoIGgkOsMYzoWBdGXA9QCrlKTFlgBUGEXsN1Kg7wAofBxBIR1SN6dsh2+1t1k5+ABnG3g2nKAiiGOFS6rElcoJKIlBYwtYxZus5moKeE8zX5pFFE6NChrJK7hrk1BjIAuXmaERzdPtbDJOESm2RIDtgt9dlKEMq9VNk3R4y2COpzNBaeIDb7esIChpqhnjuFFJv4YYj6rPHieMamRpRma1zcu1BspvQO7hBNa7y4Ln38sIbn2Hl2DI2FZw+8SS9wTqBEizPHGNhvslX3ngZkJxZe5q9zjad0SUwkkfv+xBp7WW+fO0GXWNoNBexeU5hLEYbKjOzyKKPSiqcOvZe9nr7mPQSlVqVB+57mvNXXkWJHiIPWZp5L7c2fpPZZkAULbLcOM6VrZcxRcHp448zMzhA6z1kENFceB/bt79EJRZUggW6nRVyt44KFUW0xOqx4+zsvEoxLFhceYa9zhWU2SRwguWVTxCJt8iyjHoropIss5t02E473Dd3nGqmmVsYkrbbnDr+YW5df4m5ekAkYuZWf5hhuEU1UWRSMhCLVGRAoGIefvzH6XdGGC5wMPjuZfkbC+9KglRlgvDJJnEvNDWGTmNhlyObz73UlALBKIXrlzPiGJAwGllC6y3hYQCVumA4sMSxJJgwfLt7VglQrzlO36cZDB3bWwKjBe3A0TswFNrRG1pC5YgDg8sVzkmksOQ57G4aBAIZGOaX/UZuq0wYpISwxDHMBs7nspJT2lGPOrDOESWO/iBgOJC0B95an6awc9sy6itmIoUTsK1zYuCUs9wQsBpK3l8L+NQww8kAgQHh1xPPM+9KTbsCK5HVCo88dB/zsw1CaREkBGHg45aEJ+NQ0lvXIiE43e8SVWrU3/+Ejz0tLT+HnHrTqt13EkTGVitZxiOJoydNgypnGXb3wUG9FmKtpxK2DioodlyT14eKY6vzzIytk+LOWwmiIEAKLyiMvYTGrF8CGNMRr8xXMDPxIYCHiVDnx7Is89ZMFOJIJDKJ+ND3v59Ll5b5+ssvkNRb9Ds+IHzaUOL/Tn+SjEYZSMFg0MfmGcONNt3OkLZ27Gl4/kuvU6QD0mGKKPepSCmatZDRKGVkNDv9gIGTLM2FjONXfJJlSyC/e1MvAKw89RBf/N1LFFkZu8a05v+wSCyxcp68QI417XJqOI0XEzuxInhFg2dwSzPD+tUCrS0rjwb3llrHX+/o06O/eyA1ztd554nOWYZDg3HeIhvWFdN5rvxz+bFpCsfW9QyBYNgxJDU4/kDkrdhmTGbgn3/QcbzyqQijBSYPMLl3LxbSHYKIMiZo1BXsryuWj8OY5G5/R/PVT8Px+y3v+1jIzGqELAre+pym1wnJRwEqFAxPpD6+XjgSpQiUpCjp0H1g5RScL9u5UUl4+JFltvZTNm72aS1U2dnY58TpGVaXI2r1ClGoxg3k/xzpsyOtXJ52ZJYefnI+VcPAHFrS/DwXKAGt8GhM6zuh5W/Q/e+oCzyiD5r6UQIVAWcqwSGZ4HjNLDVQFshywy1Xug2+wz3u/c5+RRsONXmWl8PdkcQJWWbodLVntLR+Td/ccmgtOLbmvKunEASBd4cx90jV8m4zhX7PA6oic2ij6XXaHiRYjYgbLLcWuL11k9vb17FCsXzQY2XtLMsrM0RRnaqKGLQ3UFJRixKMlaRKY9MMGYbQDLA6g0wijfEgSirvfpNrKH3fndFQOIRQOFdgDKi8KDcLhbMGwoBqVAXlGHZ7XjsT+QkohfI5o1RIlFSRiURLh+jkfsCU7FG2sIhAjONMcQiCQGGV9MmAnQIZUDhHWBSEgcKUE9bkFqFBCu1dBo1BITBWIZ3AjgrPbqe8tS8OmhRBQWE1wkrIDYXJCOKE3jDnINUoG+CsZW5mDucECSHoPnkesTM0DEdtLu9/niSpsrJ2hgtX1+n2P+vjU4QgYovshTeJVIAgZKg3yQtBa26ZpdoM7fUbaAwqWqKIJK9efwWDoBrOEJmIg53zDOIFkrhKVmi2ty5SaZ7k+JlFOnvb7PW3SWbP0KzUuNBepx8EhKsPEbRm+dLFL3LswUcpioxaHLPZ32PugWdQSAyGq2nOwv3PEEcxwyxFzkasLjxIEAdc2rmBrqwx/9ASzbRPpCJq1ZggTsgGPteERLN8YpX+QNOoNpiZ/zC9Toe9SkBt9Qyx1FTrTTqjLsmJh6jFIdlI06/PENj70VJxcVRQqc9RCeZotma43u4QzK8ShwH9qMJgsE2ldYwigtzFhFmfvLJE9cQsrjCcXD6DZJW1ZkTvYJ+srxllKQIYmCE7usJON2Ln0jYFETOr5zBhlXZvyMq5NXIzQygCCjsiajRpzFUIZcD9D57F1gXyySepBouEpx39LGLQ7/Lp7+xS8G0XgcIaR6/X59d/60UcUK9X6PeHE8z0ja8/1HAe/jJ1XHgSAqN9bqdq3cc83bqdI5XkzOmQMPDuXGF8KLDcfduxeO3/BtIRxN7CIVcA68hGGpN7mt+Zio9nqiQWVR9bnrwFKUs9e5YTjiITVKt+E58msxhbx8ATWHS6kjxzVKueASvPITeaK9cF2cAxTD2Jhc4ccVdQMZKPz8zjhObn+rucDCV/76k1/g8vr3M2qvGhQPGvujlaByRRROw0Q1sw0kyEndW1VT7+sQ8ThAHVasyZsydotRq8ff4Kly5dwTlHoCwzQYVMWZRSLMQ1fnRvn2JhlvPVCBEEHNp7xr01rbJ3R9q3fP0jPTCVleoefVIWo8FBEoMPWj28dp0W61kLmTiq7g5gdpcdwxw5Nia6nh4TYeDj/O4tzIyl6LEQNvX2wrGw0GJzo+n3HxVxmCvpnqr1w/dwFiECdG+E7fXZ+vSLpFu7mKtvE3eH3CczdGzJoxYaR2YMB2lKvRIxHPUIpOO/+ennuO/EPD//lQ4HhfbvNFEc/MFqm3/fi6rwa//2GtpwlNQAGLdjJAT/sxXHY7WIWCr+wppkpC2f39dcT+XUSPBunNdfz7l13s+/hfvhxJM+vsYDGem5t92YLfIdJG64i/jmiF6grO6u9caBChxBLLAG8szQ72jGBBhhDeIyP9J4/IwtLVJAbaZ0n7XSxz+VoENMmCeZTEVXSA42NVnXzxfnvC5a54qFNYeUrkxCC84K7MCy/maA+2CAUqBCRzYKyQc+MhsrMblAOh8eYYxGl4BlZD37IEJM5lQoJYESBKHixGod7QR7mynNRowKFLPNhIfuqzI7U/q2l3Pr0CJ1rzk9/X3K7W/qV+3GubzslKW83E2cZ/JzckKrc9e93mH1mnx6Z7D1DtDLQSwFx+NSozcdC1Za9x3QE451N1YGjFfVbxHMOOFd/rIcKRxGa4aDIdubexz0DDKUJTu35aCdk+WWr75QsDyTIHBIpbDGJzf+xmbB3//yPQ+otNQMux3Sfo8gCSi0YX3zGkKMJ7ohTBIaScKvfPpn2Xj7IsZZVBBTSWJEANpZBBapDYXRyDgiigJMVmCN9YNIGIQZazK8Bluq0GsujSWsVijSIRifJwRtkIErNd6G/mhIEESopEKYJESViG6nQ6BCXGaQSmDTFKNBVCOiSkKuLVaWmWRlScVpfXI3ESiMU4SE6CLF5R7ZG1uQ25hakpAnITJQJHFEkeaY3Hia5VD55xIWpyBIQvI8nwzQwKTe/U949hRnLEIpjNXcunae9vptIhkgAyCHM8dP8Lf+xl9lc/smv/XqbbI0o7N5A6MtzYUFXrr2FqGUXHv7bW8iVoogECwsrHIwGDLsdtFFgdWaRqNJtZ7gjOPc2eMcjEY8eN8qpxcarKzMEwZw/fYm589fIa40ePLpR7E25Pp1zeKi4tOf+SVU0mJu6Sw6lezvbWKyAdsb11FOsLR2HGfh9uXLJPUGb119G4XlxP0PAV4Dl2Z9Nm/fJo4rzM4v0+n1cUZz0Fln2G6TNBdYPn6a7qhHEMZsddq40YBs0Kd57BSBgINC0O93yNpbqCgiah2jvtdBWMVwMKC7+SXCWovlk/dDHKJ7XYS9xdatG8gool5rEEcVtCmoimtsd/bJjWG+Wqc1N0+v30MQ0KhWGOQZjciiIh83YtJ9ji3ME4URw02DkBnCaUbpCLAM9q8xGkquXrlFkGzSas1SWzlNTzt0/wZ7VtPd36XXH1Cf3+TBhQ8RxTV0kXJ54xpn7rufXsdwo/1yaXkZEoXfve46KqqRFwGDXspXX7nA/+l/+eO89rVXeOHF177lOqYVvJMYcxy1Oj4GAYdwsqTeBSkceQZx4v3kCw1xLAiUI8/BGYhCGAck3+OO5Q0dSQhxsxRmmsVEa8xEcJcTDTc4X2/Vb4zWCYzxmuOxxtlYS1E4kjKkJdfeitAfOi5dEh6IOcBZFpYF29uaNBXY3Fu+bWb4T0+t0Estf3djm8K/NhJBOtAMUsGvDDMu6gqdtkIU8Mmm4szeiBec4At4jb1DkFQqrK4t4UGdb9OlpTmCQHD+9dfIRgOc7vGArHCBAVpVOD6zyM0f/CijNAUlSsHHHfG6mYZK3OuzOPzu7rFXT0TX6Uon+bbEtCzCFLnyUc2wm+rZw0Fzx3n30gC7qfPEkZ/HAtkdeHDq/DJZaaCo1OuoIEBIdRTDvUPxMTmGYpSipGBpaZYkd/zFs/dR5AaBN3B+Lc+5bAy3trd46dolatUqW502CMHCfJWZ2Tpx1ENoe8fbvbva5Xe7aCfRxpRj4o7+FIJqLSIO4dyMY1ZZQiSfqEiGheHtvuZ6egj5wXq5YaOKTr2VtzKTUXKyIZD4+JU7SAp4J1h8xzifyNzlc96BcMZn1xYE9QXB8MDR3Sk4aGeTy048KmktKL+ulXKtsbB1WWILNxnfR59HTOo/xGECqx3dXUvPeXdCXViK1NFYFKzd592Ve3uW7VsGWREoGaCkpLdtGawr3vy6wVpBq6aohILtnkZnhrfeuMWVt9d56OFjnD6+Si1WpHFIjs9AMw5pMs56DyInWFqskWnYuD3koQeWuPRGlw+8Z41zJyFxYenmNlZR3LuNjxxxR/4cKSGOaJyB+A59nF+f7YSSfrr2d9J9iIkC5u7in1oc+Tb5NEnxcfiwd/WeFXSynPYop9PL6ByktPdHHgyOB8BdU/hec9qRZoYiK3BCUGQpEkUUgrUW4Xy4iXEg0GS5QR9k5dARCKHY2tljNEqnbjH17O/iOvI9D6iwGSbPcM4gSRDO4pRABAGxAuEq3P/Y46zfuMZgNCCuVak1G3S7XZ548j3UZqp8/nO/RZr2MRJENcRiGe4foBDYzOBCQaXVJBum2FQjDYgoxCrvEqeEQEsDsUKmFmHAlcHICjDCSxTaFijrGBWO4WgIRYGwOQ6DNp7IgswiA4kKoNJqkWYZptdDBhIXCFwBWIUKAqRyBE6jQoVNJHpUIBBIYZE2RxqNLLXQUTUgsxlWSqy1GK2RQvqg7mGOxSGF9G4IxuCEAWFxytOnK2sRRUE22md0sEXVKZqtFvedOA26zfO/+Vucve9BwpkTNFxAa+lBBsNd+ru3EFIQRTF5us1MPeHq7X2SqMJSo8Go02Z/c5PC5pw6dZqT95/m+o1LqMISN1s8vLbCysIClWadMIkRRrO8dILTJx/CFn3yrEdj8QQPnz2OxdCa/6NcfPMWZx9+kG4/pZIsM19JOMie5uZWwWwjYKYWcdAryK3l+NwiQjoqSQ2EotCaY1KysnAShEAnNRoyQpiCz//SP6ZarXL/+76fSm2GlSAmcA6hBCYdUUhNvdJCSkkuJYva+GR0FqJaC1lSwvb2t7j++vM8+sAzLB47h0sC6tLn/5pZPYcxhlar5b0enCHM+zTaOygH1Tjg+tvn+dJv/xq3N26SZxqFwlhv7RAyIJCSpJZQq1eR1mGcYHa2Qppl3Hf2fs6sLWCTlKd+8BlmKjk333yNN7MGQaF56XO/zuzMHAtLS8zXApJqRH/QppJY8mFBFAqKXJMO+/QKR3/nFr1Bl9Hg4Du8EHz7pTnT4qkPfIIf/+SzPPf4Kv/P//YfcvnKjcMT7tgo3lEbN9a2lsK7VI6zZySVGqSpI8vFxM4x3tiyzHDxYkazKTl7xi/XSvr8MMZREtyML5rWUk490wRAMaG7HesVjZZImOSrmkg+TmA05Lmg05Y+PYOAzoGjUpUMB46lFc+8tdMW7LUtw75nBBt7RDq8tWplWZBpL2w759i56fjSRg/roG8MunRxe0sb/uzXNtnXkqUA/o/P1fif/+oAWwlZaCUsNxWVUQZX92i1Gpw5e4pKtcZY4Ju24zQbDT7ywWe58YUvcmso+ZOLM/zSEJys8MnFJTrHl7BBjBCHlqJ3NMJ8y+WOi+/Q6t9peLrLKjC5bBxcPw3yjgLnbxVmHKn/XlaG8VljOcmBMpYgrLBy+iHS0YjBwS66GHFoDbv3nV2pTS+GBTKp0vrhD9M4f43l5Q2MsISziR9DL95g/douneIWKhBUkph2p4+SgrhSxSG90nF8hyPC/HdvGRXSK2CZsiiUnyqViL/y1z7Os0+eZEEplNGMbrXZ/7nfBj04wjzngLwn6K8HWC0mK4Cz0o8SNxa+7+ifI1+OKgcOmeA82DvSy2UnOHfH6HGU8sRh0ugJECrvX8q4h0uSEzgt2b3lEFhWzwnq8+NYiUMh3d3xDjoVzBy3yFigU9i57Ej7Dodh2Auo1RXb1w0v/GJA/XiKCgKMsfzGP/Q56opMEtUdD52OuO9YlX/5mX2GByl2OWdnM2VluUGxnDO0itujzL/b2CQ0XhPxCac7A4cKFNVGxPxcnTAMqVcSlCy4vp+ymR7d68br0jcHslNLdvmzLd2CKa1yYsyYMYV5x4yjR+bnHXPGTV0zySFVVjD2aTj8Z9KBR7CZOPL9KND2Vwgq1QbPvvdZ/uu//UtcurjOzRu7FPm4bw+VXu+AoyZlOEppd3oU2tHtdhgdDIlVgKJAWUG70+H6tRyjczASGfhx6Erm1O3tXW5ev01amCmI6FBS3lMB9vtVvucBVSMRdJ0lcBY9HCDwVI/WaHIpsFJx/eJlz7421JDUSDNJOhzx4isvEMiALMuxufXMSsbibIHTGq0tBAEqDCl07o/HCicdTlqCKPGugMKis5QwUIiKwmQOazVKgFUhUklc4J/JESDTwlN4Ga8hlkhMkXsTbyBRxhI3aljtEKlGRQFiZLGBBqlwSnpLmlOEzYAiGyKdIq5XMJnDBTA86OEsBFJibUFYr9KMA4pc45wh645AO2RhkVIhhSSIBAuLiwyHBVmeI40hd15jEFZjQiF45NgZjIUPP/skwd41fuiP/BS/+dIr/NYrX+MLVw54/Ad+nIqCOJZs9mdoLZ1Ev/U8xX6XZz/6E7jBJkljFyUEYRhyfG2VlaUltLPUWjPUG3WWl5boZxFvXtpD2IJGdZO4knjLnhJoY1BOY0d7HHQOOPPEB/nIsw8xV1Ocma/RXZ1D6T793JAWKasNQcUYhEw51qgx2wzpdDIiGdNohUhpkc67z+SBRLuARnMGn6NUUEFiRECAI6w2qc4uESApcCgZeI1KNaQmA6TwXhihczgliFsLSKdwgFIQCEUviLC5ZW5hFVmvIIXP/aLCmEYQUjjjx6Fw4HLCuEVruUaAxoyGLJ97kGdtivv857l68TWMcxTaJ2eshDFaC0wAMggInCWSDjF0vPGFz5P/mT/H3MwCkdkgSVpAxsHxM4QXeyytHOdDn/wJzr/4Fdq7baxQPHzqMQIREgFqpkV4sISq1ll+4HHq2YiQZzBWMxp0uPD5X/mOrgXfbgnCiLn5ZVaWFzDW8iu/9jsMBtldm8I303tNFL6AVBCGZUwWgpu3HL2DsevVWEhy4Bx5Zuj1LZtbsLSgUEocJrOEkq54WkaaUnk6wUFHECc+BungICCuWg46AcJa2u2gpPW2hIEhSQxS+EDyUeoZBjv7EYO+YzjSOCkIQtDasb4pUcqzaYlYUKsrGk2BwKJzw5U3Cm52JKrpsIlFhh60ZQX89kHKchCwKALWnUHgeHh2Folie/uATBuKHlgrefLkcS702rwYLtIvugjRYWVlmR/+oU9gprPwTnVAGIWsra4wSkJ2c8WzjYjP55JKIHm8FvBVFIVQh0IJ97b1fLPi7vFp/Cz3FJXuBFX3+nH6VaYEo3dymbkL4kxJsN8KCJsWZVU65IcHm7zRz3FIhAqIkiqjQecdNMxHK7K6gJGPc7NW4rKCXFte3G3zgWOniEM/8AWebj6OQqpJQLvdo1VpcvtGh6VYYcbsBGW9307f/PtWPv2Zi9y81uEQHB+KqkJAo1nn1OklKnGIQxBUauxEAS6X2KkrBI6sUyXrVDgiWZf54ES5n4zL0ZabVqj479OpvKfPtXjliMDHVo6tR8Ah0J8I6Yd9dKhQ8uJ92nN0twL/eFYwPLB01yNsYZhdlNTnJAh7WNnUhBbOEcUQEoDUXnBWoI0l74bsX4g58aAliaX3lMGR7sT+zk5hUjlZH/VQMEwNVgikg6yfE4QCKR0KibT+ic30Qj3VKqWxzM8L4cm66o0EFYgJmY3GYa25Q/3BHfNG3PvnO08pn9ufJEvwVD7RkTVkaq6Ie8z4MSi8q4+mgc2916Cj/ImHYMzddZn3gKgGsDA/g9GWfqfPoJ/e403LzeouRYkPU3ngoVXWVhukuk6nPaBa0SwdX+I9H3iOh4YFgRI0Zxq41PGDP/T9CBxKGNZWExAJRZ4SCGjv9Wk0GiRJSBAGzM7Nce36dbT+Fszt32b5ngdUiZIQK8xI+SRzwhEoiXAGkxucg67eQSpJYS2NeBZb9AnjCnmaQm3GSz55hlHSW6WMJa4lFGmKKQy6yBDZOE23QEmFRVCkGXIcNarwLDZYnDYQSAwWm+UEQYiTAoyh0BpV0hI765BhgosCn8+qyJFBTJTUGBlBrZmQSNAjQ04PaUCGIUZJrLIEhaYoNM4FqCCkUhH0ck2tkqDikHZnSC4sygW41JBHglgpZufrbBYZgYnQ1lFLYqzy6P7M3AJitc5XC0eRDRC5J81QQlFXEX/mBz9KrRrw7IPPsPTISba6I772M/+AK9s94pUaT7fm0UGAkQHVQJM7x1zaQ4e3WH3gadbf+C3ePv/bFFrz5BNPc339Np3tbUZpxvs/+qPctzhLrguiQtHt9wjjOs1Gk8zCyEoIYqwsoDJPuHCWhWMF7XTIz/7Cpzho92guHiMrFEmlQqE1UiV8IVQo410nX/469NobbFw5zx/9yb/AieMrhE4hrUBJSSAVqYGiEDgpSY1FIciRpFJSEwqnLQM0SltSBHngA8CzQhNHdRymVFdbVBhiAS0sISFGWlxuSAcpozwjsj6AfGQNgXE4ZUtXz3JjtAEFOWHJDFmgkaqGEDEECUopsJ46Fpy3YjpHIBVYn5Q5kiEVKUkoMGlGs1GhOjIEC4s4PeTMKGP99Vd47a0d6tVFBjubbNx4E4Sgeew49ZWIpKqYVzEyrqLjgCKpUgsSrDRUHYgg/k4uA7+nIoSgEksa1YT2wZ5njruTlWlK2LyX6DdJOlnuksvHFCvLijD0W5XVjmxkQHjr03DgiGLvEgyQjRzrG5p6TaGUJZBlPheBz4OHp+61VoD0m5uUZWyW9ZTkWkuMVWSpYH09JkudzzQvLdsdRTpy1CqO08ctQmiM8ZTutWZOdwi9gV/jXCngHrQNGEcoBHkIMipYmFcsLgQ45Xg8sPxn8zP8o/0+/7ptJptyIOA/ObfGj8y3+JdvXub/NSyQVvBnH3oAHVfYf+kqFVVBLi3wd/70Of7F89dJ4yqNpMIgS3n/c+/h8ccf8rTF6s52nu4LRyIkUkhiAYEQVBDMCOM16lMCxpH9/RuUiYbVj4xDGXPa/CTGAuUR3e471Tj1+W6h5u5zv/FTTu74TkjqnucfnnwwSvntz71MNlRYEbCX9slGvW9eEb4ts2FBAThtGLz4Oq88/wq7meJqYah95U3mhKW2MeJcnvN6nmKTkDiM6B0MubHZ5hd/4yVOVp8h1w7GCUXfTZXyH2C5enWDdJixuDTDzFyVg86Q3c3O1HAtwU1pCbI4jBQYpLdSHOn6Q9FYOFduJwLhxjZrCWNL2ERj4KYvx5qyR6XzzJCHWcbp7xn2b1r2bwsqi542f8LpPpbsncBZr/RFQBiXiakdGC2wWmK1YOcqvPLLYWnhEiAinLNYY8lHjjy1hJUxAcmhFWNsc4kjy7FjknxHstUxWGPo71jyvsI6yWAfkgiKoeDEsSqf/Nga/+oXr9Mf+BCFcfpsV0g6+wW91YJACJSukPUMc60KyvkYsDCRhwQcZftO/i21VlIIn0c0CAnDyLeNLM8aLwlTfXX4WdxZ7WF7Ts6785zDjj8CScTUhUfKPdaII1UeqpDuUevROh2T+N47X+GIImisv3Fuwjhbq1doNCPE+r0f6eijHt43ihXf9777eeLhVc6dniMKI6yTPPz4aVZOrWFKl/hqorxrcrkPhoEgDgOiUJIPh5w6Vmfz3AKPPXKWVquJUgGNuWV+8ZcOWN949xiHv+cB1SDNmG0lpKMMUUBmHHEUUuQWY31Qn7UaZyyVWpVmaFk7cz9Xb93kYD8jH+1iy/TMIi8gkKgYEAYhFCrEa0aiAJv5JL8EPhmhyzwSFkogqz6w3Y58FnIhLAQ+0NtaDakDIfFGe4ktNATCU5qnGilDomoVFwYo4bAHA9J0iFAggxipAqwrCBRoLJUgRhtNoiRRpYpUFhk6FucUg9GIYU+jDOgCAm3JHdSCCn/6j32CH/3E+/hf/2//c4ZZQIahHidUwojVY2ucmJvhwsUbzFVq7OR9avUKtUodKUNCB1+7tkcSat56+ybfv/8cL7/6ddqDPmk6INu+RdHdQyPYWb9NJZklqdRptFbY2WsTRRITNIiSOibtI6XCuYBCSJxwKDPkwFYZ2CqN5dPUVwWxc1gZIArt3YyzIVEYobMRUnQROicUcObEKslxD1L2+inNWsiNdkpFOo7PVxkVmq2OYb6mOD2zwGzjaRZaswRILJJCgnQWbQKM0YQqRDtvzTNSECmBlRKimICA4d421y+9RhRKZBAyN7tMElXZTW9S6BQRBBgVEyGYWTxGLiAOKtQrEThLmndRwuCwaCcQMiA3OTY3BNaic4jAAxYkzlkyY+kZRxzEaGeJVEigAjJyAiGR1hFYsIEo6WW9j7IRjkQKKkVB0TugtjqDbMzwmc9+lZ/92Z/jvic/THP3GjocsrWX8+Rz76ezfR2dj6jXW5w49xi1Rui1o1YQIqlHipEw4AKcFYR3Sr7fRUUIy7nTMzQakj/3Z//PpNmY9vjuXeLeFguvBV1b8wBFSqjULHkhKAqBsZBlPsgWAe19x8FBwdkHFM3Z8dYl0AW8/pYmCBwPnvU+5QL8uuJABTAaCYZDR28gUdKRVARzTe9kJBXESYE2Am1yugNDez/zihtlWV4O6PQFr7zmsE752K3Mv4e1sHImQkkf1+Jw9Nvwh7XiR46H/O0LAz7ft6Qjzc52jtGWD2aCBQMNPQaT3oPfIsiznF+7vsFX+zknCokVPifaR95zH+9/9mF+46tvEzUkHz62wFdv5Lx2uY2TPn5rYWGO+fkZxkLXdIuLyWcHzhIKRYAgKOnYAwWVsdvMOPnWlLb9SF/eExPdobmeVhuPpampfv/G5V4CkfgGx771cuSx36HKO8EUQOHgxY7hT8QRz+cj/se9LZwzJTfH3QLX4Q38/9pZtLUYa3C64OYg5WahcCrgtRtdzmYDKgWcHFneo6r0W02SIGLUHyGEYC9TfOG2IwgiYmPJjJkSt767gdWrXz4PQvKRH3icD37sYT7326/zqX/xpckYFHd2VhxAPUJ1S++YSSvc0Q/jr9bHOk7qm6aZnwJTDr/vf/3XFP0uNE8Ynvi4Ld32fD9mQ9i5qbn9ZsADH5EERyRFMblHkTmKkcAWPnfRxBKSgrXC/68Fzk45t5UWk8FuxBufdZwdFpz9PsFoaOntC4qBYHW1waDr6OwXDLoheabJroZcflVxfC3kqXMNvnJ7gLXw2qcVUgFCcHolYG05IAwVYkL1X8KISSJtg1IQC0n7RsEjH1oi7ee89uoW73vPMQ+QphDR3XPIk2goJVFKgJOHh9zhiWKyHhyuC0drdXf+OPWbKLHKNwJh73DsXsePFHHH3+nHmVpBx3jpjmqOrrp3K4E8WYZBSDm5Vtx19hicH11gi8KwfnubVl1w49oGQvrchsY6kiQkjkPiUDLbFGWuP1BBSBBFntFVehAYVRvc3EgxbpOZ1ogoivi+Z5fK+t69deR7HlBt7/ZwgWamMUeepzBIOffwY1y7egHd7qCE8BhIJVQqTVbXztBPO/T7XaRSRHGFUdrDuQJXWJ/LKY4plMNJiTAWtCk1SApZxiAJ4RNueqWMghTP7BNIlDZYBKFUXrDVjjAKMdLhcoMKQyQCWYkJEZjckhtNNkhJgojqTBVbldiwirE5whaoIEYYi8ssUilkIgjDGImkVY34kU9+mCzb50svv0q308dYiVSQCEklCqhVazRnqsSdPhe/8EXuP36MaGaJ9d0uKrM89dAz/Ok/9adoNSP+xt/6WyRmyEpcYZSn1BF0c42oRtw8aLO1fp39rQNeunKbr1+5xIn5Fs04ZCg0Iu9z6/pVLl98kyCa4eTJM1SrM2S6YG9vC0FGv99BqQihokkC0qTe4sTj72PPKlZPPsLc6vHS7UkQBYI00z5u2hlwDu28O6POcnShcdIhVUBdCKLCenrT1JIIQSUUzAhYs4rZwHG2othIDQMc2gDCEClFSEBFWIxUdFxBRIwm8FSrzhFYSxRGdDttfvvn/t/kg32CJKHWbOGcIh+lFFlKLDyYEVFMGEgiVWGkLUFtgfmFOo3ZZQrtMMZrZy0CJx0BASZwOC3wykA7STAYIYiU8XT7WhHKBCPw1P4IAuFBlBMOpWKkDBDSJ5F2zhEJkJmhu3Wb5soJrp8/z+98fYt1k7Dxwit0b7zIIw8/xPzZNXbXr3D/M+/jzeefx0QxmTHMicjneVOKDEGOIrCesjcThvy7OIdMHAVUKwmjUcb6xi5jL7O7tqt3NEh4RryZFkQV7+s9ygVvnzee0bPUHk8cgRwY7bBlGo2xO42zkBWaXAl29qBeU1RiD/jSTNDtSjb3LHnuMM4x6koqNUMQ+pxJgQKhJE5KzqgaH69V+XRvg2tpSjp0bGxq6jVBpJxPHBk5Rlay2w4RzlGpWoLYTSxj1jrmBBy3gor1QfCmEAwKh3OCL6eWv3Rlh2uRhFgc8mAIWDrVgGSRR+9zvKdaZ7S/QxyF1Jym6nJik+NcDCZj2B2QpylvXL7NYJDxwLmz92zu6a1ddQfEO/ssCcnZuELgAlbiKou1BnEUIX0eYMYa/nt25R3Y6R3lkyNCwd3a7XuOkXtX9A1u8v/HOe80Dqce74h4Pe4XJxgOM3IZsh2EDKy56/pJ1Q7COKE1t0JeFAwOdrDWKwu1E+gs9XlS8WuYATbCmB9571PUooDfvHCTX9va4S88fpqwWiGzGY1qwv/+L/5pzj58Eovga6+8wW+9dcnT0n+XgykArY2PSZYSbWE4TEuLjBdeJ7FK5fmVVkJSDbDOIicWJ3cH8aQ7/Ou8MvbQouDAleRbAhy27GiJNbC34ei1JUTgnJwQqDivi/AYzYkyiXRJEDJN9+egv6exWrB5PmHYkTgpWHlQk8w5OruGYV/Q2VX3iFvxFqysD/12wbDj2L5hePN3Ypq1mP/iP/sBXnlpnX/yT74GOHp7wruQAitLM/zQR05z+coF+kNP1GWMA+HIi5RsOCoBqJiAmlYtJI4V9SqcWK3z/vdX+fGPLvKZlztcvtql0HDugSpjXr/DqTNZgBmj1bEVTRCUKXJKa5rwMVZ3qg6/2Yy+u2W+hQu/WaV3ga9v4do7rnkn1c5dAMsdLi3jc40xE1fLOys/Ss4xDSwFRW65dWuT+SXJ1Uv73LjSodvzXhsnjldYWazSqEnOrJZ5AIEgaaIqLaQQk/lVnTvG1r6l2+/QamjiOOLxJ/ThvHiXyvc8oAoqCcPBPqOs71mmkFy7eon+fgeED5QWTjE3X0UozVvXvk46SkkqCbV6i/buLjYdYV1AmISEwsdUOQ0CizWasBpSaB9sGlYiirwoTZ8G6cBLxhInIWpVCEOBFYpKM0GkIw72UlQ9IowDst0errA+eNM6XBhAoIkCizWCIA4JayGxKBgOByRBTJ4X1Bo18tB4F0RdYI0jiUOkMCy16nzsfc/w0msvMjgYUa3EVBOD1ZpEQi2OmalHfPzhB/hLf/l/RVyvs1r7R9zMK4RLM3z1s1/lE089zLmHzvKP/95/TYeYxdUZKtUmTmvWb11GbR9gZEBvkFKpztBJ19ka5NRrNW5sbfPU00+wu6/J1Szn3vcAp7/vowgkUklCIZlpb8KooPHAk8wur7C3tQOBIjeGJIj4wCf+MIRNwlDRWFwhqNTIrPHA1ViUCCiwWKfBSgplEAa0jAmqFZw1OBmQG0MUCZwNCGTqY+esd5NQCKoqpqdzcmNJAkWv0ARIMqEJkRSlcJA5Syo8m1UoQtKioBLGSAz7GzcZ7G8QhZLazCoHvRH9foHIC3J9gMkP/KJbblRWG3AGXViuBAonJM3lFTIliZ1DFhkqkGhnSJTESNATxkXFyOYMHQhtyHNDHAqSpEFgPC22swJjJYHyrIyiTEYjtSFW0EDgtGW3O+LqG69z7LH38Tu/+yJaLfL+D/0Av/pz/x9WayHt7Q2qx/vcuL3D0888zPraSepRFWMt0glyoQFLFUFhJfvGEjnjKU4ndAvffeWZD36QuVaNnZ19jDHjbZrxhq2kKIOHxwlpy+IgqisqMxFRoihMxKCtEQLyMp3SmCTi0Fd+cqnXppZganffMep7xj0nBL22IwwN1arg0YcEeWbp9g2DvqTXN+QDyLoQ1QQIR1E4Cu1dCCMDH49ifnq5wa2wzU2dobUizxxZ4IgqXiGktUAqSxhYBgO4eePQbQ/hIHP8/TTjV28OuRgFeDKvcYCz4AcrNX5qZZn/Lj/gy6MOYeAtudUKVCLF488+yEePHyeQAb/6a7+LEgWqliCLgmfqAZ2O4Xre5sZWxmA4YmdztzQIjbfuQ8FnWuaxznHia6/y+P4B1aVlIrlKmnb5iw8+RVKrom3Kwxcv8MoDD2KjsOzJb6F8s334rlw991Dv/kGWKfn3LoA4fQ5QBofw2psXWU8aXFQhI5vfZZSaRmVBGFOfW2U4GjEcHCDylEjn1EZDdL+HEQJjPbi3DpCSqBITRwrCgCiJqdfqEHh3+0goooMBxc1NTJFTbO9SqhLexUb6gytuIkoKhFQYM85n58exHPswIUqCD4E05Zy705hxx7ASCIZtwa2vS0ZdB1YgnWTrkqUYSIQULN5nqc358609RMd5Kti+7mO6wVsY8hGAwhWKncuACyhGigntQWnNcMa7/RWpohiFIET5Xoa8L0m7kmHXs7LJQHDf2Tp5rrh+rVsabhybb0TsXwKjQ0Qh0KngYLONy/LJe27cLHMuCeXd7Z3E88m4SVyPRWCcRReOMIKwZDAPleTP/eRp7jtd5fqNA6JYcDASzM8l/OTHV/nsa/u88tYB6dB4god79Nz4j3NeGWo0ZVsInMsZpZruwKC1IAjHe+y9+2ry27cxrL+t1eQIAP8Ger/pRxoH5d7zOe+t1BlDWAQ44yZj5N6aHabm9Xjg+Utq1SrNRoPZ2YLLeReryz3SiZJS3x0535WPK5RCqNhboSwkcUSoArxFsdyfJ3vHu1O+5wFVtVqlt7uDTjVIiYwlSRTROnWcZjPk+q1thA145onHCRdn2d/vcGtzlyAI2Fq/jc58DBKRROsCZxwuxNP/aoeKFLowIELAUIxyLyALgQokLgyQQqECibEFtVpIrVahMIZ2d4DKcwInMP0RxSgkjCNEbsmNIXQGkYF2miQUnDt7H3/pT/9JLt58lV/93BeoDxWjoYPcIozPIRVJkIFCCUGtGrK6WOV9j85w8/WvoG/eZq3VIG04pDUURrGy0OLU7AwPHFvhJ//8/4bd7jr9a1f52E/+NTq3vkZOyA89+UFax0/z6hc/y+XNNidOnkNGVYzw8WRBtUqv9yIPPvkcs60W6aBD+vprnFiYwySWF7Y22N9sY0WFQCikCKlEIQoYYpBKUWnOsd++QXPlOB/6xI/wqz//T70VxRnue/RpwtDRvn2TxvwcjfubqDAmAJywSGMRVmKcQWpDXhRI5V3bAut8EKpWaAUqDCb5HEIZU5USKyxWCzLr2CxygqIgChU212TO+6FnaFphQug0Q61xwlsnU+2IpCPXBSefeT/OKVozczz7kz9Nvr9Df9BlcP0KiUxxhaGmWgjXYKAzXKEJtGaYjtBZCoFAKoEprU6JCqhKha4IAgRaCwoBeVEQS4kWFiIIckVne52djasomxNKaK9fJR3sIqQhCBXSgi0FvjAIQAQ4VVL4GkteaPZ6fd545WXe88f+DFc3ugxaCdV6nf29DSpzMXMyZOf2ZRaPrfHC5z/Lcz/wwwTNFgSSkQSnIZCKHD8QayZClVrqgdHfqSXg91zuO3OGmQj+8c/8IieXjlF3mh+dm+NzO3t0E8ePPXcftw80v/mV82zt95k4NQhIWhELZ2aQUrDfgYO2PXQ5uMcmd1imNiJv2J7ERFnr6PcFYWApMsn6hg+K1tZiRIFGYBA+5cNUrHelBkkFsn3Dz1+4gbu5y5WZkANMCUYcWSboCOnvJxznBPz51Qq/LXI+d2DBHgrnwjj+ykyLc7WEv9ntMMSWArwACdoYltZm+eHlFstbIUpIAnxy34pIaFRiFmoCnCRWgthJAgyjQco/f3WPi4MUZxwvv3EZbTIQh8lrffu9A2AR8CsSfmZvn1VgpHMyY6n3+tQDxYcbVb7ebDL/wEMEU10h7qjjSB/d/eXe5c5T3F01f4vlG0lc30gk+uaPdOdtnIUizzHG0NnfodfuY4ocUxSTRM7TTzUuVkhyFNaV+WeEINQZwc1LXP9nGyRRgtEGa33eGIXzii0HFH0eaRhqtRinJM7FnFtoUbl8nuJ2iM4MNs2gmhy+xXd7LNVU40kxBa4AISVOKrLCkfZH0O9h0wKR5mAplTX3rtQrMBwHG4qDDXXkyNZ5yeZbDqTg6ZagMuMBm7UeOAkrEAbyfvl4bmyhkggLTofsvB1w91jzTHx5TxLivSbAuxwOdyR6SGlZFGRdP0/rlZC/+FMPsN1O+Lv/zZcnQNHkilF+WLPOHTfevMVwOJVbrWwvIRzd7pBLFzcZDPVk7Sx1hOS6wFnHX//phwiVXy/futzh5FpMo6Go1UK0KZCyQFtJJAXVakQUB6Du8Zp39J11jls3u7TbGY1GFWcNxhS8+uYeC7M15o/FJEyvJ9/MzPQHNKa/wWO88xMcJWO/dz3u6KGSvKTQBmvvTHvwzR7Kn9tsVphtNditDOkP3GS9F1OnHY1lLeWauEK1tYAQfn6txDNMcjIGEodPcSTeRWeZ73lANer3vI7LgQoUlTBh7fiDPPDYabr722hXY751jL3BkM3bb1GLKlRlyHA0QBc5AosUEpsbnHFYDAIFhU9aZmWJ5GVRsvKBCAMCZ0p3MR8rFTcSsHDqxBpPPXA/mBGfef4FtgeZZwt0DhlIbBChQk9Pnhcp1hmQCoNic2ubX//VT3PmTIIZGQIXolyKxSFUgaDwgr60JKFiaSbhw0+e5M/+8B/h2OoHkYHljed/nkvnn+fizQPyWoMPPPooZ9fuZ/Wpj/Lm+Tf43Re+wP6tPR579SIf/vAnCKoB+7s7PP+VF3n9xg6v3dgmrlgas5mngzcSk/bp9zqkO1v0ioxRf59KvcZLr79Gno4Y5CkH3QPCaoABlFJYLMpalPV+90rEDLIRbmebrWvrPP7Ue6mIgPmFVU4//Dif+9WfZ362xeyJRzj9+EdwEs+iZ33AbG4sttDkRmOwkAtCJdFWo4HIOWxh0BYiqTw9vDFkErTROGdRQtAvHCGWg8EIEQRE+IDHdDRCWMiKgnoSESnJUAUoHNZJFLC4fBzpfMxao7GIEZJc5jytrQ/8zQ1OeSBmnKY36CJMjs4LRnmKQuJMwe7OTW5dfhOHJFAK7QyF8hY06SQidGh7KLym0jLodugebKPSFD3qMBx2GWrP9Ciw5GhCJzEIKk7ibMnQiGMUQKANaaF588IVBr09Rij29/fY73qGykEfOt0RLX2BJz/2R+m80GN/8xYPP/5xRi4gEYoCi/Bi0yTmYiQNAZLKd1JT/3ssQSgZZiNeeuMVv6iHAa1alaTbw9Yda8tNRFUTHLF2eE2d1o6Ddl7u+O+wrx3Jmukm/+7v+vxzzVnBTEvQbAiKAkap48b1AmtASEF/6Nn2un0PtsKkDOavCmZnIPaKY+9CKB2Jlfz4QotnVpf51M6WF9amAs5l4FhaEMQBPHjT8mfaOWEv5wtOYMXYRc6zbT3bqvLoTJVK9wCkZ88ab1r95YSt00t832qDDzz+AGGQIIzkrdcvkO0c4DLQuUHaApvnSCV4/q19fvuNTf75hS4fefo4djSk1xtibME4F1MQjhNdjQWSaS2oQwjJI889RxHXWLm5ztvdDnmuOdacZUYofvLU/ewlkrwMDJmuadJ/99TKfpPyjqfceWBadX0XAvvm97nn+e8wv75RdeWxnd09/s2//k3yomA46OMjT0qaZqm8d4Xz8ZxiyloipSJKKhRpSanuBFcGml/e1kR7XRLZZ5SlVBuKwPjN8cbOHijLjz1+mufOLvCV7hCERAUR33/6GMfOLaBCAVawsdeDdnH3A3/XlpK9sxQGjfVWeyc8oBoW8NKFHW48/3Xue/53GaJYNQrhQLuSQl/ca8yUlUzdp/zxUOR0ePKaUkFvrd87hJMMd0MufFaVgqqY1FfkbmKREtPzbOr2ZqTQocaZw2fo3Y6nnslbyCUgy9yfE9L48fvcoXRwVvrUC/LogilKzZCQFiUc8zMJQnh3QiV9/rS1Y5JaEnPyWI1mPcA5R+cg9Sx8CKSSRDLgwTMJsiT7KDKDzQx72wek6QqVSnSkKcfWptEwZ2urS6c9YGdzRKNZQfm8M1jjmXh73SHpKGNmtkacRCUkEdPVTY2BO0fHuNnEXb+V3Tm1O3wzMCbu/niHbucugp3J/ScHJ4eOJF4GpkmZxkPSCUGaZfzyp55nd6/jc66NFTITU7mbut091iznrad5YSkK47U9THkiTJ04gVmOCfFQpI62r/cUcz4/q3WHyPtdKt/zgCqsJwSDAJ0WKBUytzTLweYNdiqGU2tL2LMroAX7nRTlcoaZYW9ziyJLqSSK+YUWhdZs7xx4il4FIglQscQOUp98UAicdiAUofQEAkb7WJ5QBDhrGPWGJGHIIyfex9/+L/4rZFDwl//Kn+S3Dl4jUwanPRBwke/soHRiFkYilaFZjZitCB5YqcJ+l4frFfIg4q3BgGYtQASOaKZGgEBpw2yrwifuv4+f+iP/MTvtff7Z3/yPOX3/k3zkYz/K4x/4Y5jhPjKJUPVZdtZv80v/w39Pa3WO+SXJi2/s07t6kd1Kwpsvv8LZY7N0TMZGt8eN9cvUqh0W0io2Nwx0TppbMIbhwT5PP/EERXiKSzev0715m4N+F0VpHQmhO+jR0Ia8BAQgsU6jrcOanP2bt3nl5S/wsY/9KLVWlYX7Huazn/llet02s/ML9LbWSYcDwqSJECXFqbHkuqAwOZEKkFKhjcSW9xEacqUw1qCsINeGHEekFNoWCOmwQhIJgXagdUEt9jlTIiHAOuK4SqQUvTwnswZtNYXJSZ23bBVWI4ygkA5lDIW2VCoh0oYYCTawyBAqIvS09lZTmZn3rJPG54IKZIC1BQv7Z6jPrpFUErRwxAQ4JwnicluzjsB5cpJEGmyYcHs0YLBzg0G/j81STDZC595HXzqBUiHGaQLjhWchlV+rrMZayFFkUrHZG3Dr5hWS5jzz1Sa9kcUJb/1Lc4Pq7OGwzK6d5fKFSzz2EyEmdeTOkVtNUfrya2vQtvDugEqSunePqvTdLkL4NARb+220NmxKwc8Lw7WDIQ/NzoMMvKspnlRCVRUq9Mk2VRJMNsFD4WRSc3mEI5vd+HiRC6wJSEeWQDrywrK+YchSQZaW1zjDXq5RUrIsFNVKxM22ZqgNTkDWE568QozJ2AWVFM65gAfDgMQwtTf7OxsNm5t+51wYCf5Jf8S/FQ6q4aFAgEMoxQvNGvWnH+aHY8iVJJAlo561nKtXaJyapTXTYnmujkszeu0+LvP57pJazNevHvDvXrrBF758k7/xoeN85sIB//DVLpnRdHojEiU489gjXH7ta5O9WJbBqUf3xaPtG6oAFUZ8am9A7gKqSPZHipNzi/zvNtex545z6kgvHHbC3Tal329B/t8fYOCAKIw4c+4UeZFz4fxlsiJDypCg2kBIhcCRHuxg9XSqgDJFqC3JVMrOaRvLFS2InM+5dDoKUQhwgqHR/D++/BJpZvjZ/+CjRJGikoS4wpAEIU88dw7xxKp3wxQC9/Il3H5xKLB9h9ro968cOgv7XI92sjZYZ9nY7NDuFfT2B5zLU6+gFbVS0WYBeaSub+V+paQLwvkYV13eTztcaZIxuWTYVketCdNy7z1r9W+SDj0QM/pQ5HVTJ05baaxxtHe79PuGo7m4ptdBf32ubYmz3FjCn8SYBVJQrwT8p3/1aSqxB2+yjKeJY8mVa9sTjCYQKOVdnrUWk5xNJ1artDtDrtzKuXGjz95Oj6CSkaWFB1RT49wYSxgFtPeG/NovXcQYKPIyTh48sZk2GG1446VrjAZDPvjJx1lIPDAb5+S+w85y97uPP7lDmf8Qa5YKOXcI0O5O0evK/+5YG6ex0fTiNgFKd5SpveDeF951MghBr5eiVMH/8A9+k2o1RJdWqsNnE/euY3w/4V3yajXFwnzC66m+4/x7uP86hwwUC/NLJLUahIf7rSstWc45wkD5dQpXxiO+O+V7HlBF1lGvJRSjlLNnVjmzOsOrX79Ery2pnIn5+PIMqlblrUsjOFanP+zwet9yEEb0MktSbXGwueGBkgpwkcTlBcZBEEQ4WTLwaE8DapAcW27h3Iit9T5hIpFCECeKqoro727w67/0r7FBzttXruOMoRoICq0wwiHTrNykAGtJEsdas879q8f4Ez/xhzm3uMbao09y680v8hu/8UvMjEbso0kqs6ysnaZ99QIPHFvhuY9+goff8xG+9NlP868+9Yu005yrldf58j+9yvsfeoCFapPFlVkK16PSXGBHD4jFOQJpuHZtn2Z1gYtvf51TT7yHimgz7HdoaI0bphQqpxrMkYeSmfkVFk4/xEtf/G1qcZXuwS6vfu2r7N2+gTIWSQF4DX8x7FF0OmRLOYW1uNC7JiEsFJb9jWsUW9eZm2lx48KrPP7e93P76lsEesTS8gr1aoXa3BkqszNkwhE7gRUSI3PiMCQJIoRzjJwBaZCBouIibGzBCKSseM1bpjEUCOswZeJlL6MJEulQUYWKVATKc5KNckuBoxlG1B1I58itQUpJbDRCBoQyIFWCJJRegx/A0BQEBvI8Q0UhQoaYwC8RNaGwQYBVClXSoVecBCcp6k2WF09RqyTUlG9BVTLdpMoSCEUiQEmDRVFxBQFDHAad9xhlKSL3udJya3DGYKwjQHiOUeldIaWwuCjECEmmcw5SmLGaW9ev8+CD9/OVGzsk1YSo0iR3QwoLzjoG+9usnnuM9s3X6OwdsDy3jAAOrCNPcwILsYwoAoNSIXlhUebd0wq92yUd5Vy6tIkrg/SdE3xicY4bKy3WixQ36iOE8puOEMQLFcJaVG7e7q495JsZMqaPZxlsbkOr5YWKXhfyTHjuFe0Y3mxDYXkyqvDXl5b46E88zF99+RKf3eviwLsQAWN3uQDIneRXzJDXb93kptYQjPV9h2xYpnTt26lG3G7U6R50veVirOJGEALXFeTLC3ysOM4wHZFqLyxmaY7TDlEYbDbApg5jDHFsUUqQ47BS8crNLj/3lS3S7YztTkZG5LdNo7l8YZ21RkS3ZydgygH7+wdsbO6wvDSPUnLKUHWoC86N4crNTfL6HCDJbEEe1RgahVhd5UxrBq0LwjA8RLR3qoP/gMu97njXrLnzpG9zWgnGcrZnK3vmPU8gBKxv7SJ6A9J+j2LQRUZeKHTWTkHWcSUCawrS/i7WaP9wzrJqDSeVQAuoixBlHCmaJxZn+CuPHOfl67dI0hQLPFtJ0M9/ndnC8PAjSxxYS5HlLCzUceN74+4SHb8rSyk4OgRZprFGlEKto98f8Uv/5PNIFbBYaB5oFpi1JldGiitXB2zm4xgiuLvTp9vmHYReBxe/ILn2kge3zkLWlZPz3T2E6Ok8RUlV8cB7l9i7OeL2xa5f15xgsF9hWN73CFX4PZ7FaMfuVoe9TndKuD60kCjpQDiUdBijWVup8kMfmsdqDxJ294cszCQcX41Zmm8y06hQiYMpS4sryXcCtBaHxhDlY7+kA5zAOIFDcTAc8vIbbXINRQoisJx/bZ04jg6NOk4wygpwsHKsSa1RYzAoqDYD5hcbxHFMEIXMLzVZXmqxsNwiG424cXGD29c63u1xEk91xygulQRjEpCisAwH2fhVjpwXBJLltQZKyZLKfAyeHNPJ2g/5cdwETODGlhp/wuT38W3Gx5iuxx2uufbwmmmGvMl3J7DGcePWLqEK2N/psee8RSjPzTsuUYcGKzEZD05ArSY5vlbz7+knyMRq58fkIbjzTyMxQjLKNS7X47Mmz2edN3a+8spFtrc7/5OF6vdSVJaTDQZoY3jr4hUuvC2JY8XJYsR/8N5zPPbYMqa9y/ONJfau7nDyqXPsPTDDp17apNN8Lycff5hP/ct/gNrvUI0rbB1sYQvPziWkwOqCAEkQRdhQ40TAXrtHaDX3Hz/Bsx96jJ3dHc6trvD1V14mGNxk/eJXuP72eZpaslyt0u6OkNohhEFqgVHQaFQICHl4qcWPfPBZPvHJH+LClUv8nZ/9B7z//vt537Of5C//9b9LPrhJe/8m6ICwOksS1wgrTd6++Db/6Gf+Wz538SKoGkokVBrHWVxeYDcKuXjrPCvZCrP1ClXdYjfNufjCm6yeqLKz36PXdzzw6FmUtBhdJ8FTDi+vrhFHDR54/ydZO3M/aS7Y2rxJKCXpqMvvvvBZ0DlCWAqnEVKgLez3urSiCiOTYTCoQCG1xSmBdQpjc/Zvnef0Yp1P/uQfwYSSwUBzZvUxPvnhp9jqjPjK119HywhnLaGUWGGIhETJBG1NyTwGiQuIbU5eWIwGaxQSi9GGUEgS5citAqmoRxJtLUJKEgTapYAgc1CgUU4Qh5IE0CZDSMiEIhIB2hgMCcZZAiSR8xrH3OKjUpz1lNahZ9nDeXBllUAjUNYQSs+6ph0MhSO2lmYUoCsJs3FIM4SBFoywIA3Ket/1Ap/c0FpvIUuzHCWgqirkdkCR53T7XYosxYmSrlqCUCHaGZQQICRxtYooNHlWoNKcflgl15ZTj57jy197ifnTD/DAffezc/ttT+GPY+fyeR756B/GDFZp77SpN1pUXUGQQqg8c2VucrTOEVqhpGN0Z96m76Jy5ep1fuuXfwE7SesiqESSOQObBDSkYb4ZE85XqAaOMAnKjdRfP17+3ynk52g5FDJ6fctglGOMoNue2jCnNkmTW0SuOakFze0hyU4XN8zKhJxMmLtwjhUDf84lLB5b5MN/aJV6tcJnf+EF9vqjI1YzAWVwtuAHFhr8zcfu5796+Tx5qomEVzQoJViUgkerVbI0Zemh0yyemMcYwBTsX7vOK1+86NNIqACVRIzSgvV2nwv7BXvbmvnzm1Qbc6hIkUnJb17vs6lCn35AKv7I6Rnes9LgP/rVV6faRvCFz3+Fl19+gz//5/44jUb9HURIS/dgk7mF+4krDZqtCtqENJXkpxZHrOg93hiFtIPgUHZxpcgjDvvsWy3fDs75hjPiUM78JpWIb3DOOz/VtBVhOBrxC7/wa0BI0GhRaUVkwz42H2Hy4eRsMb4fIFWIlAFFOiDtbOKMmdSbGzNh5ksLQV1YKlLSUIJjcUQzChFaIxFUsbjb29SlpOo0b37+NQbG8MkffARb+MCa6SSy393Fv8AoT/nqi+dZWIipNmIG3RRnHQf7A5wThPWY/L0fYPkTj3Dl0ib/8u/8DtrJKcvQnXp6cectjh7zyn+Ge8HYWMVYiBX3uuQeg78yE/ChP3Ufr/36DrcudkuZ1p84cb4aWzvuAn3j30W5btnDo+XNpXR89P0Jj5xbQEjBbDNhphnz3FNLxEmMlPClF6/w2EMnWFme9zno5NjaZ+j1U5qNGJy3ZGV54WPEhERJxdXNAbu9goOB5sb1jM99dcAoy9jcHOCEYNjXDAeGr+7d9OQg43UQ6em/geEj1qe8kZJ6q8LsXJ0ojomimIXFGZaOzWCMY3drj1e+fJ08M0ewkaCkRxWHAGLSOhNK93LxmbTl4eB//SU7yZF1J7A5BGuH68HhKVPgaepaN/V0Y/6J8XiY2ILKZzkKBL1izdlD0OocGOfItSYvzMTyNcHp97CEOSAIBK25ClIIBoOMYd/S7uRcuLTHcGAmY56p/52bqgBv+TxoD45srq5kpfTkLh5YbW5sY92QueXKXc/y+1W+5wHVD3/ofn758z16vQxlHM16xJ/+Qx/kz/xHf54H1irEs6fp3/wqoxevEiQRRXONajrgidMn2Bh2OXj7Vd57ZoE39YitYVYyZ/rAcmdDAqXAOawEpwKklCSxoC5DhumQ61vbPHXySf7Cn/8J3vjcr/PU05/k5s4uT597kv/F6VP8m1/513zui59nuz/AOIu1UAsVy4st/n/c/XmUZflV34l+fsMZ7hhzRGZEzpmVNauqpJKERgSSkCxhS3iUoW3AjfHDC7yw3fbCr8HDatMs+7lpA2+Zabnb2AbbuHkGjLGMEBjNQ42qqqyqnDMjI2O+cecz/Yb3x7k34kZWlpBAMhK/tSLixr3nnvF39tnfvb/7u9/4mgd43ze9j/kz9/Bv/+3P898+/Xu0Oobn11t85PmrHJuq8Pgj5zhz5CQzpx9lbafLEx/9j6xvb7JdrdLLoNo4xjDpsd7dIL+6TS8B7UAVA3aGPRZmNd3rq1y72uPsqRWefv4SSNjt9Ch0nQKHDCpUm0c4c7qBj+cZdnskA8dnPvZRdlqbDAcdZJbjwwCHph5IAqFIXY4UGoQjzyw1obB5QqVWITcGWQkR3uFMQSwDVu57jMHNp/nshRfZ8zUiJQkqdeIwQAYhSiqsz7G6bHYrZClbigGPJfVl1ghrwDBK9Y8UAPMc7wxCRUghShqFsgydR+EInadnHFmaUg0DAmExuSf20JMgnUQLGJiEYZpBVCGQGqkV/TwjKgwirGCFRBuLpezv5HILypD7HIIYJRWFM7g8xxiD0xGhkhQ2p5CCqtRY53Decq01oFqJqMi4bAotx0Xdpcy+8hBJS2Ysw26HrY1NfJHTTTKytE/hDcY7hBs9hr3CKoswFl+pEIXQyQpMYRAy4s992wd419teT3PuKLe6jvu/4Ztx1SZvfq9n+/rThM0Z5uZmKWxAfPI+Vu5/iH43o99t4asVKBS21yGrl9x05UEqicsN+uu4oNxYS5bbyWcVU1ryzmNT/M0XO9wchLzvoSn+xac1AeFBIBkmXr26o+4P/zp433qsLR8pB7zwg4hyUYxqMBCjk+3x0mNG1IaJwC0e2MkM9Iec62yR1HNm33qcMelIjhYWQox64QmElAyEZC93vOH8Mb7h6FwpTSugtdmh3R2CUGjrmAsVzWppC4XTJMrjrEU4i8DipeTnfm+Vn//8Lt1C85bAEV+6ya9uttgbGhCaxxfqpDPTtEXE84MBrUJwsl5nfnaaW/0twBNGISBGGZHJkymYfNIqIYjDmK1rl6g15zi7dIaddp9rtxNkc4Yi1uzZuzetHF+k3w9UfcVmtH/lvwcR8tGuTXi+k4uLV3z/7nt12KU6fFSVKGR+ZgYRViiKgtVrN3G2eOW69jOBglpjGrB0N67gJ2g9Hs8147jhCiIl0N7xkJbMe0lBSZ/KvcTZsdsmsEKgRIh0BiHy0lYNE2yejrbn7+qQfT0OIQTGGMzQUQvlSJxiooYRh2jGHPtTb2NxfopuV5UBMT85L8aZZDic5XkVFD6eN6NFXwmzR6Bo32CUk1+Ise0ZveXL/RATKxSiJD2UU6D87iTYGu+AgFHDcUE1FtxzpjFqCuzwDnTgue9MkwfumSv7ZymFEh6t9ai/kKQ5VSOMQrSeECb3Hms9W9sDGvVRZklCZ5AxX2i0loSR5NmLbfqJJFSCIi2Fn6ZmKzy4PFO2HtnvmeT3b6rSNsgR0IG4GvDyxW3SVKA0rK3uMd0ISZOUtdUdhAdrLNtbezzw2DHqjXhfROggU7S/2xP2fOJpMQKj46TWeJ/8eG7Isaqh2F+2jLH5Q+vbxzATF90dbPQA9I5qjMpap0mQxmHb6O+I3fhyzjjK9h6FsVy5uMXqjc6he/UwIDo8LwQgJESxQEqJtQGmMCXjy3mcOQBm5WU5UNcdl0Md7OvEvo9O9D4wHGfSRid0skbtKz3+2AOqo4tVTG6phAF/6d0P8vC5Bb75ze/m7Otej9h7HmwfFWb0Mssjp85y9PVv59MfvlD25bEtLr54Eyc0aZaRpn2Ud4gowuKxuSHUAcvHT1CJY1ARswszJK01quyydstzavoIr33wPAvzJ7j3vrfwqd/97/zSb/0GRZLz1ofeyDd/49v4lrd9M0EjJO3u0hu0mZk5zcLSHEma89lPfpzP/Id/xWcvbTJ//FHIrhKqgEJHfPbyda72doiDZ1g53UKGkudfeBEPxMvTBEFMoAxV57BpRmt9m94g48jKMlEu0DgyPyRNM3q9Aa1uj6yAU8ePcd8jj3H83CPoSp0iMXS3d7l2+WUuvvQCkYy43h4gAo8QIcmwwHTbVGs1AlugaxoTgPVlw2TpPZKAzHvssEOsQ6TWKK9wEmRQCnbEjQVa/QRRAVFt4gnABaT9FMUA4wxWeKZEQOpA2YLMeIwqKUZ5UexHl5IspxLqkeVyhEhUWCvFMHAorciNh8JSyLJnWBBoVFAlRmOLgsBlFLpUJdQKnC+IfYSuBlgPuRDkSUbgPV6UdXPZcEgcgNBRKUuvA5yKyfIhgTU4YTGFwaCIowjnDJEOEMLgvCL3HmNypA7pDAYkSUK9EiN9SVkwwuKlJx1oNIJqLBFa0O+16fa7aGdRRVoqTdoyWldmK8p+adaV9UzSlb2QAqnw1hCrkEs7Cdsfu0SjvkNYbRIJidAtXGWamfPvRCHIFHgp6HdTfKFIrGXWhSSuIHM5ucnZ3d7GOU/Rb6OUgnAGk2Z/tIbgDzFKHvgoCjiK8EpZPuydD+kmkjx32FFfI5hwbe6SmTt45wAE7MecD774Ss9n7PAIgSkc1pYOqQScBCPKuW7cAUVu/6u+lNofZp5CZRiTEoQV/tSZY3xgcYF0mNK+tYFUGi1AK4jCgI1c4t75KCc2brFyYn5f3fTiUwUiLdg1YL1DNENwFucFeWZZ78MLPbinv0cxXaHXy7naLVh3EoSm56DtND7LiYRgEGiEhLmKJq4G+FDxTDvjiqySDrqjh6Fi9sgizbmSBhRF0YSX6Q+dJ4GgWp8h6/Qxw5yPfuw5QNBcXOaXTZN67pirK6bvPL938UXvCoC/yPiDPq79Ha8ne+L4Oz8cvRg7B6/MNIjDC98Buvw4OuCh0Zjig9/2PrZ2Ozzx1AsIUTZFnXS4mGx74Edy6NmAIkv20d64Z15WenhkDrSHl1JHbB1X257PpCldU2e1HeJH0WYjJNed5PbnHUVRxzjB8x/eIxvX0fDKapGv55EMcu657wiD7gBnD4QpxplnayyDQUbSLEjSnH3C4x0T6+Cs7CPdV9ni5ByZOI/7tkmw8HBEbSHEDBzrTw6wE1ogQvhStVOWsuT795vwPPKhZe57YJHf+D+eY9B2IMo+dVqW39OyZPIgoV6DOFScPFLjOz74GIHW+5QsAK3GPa8oPe2REzyWRf+G195bNnOdOKaR2j+FGQW5kVgHL10dsrbtqcQRzmqmZ6qIOGV2ISJQgkHPMj1X5577jpbCEqPaKjkpWrB/65TXZTjMEL99laRnUBp2N/us1gOSJOH2rV0Cqcizgt3dFo+8/ghzC83x3XuI9veK6zDe1F3iF/tXzYNNu2Ud48TOeQQqqqHCO7Muk6DmLtuaXOoV0+bgGXb3WM0IoLkRg8I4kqTgyuVtqtWobOnyitWVNEVjHFl60HDZFIKN1RSE4LFHF5merdGo1dlYz2lMxdx77/z+nDh/epqlhZh6VbIwI/cfkSqooSvN/W3sZ9fE+BjEyJR5rq2t0uuldx7wV2z8sQdUH/rz7+Ppp55hSc/xvR94A2fvmUEtLkO2h8s6CAcmGSBFSD+Hyxcu0d6xDIaO6bDO3/qf/grtbJdf+fBvMNdvsLa+RW5Bao2oQDbIGW7vMX/qDI2jR5mdnaWjCloXd3jzA4/yfd/+lzhxzwNstzv8+9/+MOvrfbacJDGKZ7ptfu9nf4qHTtzPt33gA8S5osIREqX5T7/2m6x3Uz717Ge5tbrFg49/IyfuuYe97W2qM/OEsyFRt8f0yTegpSITnu5gQHB0ifaNm2xdusw99zxEPF3l5o2XafV7RNbTjCK0hmRgmG9IGvUaM0cXuf81r2Vh9giXb7zE1eeepYia3Li5xtr1K1xdvwlZQeoENs+oigyLxPQMRT6kGLQxImeQGqwG60EqVTp+ziJUaRSc9ajKFKmxOFcwsK40ZrlBBIJ+p8WLVy8zN7tAtZlSOEFzah7MgN2tdfIio370frq+QHlFXmQMspwwivEItJBkWU6gJForvJS4woK1OOuQ2oF19IsM0j5eeGKpGNiUoNkEk2KLnEHmCOsV6mHMMEkodI5SERSQ5Qk6DMs6E2EQolQZ9EIhhUYUKVlekGeGQAlSkxMHMVU0xnlMmiKsw4UxwkHgHP1uq8wkRRVcniKsxfkhIqiQW89u0qemNWmeM3AQ5BlhGCECTT0qJW2NUUhj6Kd9Aimw3pYRQQOIkh5Z9iYRUFgy0QercaIEB056sDlJOqBIc4JaihKSIk+xXmJ9qXaZ5TlB4AnjKjJXOA0bziKcoxIE5KWFI65GSDzWGJorTfKv376++5SK/QeiENxIUuLOkEjkXNvp8f881WWYlwoPB87wQZTP7z+5Jh3cww86VzjSVr+MFk40AJqsHyr7cICvxIgwQAiBQ/CSzfnlHD777CqXtgYU3pfZWyijcl5CbknQOFeWt4vAMhdpHnr4DL1Wl4EforSkXosI4ohO1/DbV1uIzKCtxGRlNNI5OHnPCvNLs/z2566VBdm5p9st+L8+cZ2PX+yyupswJ5u8a5iSXr7Nrcyxe6OPHMkj12cUqQz4e287zmdud/nZJ1N+Zcfxj85F3D/jeFIF3O50+PTVDfJ8gNSa17/xtdSbdaLaFDdvru8f32EqZQkWev0EdEA4VbZYOL1QoVGNqU6f5INTCUfTDp+y1dE3vrjDPnZVv5ou/SsANeOI8GGVsP1F/MF8GL+3H6mm3OEyqzF2bu50uicymEJirCPLsvLanr+PNCtKJdA8pd/ZIRt0DoHXMipcCjBVpqYYtneBsndSPo52j5YfGBDWU00dosgIgoDLbcO4ySxlS3aubVmUUCgEum+Yjiz10KCkQKuvYwMyGiVmsnzm957ncx+7gPeQ5wVCHMiDewFpnvHS2jq7/QFXr64fgCZ/tzn4yut65+d+fIMculEmllNw7188yrHXzdG90Wfn4mVMa0JEyIMTjkI4MmP33xTSM3W6zsL5OaRW+LIimrNnJMdXBI0o4tzibEnvl6C0JI4kYaiJAkUQ6v3M252jfE8yWdvJ6H64E/AIoD0Ycm0VmrWQ3W7OVnvIjZ2cWrWCEI50KBl2BOfOzzK/WMcaTxgFJdNlnPHh8HoPnWPhqVRCHnn8KB/76Crd3ZxWvUejITFFSp4NsPmQPEmZn4toNCr7sGTylI9f78MqP4ZNr7xuh/4rkzYl5RABQh0WrjgEM8cv7gKwfbmtg+XuCABOfu3OrPA+fbx8v93q8eTnrpEOLM5CvR5QqcoRQB4FY0RpJxhliYbDgk7LEESSwaAgz8qWNXjByxd3UapTZgu94Pz9U5w520ArSaAVjzywwvxMTDXSBHp8IktKp1CyzOSOqPZelv7nOCslhcQ7x2/850/x3IXVV56Xr9D4Yw+oip0Wp08vInoB0yunCObnYDiEhZBk9zoyOspge8CwiPm1J9fYKzY4GQX0hGK3PeTm73ycb3rTm/iOb/12Hv2G1/PSlae5cvE2l65e5MbNNZZPnKHZmGXlxBlq09PElSonT30rvVtXeeIzV+kwx3/91DPs9DrYqQeYrVua3R5VnfDGb/qT/Oav/Ws2RcSHP/d5vNecOX2alSlN1lxBF3vMrxynMxCcf83jeGnYbXeo1o8z1ZhlO9hgduEEXjmEgyUcgUzZufwyg702L730PFPNGrl3VKcazDZmWTl9hhOnHmRhcZ6Z6XmCUCC9oj/MWd/a4OXLF9nZ2aXrnufShS+goxqJEYjCM0iHCApkqLFuiHGOQX8Pkw7RKqDaqNPtduknKYH2gAShcNZT4ND1I+i4xvbadaphTOY8WlWwwqGVZ5C0kT7FCouOFGYwpFmtYwrPzaTFzPQ8tbCBzwyJLyiSpJRNdyPKhBIIa+n32ygdIWVAp91FBwIrBbPBHM6Bsr7MDvmRzGYGkZNIoTDSQ2RJBh3QEblxaB0RGE/XOrwKwRqUVzQddEcFmdYMkEKilEYEIcpAbjMKkzNsbyGDBgQBeEde5FjfI5iahTxns7tHtd4kDCEKagRakpohoQ6QSpKkA/rDAcJZ6kGVIiybGBdZD5srjHGo2aPU5lYQvRZZ0UMVDuUU1ttDzTnHNABrChCWEm95nFLIQNKoVFFRFeHACkclDOgNuhiT4XND4QyFDJBWoHVAIEOKPCU1DlfkhFEFKaEY7BEah9Gl4EctjP7ojMAfcpT9NMohvOBMKPlWD5dv7fCmKOC/rK3zkfW07G8hmWAold9S3hMJh0eSMuH0eg4e4pSOvc8FKrecCxWxLBtLX04yFrSmqspG12tFgQjDUlV4roofFlxMCi6ZFPeFDayf6EUjRlkMD4tSoOphGTFuOwYvdnndnkO8sE5rKqIX1hHe0R16VFbQG4xUlqyhNl1j8dRC+XC0Dt8b0NKCvnVgCjAekxo+d6XLZ9cS8J44dGwOHDuthE/d2ObpnoKwBlJzrlLlL85LktjwVKtFEUqeG3j+l7U+3awMUgyyhH/1ic9h87SkjgoIo5A4VNgiHZ/CEnT4SVDkefqZC1y+skrt/CMEYcyx4xXmGzF5HvKNUY/KZouP5JrqTH3f8fliBW5/EDB1yEn5fcfkPBi50BMA5uDD0jlp7XXZ6wxHzkq5jBtT0UcQ8SASPs5yjaK33o/qCkpnzOFLQJUWLCzOUhhDf1gwHPTot7fAWJQKD7JVHvIkw7sCjyfp9XGj/djdWKPT2tk/nhIslABLKkXpiAukPDjWA2d5gtQzqpGRlJSyd37T2zl6ZPHLvQRfY6M8tjwzIy947PB5hPLMna7jPHRbCZ+8do10vUfr4i5UNXI/6D+Kue97vuOrPIrcIA/mzL7NFweLjv9MBCCklDg5YmwoRThbijrgRg8OYSmc4TO/cYm91Zx4LsQLi1AOp6CbpNhxA2LhWZyf4vGH5qiGIaePzqNU2SdvfHspJVAj2t6rMjlHc/quuGAiXSt8Oa9vbA14+XbG7HQEUpIWjo3bXe59uMLRlRmEVDjnaUzHRJEegZLJINnhO3ASoO5DFSl49NEVnv38Du12l421LbY3tzDGcPnlm2zcWKfejHj/n3192dfq0HoYYWLPgc0/XA932F74iddlEC+sTQHNg333o/t7gpt3sLXJkzaJ6CbXOnG0d7F9B3NsPJcOLAoCGlN1Xv+mc6VoxeSTTIyu9QjATzZLHlujXi/ho791heEwxxnYuJ0yHIB3Bo8EB5/79BpSjvcPfiN6Ga0kQo5jaRNCKGLih/EdMRFcGl3fbFRq8dUaf+wBlQ2meOGG5898z19ls36K333RMrx9g4f39hDFeVZ3+kgzT2eqRm4HNCtVNvpb9FKDnJG4LOE3r17m/PKjvHX2NPdR5d77ppCRp3X7FifOn6UoDFFUxeQ5F69tMugl/M4nn2Ira7KwlVKpzBCIgN7Llzn3wMO0Oveys9Ziq9UniOeYW7mfT7/0BJs7OzzShW89+c1E8waVGWQcsXLiNGmWsNvaILE5t29eZmn2LJlxdDpbSA+xFlgsSadPbWaRoyenKUSFWnOW+fkmq5deQrmQo2dfz+zRY1SUYef2OjfXb7Czuc1ut099qkGn04FRh/ZWL8HtbGGUJqo3iapV8qzLzt4uPgyQPsB7Q+EzUIrOsA9CYK0gUjGBTEkoUB7i6jSnzr2WZmOaIIoxUUCRFyhviIOQFM8gzXEipDCGvUEfaTzdQQ9swuzsEsI5tK5CXmZc4rhKmhc4Z7CubO4LEq8rpMaQ+xRCjbEZhYW9zi6xjvBoukWGFgJjJNmgw97mGrpaR3tPIARIkLEizxK29nZROqZWq2KLlH6nhTWKxlSVJB9Sq88TiIB2v08vTdFxQFxplOfRC2RtsWy86j3pcIjSIRQ5g24PnGW4fpOi1qBWnaK6uEJYCbEyYphmDPc65C5FCUccxqhIIIhwhUGJsOTjJyn12izm9Gup9ndI2ltk9T6dbh+sRXi3b63HEUHvxk+QkdG34PKcfNBC5wn9vFR/E16QZykuN1gEoZC0OrsMe7vEYYyO4nIVOsBEMdKDTft4IzBBhiSm0+0SEr7aLfo1P4oiR3iHEorlUPDOQHB7fYdPDfp8HMdASpQqrbYX42Jmh/AW4TxLAv6Pk4s4qfiba9tsmoOH16Emvx4qznI0EPzcyWVO1ENeaKf87K1N3j81x5unZ9j2lu+58SI7WYIrslGNs+Q7zi7y2JEG//7SLk9sDPGiRHZjcQmP5fvrU/y5Wo12ntG6PCC9+RJWSfLPXeO+f/AdTL3/7WATXNHDdvt84bef5qUdD67Ai7LvXpJZvnCzQ3t3yNbmDp9ZS1hZ6PPA/WU2cphafFGKslzLJT/+lOVDZ0K+6dxRelsJmy0NQtCSEicUJ5ohJ5oxH78tyKSg5QVOKVwgcSZHSU9zbgqAKxdvcP3qLRpTDebnZkoqyMGZPHTN5hdn4UWP6e4i4irPXtiiWY1oTs/wv99oU8tzdlckp3lFbPcPPb4Y+LpLYnJ/SCGJqzHG2hK05NkhZ4mR82itLYNUxu3XZ3jvcaP6SrGPxPwECDqokympeX6/WNs6jzHj9YCSgmZVU69MMzfdwFlTOswT20lSC96QZynGFGXQ4SDlxSFnceTQyECXIqNKohQIOYZQYr9WXwpZAiklUUKipEQJT7US3/WcfX2N8lijSCNH/naaexa+ZYqFb5wlv5Yy89gs4VzAAw8eRwpHkeTYoqxxKTPXHiSHMivjTqWCg/sdyms8BlNi1ENMIhGibOngR1RNKSzVKU0YB3gvOf2me/D5KCo0zmgIX/aZk2VtshAOg+PSjR0uXutROVbD1zMGaz0W5qd56xsfRgsoRTjHoGQCJIhXwA0mFjn8cpyF9ZCmeTlvR3NZAHlhkSqgKKCdCKJQcvKeo8wsp8wvNGhM1QhCtQ8aDgD8/mU5/Bd4ZeqsPIb6VMh3/b8epbPXpt8tsyngqdVrxJGmWq9RqcWHVnhnXMSPAPGk6Z8EiZMAp3w9DpJM7ORkPdT4/9+3NuhOkPgqS+zHaMbbGtmS8fUb7XsYasLZxqF1jW3NxJHtm6LJ0WjG/MW//FqEgDQxPPPkOtaO7JUv673lWMNj9J3p2QpBcKeaZJmBtSbHFKOaSxQyiCYCSKNjHqkGplnKL/ybD/8+5+oPNv7YA6p8d5P5aI5o8Y3860sZ/ZefRYcxw/Wc9kZCoeeYqYGuD3jN6SMEKiEf3oNuTpMNegyHkni2CWnKp6+36VjIhuvUZuaQeobrl1oQRhSt2xSJI6tEtDY7HHn82zlSF2zstJjSS3hZYe7eNxMvLnJ/bQ73+ohs6gRve/O3o2TIwnsTrHVIqdioVmEuJ13Y5Z6lB6gLy8zcHINkj0de/00kwx5PfPxj3PfYm9i9dQnhJbXmDHOzM8zMn2Lx1GPMTE+jVIRDste6RS8tiKo1bm1c4eaNF0nSFBNWkIUh0AG6WiUbpGSdASoQ9JMOSXuPsFI6zNL0wApC7+hkA7q9IRVZoVKtotCESGZrs+wlAywZVdFA0EYCutqgsXwWE0fkwlELYxCSNEvIsiFZbgnjANHPyZKUsFKgOwMCLbl19TlSazgys0huIDMFnUGHalylyAyZNxSFQTqDVQGBNQgLUgS4IsF7WyofanBGMRwmZMUAhC2NoS+Lr6uNOkVOKcKhNRUVUlhHkiXEOgIckTGoIGJmeYXtzhBfZEiraLVb4FXZfyzPSY0h6adM15tYIO3v0Rn0EUpTiRX9fkFUnS7dXGuoLy6zsjhNr2fodLv00xTjSxpdmqZYDENTkGQW4wWBihj0+5h0CD7BygqDJCkV/IImsirobm7jvUIFISZPEaOmih47Uj7So9ogAaOGvyAwWuKxBPUIJUOEcdSmpwiUAuMIlGIqL/DeIU2BDmpsDjvE1hMHGqMcsVYIUeCkRArobW+T5H+UVuAPNz7/8U8ghOIH/uc/y6//lw/zOV+gTq7wA299hB8IFUJL5BhQefDOIfIcBgbhPCQp05euoiox//FbvhkTRPtNK0uTX/bx8c6DddDrc7Q/RFnDucLzIw+eBSkwWJYDxW+84wyFGMn/WguZYaY/IM5y3vrwFNmjESLUoMAoiTq7AllC59eep93P6EjPy0XOk0nO6TDgG8IAt3EDc23kGFuHK9zowenAZnQ2BogCNvZy/vbvbnB7t0vR20PnBa9b6vG5Z7Yht/R2s7IZrHXUw4A3nZrj3L1V3v66s5y80uLir19jo59zuZvzC7cVryn6DJzHiTKLbIXEmxwGQ4SQ3Pfgg/y///Zf4unnrtHa2yPUimpUZm7HKl+HR/nkllJyZGGedq+NG3RIdYA2FZx1XJpucHJhidmZ6Vc6VZOr+XIw1qTDIF750Zfi6oRRxH3330unl+CsZ/X6FexkMQuQF4Yb1zd5z3u/meWVGda2uly5ucGZE4vsbmzQ2tm9Y4cmovl3xOA9Jbjqdodcunq77OnHyDGTEuUdMtA4LQm8m3DpPPXG3Y9CynE2YgSqRkBpfrrBw/ecI44qWGOoB2FZq0XZWkAw8gelQMlSMSy1BX2TlQ1CvSdNk9/nLH5tj5VjDZAByydiZuYiAuV5cWOPt/6fb2C4bmm+I2Ll4VkUEjnK9pRnG8aZAcGoG5WXI8f8IC9bflZWVToc7tCkLCuxVEn2HRFBy+up8MgR2PJeUm967CEn/mAPxtsXeBKf0bu+wWDXc/Lt97N9cZ3+Wp/Csj8HDteQ+v3fB7kOMQE2DgME6w7uHO9K4PTy9RZp4fZFBsZJiSCMcMOcUAcICfVGzOLyFFJKpFSHM1ATWRooM4ZFYSeEI9zo3mA/yMA42KAURWEJQpieHfWZEoJqtYLAMxzm9Af5qBzOj+a/QElJFIcle2N/W4dRxuEMlTg4vvG5vAO6lKdp8u/Bd/bPzBhEilKZVSl5GDcKQRCoEpOPPnCuDJ6N4a8Z0TzHfZblPpifOI37m78bUh2/PADGUgpCWWasw2bE27/pFIcWFuOtH+y/GBmJA2pmeYzeC5JBm6S/XV4jHVGfWTqcdZtAisNkCP+Gr8r4Yw+onngpoxU/zheueRbcJR66V7IwNcW9ywXPBHCr1aN94ybnz54nZJcwH7JwfJkbGzcIfEBlfpZbl7/A0ZMnyRmgjKGyNEMQWCojw7S5dh2NIgtiOjeuUJ2pk/mUYqdFtTqN7e8Sypz52gydnU0aDcmmOEFfLmKcRBaSSlglEWWvIJVDmnna15/jtBiwcvo8YbHHckOS1Zf4zf/ySZ77wrO8423v4IG3vJe8P0SqkEotwmWOzGRs76zT2txlZ7fFcNBj0O/QKASNaIqwMUM1Luj1+7TaOySDHhUp6Qz7VCsVXG6oVuc4efYo+IwkHdId7tHudynShNRm5Mag4yozlRpOB+RFQZn0l2XDQiURgWI2mqIydYSoHrKwtEjRWyfJDd1un1sbN0mTBKckJt2jd+tFTFGQdXsEU5q+tfQ6bQhC2r023jnM1irXX3iCqDaFTTNUqHAqIAxjnLXkSYew1iwb34YhQhiGhcGZDGMcxo6MuDeE1Zh+t0tFg9NRafy8I0kNmbFUlETYHKE09UDTz4Y4UyClAmeJhCNLUlJXqtR46xgUKRUdYryg4zIK5xEGKiNKnfQhsfbIoiAvUkyWIb1g2B0wHBQMjcH5nLDSJNKaWEuGvYRaFELhcMMBg7yDFYZqrYLMczKfk2QdlK6gbEFSDAmjKkEQUhQZiPLxKSml4r0Daw1aSKxiX0UqH/aZnW5ijCCiQNU0Fo+2GdZITOaIZ6awgyHKW4ZFgc4F+d42zjni2XnMwJAWGUIJCufJ+gPUYkglav5RmoE/1Oi2d4nDCu1+gUkNP/Zd38qbHjlHHIz4fSNgVD7DRq6qpYzyjvjd7m2PgoCjI9rTmF8+/v6hMQrrC2Daw/Ihsvx4OxMEN+8RrnQy6jAO9ZdgzTqoR2Rru3QHzxDHcO8DTVY2Kvzci6t0EsPrpUYYgSwlqTBFwY225dev5Vxpwf/z7AbH45izccpO39IbZGS9Pi7JmI4DzswrPnXT8c4jMW9cmebG7ZTcayqh5E+crXAyirl5YYPNjiH3ElTAU4Ocp/s93lPTmNiVYjJe4l2ByQ33nDjNuTc9xo1bN/m/f+UT3Lq9Q2Ycc42Y1z+wQmMUBb5bcBng/ntOcvrEUa6ubjBIC6Iw4MzKPEeqFd6x2GAmDPhMe8ilYf6HT04dcozEnZ4R3BnsPrz0/mdZmvDUk0+X9EUxdqUP71wYaM6eO8rmxi12d7dIswJlLDev3EB4SxyFE9sab/juWx+/K6ckZ08dxbkD56zTHdBsVrHWcn11g6KYjGpPOioH+zj+XepEjp0gQaAUR6YaLMQ16pU6eVEwq2ImPeL96yglodYI57nVbdE1yURs/Ot7NGaraBXwzOfXscaBDDj/fUeImlWSiwOOvW66bCQ/Aj8H3bf8/nsjmMogS0E46lGVg1nkkQiMM2MVbtj/1JfiNdaT24J41ONLTqwTL2jlfSpBBSUOatbuhOQCSH3OXjpk53fXyF6oo+OMdG2XKJQ4bzDWIpScEJG4ExaO/zuYo/vvekEvLXhmtc0oaTGipkLuwSsJ4kBIQglBbSnmxAIlYJCCQCuUVryCyjZBP0OUc/3lC7e5cnEDZ8ZS234iKVM692PBikArdKQ4d36WublxnzRI0iHGGG5c71AYhRSCMFLUmxGhVoRhQByHmNzwiY9fYjjIRlnfg/N6cML9xJ8RKJNj8FA+zv0448y4FtLvx0LKe2+U3hnPodH+Ky1Hwl0gEdTqMW95xzmqtdGxeM9TT17mwgubeGepNyKqtZCNjT2EKLOrjXrE8socp04dQWtFpRqV6spMXse7GVWxfzyH35uYX+Lgbve+VCZMhynWmhG1cPz52M6Kkj1hCzxlCwwhJIem2cGJncSYX5Xxxx5Q/fvkdbhHF6jqDV634KgFinpFMD/d5FQ6oLt3k8ZsxNnlJpXakKn4OPWpaRbrGZYqNzo9zFKNo7PTGGWJlxoUKmRuqkZDBSRFiqTAGcWt9g62VjB3Yp4rF15CCcmxE9O88NTTHDuyTNSE9rVNpo7dx1O3GyS9gsI5Aq2wspyKQgoqCoLWCxwzqywvHuX4dE41H0A0zWevXMElfSIp0bFChRKTG3Y212l1tsgGGYW3FHlCWKkTxU2OzC6yupoQVGqk6ZB2e5tKtcHc3Aw+6eKzASIKWawvEsaazfVVhmmPQhe0t9aQWpInQ7pJH01JY6sFAZVYI4WgUmtgkyEmN9jcMDAOWaTM1SNOzU+Ti5BqPaR79VmG9Tprmcd4SeFBhSFFv0O6t07W38VaiykKisEAYQpcnpMmGTUdUw0DqvUKmgGuEAT1KpWgAVpAlpI4SxgEpK0NlBIEQQUhJTYdkvqcOKphjUXHMabISLp9CmOI4ipFEBIEAf3eLs24QT0Myc2A2ENuEopCIiz0em28NxghCaVnWDj2+gNEMSSuzeC8YkCOJGZAjheKIIrIsxwwyLCO9AIXh9Snpol9Tmt3g2o+TZKVSoXVelmLpo1DuozeYI8gjpieWybwijjS2DBC2AG5SzFpQkDK3q3LeOGZiSvIUJBNN0lEgSxAmhw7UlRSSKwvGxBLXxYcSzx7ey2CuErqLNO1JirtkxUFSE2eZWSDPr3eNL32gHwwoOeGKKHJB208sLF5g8wWmDzFe4sGlIpZrh4ld19FK/ZVHkoI3v2Gh/jtj/wubzm5wlseOksQKMZNB/dBjh/V8gmJlwIRl3QQPKho1EB2TL8cOU77T+47omni8Ivy9ViEYZ/qw4GDMIqElsUp4wxB+XAzScbuU6skqcFrz/W8YNWGnKpWGPZTsB7XHbK7PuRnL0ku7g64vjPg1rYgthX8pSHvOaGZmlXc6qUMi1Kq2CEppOSWqPLQmTlWFiqsr3fwYYh0js2s4Pv+6xX+59OLfEtgWdUxQyEZK8g5BENEmdFyHrvTorW1izCezGv6W5tElYjr/R0knjjSzE1ViEL1CrAx6dZPOv5CBmXBvBAMM4cPHA0teGov5VpaHAROxd1dgP2VT1yGP/SYEI44RL4RIPwkpeXgGvqJt6SUDJMhIklfGRUW4pBQxUFk9s5o+MFag0CxtDBNURiK3GKsYzjMGA5S8qJgn0R2l2M/2Hb5YS2OmJ+ZLjNVogw0aa2I4oi94YDUGKxx5MGB0pYXE46UKKPo3sN23qPAHaI/fT2Pl56/DV4zrjVSDcO933Oazk7CiUeaKOVxPj8IlDBS0BTjbJQvpbmdZ8+mzEY1rDdlxmoEbHMPN3rrLDcX0F7dAWYEW/0+YaQRZXhtdB+VdmjoDEPpiYQo7dQoc+j94butMI5WJ2dzNyG5YqnOHaH/5Cf4oW+tsjC9UPYh7FwilRGFC8mMZKcvmZoq62tjrQhUqQSoZJnxUghyY3Cu3HQ/d3SSYpQ1HUldi9I/khNgSggJoxotNQINQkzUbL1KYGL8rxCC+x9e4b4Hlw/dS/tWZDS398Hpfmxr8iqN90VwZOX4nfBof5RgIOa973+0DIJ9KZNmcqH9wMwrt3AATCeyVpORnMkM0higj2NzUtDe69NqJayt9rh5fYv5ZsDSfAMQWA8zJxfw3pc1TMDqpW2ee3Id7wXvfv/DLB1t3tGHzN/1PBy2Zr8fwAIhPEEUoL06ZAAO6rsOHyKe0Rx4tdP41fVD/tgDKm/3GGQBay+/gLs+5NjCHEeOGrJBB1sUnJiqIKagYofcd+pRVFhmKhaOniPPB9S31zkxP0/iI5QOERKq1RlOLi2gpcA6x8m5aVZ3d2lMBQxmqtjCcv/Zk2Asda140+sepBFFxFGF1509ws7AsfWZayQmAjxSlClXIzUqCnGR45HpFo+ePMK9x4+zvLJCEJwiKSwDMvZ25njp4jwPPHwWH3me/NRLFFYzFIra1ByVuMagtYNzntxkdDop9bBZ1hyFIXMVjVcRg+4euemzsDxLpTZLniR0tjfRQcjG7k2m8ybdfhtvyxoMhSJSIYV31OoNGpUaYRCRWoNPE1JdMF2r0dACl4acXJnmG+49weVWQlcqCtdFFhI5tYyXNXJbEIY16vNHMUfPsPripwk721hnSPME5UCLAKUKhkkH72tUi5zhzjaimlHJDX3TAmHQorwWeZEhi4xIKdKghg5ClLMoqSnyFFNkZEkHrSXCOepS4F1O2uvQHSYURYGq9DE6IPUJMi/VroSSOEo1rCiKmas38UphBglHmhWS1FFI8EWKFw6bbmJN2WBwiEE4cG6I1DG1+iwyC9nr7hFVqoTVGs35JrHXOAu9foep0LCwNAdC0OlXSZ2gUqtQFBlF2sW5iJlqxHy1iWeGzGUcnanT7/Xo9TsMRI7GwIjiF4Rl9gokxnu08KN+Qx6hFDJQZEmfre0tpBa4PEcUFiHBhRW0K7CuoEhSimJAnvYosj4i0AhbSun6IsVbj1IhSnriMMYbx7B9mzDt/hFbgj/4qAYBf/09j/PDN2/w0NQswVBC4UeRS49XDlT5IPbCMa6a9TiEd0wE3Q4SBpNO9ahmT9z5AMSVV+gAMR0SGCm/f7AehMT70gEd13LZvGDw4lUu/PqTdBNLMmV497TFDSW9oqBnDS1ryZ+4QXOYk6ZzfHrVkBdlzUUgBI+dO0Iy6PPcxU2M1ARK4eIaYn6a2vE5ekpxarrC0uw033b+CKv9TS72CqyDXQMX4hqPiJST/T5TPmZ7tG/ews1ehozA5zkuzZg6cZza3BRFd0i4u875Y0epVmJCrQgCTS0OCHSpbCm482QcjEGas7rVJiksXkiMg71eTpoJVgc7WG+ZbsYEwZgCcxe3625Rzrtkn1513HHNnXN4Z8tWAqOs8CsyPGJilfuI6OAai7EIhYCDUvAxMD/YqOeO777azo2HAGs9SZrjrKNerZSCNkOoVWNyoxkO70K523c4R4CqErMyPztBzxk7P55hkZLZUva5X4wPw+OUHUXWS3BdAohSLZbRaybvja/TMdEZB+8F8WxE1rDstHcIRYdep3QEnYACi8ktEoOuSJClKItDMthIqVYjvFbYJMd5i1cSKzWD7Yw4DLkZlfW5iFJcyDkwhUBmmrCi2Mkt4MvPEOAU6Zbn6NIMt/NNcCVpEKERTpN1UxrTdZRTdK95dq4PufKJm6hihkgJzt8D73q8QhRIwODdHs6BNYJPPN/mCxfafOg958idxliNKSR9pzBW0h54djow6KfU6/GI3ixHQjNjEmMZqJoMm0jEiIYmJgIRhwMUh8ar+NJKqbJemDuCE6/2pdF96yeMwZjad7dx0ENstO8TjYMPPP87jc0rMz2HTY+4c3Ems337z5k775uJzbV2emys9xgOM9a3enR6BVrBfWfqrCzWiEPF5Jf3A4jec3ypAt6xttFjY22bRiOkWo8oZWTuctZGpuiV+/7qAGdcq1X2HVN3fvoqJvgOA32Xy/lq1+krMb7igMpayz/8h/+Qf/tv/y0bGxssLy/zXd/1XfzwD//wQaTJe/7BP/gH/PzP/zztdpu3vOUt/PRP/zT33HPP/nparRY/8AM/wH/+z/8ZKSV/5s/8GX7iJ36Cer3+Ze3PyeOP8/rja1S6izSqNV77wHkWT5xDB3p/X4xJ2Nt8GZPukBRVavVpQBPFsyyvTJWcUu/JioytXofZeoNwFAlWSjBTbVAJK9xzxJNlKV+4+jKfXd1muhLTWr/NiZlZHrh3hVgrUud4am2L+lKT0ApcnhBqi3GgtWax7nj3fTEPLT9GKB0mS4jqcyhf0tVec+8b+PxaxKm3n+f6jS0GeZ/7H3s9e1s9bt1eIxvuIRWEtVLtJpACcCR2QG+4TSNcogBc0ibNBvSGXXbbWyh5E+McmcnxSUaRpXSSnMwZwiAgrNbwaUJzepagWiWuNOh1Www6e3STAXOVCt57Wr09jlUV73v9MvctT6F1jFKOF3uSrhUQBOSufAgEQmPzIQaFL3Lq03P0mk0CGaCCkEAIvFRULRSuQMVNTOCR1YCgprH5AGty4koVLSRxJSBKQdRCICQSox4XWiMDiSlyQuVJigKPIxSCWhhRGIsSgiDSiGpMoEHYnMUgptFoIlVpMNPcoqSgMJZ2r0fiLZnXBDhCqcmSDsZ6tA5Ba7R0RCrCKY0SMSJcIh81zPTeUo0kKhAo5bEmY9Dv0u8NEFpAkZF2WhRClVnLoAKFJZABInQYYSm6HfrCo0NN6i15keNcSlUWREFZn+ADhRIGZwVOawIJaiS5KgGHI5AhUqlSWl2Byxw90y+LQgNNkAkyazC2wBhLmueoUBDIBqEMKRjinSEMY5QQeCcIKCPbudJYHJ297a9bG2Kc5Wd/9ePc3uvxwPIiDDK8lvtO7diIm3RI3l5DSYHv+xLcODfyd8V+Ib4f0/VGzuKgcIRxSKUeIazHp6Z07wX4kcyZZ0RzUQKvFEU3gaIULxBSoGoB3nsGw5zpWkSRG4JaBFqxt9ahPZLB/qZvPUlzJeDqy9usF5bMei5kBTPPrHHqfIW3nSl4rqXZakNrkOOt4bnLO/zF+6Z435kKqYj4vd2cl4Wi78B2M3r1mOdv7eHSnNA4eklKkhiMs3gEQym4GtX487e2+E3r+E1VgaLA9odcu9BHYPC7O4idXXa2btOSkqlaHRvGXLI3mZqZZX6mSbUaEwXBhBjF3T1sj8BaT6QVUa2CdwJvHTOBInIZS9aAUPQQB3jmSyrqfsWGRuPVvzfpjjz51FO8+OLzvPtd7+bo0aOHvje5hkO+xp2HOOkv7mduJgQgxiBsX+L44It39r65c6VxJSSuHFB/vIO9Th/rHNpahsP0YIUTzqvYX0uZQShrAsUrtmiNLTO3ft/DRAASiVSl2pwUCinFvghecSib9+WNrzU7gh8fV7ntoBJy7VcvkQ1zzFIdbcGrUQP3oaF5MkBIw+bTXUxh8LoMqsTTipW3N1m9mHLj87uYIsfbMs/TqGrOfOM02Sq89OEWqgo+lLjcIVPJ+bcfQU9LrvzuFlmR4CNQQuITxcrj8wRxg9VP77J1qTtqBAvKBCzeM8vRc/OoPKJ3tc76cztc+IXrvOYd55mhw8PHPcMkoyh02U9q1BB3p1fwqed3eON9NU5OJ+V5H9EJSwdd8JkXOvzWZzvMTis++KdO4b2gsILcQG7L18YJrICbewUvr3lOnzg+EUMog1jCjTKdSu5b5fEtdHBrH25DIO74e6f3PZnYHQcGDu5LsW+n7xy/HyabBG53AqdXfOkQGDk4jsNg6/DdIcbvTeIp72nt9EmGBmsszz+3yvqtFnFF8obHjlKJq6OG6GWWeH8z++s8+CfUErzk5JEmnWHO1uoOJ+45ig4mirHG+/GKk/yljztrBO+6zMRrP2kovnq46VXHVxxQ/ZN/8k/46Z/+aX7hF36BBx98kCeeeILv/u7vZmpqir/xN/4GAP/0n/5TfvInf5Jf+IVf4PTp0/zIj/wI73nPe7hw4QJxXHLjv+M7voP19XU+8pGPUBQF3/3d3833fu/38ku/9Etf1v4sVPdor96i4wNWlht84cVrPK4q1GZjBBoVRBCEhDMnSXJb0hGGBVXlieNSvUur8tFQIJiqCwrn6KUFQVAWxCmpCLTCefAy5OSpB+hUjlD1luu9nOXZOnOzs2it2dvucjOvsbTQZNsYKrHEeUEIVLTgoQXP+x+vECgxUlQqwCVsb6/zzIvX+MTtGlv5Ud585CVkZZndYoHdgWTxrGXx9FnSQYZWjqS9zsbGbQJXUIsUQxFzbW2Xbqsg7ycMkz7tfAhKkaUJrshxvkyhZ8ZRiWKcUNSdJoxrLM0vEasQVa8ipaJvoD9cx3ZaxFrSTiyRlCw0qrxmeZr3P3ycxRnJ7e2Mj3WHbPYFaVhDmSHCamTcwIlSzQkPxhcMuy2krhKEEikDCjzCS6SySBmCFIg0I+/20LqB0hppU2SeM7QZ+VDSDAJS4xj02ygpCQX4qEo1ijHOYtIUmyQ4DYXL6eQJwkkCBFp7nFNESjAoUk41m8SBQIqQzUGX0Bvaw4LEWpwUiFqdQtbZ2V4FZ/HCMTCeOCgjKk6FCMoagizPyfqdMoUdhPggQjiJGQ5Q3rMQWAa7XfqDIak3SAHZoEpmcpTyqCgqsx1InBXoWNLQmiCQZEOLFgU+z/A2pZ30EIFG6QgdVCicw46VoVxpzJ2izFw5jxeSAiiGGdp38N4RRCGokCzJKMQAEUicE3gyFFDkKWGlhjdDLA4tNVIpbGGxWYH1FutycmNxPsLypfeR+VqzIRXnGF65xZ9tzHLMOIqNHfyIRoYvMzlCObxeA79G3nJ0nkjLKOtISt0IyXQ9IhjVrBkLQimM9ewVFu1gCkliPC1nmVUaJXRZWu4cpY9aRumcFGXNlLPgBTLURIs1pHXYzNCLQ6T15XJC8Llnr1E4z2ytQv2h06Sz8/x7/htd6XjksVnOPnaEpSii8cYpPviOJd7zIUl7UPCZpxLiWJPnjqZwfNqkSFXwV761RkHM//c/rnJrU/JrWz3Wj1gWHqizM7AMc4+ZoKcMheSFSshHZpts9DSaADtow9oaD3zjN1OLQ7TpMby1yvve/lo+8cSLnD19Co3nxUurzEyH3HNmljAIDmcr7haVpsQSzWpELdL0ewXWCkxhOO8T3lbN2VYz7MiQS0pgJr/t/X5m7/AKeaU3/+V49750dzrdLusbmwyHfcY1dCVFdNI9uhMITWSbPHgxQaXxMEwSXrjwcile4wzOee695xwrK8tMOo8H+bdX7riYeNtT9hlLkoKssLTafTa2WvuF+q+M4B+cokoYMFdrEGld1lT4UkSoLM2zKKnwTuCsY9wfSwjJ0akmtUqMDBSLMmRKlH3+rg7aXEraX8aJPjy+1uzIQdawDLLMrUR0/397dLZ7DMI5XCZGHwnqZzzhn49pX0p58p/fxGR9tI5QlRrLb68yv1Sh8/khF35yE5zCjyQoznxjgxPnp2lfTbj8f25g8xHI8IJ4TnJsvkZUCbj6L7bo3U5B+JJCF0hqPxxSL+Dyv9zg5u+1wPtSuEl4Hv2elFN12N6O2Pi8pr9ZYLMcu7uDdIbXPmDJi6L0WaxCSY8Ugts7KY+da/DmBxo4ZxAjyq8Y0fdy49jY6PDn39FkuhGy2CjK/ZkEM6JsJH1zs8uFjS0aqeKDZxTWS4xTWCcxo5/UCD53I6eoTtNo1HC+1DZ8BXQaoaxxlvQg13twfx1Q5yYu4AS4EYfuW5hU5BxT2w5vdRIkjWfDF8/QHJ47kx9ObPsQnffwksaUNsE7z3NfuMmFL9wmCiTTzYB6pHjT44toJZibClHyYG+Ev2OLh+IogkoY0KhFTDerHFlqkhvP56/sUp2d2a/RGgddxnbtD5pg/v1x0YEBu8vj4H/o+IoDqk996lN84AMf4P3vfz8Ap06d4t/9u3/H5z73OaCcpP/8n/9zfviHf5gPfOADAPzrf/2vWVpa4ld/9Vf50Ic+xIsvvsiHP/xhPv/5z/P4448D8FM/9VO8733v45/9s3/G8vLyl75D3Ut8/sILnD1xiucvtdneLTuPqxoEukZzfpZcV9kZDEiynGcvbnNk6RSveSBipt6gEQqqgcRYQ7vXI/A5VzfanF6cR2pDq2dYma7SSjOEjFFKsp5kVETMLQFJEJILx+WtLaoC/s0nU57tz9PO9xAI6jKk8KUufk0rzgUW6zS5txSZQWDBDNkbJNzuZjx5pcbrFy5xbGmeorrAjecvc3vV8dbHH+TWWp/BQPH2Nz9Af2eeBx54G3/i9StMzUSk/RbXb91gfWuNazdu8ukv3GBjY5PObouelaBDnDWkmWW6EtOo1YnCCnONaUSlipAOKwKkUPQHCa3WNr5ICOoVpBaEhFS0ZqEWc2JmEVyEEIq+zZltVFgWIddNBSEjbJrjxJAoDiiKhKBw6LxPYFMqsUYREgaSQnq8LwFExYtSfa8WU6lWyLMeohAI6+grWzpNPqeXZzhviITDWJBa0evv4dMAZQu8gEAJpLCARlTqxBKaQUBVlMW0tUDTTUDYjEJokiIlyXOGI4dLa1BYomaToDpD0llHGc8QyZQOMICxDu9TnBX4vkQHIV6WDwbrDEHh6ecp3kNFK4TPGQza5MmQ/t5tAhUQTS9SqTcQQmCzIdKXD7cwCBHG0OkkVCth2Q8sG5I5X563JMPbAqE9CpAqwkuJ0gFBEKJlqeQnJERCEFYUlbjCkaUlGvUK3V7KXrfPMMuQhSXFElqNLwpy78kcYAtEkuBwWFtSdkgCAg85FiUClA6oVmLqU9OY/Es3p19rNqQiYT1L+Z7mPPq5G1x+8VYJ7sWBAa+fMCz/OUPg4OY1xX/77ymJlFzvDuhkeSmJbUuDKyQYLzCy5Kd3hOe20gRIvFfEAXxLKCkc5MIzp+CdczVSJ/h3a7u0C0+ExHhHX8J6ENLdisuqbWupesH3uICTUhEIwY3dHu9emOPUdI1gvcpHnrjNL164wvd96B7+13/4BqLpGbyPEdIjlScQnqb0HD8zyoJ4wFucLWscnPMY5/jUhT3Mc55e5vG+j0wUNekRWPyI5yKlILWe1Qx+Ipplx1pC48h8gU/6VDqbNIMGzYrkyfYOH/nYJ1m93eLqrW1CHVCrViiA4Uu3iaOIMNDEkWZlqVlmAu+WWBIHSSdbWOppyqO9TU7FlpnCMiU6tGpzmNoCZZ52Er18KZmqu3FovsgYO2FjB0OWEfTJPlN3o6H4O/4pM1BlPc1wkPDc8xfodAY8f/Ea1o8aFQlJLxHc3uphncNah3MOrRSve8059JjiOP51ByPIGMva7W2StMB5T56XDIUszw9FqO82tNJUggitNM1KhTDU3N7ZLTOV3iFFiFIar9Qh96qbF4hAU1GCji/oC0NhHbeLIZPO0pc7vtbsSFxMQoJ2AADv60lEQVQJECicc6SpIc8tw3ZO/1pBEu7hcOVzyXvUfIxorZCvOqSoIeSIVoxC2QC7C+muRYU1nC0l7AWCaqOC2w0Z3MiJwwpWlsqdzkOgA5qiishA+gAV2JEEusAJQSUNiToxfqAQMiIMy2ySKTzDdejtOPYuWUw7wQ8KvDH09jr0sFy81ae5lxIpSaAUSik8iudvJMw1Ilq9BCkloS6VX5VSZLlldWOA0pbX39coXW/n8MIfgiLOerLc8d+f3eLMfIPl8yH1KMX7kUpkCW/wSFb3DE8/c5U/941LPHB0pgRaXlJYSe4kuRMMckUuKuwVMbtdR1wJ8ELjkfv35FgQxPsJGY1R4nc/qLC/7ERr8H3gcbfM1ZeaOhkBucOptcPf37cn/uCzyWw7ZYb2t/7LC/Q6GUFgcU5Sq1U5vhxw/lSzLMkdB1Imd35/jEGhQEiIwxCpJPVqxOJsg7mZUjW1PzTc3hry3LNrPPrmOtVKNIky94/3i93Jd56RL/WO3z/vX9IavvpI6ysOqN785jfzcz/3c1y8eJHz58/z7LPP8olPfIIf//EfB+DatWtsbGzwrne9a/87U1NTvPGNb+TTn/40H/rQh/j0pz/N9PT0vgEDeNe73oWUks9+9rN827d925e8P6a/TpYPCMhpt/bodiyXb1fYbm0g1DT3PnCC9bYBJD6S3Fzr0IinefZGheo8rNQ8uQy42ktZtC0WXZ+nn3mJ7N5zYHtc3yh47NwRLqxtUDtyP+cXQtY2bmCTJhdVhRXbQdck3Qw+c3vIk88ZbpkeTmRoL8mCGOkMQgR0/JCP3Vjnzz7+TlRQ0G13aUQjpTZTsLZ6k1tX1znnenQap1kItqmpguWVaW6vvUBQZBytLdK/9Rzbu12OLJ6lGRxlJq4gmmc4fuwsQih6gzZLn3iZpy4NCCoCHVi6WzukrV3yokNWJFRdQWEy0l6PbqdLpzsgTROEKptqhloRTE0jA4UkQDjHdDXi3lPznD4xTRBHrPUsL257VGUKNzBMCYePAoyukUcVQKJ9Xjbt1DG1qXkiHTB0GaEOcSgCqSicQwsQXgExCIVUakQv8aUEuBIETqPcKJtlHZABqgQsoUIUlkoQlIDKl8owUgYUUmKVpBHF9LKUvsmZiQLSzLBTWJSGUFcwpgAn8UrijaU5O0OeG4hqZL4gHAnrSAxOCEIVQaDIvcBrQdWVRIRClLUxSkYoYQmV5OTKLKs7PYoixzmPlQJvM6aqc5iRDC5IgiAkywqUFtTCAOFLKftCeUzWQaqIoFLDqZhqw5SA1HgIACRhoKkGFcIgQsuCuKK598wyRxbmOH/2OHEUsNVNuLHW4sqNDTZ2u/QKhwKCEVVwaApskQMCR9kTRwqPdo7Ce2qBwooIiSMKFPXmNLb40p2irzUb8jebc3wyG7JVWI5kFlVYSg7/gUpWul4gPwuBLHhpVfCZXoHXkp0kQ8kc4RQNK7lvVoGCJ7cMOzl0RcBWpYaPZnjg/jNMV0PeN/8SYrXNL32uQy2QvG4p4Pj75imE5Mi/avHMdo++kAwF7CIpTq8we+5USdcYJGTPv8xWZoiVQSq4bQpWhzkWz9wvfp6dpIPWgne8oUkkC0gHoC04sAV4a0oRDcoHrRcKpENgURKU9Ggs/9vfPM4w8SSJp0gsYV/S3jb8qWbEet+RJAVPXNNsdYb4QYFl5EzpUqpXRp6bl19i/UbJBDi+coxGtc7RI6dGkfFSpj8MozLTqxVSqlLmd3xxJhyaO4fyjsgZptKMe/MOzVCSmgAdCYqR8+SFn3zmv3KMPhvz+b8c5/6gz8xEVNx70jRnOBhSrVYRd8uITW57/2UpZfz0sy8w6A/ICssLL17F6wpi6VGUDIAS5F/tO65eSsB5RBCADqj5hFMnE6JA0qxHJTNgYgNFbrDWkeWWre09sqzAA3ElZmZmms3tbbw7OE9jOt9kBF4A1WpEFGiE9IDDOofSIarUSmZfm8YfOKz9NCUzBZVQgxQ4UcqmF+O2DuLVqVVfbHyt2ZF/8kOPQRBwY63HT/zM87SvtRFYTrxtpaTd+fKcee+Ja5ZiK6darXHvW0O8LzV0hRRE05beDUNYneXcN8T7tXkA1WlF3hpSrUxx8k16pCTnEN6jIkF/K8FKyZFHj2IGHoTbP63ZnuLWjYTGqXnONmbLLOqol099vkrrhiLd1mWrBuPBejrbHUSa87krCZVQoSRoJXDGI71jve25/1hMSBe1L0QhkQiS1HFr2xBUIooiBV/WzyklcQ7StGwZ0BsU9IYFgfC89YEmSstREG88IeVIqEdSDwuWpmCm6mgE+SG7MNYP8gi2uy0+96kNdjsDvueD9+GEInOK3EkMksIpch+SFIpWEpEUUIk0qGBk+Ufo6lCOa//fUcBkTO0+mAP7WegRD87vZ6q+yHiFybkj2zzaFWMMQghuXt8iGaY4Zwl0yvSc5MhsjfmpCIQg0KPKtMm6yzvQzjgDJ0a94GrVkHtOLxCHZbA7HRZsbrbZ3Oux0/EYL1henkZrecgu3AmnJjN1B8LsB59Pbv/3B1+vyPt9kTWIiQW/esDqKw6ofuiHfohut8t9992HUgprLT/6oz/Kd3zHdwCwsbEBwNLS0qHvLS0t7X+2sbHB4uLhruhaa2ZnZ/eXuXNkWUaWZfv/d7tlEXxuUtrdAXmW41yfjZ2E+cVFbt7awnvD0vIcTz13lWZ9niOnGmzvdtha7FNsrfNgLEklfLxbYdjLaAQ91rMNbl+7zomlOnvdLVprsDkjuHDpMvfqY6zrgKoU+EpOZpoUFrJswGZueb4NG60djAlxNsdLATrAFgavFBkDMneNLHsjJh1wc2ODhh1SeIVThuu3dkjzea7euMmJuTra9uh3c2q1Bpu3bjA/M8XUnODa2m2Mc8xHjuefe4IwDqjMnOT4tCLNMzb7jgV3g3x1g2OveZTt21dYv53zmkcf5/b6FrGF42dP4NIh3cGQMLIkgx3arV2S/i7KdImUJ/ceWRiGScqgP4DCsTUQ9PMKLqxRB86crPDCxgA9yKh7hZEVBjKmIgOsAOVDlBL4PMNFM5ggIDAWKaGCBKUQKiZSiiTtlRTMQBKqEKNUqaKHxHlJ6j1VafHOk3mD8jEai/Iar0rOujAerSUShZYe6z0VPJmz7FqBFwFOh+wJhVKWircIDM4JQlVhiCcWglQ5ms0KG+ttZmpz6LplmBWkAiyS0FqEyQmlxkuIhcI6g3ACr0CrAONsqbQUCkQUUWvWyQuDVpJYa1QUg66jhEB4SyBLWqKUAWkqyEKF8oZASJSsEasI6QQFjrDqWagvMjWbUHhHqCS5GWCdI1Yx05WQowsxizMN5poxr7n/DJVawOLcHKubLWYb0ygVU611SHNLkhuGSYHFETmFlZYCgfKO3IwK7V2OQ1HTAVbEWG+JZAn4nPjSKX9fazak6TzKGl7u5QwziIQkEKW4pBo9U4tWwnsXBgR1w8efDfmvLYd1Q+6dTvmR92h2Tcjgacmff/MUairkX/xqm42rhmek44WpU9x3Yo6f/4n/hWbds/dLf5PPXBkQFAVvqwf85aUYWRXosM6Uha6DF6tN8uYxvEn5vj/5Hv7Xv/fXsM6xc2uNv/uBv8yvtDpASaW97YZ8PE05oxX/YHkBsIRaUvEFnWvbeNEmqFZHvbQ8QcWC1kDZld7LStnXSoMY1Y4JPHEgiEOFbwoEGuE9y0j+t3fEOO9JMsevfTLjdsfRzQv6uaSfQzcRrPuj6KMzPLB0lGoYjgrgPThPno062Y+Us5RUKFXK/SopicNgn65z4AscZJZEeeBo42k2I1wt4L/bOlII8kCT6YBCjZ2ww3jqrgXL/tUf7ocW2h931F6MPnXe47zjt37rt2nUp/j2v/jnqNWqh/cbxgrIFKYkJHa6PT7zmafwCK7d2qYIpkGFMH0WdAy6wrhg34tR8MU5hHDImXlUc5be1Zf45d/4Apqcv/DBx5mdqu1v0HvP9vYeaZqX1LAwRkmN9568sGzv7I4i4mJ8WUr6sDwQnRBAoEd9ZQKNVKWAz3jZcYjfA6EMCJVGCOj2euSmwArBjJ4hVMF+0X6fgp7L/sDuz9eaHZmb0ry4us2LL7VKAZBblmghZOWxk0xNlWIMTpbCM8b0kHlGY7bBkZPjukuPkB5jMpy1iLkGi8fVPm0UAFXg3YCZI01mFkYwd4xFhcElXQySk2+ujSTNy2sotSdJ+mTJkOVHVgiCsAS9wiOUxwbAwONuDfH4stee9WgtcEIRBJ5KxZbBSil4ebVAWEt7EHB5Azp9TxQ6Ql2yQxSeJHWsbWfMTCU8c9GgyyJTQq3Bl/2hnINnrqcsNTVJBsNsgLZ6vxeSFIKssHSTnL2eBSc4uyhYbAicKUoVwPHwBznWdJiys77Ln37XCkcbFoQ5dM+ObUJq4F/95iqXd3P+9p++B6kjchuSOk3qAnKrybymcJpuCsPckhnHVLO+P+cngw53vjpY4lWy3v7gxaF4jjgIYvT7BW9780N87Pee5td/40m0y6hVAk6uNHjo7DSBLnv2TfaGu3OI/V/lH601i4szzE5XqUaaaqRRStLpDrl6s83OXp+8MLgyQkYgBWaQ88SnLvKGt943upZ33codx/1qn7+6xfV3/e7dtwD72PV/yPiKA6pf/uVf5hd/8Rf5pV/6JR588EGeeeYZfvAHf5Dl5WW+8zu/8yu9uf3xYz/2Y/yjf/SPXvF+p90nHTh2kxwz7NBqFwyGlq29HkbG3NzrcGt1i6UFRdCQJN0hw1afdr/F7+0mPLjS5PpuSYVozw956ekn2NvscWP1FpdeeplauMTzz3W5dXWX+eU9nr18mzfcc5LZeU9/UNDKEjZ6Cdd7Betd6JqU3BcoZ/Fegc9R1iG8RpqU7d5tfudjn0BoA4WlrmBgJe3BgBtbCcoI2q1NdrdnqVNQ7OyRDxKy7ip908H7jKTdI7eazVvXqPcNrZ6gPp9TLMOFtQE9H3Oq3qVWlSR7t4jMNrGrkLWu0bp6ARkuMTPtePHZLxDXVnjDN97H51Z3mG2e47v/wrdhkHzD2UXwhizL6A663Fhf59mXL7K20eamh6KjOD6luJ0O2XYKHRcUVuJkRKwkUoY4DLmljJoEEWKqSZFqlHE4LEaBsZ44VGWEf2YRRARRA68EIRInNSXX2xP7svA/LyzK21JJScZYHFI4oEBpRyOWNILSECsBzgsqRQrGkniBlSGBUkRSIBwUzuOcwbgykymRhAHEQUw11vQrOcYqvAiIPETe43RBJhV4T1VIclF64FIERKVWOVqW6k2BFhRGAgFhGBEKgbceUxhCqdGVEGvystFmqHBALUiJZYD3EUNjUdIQjXpMBUDgCgolCSsK6z2NKKaw9ZEanWZxtsa543UC4SnSlK29Ho8dOUugY04sLFCtZmSFB6FY2+piREwoBR6DkJrMFigh0U7S1I7CBwjvMBQoHZaCK94SATKoYE32invz1cbXmg25kgxZdRk3bItnszK6OtYcEnikg2bgeG81Qs4KPtftkmYe61NaSUo/rROHnitpwKee73HyhOSBI47VTUuWWnCKIskQ29cIMoXrFXQSz8A6nuhYsgs9HkmGxIFib5AwHwpyZzBCl4EBHBWTkuxtUmy8RCfPaRtL4T0WR4qkITVHRcjsgqSWguyCSSydm11wnlAHjGt9qrMKoRUmVQRhgPc90BDEBbIZIWJdCj0AMowIZ6dKp00JEBIlSk2mIJT8T3+iyii/Uv72jsJ6NnerdPaq5ImlyHIGfU+WC/p9ydNfSNjaVfuORkmxKZUTpRQszjaJlZqosRj92c8IgRVgR+pQQkNfRIzdx7EC3Xjhww7Gq9FyXp1CIoQ/7IyNFRXuXHKElLLMoFUyAoyTmSJBXhQYa7HG8zu/83F22z0KY+n0C4QMIJ6FuXsPS6uLUezXQzQ1hW5MjbI/FsIQlEY258iRuDjk0tVVTq4ssLQ4y5gutXRknnET0yTJsMbhnGdnr8PGVmtUHF5ei6W5JkeXFka1Luxn3oQQWAW5Lylm3oMOwkMnWACBKkGxAPqAdB4lJSu1WepxZZ9mup716CfZ/je/WL3J3cbXmh2xxrKzO+DW2hBvS/q3M4J0YLHpcJSVBZSnsqKgWaO9npEPzKhCyhNGirnFBlrA3nZSUqlHgElIaC7UCOJpeq2EdGjw+6qQnnozoFafJuvm9HeTiWnniac1cbOKtxH9bQs+KYGa9BALwuWQQhbkziCFKue4FQiliKsVtjqSzgD0qDFzP8nopznOSaJGhq9CIQS5F2zuQqenQcLujmapKNBXDYEuqIZlFktLjx7Vmr68npK7gGEuefraKlpptCozWVop8kzS7lmurg9pxgHVWgWNIxtRrcdZYOc9rc6QtHC8uGZ46HjI0bmoDHTekSkuAYYgTTICkfKGUxErjQIpDILhCJyVNfTeC6yT/N6LO/zuZ1Z50+vOcs+xFVIjKVxA4TWFDTBe4tB4FIUTOFdS6ZQUjAsZ/SHv/7DNOaTUDmys77F2c4s4qvBd3/4eXn7hCjJPmW5WqVY0tWqIlopA322dkxmjcoShYmaqhpCKqWaV5aVZQiUYJikbW222d/vs9YYYMwp+CfAOdnb7dHs5292Ecw+cLmuoxKuDni9lfImi8l98iEN/vgxuwR98fMUB1d/5O3+HH/qhH+JDH/oQAA8//DA3btzgx37sx/jO7/xOjhw5AsDm5uZI6Yj9/x999FEAjhw5wtbW1qH1GmNotVr7379z/L2/9/f4W3/rb+3/3+12OX78OJdWN9nd22KvvUi/3aaz59hp7dLebYF29Fqz9PZ2qKga0Yyk3d7GDefIOwNyO6AfHMW0+tjU0Qoinn/hIku1Jpvbt7h2dZXlExE3n9tle8dy7+sS9upNPteF+7Sj3UsRieGmNdxKJNlggBagbZmdSZWmoCAS4H0pU9pvb/GLv/IrzE1NE0SKbNhlYf4UraSgn0p6JifuZ7T2Wmzutui2YXpasdfapd9LmcpyNAnpQHI92WX2dJUbty361nVqwzrP3wyJMeg5Q14s0F69hJIZ88059m5fRmQpc8em2bl1kSTZ5eTZe1i/foHO7ducXnwtN3Zuk3QDHlpeYnG6Rq1aZ2FmnnPHz7B84iyfuLjL9taQ59a7XBIxs8uSrNKnYnMkCQxTTGaIUOQ2Z1YaBkYgvCNPPXEkKIZ9tKpghEKFMXlWEIQBQaAxLsTpCBlqQhkyxBJ7hQVwAisMWpVlqFgDQYAoHM47qjoGUSDigBQP0tH3Fm8FyArEjprXOOFwVuKkBe9Kw2ctYZ5jhSDUpcMYxlWCMCYMwReSILSkxpNLCE2AiiTOOaIgpiICjHJ4m6McpBJqWtDQIcszhgdPSBYqFaLaMsVbjpEMU7ZaLaSwJC6jlwcUIsQ6TwAIFeJxCCVpeI81lr514ARRTeC8gSTFyYC68TglCV2AUIJavYEIPO2BolaLOHvuJMeP1lGVKYyUFNbS61mM08w254gqM9zY6eMHeSmxi0RrSuVALwmFJUThnMUJME7i0x5GBARhhFKKvLxCX5c25D+lHXakZ0A6op0ekBbEiDoxLxX51DQyNpwRqhQ9EXUGRZ+f/R2HEEOOG8k7TsacWBHcvDFgtRiy4Qt050k2+4IP/9CnefupWZ5c3eX6umHaGmquQNQlD90flP1nXlYsiRyV7uC2+njn+a//YZPa0x/lu87tooshR3uKB4ppwGOwXJM93iiqLAiBqplRk1ZBqzckTcvahvlalVqgQQiGWVk/g9UEocQaT6UaEjfA94qS5isBWbZ8sO0SHIT1EKEVKIkIZUmzlQKh5bipPUpAoOHUkkMsAj4va7+8Ai/Bex55MOLaTVM24jYeU5R1HP2hZ22jpPt4J8eclH0A45wjzy1RIDC27JXlRyDGM8qwjHwXj0Drst5DiN/vUXu32oLRq7tGYcdUoDuW9yC8IpCa40enqYQa5yzDNKUSxzjr+ejvfpKrN3cAyWCYQX0RWZlG1jSgIIghrh2sbwSIgrgExDKqoqK43AMhcBLwgnDlFGJqEdPe4mMf/ySve805FhfnGcfs5ejcOFeep15/iLWlqunRxenyPIpSprpRqxKHAbZceelbCYESJXVzmBb7zpSUaj+y7kaS/okxpKaksBGHRHGIEJIL/c0SYY1BovzyaX6T42vNjlgLvV5Bnrl9AIwog2BlO4QRjVIATuCswBqPtW6fOlayxssMqDPgjD+Q5ZYCnEBYgTMCZ0q/grHwiS0/x5b+sHdjyphAuFKwyDvwdmKdjjI6MXrfuQmFPqewVuC8IMtibCFGrfIEkaoQ1Eqa6u6eZa/jUNISSE9/aOn2SnqgMZJOX3L9dkghUqq10fEhUXjywrHRKmuhhYSXblu0cCjl0aoEcNZohonkZqugWXXUBoZnL/tRk99ybktR9jbrdlM6Q8vTtyzvOgfPXrjOw/fMl6IoQo5EM8rgQF44Ll7a4sSc4t2vW8Rbix0D+9GcLwM0Ho/Cm5R3PTbF+95QQclS1MN7gfPg/IF4xk7f8jP/6QrHlmqcOXeChcU5jFPkRtJLHVsdw/xsA8dEc15fBorz3KBEmf29cW2N1tY2959fxiRdqoHj4fPzgEQpiAKBlK5UXJy4kUb4ej/jHwSKKFBMTdU4c/oIOtTkScHmxi6tvR7dfkKalj3BnAfrHP1hQW+QY6zjU5+5SZLC428+x7nzR8pz+IcCU1+B8T8wKzU5vuKAajgcTnRNLodSZSEmwOnTpzly5Agf/ehH941Wt9vls5/9LN/3fd8HwJve9Cba7TZPPvkkr3vd6wD4nd/5HZxzvPGNb7zrdqMoIoqiV7y/udFm59pFXspS2p0titzjioSbV15CRQ2y/ja3b1wjndvk5jXB7tYmz/Vus9deJ08ykqv3cf3KFephE7e8QOfKFdTRYwwGO/R2d2lHVTY3b5Kllhuf+k02bq+zrmIGR+a5fPUm9XqTnUbIra0OUWURP/U4RhcYWxA7TQ3NQBiU8AQW9gY98tDQkxXi3GOGQ/KmIeulbLUMaWWeQTLgyvVbvPTCU8xNH2P5eJ/nn3uRkyceIM8Lbl6+yvGzD2L7e2QdTVBdotjdYkbV6Q+myO0eDFOGeQ7ZOkmeohYistYtOns9jriT7O2uIfoDGhVPa2+XmixYmonY3tlir+25cHuR7TQkLxRT1ZBAC67s9FhqRlz+wlNcv7LDI699LU89+TxFFnLvax6k2/KIvMHSiRlC70mSgmpNcFTmdIcZsR0wLdsU/Q6Z13TTgsgFdApH7mOEUhQiRIkAIT060CgLwguck6TOIYQh9oIcQ12I8sEdFJAbhFRIBJGOyCVYr0tami2jVxZH6CVGOGwgRr0NcxACZQyf+NhvMTM9xaOvexPOS1ARIojxkcTEIXho2iHGaxQa6wuMcQQE+DBAOINTmlDCsbrk3pWIR5anmGoGEMTce/4h6rUGURwRSFn223EOawxZkbPXHfDZ5y7z9Is7WGepaUsqPKAphjm5N6g4IsgdmQ9QVUFIhSLNCRV4LFIF1HSANJahD5muxlSqIYUXDKwhIsQoTXO6wU7P0NnqcHV7Fyc0URzhTYZVIToIyRD4zKC0x45yJdbkBFhEOI2xijDwOBVQCStftzbkihAsigoPywrhOPkwopzZ0j9hOoCqlQR5xGtCjVeGnrA42URllsI7uli6Wc72rubXnvFIV+G0jDhaePLc8ZsXBEvHVvjo05tsZwUexbqFY14QNRQbA8G/7GWkps7DNEZqaR65arjUu0X1oZRdo/C5IFKypCOiqKMJhUQKwRM3HD++sYcNBZ1eSg+BVAKTOCKt8VKgAkFaQDMq61la3Zxjiw1025Z1f9oRhgpVBSkk4cAgpKDYU6PopEA3NMFUiBcSWY326x2FKkGb1BM8Oi9G4dfSgXjwvOeBe0tnxY+lppE4J7l0KeXa5dsjSqHmk9eOYqhQA7zxXFztkeUZzjrKK2NGmaGyfiuKRlQ1CfOzUxyZbiDv+vT94o/1/ajnvgfsJ751B4VndKhulGeYrxr+P98ZsKra/Mtfv8bLL79EfeYIxjo63QE2OIKKmhCXGQAR6jKT5Skz8kIiZVlHVvaJdlTm5hA6KB1twPY7FN2dctvW4JIhzhhUWEE1l+j0uly5coszp44gVRkkSNMcax14z8x0CdomI/d+Ig1nrAUs3oMxjjwzVCsR0oiy+ecrTqkny3N0EPBq3s5+Z59R1lBIQVwJRxTAL398rdkRRykNf9AQnBKoFB5r/L5NofD0NxxIQd73uGJUsSYgN9B2ZVPkfOBKD3eMi4DeRorQgjw1mGIkVEKZeRxYQ9H3ZLnZz2yVE8QzMIasZykKv1/vul+35sC3DEXuyuZgXuAtZTbFMQoUAO6gAS+UfcilElgTjFQ/D4Bao1r+jUOHEJ7Ee5oNSbNRoAOPkhbpPWubgsII4noJyDcGJUizI6BnrCdNPFIYNvcE1Yoh0hanBtRCQag9gRLoUY2VLdgHLTd2c0QgqN4oCIOS0qbEiFosJGkuuLU9JPOC3c4AoVQJQKRCK1Fm40bUtpdvddjeG7CwEBIIu5+1BYEWlMhUKbyQdHoJx6Z6/PX3r6B0D0Qf78A4wX97coubL/f5U3/6PMYpijEQs4qf/9WbPPtSilaK1o7hzJmAN77hGCtLTZwraFQVJ481cZSXYKSyj2TU1806jHNl/0khaDYqLM5Ns7A4RSXS5RwZprTWttje7dLtJVhTTgHrPLkpW/dcvdnnhYs7XF/tU4k0P/r3/wIvXLzEuUdPlmBq/IzcNxd3CS59GePL/sYfEZiCrwKg+pN/8k/yoz/6o5w4cYIHH3yQp59+mh//8R/nr/yVvwKUBvoHf/AH+cf/+B9zzz337EuVLi8v88EPfhCA+++/n/e+97381b/6V/mZn/kZiqLg+7//+/nQhz705Sn8AcI4vHBsbq7hcERCsH79OsqH4HI21m4TKE3e72K7hopTbF6/REGBQrD20ouQZSSh48rlPbJhili/zd6mQPiCna1dBt0hNnd84ZmnKPo9XBjSvh3R7+yQRVPsKkeaJkTVJcJFgZEhOozLm0j4ERc9InQDojTh+qVN4sYQhCMbdjnTC7F4zGYLKbeRSrPbt6jKNEUYsLqxQzF0ZIWme2uHXjLEecXu9i6t4YDTj0xza+Mmm7fhode+DRKHyRWLcwG7aznb6ztMR1t0t1dJOinZ3i2CzgbBYIjqrqK72+huQtbeJGfA5pbh8vEltnYL2h3FkZU5bD7g4q0uJ5bn0BWoT1WYntNkwy20qRDmm1z6whNUwxqLcw/wzGefx9ebvOctj/DSy9dZXpjng9/0COdPL+Mpz1evN6Dd3uPCzXUurCuG/ZRBWlIRfFA6aQ3lKDxYJ9BeYB0UviByitwrlCpFIqSqIQNFM47QWpE6X7Lf8hE/3RsEkApHRVkiJ7h9a5VrV7/Aw+dfS6VZo9PaIM+6WPVO8BqpQupBTKo1eIcVHkfIQeo+QogCb3NMnjLXqHF0KuLcYsBUM0aLkNQHOBPQjCoIVcV5Ba6kAiIEQRQQRoqaD5iZqrE0WyUonuAT1wYY5UsJdRnh4wJVOLwUhJGlMAO0r+ByS+ZzbNggdopaJaBe9aSZoFKpYIzk1m7CTLOGNuBtBt7T6iQUeUY27FJTBdYZhrknR+IpxTw8nrCi8caiEBSjnmXGUPa8CgOUBrwGX3zd2hCcYpmYdzOPkoychjEtZJTtsILP/HeIpKLal5wXo4i8HelFyfKhsn3V8fnbknuDGc76ccS5dF5E6ln7Lzs86k9ig9IzFoGkkho++1FHkSjebiqjhqelgyI9KKlo5pLPf8SQDTTvJCp5n66Mbu65pCx0l4qaVrQKcKGkn3o0EEWCztBS+KJUL/SCQeZYaCiccOQZbLUGCO8YJglR4HEWmg1FEEqWlqZG2SePLJNMxPWQSteAEkiRsF/K4CVOKqKlCrqhGHU0BkQZMRcOEcgRyBmR/mTpDAmlue/BOe57UIEX9NKA//AzQ9ZSS2wcoTD4EzWyJMQVBUUvx3c1EolyDolDBOG+sF8/cxgvUH5M3WMUvqV8cWfR9v443MtmnD64E4KNfear167R7Q/Z2W4hEES64FTzKr3sGC+uh4hT76cf1cB79HSOMEWZXTc5wlmEUKgowFOCYi88teWjZRNcT7mMkpixWIzzmNYmRWsLqUOcigBFUJ8m9H0kbayRWJfu10F54VFa7bexONy09HBPKTHxG1FSnGv1EVC6ox7sYAgqUXywhrs6PYffFIKRBPMX66H16uNrzY54W9oKN/mmE9jMY4oDL9Tj8e3J+aTG74LwFN0C4f3oR4wyOiVSSTsZB5N4vI7yd94p8CIvj30ia1p+1Y1flJ+JcZYQvHT4LVsCaiPxdkRXG90vpaiURpnxlkfXd4K+JiZeiHHsxHsY9TsSAvq9Br3ewVEL4bHW0qhbBgMIAoeShlBbKsoSSId1lhdbmtwI+knBVBMIDT0J3VxiEsosmhVkuaPIwRnLdkdycdcxVVNoXaC1RYxEc+Rof5LM0xp4docFL65uk+NRUhBIQUVLQqVwXlFYwfOrffZ6GdX6FK3ukECWFkxKRiBNYZ1lr5tz7faAqbpCCIsrSnqsw2McXLi6y3sfnWE2HJSZw9GcMF7Q3t3h297/GuIw5Kd++hmkCClyQ6+Xk+eWrdaA6+ttHCU1+rF7FpkaC9AIQaeTEEYRcRQihadWC5maquO9YWOrw8Zmm04vHQmZlGUu1oL1jmdf6vHscy2EhO3dDOcdoMAHnD19gpvrGygp9/vH7V/0r0i66csck/vwP3h8xQHVT/3UT/EjP/Ij/PW//tfZ2tpieXmZv/bX/hp//+///f1l/u7f/bsMBgO+93u/l3a7zVvf+lY+/OEP7/d9APjFX/xFvv/7v593vvOd+830fvInf/LL3p9mxbKOoDvsl1KdXqCELR8ShcSQ4ZAoMkqGK5BInPTgJB03QEuJdUOkKDACWq0dTDKgUp3nHQ++gRfbbaTPSIcJ8dQiSb/Lxu5tQq3wFUf31iZvfOu76fQ2uHbh1zBF2Ycj7/VwQqKjmEDFhMKTidK0DZNheWNLxQsXnkF5R6/TxjrHMA5RQZ0ojnBFj6gac+zM/ehQE1UXkHGEDxRJ7kkyy1xiaW33mNIBa60WLz73JCpXnHxQceHJJ1FBjXOzfZ5/4WWmphbZbG1z9crLTNcX2NzZpLV+A5dV6O+t0hm0GG7D3tVpbpkWw04A+Wluba7S7SpmZMLG1asosYBpbxN6S2VuhjRrY92Q6bklTHeXQdrj9JEF2tvXWLt9lYXQ0t6aYtOnLK0sU49ipmp1jh1dpjCaZ69eoVZrMrO8wu52DydLzrcdDHEmJ8CR2pww8UjjEYEiKxK0VCjdIFZBWdguIAwjprzDeINRZV8x4QOEE8QIMpdSCTXd1hrPPfm73HPiOEuzDRh1rcl0WbvS2tjF/f/Z++9o25L7vhP7VNjhxBtfjv36dQ5oxAYTwEyBIsWhNKJFBXpGGv0hyxovjcfjGdujNabXzPIaa2QujTWyxxpTFIMokgqkxASAAIgMNIAO6Pi6+/WLN9978tmpgv+oc8499777Gg0QJIFeql797jn71N67qnbtqt/3F74/BbvjPq6xgFYKSULsDTiolCfSmtV6ykMnIk62Au2okTEyqqGTGkmsqCWSOIrB+hA7VWbUkzpJHAQcKTXgEDjaMuH84oi6jillhMPiI42ZuILYahwEr7SBcIo0UkT1IJTqSCOFxTgPscFIx4Xjy9TrQYCNawkCKIdjxpmhAhaPtbBdRb/yKJETKQ0+BRWRICkVRHi8ySBJkUITRxHOB7O/9RUqUuivY4X7VltDPIF1rO9K1KRf85TpIJAInr8eUiV79lmfxMRJMnzxrHfAi4nwMqk9r8krJrmVxBRkWRhlgtevCIQ3JARr6j6db2BsKjO48rKeuKMUE1e30I4Sw9BrnIOm8CRSMAa2esHHq1mXVGVFnEgWm4FtLDeBDt1ZT1FAWRVYoMgdx9oS7zxKR8hSULkMJT2JDgKwjgS+V1BvFESRmHrmIaRA6pBLSg/GqFSFsZMSHUfESUjdoBrhuDUClUaTpNMClSSMnCTHI0TEqBQUNUW6vEDsHWdOLBH5KSOc58brt1lqLAbKbutQBAHNWEvic37kTAlYfvcLI7JMcPpYi9WllJ3+mN4wm5C9hDiN5USFJOnT5z5DF3NSgz+YXNcaiwM+98WvcKvnEE4hVAMpQlxU5PcQ4jQybiJFCMh3WpAcO4Gspfh8jLABLKHDmAgzoSBXCqSauHNJvLdkt69S7K4hfEhEH519AhHVUf3b1Po3uTR6le+oXuPcd7yXzfvfE2I3JqhPCEEc310cmM1hf+DIHR+/8TIHaqfAwt/5+9dTvtXWke3dgvG4oqoM04E0eUXnSid898HdbKqkmZk2p4AJj5KeWmKxTpCXEcIfhprz1tK5PEuHTYYzCwr7wGdq6ZqStQhmrroIP1tTsFB0CrwQjIeG3e2CYgTLqaJRk0gZXOYmYY+Ty8+1cgq2RGjDfDzgfNYi78PakNY0ZQllCaPxfrODqx2kiSCOLXGUoFSwVlWlJ9aeeuJQMqxL213D6zfDOdbAGEunJ9gqBcqD8C4oMQPZJJ2eJVIEr5/tMVqHGO1IS7QMoHJz11A5x+1uhXCgN3s8U4NTCzFC+Emie4f3imERQNqVG0NUJOh2C3COwniMFZTG0+sX3HdKU5Y5U1IeIQRZBb2BpSwqxkNLWQmM8axvDMhGjt3dDhubXW5vDUJcdiR57eYuqVZESnD2zDIPPXCW+iSPqPcwGIy4fmObvV5IGWRtCI0QBK+F4bDit37vJnnhGY5hPDYT11QmsZ8CISK80qgotHPGhOoPPfOvo8wvM1/rrb9rvSNAlbhb3W9i+aYDqlarxc/93M/xcz/3c3etI4TgZ3/2Z/nZn/3Zu9ZZXl7+uhPnHVX63T2MyydB1AojgtkfPFoEEXkyNUAIHBIpgyVbKo1QHiEV4BA+JfGSQvapMEip2Nre4+J972FxcRmjPb3eCFdZFpoxUkX0R12e3f04OkqJm6d43088iR73ePpzH2aju4sQETqKJsTYGi0EFgI9ORaPxIuQT6SyDqzFVwYvKvyoolRDegPBlpAo45BKoHTC7uYetWad1sJxdjZ3aR+7gAP6Q0tSX0XEknGWUxqPiiU7u7sUZVgk93a26W13aKenuHX9Fq+98BJnLr2DF198la2b1zh+8RFeu/oCNh8T1Y+TD+rcvvYSmmWG25btN15h9YSlt5mxt/YG55I23fUReXeb5vl72V6/Tj7ucHy5Tr+7hq1GNBYXeOPGVb762uu8/5GHWIwr8gqiZou19Zu0ytuoyPDSc6+yfnuLcxfO0e23WL/ZoXl8lfsvnKR/awfdaHHPxdNs74xpSEctFbSlQwsTktN6hfMGX4AzMdYqCu+pnMU5S+oc7Til8OCw2MojpcLpQOWaxIKlRDMajXnp+S9x6eHHuf3qczzw3u/HItCJokKTRIYzLc/F5Zg4ifAywekImcQ0dJ2ammw4WpLEmlgr4liw0Iwwm6+StC+jdQtmsUeards3+Njvf5J/8TufoXbmcY6dPUcrEZSupK2h4zxp2qJyBmENkVAYW1HagkgrKhOCgvu2JNWWxEh6iylnV1dZatdppCkOiTGOVrNglOccX6hTlrCzO2BsAuBLorDhGAIhQ6o9Ua1F4UOi2rqMKDxUeBIXTwDEW7dQfautIQA5lm2Xk3h5gC1pKm+EFWQqyMwlVBVTPbHfp+iGfSHiENPchKttv5+T68iJkI4HJyZpPL2Y3X8GwuY2suntBqIiQnDaOagC0Ypz0MkVr93MeNf9KR9/pssD5xIev1gD73FW0s08VenICovzIQF5M4HmJKdYZDy+9Gx2BuAFjbqgN7BcOpPQG1YstFOkdMSRJIkF1kKURNTqEWJQzCwfiKDJjeMILxVJLAFLZ6vAWh8270hx8oHT/PL1lN/bbiG1xWO5tpPh0l1SqVDoffc959gZVKgGSKFIU81iqwYiuN7VdMlK+xbCWxqPnqPIIkbVmOONmK08Z/HSKax1lJVhvTfi5b0BsZYoHNJ7IiFoxQlna3V6VYW1BgVoEdIZVJXh9z72earSsJXXiH7obyJdhf/sP0eVT+FxmMEa1fombv0VvIhQS6eQyw8i8xHG5MTtRZTSINWcst8jvAuxMdaSXXsBP+oiEVgixKmH8CpCrj2PvPoJFqsO7xF7/NR33ccH/rP/jMYv/B95JtV8VKtZst7pTJv/NJNHDksfd5FG5mx5swMHQ9PuIt0cWaYgb18u+1o5sI4q32rryH//j5/BeChKZhT0Va/g1uduAZ7lYy2OnV5i/UaHUT+bgct5K9PpyPGjJ8fcziL+1VYzWJaEP/Ss/NwCM3/2/lq1/5s4JPfe8ST38dYEqIcDEiFixl3JoGcQ3rORQKwlWgmiyFKvSU6dtcHhbGrQnLNgChVi7g4Lxf7At+ka6Gc/zvdVTBRQUkSoROGcwJawteMRc8nkp7a/40vB+iJkhVR9GrFjcSkjiV1IRuyDWW5UCG6txcS6QuSO527neBeIMqT2wYVeKPKRxHnL3sCjtCepGW5uD8nGwUokJHQHBmcEa11LZ+Tw1nNqOebKtS0k4JygN4rwQjAcGzr9MXk2jecK6rpbe7DX81y71aMoRIinqiAvYZhb1m/uMBpk5EUVFMc+YrdfoCajYCcKm9MnlzGVZbfbpzsYU5Rm8kzD+OSF5ff/4BbOawajiltrJe6wgX4eAAsV4id1BJOkzf6AhfvQKW/RfHR0jaPWgD8lU9RdyjcdUH2rlf5wROQ1HosP2UcovEMjsF6AVEQuaKBREosLIMcLjLcoL/CuJFYRzgucA7Qiai9iRcmVF76IkjFxPUW4wH5T2hLhJe1Wm8LmOFvx1Bc+ipCaxvVX0aKiu7WFjFJQCukD25PEBV9joTHeEglB6S2RUxTGgQzB3b4q0ToliuIgcKiwiCkvcTrCCIsxFXl3D+FsCCScRJzeunoFpRN0nJCXhtUz91BL60RxnfseeiexrlGWGY32Cl5Jbt6+TVFVSOHZ3V6jKMfUErh94xrVaMiZexKef2qDoixZvXCCvY11lpaXSFPB9ddfob+3iT3dZXtvjfHeOq7Yobt5ldHeLr7osn37dXrbI1JhuPr6G2x2Ss6vrvDq3jVudByPPPYYr199leubIy48dB7T3UD4Ec1WxNPPPUdRZFw8HvPc567Q7XZ46P6HuNYxXFvb5Yn77+Hs6hKqqPiJ73uU5WMrmLJinGV0B2M2t3b44us9qkJiR4CXVMLjRIWXEiMinILMR/Rkk9JBbg1jNCMEo3yAkJayGIAzNBPN+dWIE8uChbpGSo/xCSpKieMUr0B5iRWezDgiB00piRNJLYnRUdg+6/Um0hiq3m28t2xs7fD5526yvjXkV37114lrNZryFc6cbBA3lhE+ZuAcsQx0tBUKrKGUFQZHlCQIpRFlhVUBDAkRgonHRcGzr2/zTiVpNdtEkaTVqLHaKnjjjQ1u90uGBaQ6QkeK3AZ6CSEg0jXqSiJ9hRDQUppchrxUXkhi65E6LDFWvXVA9a1XPFuUfE5Ygm2SiRCzD2im9eb2mtmxYNWYWq32N5Sg+N03dQkCcJo5OM2OT+7jJ3rraZz5RNKR+KABmkA5J4Lly08IG/aoOIFnxSmGpcLjyArHH36lw0pb0a5rLp1p8MWXu7zwxohJ9xBCcP6k4oefXAR8SOpbevaGHlPBTr9ES8HiQoLAMzaerPDsDgqqyjPcGDHOShbaMYtNzSi3eKFo1HWILdSSZi0IDXlpadcipJAoHTyBTOkn1jgBcUTeGXJ7zXB1UyK1RgrFYC/D+DEjHWEG1Swo3nlPMcoCk6oIws26DvFTSgqwFZ9d6yAF1M82IXHkZYUvKgaF5WSrhlYh71rUTjBnlkh1FKxWEwq7a5sdnutXbNuS86fbeGPZ6Awp+xafj7l2a5dq2EfECdFwD+FKaLWpti3drqc/zHDVFFRGuM413HiX4ibIxUu4Y2ehHKAbbWSzjVo+AVWJHfbAlmAMlQVTWw6CjfOo7g2S3i1+aHXET77bsPBCh8dqUH/HCsl9F3HHU3RukYIQByrcLDZq3ohxJI46YKE6oohD5x344u/2w9f4bf/Qt5bo9PWX3sBx5oFjtJZrvPjZNRaO1Th+rsnt1/bIRxXLx1vc/87TDHoZw0EWTpqhjLDSxNJzIvJkVYg98pNcSHdq6g8Krkd9mkM5R7R2/2GLyf1rx+oIKRjv5cS1GGM8UnqKbESzobGFYziqiCLNUi3sd8vHmmjBxNMiWHylCvLO5tomZZEzVU5JKSf50Y5o6mHAf4SldAag/DRR9mH/s5B8OhxXjEYp3nv63TCGgYHDIaRDSqgLR5kXNGqe1lJIqC1lCBWQWNa3HJsdx2AsqWtLLRGsdT3jKuTNDPuBm6RckfQzGJeeWFgWi5zrWyXShxinp28meCHoDEqubg1JtEIKQaQkUmheXZdkQ8Xa5hhjBcY4bq2N0GlEXsVcvOcCt24Pee75pxBCcvZMA4gmMU2C7W6Xl672ePDSHrU0jIEQ093FUxnPF57qcHtzwGvXhtjpJk8Yy6k3xOElQEw3wEjsA7M5S/2RU2tmNz3iMd+lzAO0I2bw3U46osIf7yrytgdU42wMtYSaKinLIgSkFg4rVHClcAKEwEtFRIRSnqimiRoxw8EeVWZwUpLYkomXLZYChMAJS2EFi42UfrFHPW0Gtj5T4irDbncQXGBij8BQYRl11xBSEDWbKBc0hEKCd0HQFsITI7DCURUWawxOWqp8jHeGwApksGWO9QKvQxCgReG0QwkLUgVg6EETAieN9yH+wwmc82TjMaNBhlUe5QJFriTkSYobLeJ6iu11aDWaHLvnfpxUCF+DqKLby1i/cRtX5NRbp9jYeC0kn/VtXn7+C2RFzgOPvpNnv/I5fOlZObXFV5/+AspGjLt7vPrqa5RVRK+3yfr1m5Q9Qza8zeuvvsjmnqf7+L088/QzbHYVZ04t8fILL7HV0zz24H30OptgEmqxgLwPNqZZq9HpbFPhWViq8+Kzz2NMTtI8y+c+/0XuWWrS65ymEQnSeoOlhTZLrTZnVxvs9J/lc9ckO7t9mottmseP0d3pYL1H1pvBHUkJGhrqtTqR0tQiSY6mMhWR9NSV44ffd4L7TjRoR4p6Khk6SWZipNZ4HNZJrBeUxlFNhFNpHZEWCOWJpUF7QZn1GeyuUSs2efHKTZ5fqyjUIpcuXeKHHk5412XH6Xvfzx987mVe60bk1qPxJEphK0fhXIjDmmiPHAIrYiILVljqkSSu1xHScmKphoot3Qw2ep4o6bOy2KQsKl69nREvLFCOtzHWo1UNHWmqqkJ5RSk0kQtBx5GKyb2gcDZYgRXEk1gaLwRIT/GNWf+/ZUoPTw8zCfmZbMBwQMg8cBzmrApz5Q5ZUtwpT06/+yOOwdwu5veli5kP4hTUTRsVtqINX3G7GvPqbkXHGXLrefXGiOOPLxNFikuna3z481tcHduZ9Oy9wBBTOkiiSe4hPLUFMdtscZ7+hEVT+IrMVqzvaoQQSA+m8AgZ3JzywqO0oCgVRRkSZVobhKn+wFK1LEJKdkeCk02IlUDIAPxt6dlcG3D7tmNnJ95nJassTgisrMiIDmi5fWmosjLQrStFNbGsOeegMhSZB++wowLhPLvbXV7ZGRPVBKNoAryYsqyFJMOtpBaAr4C1YcbN3YxWInnXUptESjIv2R1Y8nGG7a/hiwqfC8pP/QLRqUv44Q556djtR4wzGdg4hQ3trgyuHIQYiLiF7ca4UQc36CGXjpMsncRs3KC68TJ4F2JJl0/jowi58zqnxmu8v1HyoQtjvucvv4+VyzG9/+7jtK3DlZZq6xYqq8Ie4EWwbsym1J3izZ3KgTcpX5ec8maLwUR0E5NpPas9nXPfxkUI8pEhSiqiRNFcqnPu8ip7t0cUo5C4XfiQLnyKTsXcuQA7RvPP1tv0bQBTYu63ry2hThU5bz6OM3fDg4sbx+87RroQc/PpdRZOtSkzRxRDZ63ifd9zie3rA7761HUWFmv85b/+bhCSY8ebM1KRGSiflGsv32R3s4OckJjcvHaLvLcPJIUIrmf1ZlhPZm6Ch/oz3/XpWM1HOR7+O/s0DfiZeglMGFy9DQyKtdhTi+ogYGMtnLev//J4B+26oZaCsDmQceoYLDanLt2hznbP8/KaDoylRrDUirkxkOwUEi0sCsO1zYI08fRHFa9uDieshMEbwtqE7b0UWykG/QrrArQpC0+vV4ALAElHEf1BcAlOkhIlxrRihZaCXhkYEc+fqofkyirk8PrqK3vs7pV0egWvvTGiqFxQYB16+d8EF2GLMetf/ArPdQc023Ue+6HvJEriA2cexjbzAOnotOxH1/1WL297QKWcQakEmdYDO0xVTRYqjzTBElHiEU6gaxqpYyg9SlQoJ8h9hTSCfOI+I4WbME85LBYpIhCWsyfOQhJzYmWJzdu3GY8DyndSEMvgppNqTewjIq3CfauMMs9YWT6O0hFagJchuWx/PODmi8/jyrCZW2ORcYzXCb4qwOTYxIcYhsoi0zrHj7Wpx4qFpE4lLHnlGWYVvvLExlIGeRAzUe8o6dEOChUoTKUPVOZmPKTMx1Rlxq4Aq2OEh1hHRFGd3fUOC8vH0PUW2+s7YFO0EAy7fZwVCKcCUce4QAhNPhwzHoxQaY2dTofN9XUacYutGzd46cUrRI02z7/yGi+/do16fYkrt2+xudshJ6bX3+Xm+k3GWUrZu83uxut40cZun2K8dQuXNMk661T9HVSSYrMeeW8XGddQRtHd7bEpFFdu7HLlpZc5eXyBleOnyfpdslGfRlzn6vNPQTHi/LGH+eJnX6LsD7nn/AVEKVDErA8Ny80Vzr3j+2ivLiAXVliUYSH9kQ88TLn7Vf6DH3gf3lZoKSZzBCwJUkE+6rPVKbEWfGyDD7MKQnFVZCSjHm3nMK5DvrXJtY8+z7poc+v4Be558DLnVyWL9TrOWk6fe5gvPfUqNwcRFk3pHPHEt8sE4z6x9Ix0oI2NZW2Sv0eS6JRY+UAVrUL+re2+YXmxRqQlg6zEuR7D3KNqmqyvEXIRKSqUCBYqpwqqMgjWAo3HY53Ay5CfS+HBVVTVBMxLRWEtuf12tlCF+B2BoNVuUGQZ4+FwBmb2hfg7wdRdNwo/lQ/8wc3GHyFu7purmCWn9BP/vrnfxCQewR88EYAMz7YztAvFiozIXI7SngfPtamMDHmznJhtbpHWPPTggyjt+f/81jX+2ocWWGoIhPZoPdUABwauX/q9W3QGhr/6oZOsLid4H9ZTsMjIk5d+wvIFMZBXLgR8d2BDhnGTQmCMobKKVzbhahqEfCkdJ5Zi4kjw1a2SKy87xnsCFpOgiVrrB/IOrZDnPFJNaLrxuKoi7wyDAqsWTwQ3MSHe8GAtzjkGt7dQWuFKi62CS05/u49QQaCbxpQJAcNaOYkV8HS2B7i9iiyBl27soDXsdHO6/Yp8b4CbMPB56xHdNVxrEYoM50BHAmlLrKsCqELsu7YJR7X1Rcx2THThAyT3vQ+LpdreRqQLxPc+AdkAc/1l2ree4Vzc48FGxd/66SUevacgsR57aojLHFdv99nbMjz/2sdo/dZT/MXlgu3VE+yd2mNhcXFf6PFTS+qBaf+nVmaxGLOGHFRWfHsWwd7aCCScf2yJRq3BibNLSH3zIKA94GJ18CGMHFzJQ8hC+Pkg6LnzrLf4EA+jnfkyubyWijiK0UlE+1ib3mZGlAbrqtIapUOSYSUFi0t14iSagZUDLpuTNevig+e5+OD52cEL958ln+QdC0urYGtjm1deeDnk/MZhnUcJHxLHTro/XYt0pCdxgPuxWPOi+p2uhXPA8cDUmsSAAVOj1yzlwhwYC3GhMVoCOsL7Fls7jq2d+TuGWMDFFApb0RlmLK8ULLbtTME9HHoGuSczklEGg1FBoidWOxSVge4gIkpSrr6aIQjpJ7KhZe3mCH8y5AWcBqx579ncGrO1lfHOJcVqIvnqhqOWKLbWhygJUWQ5vtrk2Zf7DMdu9vzFNODVv8m7Nttzwjhfu7HJRz59gz/bavKi63Dm3SOOn9QTS8E+XPpmJNgVb/LtrZU/3jXk7Q+o0ho6bdFINLYsgr+Ms7iqwjobMpMTcphktiTPNI2FJSKZoKMIkTFhPbFhsk6SsrqJz773nkG/S5WN8ZWF7AInz5zl9to1+r0+EoWTGi8k2oFQnkpAKhSq2eBYq42QGi8EuXcoNFk2pshL0BG4kLtoOimVEIHaOIloLS8w7vTwRUVbex45s0gjFTSjlMVmSiuJSJIUqw3WVOz2Hd3cMhwN6fQde2PDaJwzrEqMEyGwgkArq4VG6RgnBTqKMcZiBDg/ZjwoGFY5HoPJC+KoRqwU69euo5MYncRsb2xz6txltNZ44Thz7h6cSOjkI+I4QcYpOzsdjCtZjBL2trv0+gMSXeOrz79Gf22dlWMn+MqzV6jHirOrK9y6vU41HpKkio21mwy6t6ktrtDdep3h9hs02sfor12ls3uDZnOJvY0bjHY36GJ45dWbbK/d4NSxJqcvFtx44zpKOhZPXkCWObUkYqFeJ9u+gUKy0r6Pz199CS0Mqy3FS099HpMZltIGf/bdq9x7/DT/4Opvc/nCSRqNOlI3EdogRRwmni9RwiPsiDQSnF6KKA0MxsHC6L0JsQ4RdLtr6O42cWdMe9PyvmMPUD5+P1etZ/lsSonltbVdPv3Ui6xv9hmV0Dh5iWaSEJGDMDCxbioRYUxJhMCUEudLtAYlYoSPQEoEJVlRYDNLmjSIdEQjSVmo6ZB7RjhS6akpTSQVMpbEkWCtn1EYi7SA0iEXiAQnBIn0GGuovMQ4RTNVmNygXElLg0qjP7U14I9eBPXFVWSkePTR+1m/eZPXXniJqeSzr8vdF4a+5lI/03QeqvumyntBa3GR5WPHEXKSsHLyV07asb12m35nlxkym13cYpGc0QmraYt/M1hjWFX88z+4ThIpCmMRRvLAmVPIpRWqfMwHPvjdZHnOhz+yzqDUM2au0L+wURor6WeW73nvKRaWaiACm95U+1s6z7/5XJesCHljvve9J1luCJKoQC9OQaggkhIZO3wu0VqQJoF8wyEZG0HuBcaDGxtMt0TEMvgFjqrQT+0YbfYRUqCbMUJA2RngnUdqQbLcmjHGIQRKCZJYYq1DGrAysAwaE4hFBr0MKQXWmqAcEYGNMO/nYU3znmFvjPCecmRZu7mNihTGgjcOl+cTmUQw4ZQOijgZ4YWkn2n6w0kQtw8a7SkgDjzV4X+z9iVGgw302UdRQiG1RlU5C5sv8Wh5i7/1Vxd5xxNLaOkRowEqH9O/XjJ+9Tm2OhVfWR/SHMIvDyTHexU/UCX8y+e+yNOLt/hzf+lnkFrtu/y9FWFjXxr9YywHXYK+/YHUpEyEVaU1cS2l0UxJ03hiUZmzmtyJj2bfp8qC6eWm5etxnzqyzEu7M3DlDx6XIuSYk5K4rokTTetYSvfmbhCtxT5j3x1WobnYqTtuNZl/S8cWD3ZIwImzqzzw+OXJuHiMtdy8epMqr0Ic4eR07xzX37jBeJjN3XPqggY60kRJYKK8czYdmml+cu4hy8mBb3OgY/r2SAlMrVwHFl+PkJAKzcmFlHHPkg9D3KiU4Jyl1XCBJc+kXN8wRELivcMYQZZBbkxQ0Nh9POMR1JsJx08tBPduJ/dBog9e4M55lDdY6+iNKpyHv/O3fpCrN3b4jX/5zP5zPfhEmJ9t+8NzkN1UEFhqjdPsVorPjCw7TrL1W1/g/MVVfuCH3hX6NLU6H/bEeIvlT1Gv83WXtz2gslWJdH06Y0eZj3AeqqoE6yYvW3Cbk5M8KUtLxzhx/jxWQGkNo2xEZXIUcTCTKoGtXIh7QiE1lNbiRY4SguFgh/XbFuIGcd1hijKYvIVC6RglJAJHSUWqm4HVC0Gel5SmxJgMsAjnQGmErpBOTujVNU4ohFAkScqZpSUKBVeG24hYcXq1yfG6plVrktRSmpEmiRVWSogl9wiBEgmpAOkkGZrMebLxiJ2RYac74nZ/wF5nQKc3pDPKGYwyHAKhQs4mKcArhRbgjARdQ+kIpwTGOUbZCD0estvp4rxD++CjL5UmSmpUwwbHVs+goxTvFZcvPYpLavRzh9BNhqSUW3vsbXUZiyZbw5u8ceMKqysFUbLGjdu3OX484rmXX2Rne50TcS3QEu/tkqQN1jZv0ulsUU8VW5uvsrV9A+cqXnpR0tm4waB7gs3BmCtX3+DeE6vsDiv2dm6xurzA9sY6vqyImk3yqiDPuwilaMXw3LPPknd7RP2bfPGU5sbxFbp5jY9/+gX6eYtXXrzB9q3bRKLifd/3fhQFrhphTYmxkqosMKYgUjVKV6D9mGqcsbPV5dmnX2GrK7j3wmU++L5V5GiEjT3Li3V0a4nnbgz45Y99ga2rV1haXEL7mNhVaFkRe41zjsJUFE4QSwVRAyksSkUIV+FLy7gq0cYSGU1Z0yymDZqRpNWOWIhSjINhFUgIoonb4gKWY3nFZnfMcFyhkRAlqFRhvaSqDMZKYqlDrIsQSBvk3GHpgwOW9wwqR8q3M6ACZyqQoHQ0Iam5s7yZkvctl6POnwnmgvbiEhfvewCEQko5o70ONQL7Xjbs7zOJzbxaAoHIslbc00yJRmGD+x7VYGAcn8+HfO9Kg//yr3yIP5ArjEYj6mmKUorv/I7vY70QbBSTHZ19QcXjWDouOL6qGeQhkbXAhvlgBYOR54VrJaPMISTk9Ekjz49+Z8qJJTXbbL319DNJZaCyM4MJeMHraxl56XBCMhw28MYh8uBdgLV4BN4Iqt0RwnsaqoXQUHYyvAWpHbpVo+jnVJ2Qwydpx3CyjfOefDgMFrVIIdIG3luKIkcKGTTmUiKjkM1bWh8AFQQg4jymLNla64DWxDoEk1eFmXumk/HCg5BEGlZbJV2nAzD1kGAR3iOncXJ4wODybYQZUH/kHaTtY6x+5d/yg40eP/Sg4aFLEYt/832IlR+huPJJtv4fv8YfvjDkV7YKrBNsesGTTvCT2lN6z1Ur+E+6CeLMZd752CM8dP9FfvP3Po4AHrzv0mSqzehUvv55+k0th4S5Ofnu272ExKdhH98neQgakZBsd6qSubPDRw/7PiHOW7j717zaHZfygJjmhQtxQYKJzCQkqMBkOgV4YvZlrh9TS8VhBdL0BO/nejxVQgRX3Vrt4Hr78BOPTJo1sVpOlrlTF85gqmrf7jRHAnTr+m2uvX5j+gtCBmbbQFAREhtHsZqaxoL3gBBEOsR8TVt3GGLdbRSPtKTMEjRpvAupXsJqGoW8XAJqtRQpLVaEHIOVtez1DOMxFKVn6s44nS9SSpSa5IGYgVYxG0fhBREhuswJT6vZ5C/91Pfw4Y+/EADVFOFOn4u/o/FhrGevoydRwR288uCcodlUvPPdJ+l0DYMbOzyyoti6eZuyfIxaup+P7cCl57587aXkG3z5/xSQ2NseUJVY8nGOkBIvJM4UgZ56OkG8D+DFhY0SPL2dPSKd4GRJJDSq3iap1Si9oaE0JisCqIk1g+EQ5UHFMd5adBQTRYrcFjTrbZrH25iqJC+CxtOZCuU83kjISmyUIKIISwmVndCgmhDvZS0SgfMOJVWwQhBIJlIluP/EAq2Li6xtd2glEZdW6yw2WsTSA5JcBDYo4WMilVDaGnUZFhCDoKEc9VhhFxdYcRH3ZaDrChUL9jLD5tCiqiHjccXNnR5r2x02u136vSHjLEdZi6gqnHNIobEInFCUwge6YR9yQ1VOYKVDlAXdytDb61L4kA/DOUuqNCpJ0WkdOxjTrjVZPnEPol7HCMfyynniRot+vwdCQRTR63YwZUksJJ2dbcajHoWtuH7zOoPtNcximzfeGDLc3WWx1ubG2nU622skjQa5gtHeJtupwPX69Hdu0tQlN69VDHeu05In6a29hh0PSHTE+rWXEUWXbuc2e1svUuSbdIeWUdbj0196BmElt6/f4rlnvsy99xzn1977P6OVIh8PsTZDqAY23yXPRkT1ZcrhLr3tDT75/BY3h5oz5x/hyfeucmE5xvkSV8UsXLoHW/W5XbX5zNYuz+8aWlmJ1hk1kzGOtsl6exBFNNsrCNUgNSUZPjxzFyxhyk2YLXVKLBVaSaS11OMY56ByklKDVQ7rBCqGUVbivCYzjtx4Sh8xdorCQRwpRlWB9goZaYx3WBwFIbgWKXDeopwDLbFSoZ0hqoo/rSXgj1w8MOrtsnBslYcefYgqz3j1q38894G57eOIPcRaQ5EXDAfZBLxAEmvSJEUKwYP3Pcjli+f4g9//CPdbR0dYNifXjAhM21EUXOyklzxUT9m1lqerMQtSoZVGemjWG4Cnlta458LFiUDFHQKRBxYWTrA36NIZ7dP8TgFgt+hTlLfweLyTvHClR6w9P/xkbUooD17w/I2c3/rYLkoJnA9xixKo1xR//vuOcyIOLqrq1QEM6tgMhPT4ygahTvhA2iMVZb8Mml8jZslHq8xiRwaTB/cWWRiKvMJ7KHYyzNig6hHpmQQ7Lhivd5gKKUIpdCMiXm3gSxM8EexEOy4Ezk3a4D3FMA+eDONiLhHuBCLt3UTYElkXDDuafKwRVJxU8HeaMSdSxcJxgZAWJMjlGk5bxhV07b8lvjbi/T+5yJl7GiTXBhit8DyML3Oyndf4bz/X5am+5bKEe7XgWSH5qo3JrGUgDFbCdV/jB554Dz/+k9+PEpLXr90ADw/ef8+h6XYXyerflz9CmQKn8C454YMbuLP7Vdx+zfnx/+YInXcCgFneoMOnivk1yM+MVWFKB+VIUOYIhHSzvs3xjh5h6zhk8Tpwv6/V48Orzr7CZaoEOHn2xKzavsda+HDi3Cne8eQTE+r38F5LIbDWIYRg49YuN6+uobSc5cxz3rGxfhtny1l/5CSNwj6JYljn4jhG7ifb24deYq4Z81atOx5VUHB54XFO4X24llIRp85AWQpu3FAMRtn+iIrJiE8oXoUIAGoaUru/+kwBmAARLIxIefc33N/5UUlPO7acOl7nyRM1nr/eZ03W+Jt/47t473vO8t53/w3+2a99hf/XP/4IaXuVtNzh+vUNzp49QbORcvf15E9yjfnjv9fbHlApFVGUOUkS4+PgtuGqHOn2Vy7vLcgg/OVVhR+PGYoBVjqk1LQabXQcUTMl7bRGupqQJCnjYowRMC4MUijieop3iqzIaS0ssDPsQyY5f/ICvp4iUPgio9frgHFEOmbQ6xInnrwsgjBtDVhBVZUIr1EILBVOhVw3kZIUwlOL65yo19nq9fEiIpKaiAhbVWgdQSwRVpGmTbQUtNMEYxXKS7wvZ/EEgzJCRkHLYVLB2IIbC8ZVIH6o11rQ8Ny3fC9nLjo6JuRNGOZDstIwGvfJhwPy8YDBoMtwPEBkJVWRUxYFFcEcr4XGSrDOThYzHV56KUGEOJvRsI+iR3f3Jr6yGKmIVITSCUnSoVFvsHLiAmmUkB47SXthgUb7GFYLmuUyzXqdjbUtrPc4qRnsblFUPYys6Hc6VL1dhr09bNkjrgYkHEd5w7FU4k1Jf3uDUX+b0VKM2MrJRz288HRuX6XYHVLkfSIsH/iu9/C//Mpv8OD9D/Iz/+uf5td/9Z/z5/78j/OFL32G2zsDPvL5lzHWstyqIXAU5TaLaXDLc5u3+MJXb3KjO+aRR57gR+85TkN6GlrQSATdvR2Wjp8gqdWwScxgpyBWCiljxrlhsZ7Ru/ISWXaZU6dO8+g9Z1g9dZqnXtsk9wWlEdSQCBlRVAVFVWCFJ5E1isiTe83xpuLsaooSJZUDkxds7ljuPbXIQiNiywmq0pN6TyuO8KlHuoqscgzKCu3AOhNS48jp6q3xAiLpMSLIm7W4hi8tVQTSfTvHUIV4tFMXz/D9f+YHGezu8JnpbjlLivKNXvlrHQvxb0HrKBiPRqzfeIP2ymmSpAY+5Bg5e2YVAIlge3MbJSX3eMWp1WV8EmFu3+Y7lefH3rdI5Bxyw/LeqMZ3Hlvk2SJHD/aoCYGwQVjy4nAr7uzjdItcWFhmYWH5QL1p1WZjyDve+TjeuZnmWirBjX7O+mjCHIhifTtlb7RLVU6A90QT265F++55Dux4D8YedDKZdw5khFcJyASUoNyt9oUIHK5yZDd6QQvuHQiFKx1VLwchcaUNHnYWjHM4GwDT1DCI9zgTkoi6UQGlxXRCQhy9VEO16zgfBKJqZ4jNCkQ5nrhQB1c+ELi4jjQKZIeldsXm5JVoSckHTrQ5flJy9idKROywSOzCCXwzgpMX8Vbhf+UPUD/z01Tdgs5v/zrjLKce/TKqKuis9flq4elqxU+nEe9Wln9UwT/xkuLcKf7v/9u/iK7X+MJzr/HRp57jd/9PX0VHmjyruLhU2392/778MReBKR3l2JJHOZ2dEWU58ePyUxfQqbZXzLn1vRWAK2bz9cCxI0qrHXP/w6szN73pHcDPKUQmZuIJvb5fThm5CXvoxIITViU/wwvzgHH+7m+h5XNtOKrc5ZcJqDgAAqbW7bkx01oTRVMviXlFRyiXHqxz6cFz+5edxEnu7nYoizIo3j0MhiO2N7fm7uex1rN5cxM1GYmQQ2sfqUqhqDeSCTnHQfR6hzFwmuiJqdVOzNrjOLrs1zmMjifH/fyxCdesn6/PXabXdH8TnK97/uP7JO//mYf48Bc2eObpTYR2fPxTX+WDH7iPD//h83z8E8/x2GPL/OD3X2Jja4Vf+KWn+A9/6rtpNk4eGm3uUMzNj8XRc+Uw6v8aM+qovvwJlLc9oKrXGhSDIRaDMQZKh9YxU4Ox8AJHgdARwkucrSgENGoJSmissESxxAqD9JbSGYRT5MMhmS2IE403liRKkc06416PqLaITlKOpynWhhxHK3GdKIl4Y/M6g84u1lmUlLgiZzC0GOsonQFjiIRAC49WAu0llZZImFiBJCJJGPmK57e3ON9OiaShkUQsNiOMrciIsSYiTSChQOg6SnicFvSMwDhFIiR9o5AyQsuYzCpUpAgZYqGZaIR05EZRE5DjMMHhF+0stahOrV6j2T4ZXHC1QghJkmpq3hGLgn4+phgNGXV22N7bY7ezx2i0Rz4oKPIC5SzCgpIK5wyRivBUaBljvUHJCCegsgXlOCcbd3ETtwjnJi5l6jq1RpNaUqMa9Dh+7DQnj58krjdxwiOjGKlTdnf2KPKCrvG88cZN8mGfgVpkb3uLzuY6q5fuw2djuttr1NKELJZoAafOnmBvsEevGFH6CoFka2cNaxxpZFhtSrytWGpp4ggQiiRNSNMUa0G64PI5okVVGtZ2uvzBH36Fxx9/iO9+6Dj1Zp3ecEgsCkbjIcPBOgurSxhbgozpFYayrKjHEerYSVRjkbh+nfP3XeDyxcssRNCqKyIzIC0KJAkmViEjetpAuxScwaGQ3qJiSek1V9Yy4sjRriseON1CKQ8S1ndKGg3FQqoYlTH9ccYgL4iThKgoEFbghEMqSWYczSQJ+bkmC+Q0thBtqbykFgEeRu7be6lx1jPYG5MPxxR5AUwdK+Y3pG+uf5IAoijiPe9/klq9xjivGA3HgKfVahDFCUIIGvVgnZqdJwPLYyIl91x+CHdqlau/+W942Enefb7FeCxIhOTxWo37GwlPF2OkgEiAsg7kdCOf688R+9H+ocOgckqcAa1Wkx/5ke8LRyceOB4/iUudSj6Ckxctu4OY/mCEFGLiFgWRMmz0PPHAYqwgKzJE1kMi56jjBRfuu4/haMTW9l4ww4kInx5HSYvP+3hbTIQ/Cc1VzCjFjnO8FAhTgRC4zFOu70BpwU6sU1MZtfK4QYUvfWCGtRNR0gSFERN6d+8I2gQz8VucnwdJCz9x98oqT16FhLxCwaVLx2muauz7L6DaEeXY88b/+dMs1yQL/7cPQRThoj9ERJcoB5vcfrWgV8DrV67xKVOyh+DepUXiUcm/qzy/L2MW3/8oP96qc+P2Fr/94U/zf/m7f4m0fYzX7/kzdPZqxFZjrr2IuPYHcw/vjz5vv6nlbYbyBILxoERFiqoq6O9kjHoFQgSLgTMea2yoeVgCvftF54o/tPwcDcQWFhPe9b6T+yQEBADhnZt73T3gcN5jneVmXzLqmX1rCxMpSgiCuD+xgswg1vQa00Z6jhKb34yu/y3PxiOHZ38g7uaqd7fr+4kL4srK0gF8ehK474F7D1zNGMu1165jK8s0ncbUou+8Jx/nXH/t2hzQvRugEoEIR09i0fx0W/GTkMpDrT30dR+uidnaIybzaIqpAqW5xx+aFwGHzwOzaXPDiTfGkl+46Xk8K9kbwX33H+OJB07w4qvX+C/+3i8zHI/5ke+9yLvec5per+DLT29TFW7CDMsdiaXfjNfv7qqDb/3F4NtbynkLJev1ArFDVSG8R2kdJp6fLiAC6Rze+JDPxTgQFmEFMo1wIsJ5SRQlyMjSkFEIDPSOSEZUyqJSRVJrsbh6nPjEaRqtRZZbLbzyZP0+W9tdXt9aQyvNYNDHlTkDZ/GmCgxteJzw1JXECk0zTZEexr0A2AorUF6gVIhRMEXB6aUT/MST91COMz7yeU0kE6zTqDilJh2Vd1ifsONqxDZmkBlSKTFouqUmEpC7CCsCS5xEUFqPFRBJFfJvmQhjBAhH6TwNJcmUInOWfuFRRYmQEicMSZpSrzeJMRyvx6wurVA4RV55MqOxFgoqRnZMXliqQY/+uEOvs4Hp9yj6XbrdPfLxGCpDJSu0E1ifY52YmdalCNnKnbQ4AhjLsiHjcY9+T+GNxRiP1ZJIC+pxjaqXE7dqrJy8iAdWVk9StpdJGi3kcIBqNGnEKZtbG9iyJE0lvW4XZyqW6jFZz1COM/CCKILlOCRTbCZwqulpUHKpVdFOJPVU8+T5hHotYjDIQaQM+30EObWTCY+ePUnefyf3nTlJrD1vbPW4NrR0r70C2ZiLi1BEW9xwx3BRzNbQU7gErdsMh5ZTbcsP/NSfY+n0Ja6/8hKjOtR6DUbDjBuvX+Xk5UdICsM430FFdZySREKRSk9lDFJpsqKgoKAWRVQ24bWdguPtiFhbYh0YLHuZ4KXbIwZ5RakF4yyASes1SjiEMCRSUYlAWiKtwJkC64J7hBOOSEPlHd4K9F31a98OxeOtpXt7DfmpT6Nu3EIIwfHjx3nk0Yf5zKc+S1kW++4zky1BHLpGKHeJdjisVZ4oXZ2Hra0d2u02T77/3ZOk5BzMszK3We0bzDyRh9g6IjwKSIVHKIHQElDEkx04n1CrazHFhGLWjPnyZtvZ3fp6QHiYfBVCTNyr90ukND/6Iz+8X39yQWMs/X6PanLyB35ghDVuX6Dznv5wiI4Ur792le2bexNJRCLyDovHVxnbPsV4NBt5ETdAaMAF8GVMGG8jcdVknk4Ys3AVFHt4u4oZ23CaL8FUIGN8afHZJAGxsohxHzEah/MmrlKzDnkJHmIpyEvHuAyuXrn1bK51kWNNcn0Jf6GJHUT0blc0UgmlwDtFcQ3UL/wqw+0Bv9oteM4Jnisr/sOG5T9paP6vvZznS3hBOBZrKf/F9/8A7z/WIBvt8vprG3zkU1f4Rz//Efrv/gtUlx5n+PJTnFAFDz708Nd8om9WDs/no878WnXeyjXeFsV7knpEYzHBVjneO6SUxElMEkfU6/HMIj05Ye7kb1RRc1hEFWysDfm1X3hhZo2aLidTK1WQrR3TOCWP59jDp1GLSagnpnXdzC4jZmvfIQXLrCsH+/RWWPC/Vo+P+l0cOPjmgvuRX+Z0ZFN8esddAwIBQGvF5Qcvzc6Zh5N4yIsS6wSmnKwJYgryYBqbxuRya1c3GQ3K2bUcHm+hKDzD/hGxux6mls3Jx0nDp6BRzD2Xuf1hir5m0Hn2QA8AqXBAYLxgYxxx+0aX7Y0hr7xSsrZ+g0cfrXH2bJ3v/e53UE8inn3mGq9f32Nrd0xZKITS+wB9boy9OBiP9i2mxvmGy9seUDnrSHSCjjWjsmQxbdIddDDWoZwEHwKokR6nPUYIIge5ydClBSewY0UeZzTilLIREUURzaTOSrNJ3F5AIxBeonRgiiqto9vtU45zXGzZ2lujKnOElwQa3UDUoDygNUo6Eq2IpKCVRsQ6oqZgbR3qaUQ51lRCUIlAbS5ERFOnrOgancjgcIhIo+p1KlsgVIoyBh05vLCBGMFH7NoQY2A8VD6YwROtqLykESuEdLQSxbBQREIAlkzosOArSz8vqUeWymSUKsHoikgkVEKhtQqsO6LGnhFkfUmkHAZB6TVG5dRUQmIi0khQpYs05D1cuGzRVpJISWlz8mKAKYbkgy7Dzh69zjadfo/ezi7ZsEdR5JMYIYnCYQSkPsZ4QyU9Wmri2OG0QkgY2QJnKwZbXSoMSEnNK0oF0Y3rLNQXOLa4QmVLTl08x9KJVWrNFpk16GrMaJyFQHEJsVNoIfEe0kgRx3VuXlujtrCMPn2ZnISldhu1dBGvPWk0xJclaSPFeIESYPKSdz72MBGWTz39AutqkSJZZH1jxIIquXisho1rPN+pwtg7yZIteHA14rvf+100pUGn0GjFtB86Q6IdV2/uUI132bj1Es3jJ0nrbRAgncGqFOcNHo2M6hRFiZSWNNI0ahErzYjSCLJKs5dZ2klCWRpu7IzpjTLGuSUvS5ROcb5Cy4LCQkzIAq+8AlNR4im8IYmDdsxWijLPiaXEas0wM1/rVf3WLRPA0ZCC9zjB5yoPSN77nsf4b/7ef8qPfOgZdvcC2cG+7DLnRx8uMtujdBRTS2uzXe2gQnmaFNFz4uQxms0mCEGSJmgdXHMPuIWwv0lO98HgcjIJHEcgvAr3lQLFxE1HCGIEUof8YeCJRIh/87OrHdbu3qldvvPbfDkig8ibCFFy5mq0f34cRayurM6Em9nnaWs89AcjdnZ3WV5sc/HimUDhLIJLc3NpiZdf7FBQToCWQIxvEdkG5WgPITRCKEAioxTbuhDG0016bXLor0HSxssIxgN8bx0RNRCtk9iRxY1zvFDBFarygELYcjZe0yc1FVqkFCy2PI0RIDzrxvPTL9zkbzQS/urPdnGpJ7OKre2MYyfqwWtAeMotwWeff5oXS8cVZ9j1kqEXxEIgtcN4yf33nOWv/qXv5dyZJX7jdz/Npz/7Ku+59wLHzx3n2d11huMSv3EN4Qz2qX/J/U8+zuULT8y18xuAMgeE0aPnyFGnvFmNt4uANV+iRHDufAsdK/JigMMx6uZI5VBRjtQlRVYe6vzhUQpaj0MZEw7VfzN4Gn43RtDrlXd5k/1sHZl9R7BcebT34PXkaFgjJARgMAshmru/OHjN8Ed8renxNXs039q3BDPndERveW59rYpH0IuL2b/7yCVNE554/6Pc0W0xV9MD3nPz1CZ7OyOs9Rjr6HaHPPW51zhzdoFaahhl9mDDPJRFxdU3Ntnd7SFlWGecCxNEAWo65gQrunOeWqrQkcCU034Iji1ovvvhFi/czLjnvgvoNOajH/0qauIqaY1hc7Oil0nqTcGf+eHz/IUfu4zD8aUvX+fazQ67nSHjsWX9eoa1U0uYvGOcpl0+Ynb/MZW3ti79UcvbHlDFSiMiSWUNsa4Rtc/SlnVkOcRUBYN8jBAqxDSLCKkUSkRIGSOEQscRMklpNZrE9Qa1Rp1YQk0lSDR2bCikDYx8RuBtRWU8xWgIFHS2tqnKoN2PhKP0gkgoEi2ocMRSkcYRHkcaCVbadVpRjDLVTJsZaYFDU020/B5LGimaccS4DEkA66nmtPQMvUJGnjKJUSJF6BqRFESUtIwijgTDCogiSldSeU2kNImQlD64xCSRpy09zke0U4HEsl14irGgbzyOGqmMMMKTWZBRjPIOby0WT+kl3mbB2qEjvCiIdVh86jomtw4ZgfYW5RRl5SDyxFqj9QmoryKWFf6iDVnVkRSVpTQZRd5h3Bsy6Gww6G/R3dkj7/YYjfuU+RhLiUUTK4XHEUmFR6C0mrDeQSwkifeBlXDUpT+syKsKay3a+5BUD0VSi8nzgvbSCo8tneHVN9YZjUY882qX3Aj6RvG7n32acbTKWC9jvCSTNfJoAac1RXQMa3JMmeOLHqkZUMiYtZuvcM/FC+xsbrE53KOK23Q2Njhzqkbel/zORz7NA9//k2x0upwdjrj3+qs8cPksD9xziigqaSQVmVtglMa8sbbDwmqDlXofbyOiSEEkwSuE1kRopPe4bIystdG1FINAxpLSC24NPOdXJcpXCMKzyCtPI1bESmEiwWI9obQe14jIcsN2d4SV4K2iNAWJUsRSoqTE2pBfRwKVVqgJZfTUsvLtXHLr+MXPfpHnbt9EIFBCIMw8+cCk3LFTTFWe4e/KyjHe8cS7A5HB3MYrZ8QPod7xYwssLDZme5FUk0DiqUvG5J9ZAPL0nwmzppgGXxPie4QA5TzCh3u1hKe1ElGue+rACeCkGpFgKdiPrbhTsjgMtI6u5o86eHhM7vJ1evDANjjp52H63VarTqtZ48K5M8wIqCdjWFWGdrNJWRZIAUJIpNRs73SpzOrkguHCzsPNW9epynxCdBEsaVFNkHffACHBVgjnwQcPA7yBcie4bKkUX18GHSG8OdR3P2uTEB7rFcZF4CucE6xZSa/0ZDsVTnosllU8qfMIa0DFYCS/1614oaj4z5c8v9EXPO8jfjFL+XhzCX8i4vSZk9xz+UFOHDvJd/3wffSWNvnkRz5C3SxA62F4+CGq9eeIrn2eD7znES6cP3voiYm7fn2r5bDo4u/6yzd23W/XomPByvEkJLPOHe/67vu48uwm6zfXOXO2SZIoRsNtjMkPWA9mFo3ZAByh8v+6yj4UOVrM5eCjmrjxaREsrFJM1nI/pYNQQckzm99BJpnRp8+u4b+ORz9f0d/ltIN19o+KO2JAv7ll7sW4W38OkW8chrTzR+bICDl3+SRn7vVceWmL9bU+g8xSOkuUCJT2aGFoRNArFQL44HvP8sADK3z+C6/yAx98mP/mv/pxhqOC//Eff4zRuJo8HRBeoYWhLkr6mxu898E273lwkWdf6KCEwyFII1hq5dx7TvFf/Ocf4vS95/jEJ5/n+EKdV17f4L/+2X/FLz5dYYXhP/jxS/yZ77/I9dtdnnnuJmsbAyyS11/N2dk01OoJ73rfcRYXG0ctBHeM4+Fh/JOBP9/88rYHVF5qkqjOycsPMxqP6HR6CBqUw01wjnqzhUoTlIxCDFCk0FLjpUZpjfYOoWOElxR5hTR9HJqRKBBKI3yBlGCEQhBY1LRU+KrggUfeRbd3mysvPY+zlth5FtKYeiOmdJaa0qRaIoVnoRbjnedUO2WlnrLZHeKUYKXZYDgchvwlhcXJEKvUSmNqtRg5UkilUR5GOJLEE8Xgywpvw6afqQYDFEiDqyJKIanj8EJSygghJakMMRfGWmIh2KwEOEtmHJn1OKvZqwrqCHIJzpUYHVNJqAlBhSSKY7wIWqwoUkRa47XAeocznkoKIiFQTuIVJELilcArRSoVWEmJC+xB3lL3MDBQU4pICbxqkaYtGm3JmbOPIpQDFTO2BVk2osgGqFGf3X6HqrfD9u4m1aiDGWUMB31MlVPZ4M5gjEE4jxAaP3H5FM5jpEU5gfUlqgRvJTdu3KYzKFBeU7mKZ15+AVyEQvKe9z7OHz59k0U5oCZznJT0DSQisDNCDDoG3SKmz+7mBs988UWsS8lyy6rqIoev0PYDfEezJU7xF77vSb70zO+x8dIVHnjy+7hFRb1zg/ajZ1GqhiOhNyjojjwbu4bf+d2P8NLrLxEldbRuoFQKWmFdyOMjhSRt1QIxROmpRQKf5/RdxHI7JdWSYy2NsZLbu2OWGjFKQi2OKFzFRneMEzAuMmpxExFFuMqhREikmlclSZTgvMIrjysNKGiqGkIrvC+JvP2a7+q3bPECqWI+9Nd+hn/5yT/gys3bCK+ChRt/wKpzOBy73mzRarXCrz6wi9ZqDba2tif63XlXSMHSyipKaaJIo5OQvHYWx8NEWJjmKzq0QQnCzuxcSAbuAS9hGjskAeFAlhaJwziQeyOMd6wCF7wjyTJ0E4qZA/+bDMuBe+8fORp+zde7+9HD5SgN5ixpsg9a8pCDS6DVnUKMTGLe/94nDhw31vLc81coSzOzw3nvqCpDr7ONidUkgFyyuLhAvV7jpedfYUqnDArKAlHuhfY4AziEbkC6wIws41AfhC0RtqCbeTYHEYWJ8KJCCo9G8m+N4+lBBnjuF4L/qJkgMsver36eqN3E5J7cwY6TfCQzvFQqvBX82E98kP/qf/8fUeYVG+sDdsfwzz+7y6c++lH2en3cyQfwK2fINl6D4RZytE49TXj88ceopemh5/FHEWXmJMM5APlWBP+7CVR3P/DtV8YDeOqzHQTQXIr4QC1Fa8X6zZLN23u0FxPuvXeBqgrxSDNR88hHEtaaO8HqHRXvcvyoOv7Qt4MWGF9W5B2D1BXeikCg5aPQUjd5k0RokzEWn3uqytKoJ0gt+YYwzvwL/yZ19hPuTg/dfe4daaX6eqf7nGbnKIPc4XvsuzfeHRpOYaNzji9//mW0rTBFyaVjCWo4piYqImk5Vo/oFYQ0JTrC+ZhxVvL6Gx2MtSwsxCgt99c2AC9430LFB9tb/MHf+4ekcczZPcs7TlkuxCCdZ+RKXrzh2C00N7aHnLxQ8dADp+j1evzTX/o9lpYF3/Wdp3nXO1bQkeLDH3+Jzc6I3l7B1nrFzo5lOLJICfc+uMST33EP9Xr6Vpf6t0V52wOquJ4S149TRvejF4ZU65/g5KljDF0dLWocu3gOqYN1JTaSvHLE0mGswVmPEBIVqxB34BzKGkblAKEjYp3O8u9ULscTI9wIn5U0GjUG21uMihGR9DhnaNRrnGo1EIkl9zF16xHW42NJO/JENgoxDy4QVEg0FZ4Sh1TQqKXk3lPlip6VvLJjGfcclYVKxlRWhgSupSOrKqKojtQJpSlR1PEq5HlxUjC2ish7asqSl5bNwpMT3GSiGEonsKVD6hBjljsTjPvSU5tYs7BQl5JIQqQUVBYrHZEW5NaTC4O2AbBIoShlhfMVStaorEdFArxCQ3BBMR4VSRwSLcFiKIuKqrAoAWktBhfizaxzaCvoVzmNKKHWTHFJk3j1PKe9oHA50gms9yArhsMB5bjHuN9hc+Mmo70dxv09Rnu7DIaTRKElKBfi0Q0O6x15WTIqS6TwgVLVaRrtBnlmccYQGYOKY8q8j/IlSkmKsgrtJAi+zgS3CKMto+GAT3/5Rc7dfy/LTc13vee7uHBc8YWP/T6vXN/liYcegKzkAx/4Pj70oz/GjdducfP6VYpBnSRNcc5y7cZtNnsFX/rydX7rt3+H/qiDE5603qJKYqyKgmVqkhtMypDwz3uNlIbBYECceoS0pLoOlWenX9EZWAphQ94PF2h9y6qgMhVOaRpJSj4uw/UmSU9L74glVLYEIqTzDEyJsoa6TvBe4mwQYr9di5QhyfWxU5do175CLGp4oRBeYK1FCo1W8az+lDpcCDh//gKPPP745BePMZYsK+l0ehNihpDawDlHFMecv3iBSGu0EsTxfmD6/EYtpD9SYAgJLsXM1aIUjjiNiSY0vxKBdEBeIbzDOke/aXn3/Zp/u+b4f/d6HH+1S/WEAMlbEGL3EdcRzn0Hq82fccemehiIHa21PHQp5l2fDoiKh4bmsGeOVoqHHrgXNyWTmNxMAO971yNIOdWuhzw4o3HGpXvOT54XzAXLYSrLlSuvIAVcu7WNGGyEa1XZPr7wBDbMcghVzu7Ys9lRlCYMshaCS1LQd5YXraUEbgnJvWPLRpHR/tWnOVOPeF894YKM+U2T84uDBCESdCK5cu0WP/vf/xLDLKPIK5onLpAdv583XvgipqqIvuNJxukiBTXOim1+8M//EHEckSbJmws4X5fwc8Tzn/I3/xEuPU+i+e0ui4kZa5/HWccXPnGVrfVBYJTD0WprLt+3wvWrA0ZDEyDTkS/MvGZ/H20dfjdmE/uP1mqmYvnVZ9bxCBYvLFINKrK9Ia3VBOElL33uFsaG2MbhsOAPP/wqo1HOzZtd/uJfeSfnLqy+qX7GH/5yyCrn5ysdHo+vtU69RSP5m9U90pI3rzyYB3Rivv4dB+4wMM53yznPeFgw6I85f7pOrwNvvJEjpcNawemmJpEaP0k60Rk61ncNO52K3/3YVUbDLu98YgXnAjzrlY41H3h0to3gs90I060w3mA8vO49zyhJJARSeB45t8oH33mBhYWYf/fhL/Jvf/MTrG0NeeL+Jd7x6AOcPtnkhRe3eem1NXqDnLJUvPFaQa9jccKhtOf85RYrq012t8acOLHMLLfdofF+M/fib9d3/W0PqB69+CjRQo3PPf95Eq1oJpblNCaLF1g9f46TK4s4aymtQSlFZA2ytOS2QlqLlzFCeLzwSOdwNiKJYrwQGGPIjcfYEmkMpR0SCUO7VsMXfa699lWcGVP6inaakkQCpzxaKGo+xBcl0pFGHmEEaexp1QTG5gjrsEDuJF6kxDpFJquo2DDs7JGVZhJLEeE85F5zOw9Wk0xGIFPSUhBpMCoAkayMKAk5CJy1SKmJE/CVJI0sWhMSCFuB9QoZhQSVldf0jMc5R24MWkpy50NSS2sQsSTPDDUt8YnAI/FFhagEWhm8UGgtMVYxkAZts+DyqOpI66msR2pJYR3SFMgophQWKQSJDvkdKgSZscRKBUbGCHILsfCMsoxmLQnLvhBYPLmIiaQLfUHQWDrJ6vGLVNmYyw+/H2cVUluqwRZXvvIJdNFnu9PBu5Lu3jad3Q6jwlLYCmchrdVJ0jqJ8bzvve/iC1+6gtQKudCgUnuUVRWeh4wpK4PwHudDrIp3wTJRmoKqrLh83zmWd/uM19dpfOc7aTYWOX3+BBcffYKxP4YbKXSV06otMhx1ePTh87SXj/Hqq9eJmy02ti0//4u/yUuvv0xVWUpTUpYjFpZWiJ1BVCVlOSRWCc6OkHENQ40kjmlqxWJqGVeWc6eXEBZu7w04d7zGPSfqKAneSTb6FSaHs8cWWGgU5KUlyyxVnE/mjsDLCO1D4KwWUOQD4jilETWpvMf6oNUMi6N8s9f0W7r8w//x77O00Gb52Al++B1/l2w8DgJQo46Kl/iH//DvY6xnQjsHUtBs1KglCVGiqdXTYHUVYuJ2NgkinrjmTS1OUgiSNN1P2Cv8IWaniY1q4l2znyhzAmo8dLsD/sHP/TxChBxUH/zxD6C2e7xEeDcQjsJXKAX/qsrZeLnHX378DFG0x5ZQIPeT7b7prjaTIQ5JBXCH/HDHqYd/vEOdOw+wjmiEn/89fBJHCe5iv+5hDXGjls4FcB/uwNwR72m3mjz88IOH6gURvyxKtDIsLra48eu/jR9v7HeotRg+9feC8n60Da5CKMWVzYRxJcBLpIAFrSmdILUwxrMLfDIv+ZhzvCuOEHnJo/U29zYTzmjBX//bf43zZ5awZU6Z5ZSDnEF/wLOv3eC3fvv3aFweoh/76yg8eusV1O3PEQ93WDyxwMrKElL+SYos3+C9/Jt+/bYrx081efjRE9TragJ/PKeOp5jHlimLEmsNN29tc/mBFtwnEd5TVZ6XX+iR5wct2ftKiH3twR322fkD/tBvb6FM35mppWqqTBBC4Z3AmYlhSmrWb3Qn5yhGI8NnPnETpEBpwXhUztow//Ycfp4HDHET08qRxqm5JUfMH7izB3e//pudBne6cR91/txxMWedO3DdSdLcA7B31i9x4CIe2Fjf41f/2WfIspxuN6csPOMi1JVCooSmMxdmt7GTYeQQISV5XtDd7tHv1yc5CgWvjOCVyVx4LYu4bgWrx2soJZDSTxIDg1agpeeXXtzkbz52llc/+jy/+C9+n3vOtvmP/+I7OHu6ySuvbPHcS3tcudLl9tqY3R3H7o6hMobmouPifTWOHU84fW6Vy/fdTxJHE0v/neUbitX8esqbofc/xvK2B1S3truUazdY8oZsUHDi7GXihTrZiy9zcmWJ1eU2TgiKosJJgbee0sKSCwDL+0CxbmyFsAbnHCWOqrT4ImeUjRiPC2IpaCWalXqL4TijX5U4UaGVYCGpcTJN0ZHCCYsQEbWkhsITAxGWRCuEThjnkKHYGBuEh8gJrCnJSknRu4FKE6QOoCV3nrE3xJHCVyWbfU1fSbxzpDollWCVIpZghMD5iEo5WtKhlERIz7g0WCMpSGCy7o2Eo/BlYISrKpy39C3EaIYuwlcVxiliHaGlAyPx3lBYSWwirDcIPNJLKidQOkaUHusqajLELpkoxpoCLTyicrg4ItZh7JUXNKOIoXMIrymrDGst9VodVxqklygJtvQ4WyFsxdC7EIAZxZRYUqHwQhJrgYpaWFdhqhKlIkofgS8xY4MrNb3eiJef+SzeWKI0pSgyhHMoYZHO811Pvoe/8tN/gV/8Z7/Gcy+/wVKjSXt5GaTAjDVxadjoFIxNxKKtEMbghMf4YBWovCPkE/WM4xbvfOwBrnzxdZo2I04SVLrA8olHqC9f5plrPep1S3NBE6uId77jMTrbXXqlZ21vxB/+5qf4xKc+wqAYYrxgMOxQi2POnTvP6sXLSBWRRlOmqAoV1ZAOIm/Jsj1aS23OLh9HKEleFOTGsLLUoFsY1KCkNIpCWIpxBk7zxloXpTSDrCC3Gi9iHDkNFVOUIQm1cDAqxsQyUEKrCcPZcNzHWYEkxIR8u5aXXn6Req0OTPb5iXXHWYu1NiR2tQ5jQ9Jt7yFKFInWeB8S0lobwNEkVpg4jVlcWQ10uBOLRxAy9pOOH6ZkEoc34dnXCa+Uh8pYBqNA6/6KNfz8b36MDeORHnIhEWXG+ceP8d+dbPG/+/Uvszm2bN0YUXpJLDUfXtskfbhCqYRZQpdDUtB0rzpC5rjjuD9wspjEdR066bDgfKDK1MqxL0X5I068Y//0hy471+6pxDYfHH80rroT0h3CjUDIrRcnKd/53e/BGkdRVnz12Rco01qo1d8LnXIGrWNajRonH/pz9PMC/vDXePKHfoAPfegHkULxT3/+57n6wsusCo82JUuR5gaSgVX8D3s5Mk450045vdDk8ccextmKD3/iWT7+uRfobG2yOXKIJ36GMl1A2BxlxtxT6/AdH3wCKRVJnKCmQs6c5W4m4EyH+usWRo4QkacxNV/vpd6m5dzFBKkrUIHkSACR9rSSmKWlxYCBRKAu9z6QV+VZydUrffJ8fxznZ+WhKEOOtBS/GZgSR3w5TLRw6H323lKOR4x7fdZfyCg61f6LNb2ECElm8WCNYzwsDjdk/1YTsDZ1iWa6Bs7QyXRlFEfNsoPgR8zPxP0F6473VjC3nvoDc35KLb6/5IR16+A17pzVR67Pd1SarISzf/Y75D1srnXp7I75ju+5h0Y94fobXb767DYgcV5wpeOmS+nkRDcdRJx3bK4P+Nyncqpi/iUWTDNGN1ua+x9ukkYKrRRaSpSGWqRYbkb8xu9e5zc+/AquyPiRD1zmR3/wAbLC8PFPvs7NG7tESczmVsnV1y1Z5pHacPai5vJDixw/WWNpZYGTJ8+RJvGckuvgjP2TL39y93zbA6rdzhomH6G14vjKCRptT9qC8w9epN1osrS6jI5S0MHfV0mFcoGxzOUgnGVkDB7FqN9hd3sHUWQIKqT2nKp7XKuNcw5nSkRVUU81C40ldArHWw2OpSkmUhRFQZGVCC2IpcAUBc46lNIYCbGoMDKipjReeAqTM8jHgKMoC2IhsLai3qiT1hTDLOe17T18lEKcMLKOKEoh0ngnyLwBZ5EyJnMST0lsYKAEznpkKSlNsFIltqBCMHaemkyosMTKkVWONHGkDqxQSCMZGdBCMDIGay2N2BGplNKMSaIllDGMTc5qrU3lDMplFF5SlCYEbEuFGWeoWDPyDuk1RkiEsRR5jqQgjzRGQD11YDxCarKywjmDrQwSAalCqwhRWqSDSiqy0mCdR1HivCS3JYnMESqhqkbIJKEuDSLRxDpiUMLpS5dYOX2SrLODKwYMRkOsNeyubdKsN/npn/pfUfMVRTFmVGZ8+ctXaNTb3Li+xj/5//0yp87fy8btXQrrGHb2+PLTL1AvK8bDITqtsXDqOF5HdK1FacmD7/h+3PkHObVQp9FcJasUewOoLRmWmop6EjKL28rR2xtwc73H1bWMX/wX/4obG28gnAFrycYDavU6qyfOUj97ibS+SmQ8Qkt0JCmtJNI1rPM0EqirhOGo4GaZI6RAKkkjjujuVuhU4ZIUYw15KdBCkWNI0xoSz2CYMeisUTlNO60zcmC8QkpFJEE2F/A2vAM6EjgPiW7gigqRCKi+fRP7/k//6H9GSD3ZiKdZ7P1EK+nxzk6kjpmukvlFXEpJa2ERqaKJdUmyvHqMBx9+9A7LylQ42N98xEwCOJCI8YAGer+eQEzcKwU973hhb4DxMMDz+6Zg5aUdfsomPNH3HJOKUWV4rjekOy7pCMP/8voaf/2DhmY8cWGcF0bm4ynm//pJ+zi4dXpCvjiYMPgJP1f/oCAopqCQfRe8qWr3zu3wMFqa3u3gBn5U1X3x7GB/Dta4E7QdBlzTHGTee55/4VU2tjp8zwffQ6QjBqMxL7/4CsXO2oG+Cjw//dM/ybvf/S7Onlrlk5/+EnjByVNneODxd4P1k3cq5vs/9EGevLBC7zNP8Z3f/W5+99NP82JliCIJSnBzZ4voxWsMM8O/++Rtvvj0Gt4VyNoiunUaU41oX/1NzqzEnDl1jIX24pyweRfV/DcqdxyJpb45QszbCYydOrtEFKeEXEXhOVSl4dVX91B6jxmB9sQybZ2jKEqSFqzU5CQsT87ynRnjKCuLc362bkzn9T71NYeezVEqgUNlPg3DZI3bl/oFzhjK7pCinzPeHCOE5iADxdzr6wW/869fQcorMwxw2JZ2GERNgdVsns6afIT247AWReyDnQPz/EC355QH8z8esXzgD1QELzgMrY4CigfA1ey688DPH+pO6Hyt7qg3E156cY80ShgOi7n8UJN6k0Vs/jzhA7PrKLO0fEygXHQH+uDx9LqOL36my0zBJTxKeqT0xJEgTgqeeOQkP/a99+Kl4otfucGtjT06OxnjseH2bcPOXmCWPnOv5MEHlzl2rMbiUhMdRyRpnTRN5wDfn1I5sDf6wwf/2MrbHlD90I/9CMNeL2gZDJy7cAYRR9jzD9JqNfE4hFToOKaJwDqDV7AgQu6Z0nrc9i7jLKO/t0N/b5uFdo3UeyI8OgpapUpArBJ8XCGriXVLC1Ln6A4GJPWIVMLxhZieD+56ReFx0mIQWBSLChqRpFvmNEVI1qulIEkC6QRopFIkUuJw3NrrMB5XNGsJ1ueMxx0aUiFTibUVUjiUrKOkIJUe4cAKQewFHVuiZI00hVSHtCleWKQRRLWQu6aSUE80Na0o8wolc5aTwEiYI9EIFGNUmeATSWVhu9OlpjT1CLaKEdJAPYkoiPCmpCoLSuHxKiapAkAqnWGsI3yRgRRYJDUlcM6x5QypiNBxirUl46IiUmnQrLRjXAVJlKKVpsj79GyBlimR9lQqJXIw8h7cmKoaoIVgoCOUTvAKBnmObt9LWstpLNzPuCqJ+xusXf0ypA1KZ0FabNmj5T3eevrddRbqCc3lOpfPNrnRMwxNgXEeS8W1rVv88t//B4i9DolOefef/WHOfMeT7F65Qg3FiWPHWKoNkM06b1zb4LHvej/GVhhnWGgqSiN4+oXXOX/+Ihtd+Kf/8g/47Fe+SFaO8TYwy+XlmEa7yYnV00TtRRYaLdIkwmqF1IY0qoGtISQ4IxnaksRBOw3xNNaW1Os1EgVj44NLyWjMYi3ibFNQUymj3NLLLd2xIYpSVpaP0W4k9IcF1jpiLbBOU1FAFVwcrXBgFHgB2qPTCOMdSn77svzpuI4UmsbCcd7xwT/D53/n1ymyEd/x3of4jvc/zj/5hd+g2x9wUCM4/ejQkead73uSRr0NQgbt7UQAcTAnAE0EI+9nYsk0T4w/IDzMswFON20xO16ZkHyzAm7fuIIxnntVzIrSDAeSnY0xn7qyw9a44oqveKqf4SZCkZQ6KCu8mNuwj5Y15vt5lMzmPQyGObu7fbRSNBoJy8vNg+d5x3CYU5QlOtIstOozQayqKorS0G7WjnwuhxTTd7QOIC8rbtzewVmHELCy1GZ1uXWgR346fAcucRSQ2hfwPJLKVHzuc19gd6fD+to2V155lSnIKoyCaGH/Ps6AGVBbPEWul3nuRsnNrRwQ7HWH3Li+TT323LpxGyEUQy/5xBtbPLu+x7GNLlEs+Hv/9d/lwrlzGOGoKse/+Ncf5p/84sfIF5+k8Y6fpHbiHorNlxl96R+hhOPEhZP8yId+CDERrKZjdFjEuGPUvk65Y154/qaW+cv9Kcpm36zyxDvPUqvPz+Uw+u978tIB/UggnfRTWTlYwb3bXyd8sHoPBgM2bt/GGjtnpRHz0/SAMsSz/87MkpILwdQd2/v9dK8y+CYH1+PJb+PRiH6vYnO9hCLj3BlNljm21sX+fef7Mfk76Nu573ebIxMwdIeuZNomcfCHwwaYAz8cOn547og7Phz59Q4tytzbcqeS6SC4m8dTRzVmXmEzO+KDddIRs71RABkg0JGaG7uwR1jnYeY6HsCUx+EFtJcabGzlYMKARlFI9B5i9QRVMeVCncT6SkB4KuP5K3/xAR5/8AS9Qc7zL69x7Y1djPNcu1qwsyspK0G9Jbn8YJ2TZ2s89sglavUoKM4mysL5R3O3of2TK3ebNH885W0PqI4dO83Zc5fQ0oOU6MpQAiYVJGmMcA4vPcK5Sa7viNF4zHAwprO1xiDPwHucBl2PWVlaotPZpVMWLNV1CO6NFVGiUU6A12hhEdKBAiEVSZLQrAlUFIRKOzaYIqemPN6FJH6RMPQL6OcGISWZk9QaDYglrtDUUBivqLBoKbFVgckKcm+Jaim1ZhN0grIZvqgocaS6hncFpgo5meJIBcHWO6w1YEc4D9IphNTgJcttDRSkWpFqhVQGaT35IEMD3lakxlNag7QVxkOWJDRcgcr7mEqjmnWcl3hb4Kxls1NRazTxJpj9y8pDnCDiNLhFVhXearAl3ki881RaIrQk1hE4R7ezQ5X3aS+voHxJlVsKMwAHanGVQlgwOaPhHqbM0DKi3lgkMw7jSoQLgb95NgIV0UwaxEmNvKoQUUw6oUrPR12MkTRXLtEbWKQb4X3MbhGxKyK8dySNJqPxiPPHT/Hnf+LP8XP/319DWY8znsJAObTYUUaSj6jkGJlVNNUyT2+s8a4HLvO93/MI5062MLu3+MpLNxmXFSfOncc4Sadv2OuPWBtqPvrLf8hHP/5R1nduEOsUZSyFydGJ5uzJkzSWTlOrL1JbPEV78RRxnCK8xBYVRVbhlZ7loTDC4ZTEyAgpIanF1HXEyHmaTUW7oVmIJLmDEsHmXk5nZPCuxFjwQiJEyqhQlFQoKUKCVW1QTiGUoHRVyP9jPZGEkmA5jISm74o/tTXgj1r+9t/+P/DuhxWthQU+9qzki78To2RJI41Ybas5muCwYCsVNHVT0CSVZO3WOnHcRUqFlFOBJpQpgUUoR1hfBHf49B9wq5vKXhMJatDbDbn1EAx6fRCCtqxx3ii+N0q4bTQ/W5bseI/1kmPHTnDu3GlKJ8hLz253xGBc0azFh5CGOKAJd87Pfp4GQYPEWoe1FiElu3s9tra7rC63yYuCsipJYj0bM2MdV167zjjPWWg3ufeeczgXwHleGHa7I5qNGrFWnD25gBRQVhbr3JFxDvttDX/y0uCsI63FdLsjdvf6tBrJRDSZPLN9RIAnJAtXWh5pwPKekMRXeIrScOXlK5SVxQvIXczExxPqpxGqNnmcHqo+3vYpjaM7LNnrDBnnITWG8BJnPGiHMQ6nWnzsM6/ivMWUEb/8218mlo7/5//0S6ysLuM8jIY5V/Yk/WQVdfm7EXsvMfrih/HFkB/64HtYWWwH1+UDgPiIDom3KGLMWQzulkdoRt//78uRZaocOSDQe5hmlDgohO8PsNKT+NM5wAOCei1mebk9k+WD9XvemjGZ40w/7/87f7N5a+LMsiL2n7MQAuc9b7z2Cvk449I9E9KbzPLKixmDXhlcl6fzY4LTqvJgP+buvn8/5sRczyyu0R+qEBRKcxPsbmD7kHvwfp0JMJz9PFksZ30Xc8cPt3ru7TlqTTiyHYfrHgUTD//quXS5zb2Xl1BKISeAyTmCu7gL68PttR5PfXEz/GZdYCyexPR778jyEj9Zj0+cqPFTP/kwaRJNQLJkZh0TATgrJVBKohWcPh7zxrUtnn/hBpX17GxX3LjpGI0lAsfps5aLl9vce98pHnz0PsQhRekUqIsDx76Vyh/vCvW2B1SRCix0cRSDdVQ+YqGRsNvrMx6OaCcpGM+uyTCjir1Oj0akidMU1VpA5GP6vR7dzg79fg9TFSAFaE1R1EAVxHFFO0mo1xSNaJJEM/Y04hSlPMI7UpVSSwWohOVYsDt0KOsRxqKtwktBIhxKK4aFoRQGGXnSSFGvxVgk2guMlUQquAxWJkdZSyQl9Ugg7ZDSC8YjQb2W0E4sxkmkj4L7wFgEFzkJdlySO4PzEpvEwaqU1hHGUjpPYj2lqBFZTaEqlhsWZy3Xtgf0C0+VJDhniYVHmJxRrvDeECmFHRUUZYXzZXjppaYoOigPhTFUVQZpDZ00sRJskhJ7hXeWcX+XxaVVpAugpDSezriAuEEjSZBVhhAWLR3FYI9xPkKMdsBYrCpQqk6ruRgIGbQnUQpReJz0xEmbzBmMq9CmQ1L0yF2BcYLeaIBUdaKaRErLeLjB9o0r5IMBf/s//S/58z/5/XiXUas1GGcFPit56ss7vPr6Nbq9Lv/D3/+HZNmIi4w4497g1MmEkW7R7w+59twXOL4gqHc2uPblAR8e5Jw/fQIV5WSVQUuFLeHp566QHDvD7et7/Po//01eufoSuS9ROkKYnDwfsnJyle96xz1833e8h+e3JOtZExelxAKEMWitkFEa/NydQHmBTELSaFNaepWgFkeIwlFqx+piihZQlYYbI89ikmCEI4k0D55QbA3gle0xsU5w0pGVOVKGvGCmKjGVRSHRuoZ3HpN1qHREmtTAeQpj0KJCF9++iX0fvT+hs7PBxuY2b7ww4snvfB94w/Mvf5XPfeUKWV6E3CyT7O/t9gKnz51HTjav/e2lggnJCRMyiqkkJMT8JnRQWjggF8zt3tPPhwkunDUIJHG9SX1hld72dQyeHChLxbO7Qzp5ga61iIRmcXmZpeVlKiMYl47Xb2yhtaJViybtEgeEGTe5j7VuQovrGY9zer0hfqJBnYKtKdC7tZ7jnEMKQZpGeOcoyhIEM7fAbm/I08+9ghAhFYSYaM8H/SGRlizUFDpSvPzaGuOsnFjzptr8fX38QdvavsDmfJAnNrZ2mWnEEURaoZQEL/AiWLHuvXgS72F9fZfFhSa1egIEMHXljbXgYZAVFMaiFh7ClX1863y4U5XBhErfiwnAmjxTY2wYq/6Aogqxhs1mjWMrTawd4fE4vcLIL4VzJp6XJYbf/UKOcNeQFAjhaLznp9GPn6UwliW7xWK6Sy5K2s0ap06fOgCivplihAcOeJ/Ola8lPB0lDx9V7pBH3wZFCDBFRlXks3c+SlJ0HBNm4iGJfIaEJs9wskbMIICSJCo5eI8D3/wRn95SS2cXEpOGSwErx44x6Hbpd/sID3GieOixOg8+2kAgsc5hJu9ymVs+8/EBxUyPNnk3/Xwrp2qNyZyaIZ65Fh+of2TX5ho6f/wAVAs/zV/7QP35lfdOM9X0KoKDiqyjLVCTix6Y6Idm81wb5z0PvPesbfQZjgqSmkSpqQXqoKZiMCyYeiR0+0OstyCgKIK85Z2bge4ir/jKszfRWu4nXp41bLq2+7BPCUcaS7IsIx/nbNyGjQ2HsY5L96Wcvyeh3hA8/u7HaLcX5sDo/GXfjtx9b7287QFVPhhAnmCiiMJUlFnFzbUBw14PnKT0Jfl4SJGNUXFKs5YiFpvc2uqyt7MRzNyjDFdOVgal0EnKQtokWW4Fa09l6BWGWwPLgpAIF9ztlhslp5oN6qlnozsi6gkiMaZwVQhq99BMI3QCWItzoH3MQhyxWitpxxovJfV6k1FRYIxHS4mOCHmyYkliNDDGFCOUVTSUoF3XtOueRFRESYxzIFKNk4KqHFNYTakLUhEjhSBShmbiWV1ReAnSQmahZIQvDUXHsjYqqRwMcsPKyioLx1aorCFp1LC2Ii8LRoOcndsdSBN05PHGAILcZBTGQFzHoxDSkziDHe8gJDRkm7SZUGQ5l87WSZuG9Y1tFpabjMcjYlshpGdQDBiPLfl4TLNWw3gREhIXnSC8lAbrevT3blNPa0iVEGuNKy1OCby4gSmGaELS37waUWU5Q2vwRHhn8Epz6YGH+OpT1/FY6otN0iQhqrfojgxZnnHy9HFu39ykqnK63U0kkGcJZVVgopiL9z7E3/nftMh8yT/9ld9nr1fg4whnHB/+/Gf41x/7JNoGV7AP/fAPsHriPA89eD8yWeRf/Mpv88nPfJpxPkCjiJxlnI/xseDEmTM8eM9J7jm9SmvlOPfEKbu3ChIZYfFUUiGkwzmLE4pIeApTEpUSCHE1CQ7laxgUPeModkecWG7RatSxWYUXksGoZDwacN3k2MzivWZclUQqRrlAfBDLCJ0q8IF8A2+J4oQkXsETBNPUSrwGGaWU+tt3MX3qmdtIpTHGcWw15tjqCUDw2msv88ijD9JeaASWpCikCBhlht3OANjfoGdbqghEJdMd+q5WlhlQ2D/gD1xoX1OtI0V7oYnSCucdvY7m9hsCnTZorpylt3eLr1YZV4Xh6fWCrNHk5Nn7kTq4f3opuLG2QxInLC8tThigoKyqifVMzgSr2X8TV2Q/a1eg0Z8GdIe/U9dEMBM8vbDYpl6vU1Yl452d+Y4A4JyllkY0G/U5LXu43mvX1wFJlhVUxs0YEGfAwbsZfBAzQWXfRiMEOBtcqKYaaqU0i0v1ifASLGZZUbK710Mpxc3bmxRlyfLyAh6w1tHvDej3RvR7XUxZ4NxuyEXlynDdqoOv+kyedDhmcwBGWYnY67K3s0uWjQHPOP//t/fnsZZmd303+lnTM+x57zOfGrqrR4/YYOOmiTHc676YQQRyI70MVkQIAUGMBApBDkJMuZGw4Cp5k4hAIiXwRyJQIoF5hQi8xjZxIKaDHQ+0h6K73d1V3VV1qs6w52dca71/7HNOnX2mOlVd3TV4f0v71N7rWfNaz2/9hrV+K2FzsMm1tavYMsf7dSiG22O97b3ACzwKj0KtvhG5+BBlPsI9/38jLv8Vjz3xTr7+W76bPE+3p5bfx6DfDuxhTjk5e3QrtTgszb1LQSYQAnQQIPVkCxaAlGoPEy8OWPn2suLTWn9xgg7ZIyjsd6pwGDO8PaiHlwet1jzVaoNGc4T32x7ittsigCzPSdMUgSBNUwajkrKYnP1ybpK/30PShFCAxFlBkSeTawzYY0natdxvm6629To72/92HVoAzrvrDn62O9G7PW3ebpvg+jY3uf3Z2+i9Vj6/82/vZN81cTkGQz8517Y37b48dp1P7Hm227c7ZW+fLR0NMy69nHLllYzGnCCMmJzX9YLdLdgeivJ6Pw0HY8qywMPEUZoTXL2cYu0kRl44Xrywyfa1envOdm0LVLuWO4/AYQJIRpb1qx6bS6oNQbtiOfdAha978nEanRZS6Cl5f18XT+HueWdfn5rc9wLV2pVLVKtVLCVJlpCkKdpO7n0ZJRnjfIDUEXGgwedc3tiilrdYWp6jOVdnmAx4eX2T7HIX5y1IQRg3qMYT98a1uEniStIipRwVlNaRpxaflvTSMRe7KcpZNI5KKFmIDaFSFM5TD2GcB8zXQiKtkYGn1m4zGPdJhwG6WqVMM/r9EQ5J4ez2lqGYSCuM12yMhySlpbAFztmJxz1RoHSwfRbJI0wJgcOVBqk1TVVQlw4pPIOiJM0dw0Ki5QbVeHLWLM08uZ2c1bqwmaFCRT0MiJXk8rXLXLiyxjizqCBCB4o8HxGjqNcjXDGgzAqkDiitASvxpUI4izUO4wXDZIjRCqxFuoxq2KShcgQSmcFSNSJHMF+r0B902ehtsrLU4MXLm4xTR5KMCHWIkBKnFMI7kqyYmLaNxOYZzk8u2hUIOq0KUk4uKT69UseWluFYoehwrbvJVndMmo65tt5n/ZU+/W5KbJoTpwxa80d/8jSjwSbOWl65cAWkp0hG5KMROtATJx9hyIULm/z/fu0/U6lWsTrEqdN0luErVzP0wiM89NYqW6MB+XCL0XDAn/yPp9nMFE+8c8j//dGP8pXLF5BlTu4sLh/hioxmq8Pi8kSYeuhUg697+8OMy5L1UcZypaSbOEorEVbhA4Erc1LrETpEaYPTAuU0pSuxBpSQ2NKSZxmZEpSFp3AlZeFAeSwK4cARMibBuZJ0OMLFVUxUJ9YC6QWZcyhpcU7ihUZ5h0WC0tgyIRCGcttKJbN71ynFYNDH2onVRQox4XGl5Gve9kYeODVPrRqyY4nqDsa8fGkTtoaTxHssVLvbIbaFFBB4sdej1F6NsjvAVR7Q2ovJQluv1zh1ehnnHJ//3BfY2thChzHjwRbpc5+mLHOGwpKogIGJqAQ1WkGIVGLiLIIJE2KdZbO7hRRyey/89UuErwtUoLUmNBohr5+9cNsXe+5szdnNl20t6/aG6t5gRH84mha49mGc5CTp1nZH7IpseA/1SsRjZzs8f7HLKC2p1yIePLuw6wbcO0dZ2onbYCkYjVJeubyJx+9a206fXqBejRBCcG29R3dztN3n25a30rJ2ZWOyrdV5XnjpCi9eWGNHCPMegkBz7twZtjZeptu9PDmfsNUDJHg7cRwzpQaftOLq5Q02txK2ul2KpAfAx/70o/zPT/4VzlnyLMf7a1PCthB+IlihEMJg8wXIhhRbz3O60uct3/L1LC8uI4UnCsPrQtye2fSqsX/ynZA/uW0i3d3Dmb0qKKUn56v3NmjnzOReZnsv9klZB2WhyeAc1kXXjSEncFR9VPl7HOUYE9BsB9vB06MbVSo0YXf7Wa1RuW7S2ZZK/PXsUEoThiFKKUbDPkWW777rO3f5OefoddcnW9h2znQJMfFiuytwCcKoSrA797n+TOycHbqe585ugH5vg3KyL3HbEnS91yZ30EnCuHo9nz0vQZIkjEbjKWMXeJSUSCmpNtpIdd0kNCWcbtdZbPfhYNDDO8fVK2MEFlvAYJTRG0ycH+1c0r5byh4hLh2XFLnHlQJbOLwXjIduW4jzFJlna6ucLnzKijc10EghKHLwpWRpQfCOdzVYOD3P4uoy9WYTue2c6bC59NUuTMFXgUDViD02H+HLgoYWGFK8T+kOh1y+vMEwzciTAisFoQmIqhWskDSLNp1WjUa1CirELyzT39wijmOs98RRlVazQpEmBIWlngVEPiUtc8pkhBUQhsFkd2AYoUWBs46r6eSsVhRoQi9xCaxZy+m5gPlAMx71qAqwWYa0DoMgVoJRURIKTS0IqMcBW4Vn2C/IXUS7XiMwAYUPSQFrwfYEK0sVcg1n5poEClIhyJKcZOhY6w3wWLI8oyIVqRVk2YB6JWKclSgnkMozsCWRkwwG0JxvsOUFhRZEWqGrAikcZZbSnqtQDSMCYRgVgkG/R5qmaOFxOCwFVeVxpaJwDuUhLUuiQBM3IhyekXdUhKQ/LhnmOXFoKWVIq1VDmpBxXnB2ZZHhqGBrmE5cFBc5Mk2wHoyQZIOUXHqMgMgYmnVFgOdUI2apXSV1ASu1GoP+gJfSggtrG/gyp0y7JM4yGFxl6+qXtrVlOy5KBTqMCMMYJwRpkRNUIpyYXHDrvMTlBUFUIUn7PPOFp1E6Qkizzci5yf1OVmC9xDO5t8mWOa7IePovPsGXz38FT4koMzJb4NMUFMTtOq1GlfkmfO3jLd5wZolqUCHJYgKVsWFDim3NXhkIMjtGOYMwBlEUgKMsNVE1xJeK0ARIC15L8iwlKTWBCVFKIAJDOzaUVrLRH5MkY+KogncWEUYoY7DlRJs1dsXEuYXQWFcSeU+eZ1glCWSACg2FEoDGWkde3rtu02tVgwmC3RV3536xlYUqWgu8n9z5YT288NIal69sbLuthx1mRwpJtRJjnaNer7M43yRJC16+tI7zE8tMWZZU4xDwDMcJO8knG0PEFOPVatZZXuxQ2omb9CxJKUrLaDgmSVKEUpNtsKVFSI33gkcff5zVlVXSvKTbG1GWFq0VSk4ugBYIFufaLM612djqs9UbIaUkCCZadOss/WGC9yXeOZr1KmEYbJ8dgzTVDIcpyyuL1Ou1bSFHMByOeOHFlwEIQ4PRk74ZJylKCk6fWppsudvu20uX1xknOQKI4wC1zTxJAUpqLq2PqVUjqhVPox6z0GlMNOVC0O8PSLMMJQNarTrWOubmW9su6z0XLq7hracsHVJIAhPQaU/KFkJgnWNjo0tZMrlbDACPMRolJ+9ukU/OEMZxxNkHH6M9GOKd5crli9tWJ3mACd4Zy888/adTwipCMOp3GfW71yNNipy4nRbXGeilpXne+pbH+dz5S1z7ykUUjlMPvZE3Pvb4daF3m8N7NSzESXY13Qlm6Xbb215viN1B2hZudpQoN+jMo8bgetB0z9xsPx1Q1JygLvutETsCy04cYwwL80sHX4G9kuMegaxSqUy2tu3LNBkPSca9XacyOwqpvVKlEIJGs0290ZoSTKcrLaZ+eg/JaEhZFHssZtuFbluFdRCytHJ2V/m1N/1g0EWINZz1hNFky2aaTLbDSymZm18iCMPt+h7di847knSMLQsWFgL+X//vNs7Bp/+qz4UXC0Zju2ugu96U634MbeEoc8/KmSpYT1E60swz6E6s5aWFYry37B0Bd8db4fW6CCbeWKUUvOuJKo882kKbCs1mk1anc9CqecS83ZlPN2PFvl9w3wtU//tTn0FFhma9yspSk1YjQKKoRorheIyVAhMarPDUoxpnHnyIpYdOU6/UUYEkTVIeW5xjdXkZKzO0MqggoNNooLxife0aG9111tY2uPbyJsOyJIwkxSCh1mjifUa7WqEsCi5fWUcpB2XBoJ+RpJ7FRot6cw754ArSFFTzMWmSMVdPUa02Y2tpDzOuXt6Y3C+jwHpPM1CESjAUAhRAiRIgoxqNOGKxFRJEimoY0KhGpKM+eZrjhEQHOQuxxtkSG2h63QKtNc1AEPkELwSF1lgvMDokc2CqLXrVBmcfWuFNtZBGvU7UrKOiGIljMEhIBwOGgyGXrlxloz9EqirKgHeCcZ7TywqCIKBwKdp6CmcRzjPuQnulzVK7Tr+fUqvW+ebHV3BK8OLlLa5sjukOuhSFZ+AHxLUa1uUT1/auABlvMzwOm0PTaIIA0qwk0gEL9YizCxXGackbzq4QVySXewOWljuoRoUkK2lsNdnolyS9nM1rVwC3eyxDSI3UGoyCLCdQYJRGSLW7fQAhCZXCKxAq3A6f6Ja89/iixNrJtiLvLYUoUQ6syxH5iPF4nUBXsDbDZwlaS+pzc5xeXebr3nyOd77xAd702GPMtTp85ksv89zVhCwH4wVGMBHGvMGWIZFReEpQkkKHaAHjEnzpcSKlVqvgZEAYthmPC3p5irSWerXO5lBgcaAN7fk2IncUmcdEASBJrEV5gbeTsZNBhTA0+NIijKGuDPiSQghE6SgmJ2cx8t5lhyqxIgwnDhqK0vL881dwznPmVAtXCl650iMMDEtLLZqNGlevdbetNNetIkFgeOThVXqDBKMClhY7eA+rK5OFqtcf88wXX+TRc6fwzvHX51/Auh0hdCJM7eybDwPDXLvJ6VOL5IXl4//9f7G+3sN5R57n2x6gFFIbPKB1jFaa+c4cywsdgsDwpWdfotsb88i5UywtNPn0Z/+GwloqccTq8gK1WpXFhZwoCKhWY7TUDIYj/upzXyQIJkLU2TOLLC12JlX0nvWNPi9dWCMKQ8Jo8g7gBVpPnNEIBG987Axz7QYAzz7/MmmScu6BVbRWeD+5mHjQT1BSIaXkzW98iEo0cTcvty1cn/vCRd7xtnPEkd7DsE1c9Z//yhr9wZj5Tp12u4ExmvlOY6eKJOOM0Shl0J8waI1GldOn53cZFe89n/7ff0OvPyIKJ2fIrHWcOrNCo14jzzPWLq8BUBSWhYUllpZXkUIyGg1I0gyt9DaTNdEwF3lOnmcIJMnoujfIna1Eux7XdtkPSavV5A2PPwxics+Vd7C0tMCjjzxCe36FUZKAEJxeWUTuvShoiie9uXfurn5D7+rKnQw7o3zTTdmf4JA9eYdt0zs0/W3icAVMLgqfytbv+30wza4wuZv++h7AA4KHmDj0qTda29v39jTEbV9XASAkxuhpYe2QvK4LsROElRpi+yLzvYLiTh2VMZPtzodsjzQmoFJtTrY+bjuQUDrcVZJItb2Vc89rLfb83bF0CyGIKxO64k1EWPHgPO94V8TC/ID/+T+3Jtv3PLtn6A5uXfA88GCTfjchCB3Pnh9PlbP71+/fEzBxrrPT8c2GYnU1orNQ5ewDDeaWmiyfOTXZsbCvL/d+PX4+3wGR6kYaiNcQ971AZcOAer3G0tIcvvRoP2H4LHDqzCLBRp/RCNLSsfzgGVqdFm9+01vpZxn10BBWA4SXNMKYNBuhoog4qtCMNb08R8Y1zrRbLJ97hHQ44svnv8KF59fQlZQ0y1mtRgQabGxQ3Yg8kwgyTABKayQBo75FyTqqE3BqucXGc8/SSw3pMCUMLenGgEYQI4VCRBGxCDjTrFONYX2rP3EtHIWsViXLdUl7TrGxuU4jmCNShlotYjDs057vYIIIax2b6RYvb0zOEDkZMcoF13Iw0mGdx4qAEomUGqsM48RRlQmD3os88qZHeOjcAs1WHYtHo6nFVfpRwGgwor+ZUa81GfW7FOkY4UJCFVIqT+kzIj0RgCJKcBmDrODytS1Wls9AP2Pcz5G+RZlnVEPFcrvOeJyTpo71wYjBVo9YhzihcUzubBKBBl8SxVUA6rHAuCGDfko9Crna8zx8qoH0BVevljzxxscYZ5aXNjbpj0uESUh1RlxdQ4jJVkfBZLuSdFAMRxgdABNPixVt0FKSb+/Vdr6cLJhucoauyEqk0iAkZZniXYkUCqkDnAclti951hMLT5aluMIiA0NzYYGFRpOHz66wvDTPu99whscefZBuP+fly5dIc4t3ll7mKLxAaI0oPTbpkqUZ/dwS+QJbOqJKG6s0hVRIKSglZDZAyIw0zQikIvcZRkGeODI3YZbzIscnI0qhcVpighq2dHTqVXrDMVpolACXDhk6j9MBWigSmyJ0gLMWLTTCW7RwSBPcQSrw6qCNxgSaHeJc5CVl6XjuK5eI4oiiBJCMk4zBMCWOI4SAxx5apVaNQEq2toZ88fwreA+nV+YYDcdUKhHxtnaziCxaGr787CU8nkcfOovRiivXtgDHtfXJOcE4DHj7Wx6htI7nvnIZozRvfvwhkrMTC5XzjudevMLSXI3hMCErCur1BkEQ0BumfPHZV3jzG87ypsfOMhglrG8O8N5tO5EQbG71KJ2l3a7TdI5nz1/glbzg9OkVirKkEoa88x1vQGuFMWp7a99ksZ+fb9HuNPjSl1/i8pWru/1VlhaxramVQmxbowSPP3oG78W2Jes6S/jYI6cJtvtb64kXKWcd3e6QwTjDaMX6xoCF+TpxHFCUlhcuXqG0niTJ8Dh2lNh7t9cIAQ8+sHx9YKf5HSaWRAgDw8Jckze98SxCCAbDhC/9zWXWrvZpNSPe9jWPbGutr8u5HhiPNmg0GiwszPGOr3sTctuF8P/+zF/zF3/+NOCoVKu0Wk2K0nLt6tVdxxpBGBGYkEcefZjcwsJcm7e+9XGsB60UtUq4ezbjsUZ1u7bi+pbIPergnW2aR2E/f/1ayiq3ws7cB7LTsdg7365vprv1Vt/U5s4jzAa3UoP9FqrDMj5u/HcFDHFI2dsBYRSzuHx2O+gQydJvO/PYVjYdN+/3F95uz++rpNj3/0EReOdJHFeI4speeXCqXrseEvcJNlMC5PbfxaVVdvwT7TRg7dJLeGv5/9QVRekmF8NPZC2KsuSZzwzIc8Hc8sRTaaPlSVNwpJx7RJFnalchPHW/nwex7SbfOU+7Y6g3QqRUVCuG+cWAVrvN4vLpyV2VO0Ty0MmxXwzd++QO2aaOEKZeazq3g/teoApMhygKUSLi3ENNfDZE6IAgiylzS6c+z2YK45GntbjEm97+RtqdFnNKYaRBKIkrSwZ5hgurVOIqtSBAhQHLNUWr0WYwTnEe+ija84v0NgpkllCJA5Y7MSoveO7SJq25kGScMhhlJElBVQlSrZFa8NzaJq35h0hthcrSA1TTl1ltWwSO9fVrdK/1USomHxWcWTC8eSWiJiyX4jk+d7GH0xUqtSYoRz+HsDlPvbNI1GqShYbKSkirzBmXjl7fsbTYIggkVzcKklwgCkPuDLktkIEnUhrhFN0iw9uMufYCubUEvqDdqLCxtYVDsjHoUY9DQh0y3BpQZBLnHFlZ4rXGuCqF1WgFaT5CSUB7clvgvECLANSI1VNLxKrCuVXPm84ss9YbkeWOWGta8zX6vYTnRxlB1CQvS4a5Q3s/0c6W4EtBLjVhYEBqUu8JQ0N9tU6rXeXxh86w3JSsztfIvWajP8JEjkWjyS5fo24DBumY3ETUOvN4Z7FFjitLfOnwwuPKEukdgYiQOpxot4TAIyfb3xzb+75LpAbv8uuXLgoFeHyZghdYse0owk/u5JIO4maHRr3GQ6dO02pVqVZDlKqwmRmev5ySesXL10ouDwpsKehUaxQCysJS5CBFhagSEgYeoyyFD/D5mFAVNGPDKC9AKMajPi6oEpqIMs8m54NKjRaScWFp1wOq1ZCw3cApTZFbxmjwDqUkYRRPLgB2DqMMSoAxIQZPbu1kz6koKWwOIkAiyQt3hynBrWPvVhalJPPzDfK8ZJykrC616czVcR62uiPm5prMdepIIViYb2GMASA0hjCYWFSiMKASh2izc1kw1GoR73zHI7uLcCWa3DS/uDjHcDTe3hboEFJy+Vqf4ThlOEw4tdTm7JkVxuOUtWvrhFHEy9eGdObnqFRyrLWUDvJy4pHPWsfa+oBmPWau1aIoJwv16VNLINj1eCfEpK0PPDgRpPK8JEnHrCxPLFzG7HOXu817aCVZmG8RxxNtrQCEFATG4JyjWomuH8yecjs1YQza7er+3gc/2Qo4SjOccywvtdg9E7V9riKODKV1nFmdR0pBbfuM1JRLaK4LWAcW1x0rj4eHzi1vW/YmB+6b9Spve/OEqdNaodS2U4Fda9Dk75kzZ6lUG9RrFWrV+jYtsGys95BS473n1OkzvPubnqTfH/IHv/9/UeQZQki+9p3vAO949ze+C6U0eE+57TVNCnmd4ZpiK/ew49uWrtvJNBzHEr1W23nud2EKePWNvM0dv9e6dZKqHRbv1VZpf/odu8oOfZzMt/2S1/bukG3F52EWrr1yzMFCD2H7pzLZ0VAckXwq/t5I+2xxNzRNTguCQgi0iai1KlSb8a731okHV0eel5z/6xE4waOPTzxJG+MJI0m1VmG+E+4qavYK77t12z7j6j1IPdnxoLYdjLTml6jWqkgp91fx8PYfCLmb3uDXikodjfteoBImQMuQWlQjEBG1TkRgIrzIubreZaNXUBZDrAip1FukpeDixStUqjHVVoMoqmCkp1qdOCeoBiEWQc2EOCEprMdZydZojM0kneocyXJKd3OLskjJxikrtTrnFuH8K+sMNIyGA5LMYgPJ0EYgPSV9nvz6Dt4oVL3B6kOP8dKVVwhw1BvznHtojmpgGGYFGseLecDLawPSUiPCObpOci2FqFnnVKtOHFV4pZ+yGKWc60jmqxHW1rl6YY0r17okfuIRLEs1pQwmF3tqIJxsr8mdQgtB1UjmHnmY0WBM5BUL7Zh6pU5UMchYsdw6TdYf03MF9cUGm71NAjW5y6gsNIkoCYTFS0tNS6wSKBXilZioW1yKJKC/OeKq0Lz76x5kfqlOVA0pcXRHBRde3mRYSLqjDC8igrBBml1DaIVREms0okxw3pNJQTWMcFaRyBKdSBqLNTaHGedWmoyGCdIa2nGFYVEiZIRYbaDWtlhbV6yeepgoClnfuESYF4zHfXILCIfNC8JIE5s6eWoJ4xglW2ghcUy8ovnAsvrAKWzpKG2BlIKisBNvgwi0FgyHQ7yT5NuXTMRxneUzj7HUXmCp3qAaxTTma6yeajPfbNCuV6lXAy5e7VPVJWdamvVBSacq6KYOr8qJe3KpEErjtAZboIQDGTFIJ2e1VFDBS40tCkJnkXlJng+RUQ0TV6kYTegFmbNEJiQ0CryiaQRXkgJnFWnh0dpTbLvvLwqHxxMJQeE8aV5iJJRao6wF7bB4BqPunSUErwI7nqHwoKTk7Nn5yeLmJxYNISaavIW5OgvUdjWB1+EJw4CVpbmD2uRtRkApQaMe75a4k0GkJGFYo9N5w/Yh8MlCeP7Zl5F4zp5dRiq17bRGkQwzTq0sUjiYX5xjZbFNbzDm4sWrvOGxs3g8n/nrF9jojmnWqzz28Bmkmt7Wcn0rmqBai6+f4Vlss8vh7N8mI64vXSvLbaB9naHYva1TXI+/27nTTNL1nPcGTi6nPH16nr0L5CSWxwjNqZW5AwzS3kPzU9uB9vawOBBCtRZPMSNCCqrViGlMtOMTp1+TdGfPLHLm9MJueTsC+Lvf/QRe1Rn0e7Rbc8y1mxitWFhYJs9TvHecXj3FysoSQWDYOf6umZzZmmxJcrta+Gk+YVo7vK+Zh+I4vvO45HeaXbpDOu/bBgEHBYLtb9MuJY7o5ZvogKmxOsRIclRer/kY75Xejgo/pAIHjEj7nx8WPtUB05kems3+TPwJ0rBnG504unk3NaTeM7ewRGdu4Xoy7xmPh1y+eAEhHG/4mjrpCJYWKjgm9z++7X1fRxCaA0LUwTI8G5deIU9TvAAVRERxjFKKdmcOtSNMHTPfjn50G9/S/fP2JDhyAF4f3PcCVekL+mNJYQs6saReMRQOklKz2F5m6IZUbUwdSbrR55pQtJbbRHGVKIgJazVC71FCk5cp9bBKHCm8F+R5RqMSsVCJCGXJs+trjEc5HjDVmHmlGQ0T1rKERjtgIQnIxmOSOMCKnLIsKdMtGmEDFRg++fnnePyRVU6d6VCaIbVOk9Eg49HHHqXwis+dv0gQGybH1mMWFwO2hmOMqlI4x1g32fBtsmFAG8npMx3OtEIqVbAF5FbS6iyTm5iXN4Z011N8rNAWKgYCYSm9RgaCQoeEQhOFEeNxRlCt0jIhva01zqeWpdUVTukq2qfIMkUlKYury/DAWWyu+PznzyNERmQ9aZmgdIQLIqTPCUWO1wqEoSzM5B6mSsBDDy1TbUw02NVII5UnK+DlzZyrQ0FYaRAHIV4FxKGGMEY4T2kLsBnOSVSZYG1JGClMFNNuhswtVlnfHHFhrcLj5xqko4wXXhlyuZ9QFA5XChCagVb4egdjHS0V4ccDXBDBqIf3BcIWNCoRaZpRlAn1Wohpdmi0Y7q9IcNhwdx8kwfPLJOkKekoASFxeOIwoCwLvuFtD/Pi5S5FkfP8Sxtc7o6oxg1qlYhmM0AZgSehbWqMhxlrrk+gJdd6Q7JSUI0VkYL+OOPqOOL5zTG+FEhXgBYIqZA4irKgIgS6GhFENfIyR6vJwXplHanNiYMAHXUwAGWOjULmmjFYT1ZYhND085yy9HhboIXDyZA89xRFhhUTBYNAkDqPlJooBOkdhXVIERACTpRU6/stD/cgxJ7/xOSOr8MiTZ7vWQX2nCjew39PMb9TelGxzazv6GV3LTrXNZ5vePTURMO4va+t064y16lNHm9LajsCWxgaOs0qw1FOlua882seYmOzz0Y3o1avUtneVie2bRy75Yi9LN9Om/ZqX/dYSPZ10jQDNN1P00Ge6bPoYqrr2Jf3AcbKH73N57CzD8cLD+K6YHiIoHUQB1XXe62ZO386nQbv/Za3450jMBqjJZ12gx/4/u/e3m7pCEww5UJ7Z5vOdVZ7D3fxGjMLx+l1X3c+5W5SeL+GOFacuqGAfNgcnb7Xald5sE95cXN1uxUO9yaxlzbutuD1mATi2GJuvq92cGt1F0JMHAvtyTMMIkwYIqXkLW9ZIE0yHI7R2BNVBHFsCMNDFD8HaugxYbR7IXCtUac1v4jgcMF077Q5OBf2rRF3KV4vMnLfC1SBjFEm5trQ8tyllNPLAY1qQC9J2ep1ubSV0RsNCI0mTa+xaKC1Ok8chmxtrFN3npQSqwMiSq6MM5bbHaLQ44sUBFzsrjNOErrDPoPLfUbDIf1kzJbzdIxAlwW9YUloLUYI6u02K9rwykaXUgg69Sq1Wo3llXlWTs3jrUOETWreEOUbpIXkSrfLqUadrc0eVgmc9BS5xskWCaADhQwMg3FJLiWDUjLWsLBY5eW1AUjHxvqAWmQwUY0gkngDoiwxKqFrIZUhsQ4ppCFJckZSUAkq5OOEB5YWqNQMzYUm83MLFOSEUYAxBhtDmYy4+NJLfPGvX+Zav5i4do8CCiuIwxIvJCkFiAiLwitNaUsq1QpnF2MWF+Y4NTdHkXu6VlKr1RkkGVsjT6XSpN2OEYMC56D0JUYarJN4U0PHGudKvHZECPLSIXBoZYnDKs4GvOmhOouNmHq1itZV5t0QUQvoDXPOX0xJU491EOCpVaoEUpLJkKjeRtqMMu3T37pC4QoSclRgCCsxc+0qlcigZYhkwFJngTCsEMQVlF8nCkKajQYiCFFS4a1meXmOL3/5AgDNKOAtDz3EmaVTvPWhBTpRDROF1CuGTCpkHGJlQFw4YuOJ45DLGyOCZcNXep5KrUKROcgFBQ6tFF4ajICRTYmcJBAa7yypLWlHkjAI6JdQOoE0kiCMiYykKB1Xt/oYBHlesiEVoTS0a5qSiLQAlztKQOkQreWk363AupxSSLzwSBVgkDjvwAsSL3fvIbo/sLNvn0M1Yn7K9LGXAd5mE3ZU1VNpd55NCzN7T1ns3oEi2PWKN12n6fx2Uisx8eCo0hIvPEVZcmZ1bmJh285HTP/Zn+MBC89O03breqM9QDej7TxQj6NSbF8evLceO8/237uzJ9mOwez4Kl4XYw53SH0QRwl2Wiuajcq+uILxOKdej9BqrxexPWaEnfklpp8eXszrwOwekfvdz07dS9ivmpgOnRa42f11o1E4oIi4aYh93/0Rv26MXcv8vsSHGReuv3+Hl3Dwya2+Bzcwkd0yjhWVj02yf6iCMOLMAw9jrcWWBZcuXiAZj8BJQG7fy3ewjMMoaXtpkUY5cSiklN7jJXQn5mHU8HXGUdP6JEP0+u/2A74KBCqpIFAlcRBSb4Ysz2uKrEcn9MSNkiRPqBjY6g2IKzWay22MF+Q5LK2eJktzolqdxBVUCahEFeYaVYT3hDpgPcloVtu0Wx2Mifmf3c+hVY3FakwjEDQqIQ5Hno54/vw611KPKnNUyxAEDSoVRWECKq156q0OeS7RgcJQTl4cbegx5lovYZiOGWdjakEFhCGTEl+tIW1GJ/BIBLWaRGl4eKVNLahg0ZQupF6r8ehjywyyAf2uI3cJiQ/YUhrrDd5ZQq8YeIHPc7w3pAV0N3tUjOLalas05usoEVCtJiy26zSqAaOyxOgAbWq89NKLWDVxp27zlNBEZEWKtyHSOiraUIrJhcYSqEcxRgcEpo53jq9cG7G0UKVmDOMR+FKxkUK1UaOjU0Y2IXcOSUjmPFJHuFKihMPoACUmng+VKlmcC9GBRuO4lmnmVIvSKK6NYZhYkkJgE0WWG3IFWeBYWexguxFu1CdUGltaQilQxuETycJKg6trL5NcyraZMocOAqJqkwffuMxXnr1AxWiUlsRxhUZFY2RIXI/QOmQ8GnItK1ia7/DGx8/x4KOQjaAetTk9t0gtqtGKQ0Q9okgzuqMUaT0XupskmcVbx/JCg42+o1WPUFhUNrnnbJTmWK1QxqOdx5aCpN+HMKOM2wht8A4yK9BKECtFFGrqcUhWlHjrkcIRBjGhsiwsVtkc5pROcHVsiRV4LKLIsFmJDg2FVSipKYTFKVBeEAhNXpQ47wmlpMSSFynqAMd9L0Ew2U62rS/dq+49IGjscQjgj2PGxQGCf7h28DrLdHhWE83q1B783TpeD1cC2q2YZjOiP8i376Da473psEV82yJ19Lp0UqvJUUzFSZmXGzBJN+AWDwyROPTrgQGY+vVqp++erY07X8Nt74WTSzUPgz8gyN5OYeoO7445Ge7qyt0u3Hhrmdj35HCr1E5uh231OrmgcLtFimncmNO9WV54b68c1SPTMW+eBh0n0h1UurzK3tvXARMBdJKnUgqpFNpoVh94AFdanAOl5bab9uk6H8x48teYAKPNgbYcsizdeSvxSSfD66NTOhb3vUBVDw2PPLDAg3N1hJS80LUMEkVFWISsUJ+rEoz6JIXEtFY49+BDRPUKHsGgN0BLTSwVjSCgU4kpnSWzYIyiVxYUSuGcpxjnpFnB2dU5/uZLLyAdDK3AFiUeSSuqUm+lbIw9TnmGVImrAXFT0k0tF9bH5GKDRjRg9ew8K4tVXKDodnOq8TIPPjLHF5+9TKtyDqkcpfAEIdQCjbMBFaUQJmCu08L4jPVujmsaamNPXI9I05RhrjDKMBpvElTqxHXJsDdEuAo6yqlJR6+U+BLCoKQhFF6AVYKiyNhYV0hhibTh8mbCY+cMKpxcDGulIWh0GK1foyxTapU64Am9RUqDjTTOajQW71O88BDUmG/FVGuaQIXUKhOvWFuDMZnXhFLSaFdZWahydaNkUI7oJxnjzBKJyb0zhcgIhMEFGu8mrpVrFQnSQAmPn25jrWXQ79KpNekNJGuDlKpRqECg8pwzDcWF9RFrvQxrNWHUonSC+nwFXYxQWGxcJx0McPRYaDoqFc1Su8pb3vwAztRozrWxaUo2zqm1mtSqdULjcEKiEBRpwerCKjKQdPsZtU6LtnRs5J7FoE21UmXdlmQDh3YFK9WQ+XaNUaB52/wcUagYZhllnhFXJFe2CtJSkRUW78EKiRBq0q94cg31egOht7cSCYnPRtgwxpiAkIDIeYrCT+4pEpJAO9oVTWlDekmJVDGhcazEisEgo5tPhHYpFC4vQXsQCuMlmQBsSeYspQDB5H9rJwdg99tT7mXs7rw7dMvf3ojbNP7gzrAj8zwmqwPfjg3ao/7dy04oIWg1JpuGj81gF8fEuxm19+5it1+aEQc652jWZH85+9nM6UfH1epAf96oCcct1nvK8vuf7zWh7Ykn8MSxObTY60VN99WN2dDbhzslbL22zPzdiFfT2pvlNG+1dw+Ws1fNcvOuUPZIDDtfb5jFwUjHvP03zGv6dd7vTPxGqabjHGcT2p/+ZFsYxe6aMVWvHdOen+QVRfE+pzvigEX7iNy3a7HTp9dp4FG09Egc15TDxvVmdWi38vxm1qXbjPteoPIEjEaa8WKF+XqA9o4wiEjzggqeIk2pVFukY8U4T3n+r5/j9GOPMP/AHJUoQKHISofBM8wdUnlwOYPUYZ3DCMeVtWv4wmNQKFPFIomUp9lp4JKMUXfAsLC0dUS+oLg6tGQOqnXF8vI8i95hEYjSM3+mzrX1a9QrkjLLaDbnGPS3KJKCSjUiSRw4S+IdCk2Z5jhlSJRBWUlhHSkK7R0ikFzqj5lvN8izjNR5nAMd1li/mnBl6MlEjVArrPWMcFQVpIGiW1g6wbYTCa1pViuoiiYbW8oSVlaXGOeWRqCBEoGjXatQrDbYuGrZ7JcYBVpEWDtCFG7iWQaHVSE4RZkl9JKIKJAE0jLX7jBXU2htuLI5wHsIRcDlbkLqFDhPJayDyrBJRmGqk982o5QafE6uJNoFVJWkU5fkznOmHdGMmiAdw9zSijXWeQZJyVrPc7GbkZUBFRPhtAUEpdHYMoOxoBj1SYZ9fJFgCJC1Ku94wzLveec5Kp05Xrg25qULfYZjSSQCxv2EwBha7QWsnZy/a7QUNWEYjEY8vFphs29ZHxas1Fo0KoaluQCXBWSp5kyjQmgkaVbgcstWnnJxPSXJSrSaOHn4ymaGdYLEi4mr9ljgS7BZijaSmtSYSn3iktpKrC/IoyrOWxqRpLSCDE9FKHJrGeYFRhXEKsSWGRooyOgnDikl2iicLcnKnNBZvNQMhyNsaDAiRCmNFRatNd6XSBFO7jmTktL57W0J9yiOoMv7gw/TC0+CtpeuY5nxkwlKhxQ4Hf+QMg4TQ/Yy61OL9pR88SoXpOOkhUPCjnp0aL+duPATiAa3pg4/+rmfMkhNxvgk43KUvHpo6J0RO16P0o/kuV5//ug1xMEW3i4h9qCr7lvJ43bh1YvIN2P7uV7a0eWKI75fDztM8Hn1PXJddnw14zPxhjqtEtpp683Z9g7dxn27cJQwddSzw+LdcoF3jlDc9wKVFDBMM/rdEdKOaVQisnSM9I5cOHwKV4cpI2uo1Rs0Ow2UhP6lPtHKPASOPC8QQY1Qerx3SBR1FaKMZDBKmG/W+eKzL6DDmFHSR/oS6yTDbkKWW+babZpxyKWrQ/QY5mOBiSOcCrBeMNfpYMnpzLeoNkOWFhqkWyO0MvQGQ8aJptcXWBeipKca1UFYinGO0KClYlhCHGo2E0uRF9QDyTD1VKOQtSsDlBF0+wM2BhlKOda7BTUtCF0+ueOkLJGU5MJgck9DOTJvEVYQa4nPElpLZzDLMdXQIGSOFJ7MVRgMHaNRinMlqbVkUqFkSWIdpQIfhTgb4BEoJVAovHBEgaRRiTizVOd0J6LwcLWfM1eBqjIkDlKX089HDEeKvJSMbYFQGmUyUpuidIAxIThP7sA6x8A5xl3JpUHOahRQ5gWBKAgDSegLhmWJjCKMVmR5jlGSB9oRL230yBNLZCZnqKTU9MoeUaWBqlXJhj2E9qyurDI/X2EwkHhjsV6QeMfIS4IoRriMWlzFi4AwVhgk1uYMlKVfCvobOVeupbSaTQZ5Rj2UjNZHFCXUGzVGwIvXhnQTS61Z4eWtPrVqQJ6WnL8ywAk58ewmAkRhSfIhQSAoC4cvLJlOEXhq1QomiPGlRQqPkxohNWVhSZ2jZgxeWuYrhiCxDJKMvCzIC0lpc3AWKxRFbhlkBUJIQhOQiRKlDE1j8E7grMN6QDissgQYnHcoZwBHHFZI7OAOU4JXh5No7vYy/9NrxrZ4IuDwleQoieLwlWc39IDwM9l6Ny2AHJLHMRrMA4LUUdzMcYviLaxnxyocxb6ibrRuHmj/rdXpJOzJwbMGh20D3S9RHTo7uHUu49YY1uPnwK2lneFux1Hz7CaY/JuRcA7J+8AmYj8d67h8JrU/ngBMx5muw0nn7V7B50TGkG0c3x3X23/jeAdLva5wOa5Uj5j28nNC3AZVyY1I2EnlnZvd8zlVgTuL+16gysuUM3Pz1GuaSmSwRUoQQa+XU3jPZl9S6gqtcyt0Fju8/PxFkiKhUl+g3mlSMzHVWsDGKKGwnshonC/pjgdUNAyHKakocSVIaXjswYfJvaYYJlSzhADojTPWN8Zc6mWME0EYxPQ2x1RCT2/ouNZLOb1Yxcx70o0hK0tt4npA6QSjTGEiR7tj0L2UkS8oBAQoQi0p0ozE5nRaIUtN6I5TjNSMhhkYSVZosnxMGGuqUUh6bUCjFuOUxYqJ4wNrBdWwSp4XbGZgnCEVUKXAKEEpBKraIh0mbG1ssbyyiKwqnJK4LGF9fcBCu06nVSMMJTjB5dwROUVvOMSICt4ovLN4KTACOrWYwklqsea5r/Q5/9Im73rTKWINL1zt0anX6KcjegPHej9gmGfkKDKXEWMwKiaSBoSjSPsE8eTuBInEC0GejdkcDOibLdaTDsudkFMdzVgr0kyQ9wpyFFeSgk6jipAaSUxkxhgsw3JyXsgEMblLsbnFW4OQAb31lG4sCYTg6mZCZmKC0vGGB1eIggBfZDhvGSdjKqI5uUndxKAU1VpIUVhWgjpbo5zEOcgUlzcGhMZQ61sqpmSuEaDDiav4Rx+YY7Nf4DV8wxtOk1mLtYJr/YxB7OkOJUU5JggMZVRFC0UhSnQYYb3HRAbnBcp6qpEmMpo8L8gKyWCcUjiITYQSOd1eiTSaWhAyKHNKLyhchvASEytCZWgQMxxlZLbAlWC1QlqB0AGxhwKPK3OskDg0RV5gi/vKK8WROHCWCQ5n8A8k3Plv/2J7MP4NtacHFrbDyjyOqTosyd5F+sQc0IlwI/5MsFcLu5NA7Im/X2A8WhA9DCfjAW7EBB0s5TCx6UZ1OSqvw2p0O+1Ed54VuY77esvfke/m3djqI2bFPoZ3v5izN+2tzPob1+pm87k5YWo61SEB/ui8bkTLJl3nT0RPDvbdUdTxds2dW8jnVob0KMvVzrObyvMoentncN8LVMPU8fnnLxFfimhUA04vVKnFijDQhEKxJR3KVDDeEQch3/C33k4QxSR5jhWCAk8xGDLOS4TzmEaV0Aja9QpGeVQQUMlT8nZIb5zQS0M6QczVYZetYYK0niSzFBaEUKRuQDaSqECzMR6hMWgDoyBALXvm2zWU9WylOf2NEVEYUu9UGWwUSBeRWehlJUVeUggHBDjl6WeQ9y3j3FCvCjIvcIlnnAwxkWLoMlJZcHahyfpWRiQEWenoBKCsJU9zNJZ5Y7BliRcC5zV5oUmTjMAl9GWOM1WMNVR1gMvGVAPJAw8tEzjPV17aYG2jz1Z3TGolkXcYWUFSgrNoEZDZkk61QSU09EZDXljbIk1zKhXDK5sD0qyH8ZIL62OC2OCsphCgTESRJoRy4lku94JSeIxQWKHoJ0NCHSIDQ8NAsxqStRpI58nyBGsFgYs41YoYRgEvbli2+infcHaVRlXy3HpC4RLSjS660SSSIUQRuZaQFhTdDbJ0gLcjZKhYXlpFm4D17ojNawNy76k7ix12OXVmASEMAk1SeKRWkwtBvUKbgtwL5iuauWpAb+QJlCZYmiMSkqIsibWigkS4gtQ5yiTHUFAJBGvdFGsLnPVYLwnQSGPoRG1K69gcjdDGEOsI4Sxl5qnUAkrvsVohmFxM2okdTgpaNNG6REjLqTNtBkmCkpr1UUGoDU0vSRSMS4uxEldaclPihJ/caWUUQoJQMMxHBCUobQhVQOomVktUiD1wAParCDdQCu9dEk6+IBzGVuwXOvbgJGcUjlzI9ttQbt/SdXPK7qNafBjbNi1wHWSpbqb+Ys92nZvDTQ/DDPc/BHDI+cud+XXLCvpDczyyAjeZZh/80T/vBjfa12Wfw9p6m03oJ0zi9/1/XKbikO+vLe14lbnf6m67/Y17FcLU/uR3gtbe9MGGT3ziE3zXd30Xq6urCCH48Ic/PPXce88v/MIvsLKyQhzHPPXUUzz77LNTcTY3N3n/+99Po9Gg1Wrxwz/8wwyHw6k4n//85/mmb/omoijizJkz/Oqv/urNtw4QlQalbpD5GutDxWdezPjKVYstKmjdhEqV7kiyvuH4yvNXuHJpyJWL6/TXx4yu9DClQ0pFICSxlqRpzmCYM+iOufBKl81uxjDxSN1ikHjWLvfoJg5XadMThr6XuKgCQYA0nrlqjVq9jtISFccE7Tr1uSZRLebi+oCLmyNeutbHOk2tWaOg5NrGFmtbY9Y2Uoa5piwkQ69AapTIaVQMWZYzGuUYEmqB4tHlBmcXm5xajjk7X2W53UQFFTYyTdyqcmapxdkFQ1wJGHhJ10dkVIm1QWhNICRag9QZ1aokjkKqnTniuEo2KrDdMWVSEOgIspIXL10jEiUmgFBaVJGRFRbrU6QrUUZiAkNkFINhl5evXmVQgtRVOo0KzSikyHLmaw0eXF5gvt1ioVLj7GKVRmjIkoLFWoWKMThv8FIjhSO3BUJFBKaFliHelvSGGcm4JFAhUltirak321wsHE+/OOALlxN6gyFFlnG5P+bPvrDO5qCgICBqdnCAL8Zo5dBRlbDSor1wilazyvLZhwkqy1y62qc7SrnStThdZb5Zp9kK0PUq40SxvmkRKkSEilGa4pxknDte3kwZ5iVYQy2uUa80aDc6nJ6rMzdfpdGOKZSguVDhzEPLLC92uNZPeaWfIrxlvhkifMbzL36Fy+sbPPfKC6SDTTyW1FqCahMjDShNUXgyIekmCcNsiJQFlpJxnpPmJRu9MUmWkGWOMvNsDhJCoxkljsE4oxxnbA7GKCWZq0aEsaReiSjd5AJhIwWB9EhrkdZTIUYYgxACa0uU0wRKo6Whoq/rbu41GvJqMLVLY/9nG4edvbp1lkTsz/4EB1KOY7ym8zu4hL0eOL6sI7p1z7PDnkxwM4vuURrnI7v3kCKvBx9Xa44I25tuJprd03TkwLDfKSHk6Hfj1nJ7FXnd6JW4ycyOdrd+jInpdYM/lmYdjmMWkd0YxynGDsvvZCWfGLf32Nk9h5sWqEajEW9729v49V//9UOf/+qv/ir/+l//a37zN3+Tp59+mmq1yvve9z7SNN2N8/73v58vfOELfOQjH+EP//AP+cQnPsGP/uiP7j7v9/t867d+Kw888ACf/vSn+bVf+zV+6Zd+iX//7//9TTcwG21OHDUkA7K8YJCPGBUl1xLFlS3LXD2kphNsntBeXCSo1cgLT+oCSm24tpUyyCxoRYankI6N0QBtwIuMUTqiOxigjeTs6hz1agUjFb1xwmBYcnVg2RrlYCI69SrSKHTgqdU7VBtt6vUqRsWUQhKbiHqtiisEL17aYpAJrow01wYho0QwslCthMzNhQRVjSkLlNAomxAHimajRr3ewnrFeq7ppSVWK2rVgE4Ay7HidDOkU4vwErwIMFJRCQOWaoZK4EmtZly6ife4QiKUwcYBpVHEUUCnbphbDCiVQ6qAfj/j0rUh0gRU6g2WF5osrnSYm2uidERkqpQ6RImQ8SihyAtcEBBWmyglCbUgiiuoSsyzV/t86rl1nv7yOuPMkznHK9f6rG31GZYTJxLWOaQC60GhcM5hvSPBkbmMvMxw0uN1gCBlazym3phcXjqnDWfqMVjHOPNsjnKuDgq81uSuBJfitKAQEi8rpC7CZ45xCYMyxas6hZXkKMaiSX/kUNZRiSLarTbIiEhXuJZ5VL1G7jyXLo3ojyQbvYKtscMHMaMy4vxWxpcvDahIhbcpX7rU5bnLA5RSlM6zkZRcutSnHkV8/WOLvO9t51ieb1Kmlqw0vPEtb2KxVaNaqeHDFuNCkJUZNeXxEsqiwKmQRiUgCkOciBiOHOMs5crWgH5aIp1iME5YH6WU1rM1ynlxoyAvSmo6oD8cMRwMuNZNeWVzxNWtIS+v91kfZAzGKYO8ZOigV1gG1uGEwCPxUpAIQa48uRd4X2L3XER1r9GQHQvFrbKwN7OuHC68HI6j63OCEsWe0o5kYA535307WbCDWtuDZR2dcu/nZsr0x6Q6rMTrsY9q+5E1uCkG8ZDIByTjVzMT73Hsa/a9R0cOacw+oWpa4D4mzUn0Icfi9gtSt90ydRzxub3VP74Oh2tpTpbumHh7N0keiL4vwO9LOU0Hduj4zQpT++nIa0BXTiqz3eJ47iTZvxrcKQopvL81H0oAQgh+//d/n+/5nu8BJhqh1dVVfvqnf5p/8k/+CQC9Xo+lpSV++7d/m+/7vu/jS1/6Em9605v4q7/6K975zncC8Md//Md8x3d8By+//DKrq6v8xm/8Bj/3cz/HlStXCIIAgH/6T/8pH/7wh/nyl798orr1+32azSZPfNv/gdSAK6jWGqwuLVGtVwjw2MKTFh5bqRJWqtTmmgipQHmG6wmgqEWGHIfPc5I8o77QYb4Z0azFZEVOXuQEUqFNwGZ3yPqla6RpTnc0JHSC0tmJG3IEDotVhmFeYhNJEFoi6WgttHE6pCYDbFCio4iaEZRZQVHCxuaAwGhUkZEnJQQhPpDkSY98lNKMDe96wyqVWo3cBlzpDnlhY4zwEAl445kmghKtDFtJyqifMCocznm8swgnGRUluYXE6YlbeOGItGRsNXEYkFrLYifkwdOLzC+1ITA4UVDmJbbwjNOS8bCgWosZJSm99ZS1Xo8sSRlmk4lflgVhpIiMQomAWGu6yQCJ4WzHkOWQlgUL1ZBKFCCUJs8yxsJzrWfJxiNCaSikIS/85DbxQFE6h7XQDDS1SFOiGVlHNVQ4O9lueaoZ0golUsOlrS1CHUw8FypJ7j3X+mPGg4SNzKK9ISsFUitKOyIrC+S4ix1dxqdDAi3YGhR8zcPzVBoLDJ1hfSunEhuaNTBRHTHust7ts54IyiJnabFDYQ2j7gCcp9Oqc3quilWawCjW+wkKwRtX53nbQ226w5z/6+m/QUUxjy40iCsBo8yy1huz3rfkMqLdrKJ9wUuXNymERihFGMaU1k6cQkgJ3qO8QygDviRJUyKtCQKDLy1pkSJVSCMMCSPNOEvJC4EwGuctpRMoClLnKTwEdrIdNAxCAqVIvcR7B94hco+XFsjxGKxXCC3QHkgT/uv//8fo9Xo0Go17iob805/9FcJo4mr81azhx7scuHULyuGs1zF7cg5JdJQu9zgm6ebdJZ8cN7bXTZ+eOlDPY4w4R9d77/J8dM2Osw8da3S4lf2CU2nuV0Fqut+PamWWpHzoQz93gIbAvUFH/tX/+S+J45hpRniq6ftwon3Cx6Tfl+xunz5HkZrjtoPdoE2H38kFBz3dnLA+h9XlBsdRrz8/zFXGCYQgf5hANV2QuP71BLjRZLiFyXIjy9RhRz9vg0B88rOt15EkCT/5Uz91KB15tbitvoxfeOEFrly5wlNPPbUb1mw2eeKJJ/jkJz8JwCc/+UlardYuAQN46qmnkFLy9NNP78Z5z3ves0vAAN73vvdx/vx5tra2Di07yzL6/f7UB8BEnnOnOzz68FnOnV5iPgrQzhJJQRQF6LiKciCtQ+U5iolThbCqqDYlraZhaaXFqdNzrJ5eYmWuznKrTq1WwQoIwxCH4pVX1uht9jAKXOpoKY3yoKwBL+iXBf0C8AXtUNFoOqrGYcuSzfUxvVFJ2Ag4u1gh3epx7UqXzX7OZlYyt9yhXtcUEhJpGDrI04KRq5KqFpuiyZeuFVzpZeRlQqvqeWS+ykozIgg1F66NOH9lyFeu9Oh1LYkIQUbkdiIw9S0kTuGkoBmWNIISaQChiSqaYZ4hpWKcWT71pct85M+f5ROffJ5nv9hlY71k0M/JshxbjPnc55/jM599iRe+cplxL0GZkFoowVu8c4jCkQwSxoMueVFQNTWWWiH1KEIagdaSa+MRL69tMBqljEeWja0SSkm1PgcmIC1LcI6iyMhGXdxgHekzUjwFAnTBgx1FswaekooWvLKxztVxQlJkaGcZJilp7kgzy2BU4kpFL5f43KO1ROoClfcJi5KWMNQqLUTjNNRX6fqIoLHCK8M6hWlTa8/R7MR0OlV0VCMrcghjolqdx1cbVAKNzT2jUUqlFrF0ZgndavBK4gmCmNOdCl97psOpjubBB1q0qiHVquab3/4g/993P8o3vv0cb3/sFG86O4eJYjrzNRoBGCxZ6Vnu1IiNIjSavCxxtgBXorFgC6SQGCFBKWphAFJirSC1OUYFRIHCuQKbFygvKMoMO+pT94LFQKGFIZYhC5Ua880Oi7U2kTQIJzAWtC2R3uJ8iRMgZUgUGKqhoRoYnLVYezKydzfSkOu4eUvVYbrEk8S7GexPd8MdfkfkcXy9Dv47LNaxFbsJTGsb/Z7w66UfaxXa+/+REY4q9fiaHRdjqiduOKh3Tp962Jy5cdhrZRY4QR/cZBfd3XTkVnFM3x9nETnJkB1nOXg12G9R2mNxOfGQHtau/RkcVo7YaznbGyiOTnOzOAExOEgvrxd/bJkn7KSbE6Z2Mj4pbpNJcG/yG2R1M6W8lkq9W8FtdUpx5coVAJaWlqbCl5aWdp9duXKFxcXF6UpoTafTmYpz7ty5A3nsPGu32wfK/pVf+RV++Zd/+UB4TpNL4wZzdUWjWiNN7OTMiKoSVSOKQUGZp6TKIXopoRWUQBwqrCvo5wGRttSjAOVzBv0RNncYk5PnBUEcMRj26fZGXFnrolWExiOkxxUFHs+wFOQJhNoidMDmOKNV0WSZoJ87EAW+N+CqgfEwAKMhT2lHESsLLfrZmN5IYEtDLXb0R5YiTQiMIkXjpODSRk6/X1ALQ+p1xWqjgnEFK82Q3tiS+skFs8o7pLVsbbsYT3LHqJx4xwukp1tIxnmKUiEmlpxabbPVHaCsZH5lkSBQOJ9x4ZUNXCkYDDMatSpREKClIowSxnlK7iRaKsZpRqDM5IyUdlgshcgJtEZrAd4jZUTuQQhJM9TkTjK3UCGSijRyDLZSVMUwSMbkeYpAkSsFQhKYJpXAMPQO6yTWg8/hSmYnd1qVOQObgdKUKDa7KZkMONWusjW2DMYJo2JCuUrvCOIKJg4oc0VuHYGHwhVk4yFZMaIaRnTmzlHXCamVvLgxpJaMqASGZjUEITGmSjYaomjhlKDSdIwHKUFQpZAB/aFD+SFhrNnsD9C6ST0KmW/OUwwtL6Rj+lnBhWs5X750jWYkwTv6qeDSsMSXBcYIit4WmRXUW3WUckgt8U6Q5QLpS8rUoQQU5BTWIjzbd01NhFecRMYhVmhKW5IC85GhoMR6Sb8YoF2IUDFGSqT3aDHJM0egpCAXnhBD6jyR8eSBIveeMrcENsHEVYIoosTdszRksgDdPhXv/pxuZPE4aak3jPda8MLHZHwbFZE3KF3s/XHiVK9uPG/cOr/36SFFHVDq3tBAdtjM2ZvfEdr4I8o8qqjXkkU5XpF9+96xu5GOTAum+3Bo02/xzbnZbryhAuI245D67SggbnTB+ZGYetn2lXUrOEk6f/Dr8ckm9pSduB6BOKre+14U4Y+ZP7d93PZX6qRS3e0r/V7FfePl72d/9mf5x//4H+/+7vf7nDlzBoMkIKM/CDFuhHKeHE/kEsqyhhcKU5FIZxkOE1qLTfrjEeO0pF4JiSuGIJxcWlq6gkpkKLIM53JG44SLF9axWUZ/NKbeaCBdSZmVeOswQYRyJXPzDYajMcPeiH5/RFIWWB8iVEjFVNkscnLnubjWo1YNWVno0GwYytJyZXODZDjC+hAZeIaDnDItkUhy73hwoUazatgYZ/RGBdc2hqhNuFAtqUg4s2AohKc3ynE4tNQkY08/F0SBoFlV+FFOYQOsEBhlqIeKVErGZcHaxXUq9QBXpLxy4QrVRpV6PaRSqxM1qkil0YGkt76F3PYsFwhJpWkYbm2BgyKC0qYY67BCU1HQjDxxoFgbZOSlZ6Tg7Hwd4cdk4xKEIMlTpA5oVxW5g36uiaMGJtAMM0fhPFJrbGFpCsfYORySQQlKetLeCKNDjM5ZrYcICqKqQSuDFAInYJwN8dbhZZVQKEqb0+uPcYVHYrHeQjnEyBxlU+KwRVEqrvQSHj4bcDqusrDQphkb8nFK6kpevLQFImRxrkZFK1YXW0ibEMuQQeHJvaM3ypBKsVKLqIaSQV6yOSqJIsliJSZJHIvNgItXtnjxasqZhSZxICAbYoIKyueMrcIrQ5qUVCKFc5KsLIljjc4E/aSLVAqsYK5WRQqFd4qBd4jMUg9ilNYIPEZrstKSFSl5kSNVQL09h0ZM7tlKc3IvoPAUSUJpDJQlzgtK6RBCMbIemTqUL6lEMQWCbFuQc+XdTyaPoiGHcRyTJefwNk0vfAc3edyIqX1txLbbkd+NcCvl7ZciDpMqxBHfT7Rb5oZl+wlrc4Nc9j+/OQ7i8HqIg5HE4czZbvo9W5V2v15/eGRtr0c7ql8PC7/RGBxb0yPK3/tb7HujjlFc3Lwa/o7haDpy9NhMdaU/vGdvCTfK4DXs0uPacFva9VosKTdZsUOrsHe58PsUPhy/ZfjYeu15708U8dBKcSul3wbsbffBNfFYjdO98doDt1mgWl5eBmBtbY2VlZXd8LW1Nd7+9rfvxrl69epUurIs2dzc3E2/vLzM2traVJyd3ztx9iMMQ8IwPBiuRizWYlyRMU5zdLWCURKHwRaGkpKwzPBhTFStsLm5yaA/QukG5bBk7eqA7maXxfn2xE154SfezuoRYWQ480ALrQOKvCQ0Bl3RXH5ljcHVAVaCHw0phj3KwuNDg7SOaqBpzrXxQQBJSpE6ImnwoaIoBNe6Q4KwgQwDrHV08xTrcpzTJE5SAMJ64jDk5d6QdGiwoqQdwVLNTJxOmIB+4riwNSAIJWWRsdhqcm2rx7hwoAIK58kKSV4aunkOWCLlMUIgLHjpGSVjsiwFFKXI6Y8ztoYxqbWsXe6RlwUtLcjyjLASEIdV6hXBOO1ii4zCKyIqCGHIlQObk+c5faFp1+qcbQswMMpKrgxH1IDFZoU4NIShQRqFUoIX18eUWPqJwjiPFIq88KjRGCsSUqFRYci4EAgpUKUjigRGKUprkCrA4djKLKnNGThHJAwlddr1iFpFcmlzTJKXCAdIS1nmjNOUqg5ozzdgSzIYDlAoIiVZ27CEYcalq2vMLS9QCQTVOKZRF6RZwWZ3yEtJjjAxNVNS1Y5GNSBAUglCOrFBC09kIs50NL2kJE1yMudpBQpdMXSaS9jcsZXBWq9gqSO5ljvSYckod0SBnYynhDg2COdJxgXgiGs1Sj+xtHbTAiMz5hp1lNNsDkesJxl2rJDC0QhC4iikUm0R1kryQlB6zzgvMXgKSlzuGSGIw4BQaBIlcaUgFR4vBVXjcUiyzJOlI3pJRlg6VBxTcrJ7qO5GGjKNvcT/JJR+vxXh9cT++h3Gzr2KVevAOrhP2BE3au3RgtJh/XbYTpEDS7NnV9I4+XYQcTSje0RdDoYejuOF60Pi7dV6++1UR/BCx51+PrqOR9X6eLb3cNHq6DTH2dGOw7E2tpuYonc/HTkCh1huppp9ZB/sEXJ3pWwxncHtEkKO49kPnXj7FQcHEx+w5B7Szr3JjhVLjmvjqxLM/VRSf5ilTexEEdPxbyTjnOCZEMdldtKMbyXdUeGHCUa3Ws4hyqUDxe2ZHHepkHVbBapz586xvLzMRz/60V2i1e/3efrpp/nxH/9xAJ588km63S6f/vSnecc73gHAxz72MZxzPPHEE7txfu7nfo6iKDBmcn/NRz7yER5//PFDTezHQZsag8wQVQ0dY8itJjTgnSBshvhCMhyNUbkizwracy3m5+dpdhqsb6xT1QGtUw8w3kqphAakByfwXnCtOyK9NKDZqBOHnkIH2K6lKjWuYli7dJWqLEGEYB3KSbwDoTVXNzZROmBhbo5a4KAsUdLw0AML+LwkS3I0mnFu8V6SFBZXeBIMsdZkRZ9hUdKoGqKGocggc4L1wcTbmnUZOEdsBFI6vFL0ukOywtM0kpycmpHYwuEMxErgVIhxktKXBDhGlAxwhMKAUigkMjDMzzVx0hNKweXuiCvrXdJRhs5LOh2Bco6rG0NMpUosAypKkzmPE4oMAYSURcEXXr5KxYTMRZJ6HJDZMdZLrJXY3LGelvTSkq3UIRGgBFUpcEIgrcc5izAC4TWFh9JbRJFQDQMaVY33kmyUMExzeoMhi60WRgtalZA5pTBKccFnDMcjoIorLcqW5IUFBSZqEcoxBdDPIAgbFOUGthwzHA2JUkF49gEkgo2NPmWoGRsYJzmxkZgwZLER4VAY6Qljg9SKflJyeSvDpm5yt9Sgz8ZQo9Eko4JRNqCwjmGSMioto1IglCEvITaecVJQCSJadUVpPcNxTu5yBlsjUqHxKIzRRNowKh3eO7QRFLbkcm+EkxrtPbYoKLMRwls2PYg4okObSGicCZEC5loV0iRDDoeU3qNNSGQ0wntcVuK8J0RA6bASpJDEJiYtHJEEUQkQQUCenWzL391IQw7iBpzJiTjuW7Gt3MiKcoPkh6/SN6jHvrymmPsjFnh/WOSbwBHJTsILTnjJw8Svoxb/m3M0stcidKBbdo1HOzppP53yFviPSXm3rl3ecR194jbe5LQ7sjZ+39fdPMTBZ+xlFo/O/GZafnfSEQH++qavyZy5Pg9P1r7t+FPShdj+ebg46vfMnwPzckcBcdik3p/Pni+HTQm/b7pPDfm0KfUABT2Q3w064+CrtDOvbtCPflt9sme+HeWXTRzzazp8uj/3WmH2X3o8Jdvut0Rua0/2e/+bfNkryR1e0+snS8WhMoffNya3TJ/99Ew7dgnZ2zUnLW5/v+z/jZ+a0zesw+uImxaohsMhzz333O7vF154gc9+9rN0Oh3Onj3LT/3UT/HP//k/59FHH+XcuXP8/M//PKurq7ved974xjfybd/2bfzIj/wIv/mbv0lRFPzET/wE3/d938fq6ioAP/ADP8Av//Iv88M//MN88IMf5JlnnuFf/at/xb/8l//yxPXceUmEihjnlt44oaYUSof0K4Yil8hhgreeqBrSqNWoVAMuX7pMu9lkczRgsJkRS4UzG5RJRr3TIc0yKnHAOPDU4ogwMNhxRi91YIes9wcMeymhL/BekJsCUST0khItJak36KwAqcAnbFy8iNOapcUmnbqhrlL66ZiakqRFikgdtVDSqmteeXkdWUhGgDYgS8e4Z3lhc0zhHa2GhtKRCYcTkgKHRbAxzKhFknFeMhhaqkYQxYZrXmBLcL4gNAFCpoy9JCkFdUqqgacWBsSdJjjHZj9lPN7ii8/1qQXRxNmCtay06/hahSLLyMcluS3QVqJyhwok/WECtsDaAmkLnAkxgSaOA6wtWRsm9LKAKJYo73nxpT7GCRAa6zxSeAon6DQqSHJ6w4L+KCG1GVpO7jpyQYz00IgkVSHZHIwJZEie5fgipR0ENLXDupJLr3RxwmHQ9Md9BqMxWzJAVwNyKwhQjIREJhlCqskFuVaQW4+WFcIoousjtoQjXx9htrdWVpQlzTO0LMlKiSpKXuyNEVJSrUZURmpyzkwJHl40KOFYuzpg2Btz2YRU4ojTCzWu9XIKB8I5ktyjvcMoy1JF8/IghUwhgoy13pAkycjSEYWC0nuqYQ2Eoiw0QhpSazFSIYQgFprClgzzDIEiiDUag8RSCo0WkixNCU2MzwdIqVnvj0nLHKUVobeocoAipJemCCSl93i3TSwFSJuQCoEsLSiDkgKXjhB5tvte3ms0JM3SQxaj47Sj28+OpPJiahEXYt+ifESa/UyPF7ucyk3hQK2OE2D8IVEOckpHVfHY8m+k5N5f1HTFDot0/flelkQcOl57mZDr6W60MN+KT9wbGhVuB/a2+SQK3GOElZvWAxzWtceN0R6mU+x9eMg47kWWJZPg7UG45+hIkk1LJXB9wp1gYok9/TRFP5hmwm+Uy2Ean5sV6w7L7XbFvKmSd3Qn+0WXqQl9SHu3+/3kTq5vQhq4RYh9gvEUpTyG/l33dHfISyeuC29HFzxd2hHFMG2Sm67joXTzJEvaYclOoqXZL+6K6RhHWzA9aXqdF7nt8DeJj3/84zti8NTnB3/wB7333jvn/M///M/7paUlH4ahf+973+vPnz8/lcfGxob//u//fl+r1Xyj0fA/9EM/5AeDwVScz33uc/7d7363D8PQnzp1yn/oQx+6qXo+//zzh9Zz9pl9Zp8797l48eKMhsw+s8/sc8ufixcveu9nvMjsM/vMPrf+2aEjtxOv6h6quxndbpd2u82FCxdoNpt3ujq3HTsHXS9evHjbfenfadzPbYOvzvZ57xkMBqyuriLlbb2t4TXDjIbc27if23c/tw3uHxoCMzpyL+N+bht8dbbvtaQj942Xv/3Y6ahms3lfTpQdNBqN+7Z993Pb4KuvffcaMzGjIfcH7uf23c9tg3ufhsCMjtwPuJ/bBl997Xut6Mi9o+aZYYYZZphhhhlmmGGGGWa4yzATqGaYYYYZZphhhhlmmGGGGW4R961AFYYhv/iLv3jr90Hc5bif23c/tw1m7btXcL+04yjM2nfv4n5uG9xf7buf2nIY7uf23c9tg1n7bjfuW6cUM8wwwwwzzDDDDDPMMMMMrzXuWwvVDDPMMMMMM8wwwwwzzDDDa42ZQDXDDDPMMMMMM8wwwwwzzHCLmAlUM8wwwwwzzDDDDDPMMMMMt4iZQDXDDDPMMMMMM8wwwwwzzHCLuC8Fql//9V/nwQcfJIoinnjiCf7X//pfd7pKN8Sv/Mqv8PVf//XU63UWFxf5nu/5Hs6fPz8V51u+5VsQQkx9fuzHfmwqzoULF/jO7/xOKpUKi4uL/MzP/AxlWb6eTTkUv/RLv3Sg7m94wxt2n6dpygc+8AHm5uao1Wr83b/7d1lbW5vK425tG8CDDz54oH1CCD7wgQ8A997YfeITn+C7vuu7WF1dRQjBhz/84ann3nt+4Rd+gZWVFeI45qmnnuLZZ5+dirO5ucn73/9+Go0GrVaLH/7hH2Y4HE7F+fznP883fdM3EUURZ86c4Vd/9Vdf66adGDM6cnfMxb24n+nIjIbcfzQEZnTkbpmPO7ifaQjM6MgdpSP+PsPv/u7v+iAI/H/8j//Rf+ELX/A/8iM/4lutll9bW7vTVTsW73vf+/xv/dZv+WeeecZ/9rOf9d/xHd/hz54964fD4W6cb/7mb/Y/8iM/4i9fvrz76fV6u8/LsvRvectb/FNPPeU/85nP+D/6oz/y8/Pz/md/9mfvRJOm8Iu/+Iv+zW9+81Tdr127tvv8x37sx/yZM2f8Rz/6Uf+pT33Kf8M3fIP/xm/8xt3nd3PbvPf+6tWrU237yEc+4gH/8Y9/3Ht/743dH/3RH/mf+7mf87/3e7/nAf/7v//7U88/9KEP+Waz6T/84Q/7z33uc/5v/+2/7c+dO+eTJNmN823f9m3+bW97m//Lv/xL/z/+x//wjzzyiP/+7//+3ee9Xs8vLS3597///f6ZZ57xv/M7v+PjOPb/7t/9u9ermUdiRkfunrm4F/czHZnRkPuLhng/oyN303zcwf1MQ7yf0ZE7SUfuO4HqXe96l//ABz6w+9ta61dXV/2v/Mqv3MFa3TyuXr3qAf/f//t/3w375m/+Zv+TP/mTR6b5oz/6Iy+l9FeuXNkN+43f+A3faDR8lmWvZXVviF/8xV/0b3vb2w591u12vTHG/9f/+l93w770pS95wH/yk5/03t/dbTsMP/mTP+kffvhh75zz3t/bY7efiDnn/PLysv+1X/u13bBut+vDMPS/8zu/4733/otf/KIH/F/91V/txvlv/+2/eSGEf+WVV7z33v/bf/tvfbvdnmrfBz/4Qf/444+/xi26MWZ05O6ci19NdGRGQ+5tGuL9jI7cjfPxq4mGeD+jI68nHbmvtvzlec6nP/1pnnrqqd0wKSVPPfUUn/zkJ+9gzW4evV4PgE6nMxX+n//zf2Z+fp63vOUt/OzP/izj8Xj32Sc/+Une+ta3srS0tBv2vve9j36/zxe+8IXXp+LH4Nlnn2V1dZWHHnqI97///Vy4cAGAT3/60xRFMTVub3jDGzh79uzuuN3tbduLPM/5T//pP/EP/sE/QAixG34vj91evPDCC1y5cmVqvJrNJk888cTUeLVaLd75znfuxnnqqaeQUvL000/vxnnPe95DEAS7cd73vvdx/vx5tra2XqfWHMSMjtzdc/GrgY7MaMi9TUNgRkfu5vn41UBDYEZH4PWlI/rVNuhuwvr6OtbaqYkAsLS0xJe//OU7VKubh3OOn/qpn+Jv/a2/xVve8pbd8B/4gR/ggQceYHV1lc9//vN88IMf5Pz58/ze7/0eAFeuXDm07TvP7iSeeOIJfvu3f5vHH3+cy5cv88u//Mt80zd9E8888wxXrlwhCAJardZUmqWlpd16381t248Pf/jDdLtd/v7f//u7Yffy2O3HTn0Oq+/e8VpcXJx6rrWm0+lMxTl37tyBPHaetdvt16T+N8KMjty9c/GrhY7MaMi9TUNgRkfu1vn41UJDYEZHduK8XnTkvhKo7hd84AMf4JlnnuHP//zPp8J/9Ed/dPf7W9/6VlZWVnjve9/L888/z8MPP/x6V/Om8O3f/u2737/ma76GJ554ggceeID/8l/+C3Ec38Ga3X78h//wH/j2b/92VldXd8Pu5bGb4d7EjI7cu5jRkBnuFtxvdOSrhYbAjI683rivtvzNz8+jlDrgkWVtbY3l5eU7VKubw0/8xE/wh3/4h3z84x/n9OnTx8Z94oknAHjuuecAWF5ePrTtO8/uJrRaLR577DGee+45lpeXyfOcbrc7FWfvuN0rbXvppZf40z/9U/7hP/yHx8a7l8dupz7HvWfLy8tcvXp16nlZlmxubt71YzqjI3fnuByG+5GOzGjIvU9DYEZH7uax2Yv7kYbAjI7cCTpyXwlUQRDwjne8g49+9KO7Yc45PvrRj/Lkk0/ewZrdGN57fuInfoLf//3f52Mf+9gB8+Nh+OxnPwvAysoKAE8++SR//dd/PTV5PvKRj9BoNHjTm970mtT7VjEcDnn++edZWVnhHe94B8aYqXE7f/48Fy5c2B23e6Vtv/Vbv8Xi4iLf+Z3feWy8e3nszp07x/Ly8tR49ft9nn766anx6na7fPrTn96N87GPfQzn3C4Bf/LJJ/nEJz5BURS7cT7ykY/w+OOP39GtOjM6cu/MxfuRjsxoyL1PQ2BGR+6V+Xg/0hCY0ZE7Qkdu2s3GXY7f/d3f9WEY+t/+7d/2X/ziF/2P/uiP+larNeWx5G7Ej//4j/tms+n/7M/+bMqd5Xg89t57/9xzz/l/9s/+mf/Upz7lX3jhBf8Hf/AH/qGHHvLvec97dvPYcXf5rd/6rf6zn/2s/+M//mO/sLBwV7jz/Omf/mn/Z3/2Z/6FF17wf/EXf+GfeuopPz8/769eveq9n7gqPXv2rP/Yxz7mP/WpT/knn3zSP/nkk7vp7+a27cBa68+ePes/+MEPToXfi2M3GAz8Zz7zGf+Zz3zGA/5f/It/4T/zmc/4l156yXs/cVXaarX8H/zBH/jPf/7z/ru/+7sPdVX6tV/7tf7pp5/2f/7nf+4fffTRKVel3W7XLy0t+b/39/6ef+aZZ/zv/u7v+kqlcle4PJ7RkbtnLu7F/U5HZjTk/qEh3s/oyN00H3dwv9MQ72d05E7RkftOoPLe+3/zb/6NP3v2rA+CwL/rXe/yf/mXf3mnq3RDAId+fuu3fst77/2FCxf8e97zHt/pdHwYhv6RRx7xP/MzPzN1f4D33r/44ov+27/9230cx35+ft7/9E//tC+K4g60aBrf+73f61dWVnwQBP7UqVP+e7/3e/1zzz23+zxJEv+P/tE/8u1221cqFf93/s7f8ZcvX57K425t2w7+5E/+xAP+/PnzU+H34th9/OMfP3Q+/uAP/qD3fuKu9Od//uf90tKSD8PQv/e97z3Q7o2NDf/93//9vlar+Uaj4X/oh37IDwaDqTif+9zn/Lvf/W4fhqE/deqU/9CHPvR6NfGGmNGRu2Mu7sX9TkdmNOT+oiHez+jI3TIfd3C/0xDvZ3TkTtER4b33J7dnzTDDDDPMMMMMM8wwwwwzzLCD++oM1QwzzDDDDDPMMMMMM8www+uJmUA1wwwzzDDDDDPMMMMMM8xwi5gJVDPMMMMMM8wwwwwzzDDDDLeImUA1wwwzzDDDDDPMMMMMM8xwi5gJVDPMMMMMM8wwwwwzzDDDDLeImUA1wwwzzDDDDDPMMMMMM8xwi5gJVDPMMMMMM8wwwwwzzDDDDLeImUA1wwwzzDDDDDPMMMMMM8xwi5gJVDPMMMMMM8wwwwwzzDDDDLeImUA1wwwzzDDDDDPMMMMMM8xwi5gJVDPMMMMMM8wwwwwzzDDDDLeImUA1wwwzzDDDDDPMMMMMM8xwi/h/ANsUJdeXWem7AAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 1000x500 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"num_images_per_prompt = 2 # adjust according to VRAM size\n",
"generator = torch.manual_seed(29) # seed\n",
"\n",
"images = pipeline(\n",
" prompt=\"a [c] in pixel art style\", \n",
" lora_scaling = [1., 0.],\n",
" guidance_scale=7.5,\n",
" num_inference_steps=30, \n",
" num_images_per_prompt=num_images_per_prompt, \n",
" generator=generator\n",
").images\n",
"\n",
"content_img_path = f\"data_demo/content/{content_img_name}.jpg\"\n",
"content_img = load_pil_image(content_img_path)\n",
"\n",
"_, ax = plt.subplots(1, 3, figsize=(10, 5))\n",
"ax[0].imshow(content_img)\n",
"ax[1].imshow(images[0])\n",
"ax[2].imshow(images[1])\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Use style LoRA only"
]
},
{
"cell_type": "code",
"execution_count": 245,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded lora weights of the style image from chenblin26/ConsisLoRA-antimonocromatismo\n"
]
}
],
"source": [
"# adjust image name according to your needs\n",
"style_img_name = \"antimonocromatismo\" # see \"data_demo/style\"\n",
"style_lora_path = f\"chenblin26/ConsisLoRA-{style_img_name}\"\n",
"\n",
"pipeline.unload_lora_checkpoint()\n",
"pipeline.load_lora_checkpoint(style_image_lora_path=style_lora_path)"
]
},
{
"cell_type": "code",
"execution_count": 250,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f37e7bea9ad148a7b552279d374d17f5",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/30 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "2fae4b58000c4e2c9494259ec8f3db84",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/30 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded input image of size ((512, 512)) from data_demo/style/antimonocromatismo.jpg\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1000x500 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"num_images_per_prompt = 1 # adjust according to VRAM size\n",
"generator = torch.manual_seed(29) # seed\n",
"\n",
"prompts = [\"a dog in the style of [v]\", \"a street in the style of [v]\"]\n",
"style_lora_scaling = 1.2 # you can adjust to control style strength\n",
"\n",
"images = [ \n",
" pipeline(\n",
" prompt=prompt, \n",
" lora_scaling = [0., style_lora_scaling],\n",
" guidance_scale=7.5,\n",
" num_inference_steps=30, \n",
" num_images_per_prompt=num_images_per_prompt, \n",
" generator=generator\n",
" ).images[0] for prompt in prompts\n",
"]\n",
"\n",
"style_img_path = f\"data_demo/style/{style_img_name}.jpg\"\n",
"style_img = load_pil_image(style_img_path)\n",
"\n",
"_, ax = plt.subplots(1, 3, figsize=(10, 5))\n",
"ax[0].imshow(style_img)\n",
"ax[1].imshow(images[0])\n",
"ax[2].imshow(images[1])\n",
"plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "blora",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.10"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|
000haoji/deep-student
| 2,908 |
src/chat-core/utils/tauriApiClient.ts
|
/**
* Tauri API Client
*
* Simple client for direct Tauri API calls without streaming.
* Single responsibility: Non-streaming API communication.
*/
import { invoke } from '@tauri-apps/api/core';
export interface ChatMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp?: string;
}
export interface AnalysisRequest {
subject?: string;
question_image_files: string[];
analysis_image_files?: string[];
user_question: string;
enable_chain_of_thought?: boolean;
}
/**
* Tauri API Client - provides direct access to backend commands
*/
export class TauriApiClient {
/**
* Perform step-by-step analysis
*/
async analyzeStepByStep(request: AnalysisRequest): Promise<any> {
return invoke('analyze_step_by_step', { request });
}
/**
* Start streaming answer for existing analysis
*/
async startStreamingAnswer(tempId: string, enableChainOfThought: boolean = true): Promise<any> {
return invoke('start_streaming_answer', {
request: {
temp_id: tempId,
enable_chain_of_thought: enableChainOfThought
}
});
}
/**
* Continue chat stream
*/
async continueChatStream(tempId: string, chatHistory: any[], enableChainOfThought: boolean = true): Promise<any> {
return invoke('continue_chat_stream', {
request: {
temp_id: tempId,
chat_history: chatHistory,
enable_chain_of_thought: enableChainOfThought
}
});
}
/**
* Get chat history for a mistake
*/
async getMistakeChatHistory(mistakeId: number): Promise<any> {
return invoke('get_mistake_chat_history', { mistakeId });
}
/**
* Get all mistakes
*/
async getAllMistakes(): Promise<any> {
return invoke('get_all_mistakes');
}
/**
* Get mistake by ID
*/
async getMistakeById(id: number): Promise<any> {
return invoke('get_mistake_by_id', { id });
}
/**
* Save mistake
*/
async saveMistake(mistake: any): Promise<any> {
return invoke('save_mistake', { mistake });
}
/**
* Delete mistake
*/
async deleteMistake(id: number): Promise<any> {
return invoke('delete_mistake', { id });
}
/**
* Batch save mistakes
*/
async batchSaveMistakes(mistakes: any[]): Promise<any> {
return invoke('batch_save_mistakes', { mistakes });
}
/**
* Batch delete mistakes
*/
async batchDeleteMistakes(ids: number[]): Promise<any> {
return invoke('batch_delete_mistakes', { ids });
}
/**
* Get supported subjects
*/
async getSupportedSubjects(): Promise<string[]> {
return invoke('get_supported_subjects');
}
/**
* Get subject configs
*/
async getSubjectConfigs(): Promise<any[]> {
return invoke('get_all_subject_configs', { active_only: true });
}
}
/**
* Default client instance
*/
export const tauriApiClient = new TauriApiClient();
|
000haoji/deep-student
| 12,291 |
src/chat-core/styles/markdown.css
|
/**
* Markdown & RAG Styles - Markdown渲染和RAG相关样式
* 提取自原项目中所有Markdown和知识库相关的样式
*/
/* ============================================================================
Markdown基础样式 - Markdown Base Styles
============================================================================ */
.markdown-content {
line-height: 1.6;
color: #333;
font-size: 0.95rem;
}
.markdown-content > *:first-child {
margin-top: 0;
}
.markdown-content > *:last-child {
margin-bottom: 0;
}
/* 标题样式 */
.markdown-content h1,
.markdown-content h2,
.markdown-content h3,
.markdown-content h4,
.markdown-content h5,
.markdown-content h6 {
margin: 1.2em 0 0.6em 0;
font-weight: 600;
line-height: 1.3;
color: #2c3e50;
}
.markdown-content h1 { font-size: 1.5em; border-bottom: 2px solid #3498db; padding-bottom: 0.3em; }
.markdown-content h2 { font-size: 1.3em; border-bottom: 1px solid #bdc3c7; padding-bottom: 0.2em; }
.markdown-content h3 { font-size: 1.15em; }
.markdown-content h4 { font-size: 1.05em; }
.markdown-content h5 { font-size: 1em; }
.markdown-content h6 { font-size: 0.95em; color: #666; }
/* 段落和文本 */
.markdown-content p {
margin: 0.8em 0;
text-align: justify;
}
/* 空行优化 - 使空行变得非常窄 */
.markdown-content p:empty,
.markdown-content p:blank {
margin: 0.1em 0;
height: 0.1em;
line-height: 0.1;
}
/* 处理只包含空白字符的段落 */
.markdown-content p:has(br:only-child),
.markdown-content p:not(:has(*)):not(:has(text)):empty {
margin: 0.1em 0;
height: 0.1em;
line-height: 0.1;
}
/* 使用CSS选择器匹配只包含空白字符的段落 */
.markdown-content p:is(:empty, :not(:has(*)):has(br:only-child)) {
margin: 0.1em 0;
height: 0.1em;
line-height: 0.1;
}
/* 全局的空行处理 - 适用于所有可能的空行情况 */
.markdown-content br + br,
.markdown-content br:only-child {
line-height: 0.2;
}
/* 连续的空行处理 */
.markdown-content p:empty + p:empty {
display: none;
}
/* 更强的空行控制 */
.markdown-content p:empty,
.markdown-content p:has(br:only-child) {
margin: 0.2em 0 !important;
height: 0.2em !important;
line-height: 0.2 !important;
padding: 0 !important;
}
/* 对于包含只有空白字符的段落 */
.markdown-content p:not(:has(*)):is([children=" "], [children="\n"], [children="\t"]) {
margin: 0.1em 0 !important;
height: 0.1em !important;
line-height: 0.1 !important;
display: block !important;
}
/* ReactMarkdown生成的空段落 */
.markdown-content > p:empty {
margin: 0.15em 0 !important;
height: 0.15em !important;
font-size: 0.5em !important;
}
/* 全局减少段落间距 */
.markdown-content p + p {
margin-top: 0.6em !important;
}
.markdown-content strong {
font-weight: 600;
color: #2c3e50;
}
.markdown-content em {
font-style: italic;
color: #7f8c8d;
}
.markdown-content del {
text-decoration: line-through;
color: #95a5a6;
}
/* 链接样式 */
.markdown-content a {
color: #3498db;
text-decoration: none;
border-bottom: 1px solid transparent;
transition: all 0.2s ease;
}
.markdown-content a:hover {
color: #2980b9;
border-bottom-color: #2980b9;
}
/* 列表样式 */
.markdown-content ul,
.markdown-content ol {
margin: 0.8em 0;
padding-left: 2em;
}
.markdown-content li {
margin: 0.3em 0;
line-height: 1.5;
}
/* 空列表项优化 */
.markdown-content li:empty {
margin: 0.1em 0 !important;
height: 0.1em !important;
line-height: 0.1 !important;
display: list-item !important;
}
/* 只包含少量内容的列表项 */
.markdown-content li:has(p:empty),
.markdown-content li:has(br:only-child) {
margin: 0.15em 0 !important;
line-height: 1.2 !important;
}
/* 连续的空列表项 */
.markdown-content li:empty + li:empty {
display: none !important;
}
/* 减少列表项中段落的间距 */
.markdown-content li p {
margin: 0.2em 0 !important;
}
.markdown-content li p:only-child {
margin: 0 !important;
}
.markdown-content ul li {
list-style-type: disc;
}
.markdown-content ol li {
list-style-type: decimal;
}
.markdown-content ul ul li {
list-style-type: circle;
}
.markdown-content ul ul ul li {
list-style-type: square;
}
/* 引用块样式 */
.markdown-content blockquote {
margin: 1em 0;
padding: 0.8em 1.2em;
border-left: 4px solid #3498db;
background: #f8f9fa;
border-radius: 0 6px 6px 0;
color: #5a6c7d;
font-style: italic;
}
.markdown-content blockquote p {
margin: 0.4em 0;
}
.markdown-content blockquote p:first-child {
margin-top: 0;
}
.markdown-content blockquote p:last-child {
margin-bottom: 0;
}
/* 水平分割线 */
.markdown-content hr {
border: none;
height: 2px;
background: linear-gradient(to right, transparent, #bdc3c7, transparent);
margin: 2em 0;
}
/* ============================================================================
代码样式 - Code Styles
============================================================================ */
.markdown-content code {
font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', 'Consolas', 'source-code-pro', monospace;
font-size: 0.9em;
}
.inline-code {
background: #f1f3f4;
color: #e74c3c;
padding: 0.15em 0.4em;
border-radius: 3px;
font-weight: 500;
border: 1px solid #ecf0f1;
}
.code-block {
background: #f8f9fa;
color: #333;
padding: 1.2em;
border-radius: 8px;
margin: 1em 0;
overflow-x: auto;
box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
border: 1px solid #e9ecef;
}
.code-block code {
background: none;
color: inherit;
padding: 0;
border-radius: 0;
border: none;
font-size: 0.85em;
line-height: 1.5;
}
/* 语法高亮增强 */
.code-block .token.comment {
color: #a0aec0;
font-style: italic;
}
.code-block .token.keyword {
color: #63b3ed;
font-weight: bold;
}
.code-block .token.string {
color: #68d391;
}
.code-block .token.number {
color: #fbb6ce;
}
/* ============================================================================
表格样式 - Table Styles
============================================================================ */
.table-wrapper {
overflow-x: auto;
margin: 1em 0;
border-radius: 8px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
.markdown-table {
width: 100%;
border-collapse: collapse;
background: white;
border-radius: 8px;
overflow: hidden;
}
.markdown-table th,
.markdown-table td {
padding: 0.8em 1em;
text-align: left;
border-bottom: 1px solid #e2e8f0;
}
.markdown-table th {
background: #f7fafc;
font-weight: 600;
color: #2d3748;
border-bottom: 2px solid #cbd5e0;
}
.markdown-table tr:hover {
background: #f8f9fa;
}
.markdown-table tr:last-child td {
border-bottom: none;
}
/* ============================================================================
流式Markdown样式 - Streaming Markdown Styles
============================================================================ */
.streaming-markdown {
position: relative;
}
.normal-content,
.main-content {
position: relative;
}
.chain-of-thought {
margin-bottom: 1rem;
border: 1px solid #e0e7ff;
border-radius: 8px;
background: #f8faff;
overflow: hidden;
}
.chain-header {
padding: 0.75rem 1rem;
background: #f0f8ff;
border-bottom: 1px solid #e0e7ff;
display: flex;
align-items: center;
gap: 0.5rem;
cursor: pointer;
transition: background-color 0.2s;
}
.chain-header:hover {
background: #e6f3ff;
}
.chain-icon {
font-size: 1.1rem;
}
.chain-title {
font-weight: 500;
color: #4338ca;
font-size: 0.9rem;
}
.thinking-content {
padding: 1rem;
background: white;
}
/* ============================================================================
RAG来源样式 - RAG Sources Styles
============================================================================ */
.rag-sources-container {
margin-top: 12px;
border: 1px solid #e0e7ff;
border-radius: 8px;
background: #f8faff;
overflow: hidden;
}
.rag-sources-header {
padding: 8px 12px;
cursor: pointer;
display: flex;
align-items: center;
gap: 6px;
font-size: 13px;
font-weight: 500;
color: #4338ca;
background: #f0f8ff;
border-bottom: 1px solid #e0e7ff;
transition: background-color 0.2s;
user-select: none;
}
.rag-sources-header:hover {
background: #e6f3ff;
}
.rag-sources-content {
padding: 8px 12px;
background: white;
}
.rag-source-item {
margin-bottom: 12px;
padding: 10px;
background: white;
border-radius: 6px;
border: 1px solid #e5e7eb;
box-shadow: 0 1px 3px rgba(0, 0, 0, 0.05);
}
.rag-source-item:last-child {
margin-bottom: 0;
}
.rag-source-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 6px;
}
.rag-source-title {
font-size: 12px;
font-weight: 600;
color: #374151;
display: flex;
align-items: center;
gap: 4px;
}
.rag-source-title span:first-child {
font-size: 14px;
}
.rag-source-meta {
color: #6b7280;
font-weight: normal;
font-size: 11px;
}
.rag-source-score {
font-size: 11px;
color: #6b7280;
background: #f3f4f6;
padding: 2px 6px;
border-radius: 4px;
font-weight: 500;
}
.rag-source-content {
font-size: 12px;
color: #4b5563;
line-height: 1.4;
font-style: italic;
background: #f9fafb;
padding: 8px;
border-radius: 4px;
border: 1px solid #f3f4f6;
}
/* ============================================================================
数学公式样式 - Math Formula Styles
============================================================================ */
.markdown-content .katex {
font-size: 1.05em;
}
.markdown-content .katex-display {
margin: 1em 0;
text-align: center;
}
.markdown-content .katex-display .katex {
display: inline-block;
white-space: nowrap;
}
.markdown-content .katex-error {
color: #e74c3c;
background: #fdf2f2;
padding: 0.2em 0.4em;
border-radius: 3px;
border: 1px solid #fed7d7;
}
/* 数学公式容器样式增强 */
.markdown-content .katex-html {
white-space: nowrap;
overflow-x: auto;
overflow-y: hidden;
}
/* ============================================================================
图片样式 - Image Styles
============================================================================ */
.markdown-content img {
max-width: 100%;
height: auto;
border-radius: 6px;
margin: 0.5em 0;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
border: 1px solid #e2e8f0;
}
.markdown-content img[alt*="icon"],
.markdown-content img[alt*="emoji"] {
display: inline;
margin: 0 0.2em;
box-shadow: none;
border: none;
border-radius: 0;
vertical-align: middle;
}
/* ============================================================================
响应式设计 - Responsive Design
============================================================================ */
@media (max-width: 768px) {
.markdown-content {
font-size: 0.9rem;
}
.markdown-content h1 { font-size: 1.3em; }
.markdown-content h2 { font-size: 1.2em; }
.markdown-content h3 { font-size: 1.1em; }
.code-block {
padding: 1em;
font-size: 0.8em;
}
.markdown-table th,
.markdown-table td {
padding: 0.6em 0.8em;
font-size: 0.85em;
}
.table-wrapper {
box-shadow: none;
border: 1px solid #e2e8f0;
}
.rag-sources-header {
padding: 6px 10px;
font-size: 12px;
}
.rag-sources-content {
padding: 6px 10px;
}
.rag-source-item {
padding: 8px;
margin-bottom: 8px;
}
.rag-source-title {
font-size: 11px;
}
.rag-source-content {
font-size: 11px;
padding: 6px;
}
}
@media (max-width: 480px) {
.markdown-content {
font-size: 0.85rem;
}
.markdown-content ul,
.markdown-content ol {
padding-left: 1.5em;
}
.markdown-content blockquote {
padding: 0.6em 1em;
margin: 0.8em 0;
}
.code-block {
padding: 0.8em;
margin: 0.8em 0;
}
.chain-header {
padding: 0.6rem 0.8rem;
font-size: 0.85rem;
}
.thinking-content {
padding: 0.8rem;
}
}
/* ============================================================================
打印样式 - Print Styles
============================================================================ */
@media print {
.markdown-content {
color: black;
background: white;
}
.code-block {
background: #f5f5f5;
color: black;
border: 1px solid #ccc;
}
.rag-sources-container {
border: 1px solid #ccc;
background: white;
}
.rag-sources-header {
background: #f5f5f5;
border-bottom: 1px solid #ccc;
}
.chain-of-thought {
border: 1px solid #ccc;
background: white;
}
.chain-header {
background: #f5f5f5;
border-bottom: 1px solid #ccc;
}
}
|
0015/esp_rlottie
| 1,149 |
rlottie/test/test_vrect.cpp
|
#include <gtest/gtest.h>
#include "vrect.h"
class VRectFTest : public ::testing::Test {
public:
void SetUp()
{
conersionRect = rect;
}
void TearDown()
{
}
public:
VRectF Empty;
VRectF illigal{0, 0, -100, 200};
VRectF conersionRect;
VRect rect{0, 0, 100, 100};
};
class VRectTest : public ::testing::Test {
public:
void SetUp()
{
conersionRect = rect;
}
void TearDown()
{
}
public:
VRect Empty;
VRect illigal{0, 0, -100, 200};
VRect conersionRect;
VRectF rect{0, 0, 100.5, 100};
};
TEST_F(VRectFTest, construct) {
VRectF r1{0, 0, 100, 100};
VRectF r2{0, 0, 100.0, 100};
VRectF r3 = {0, 0, 100, 100};
VRectF r4 = {0, 0, 100.0, 100};
VRectF r6(0, 0, 100, 100);
VRectF r7(0, 0, 100.0, 100);
ASSERT_TRUE(Empty.empty());
ASSERT_TRUE(illigal.empty());
}
TEST_F(VRectTest, construct) {
VRect r1{0, 0, 100, 100};
VRect r2{0, 0, 10, 100};
VRect r3 = {0, 0, 100, 100};
VRect r4 = {0, 0, 10, 100};
VRect r6(0, 0, 100, 100);
VRect r7(0, 0, 10, 100);
ASSERT_TRUE(Empty.empty());
ASSERT_TRUE(illigal.empty());
}
|
000linlin/ConsisLoRA
| 3,304 |
utils.py
|
from PIL import Image
import torch
from torchvision import transforms
BLOCKS = {
'content': ['unet.up_blocks.0.attentions.0'],
'style': ['unet.up_blocks.0.attentions.1'],
}
def is_belong_to_blocks(key, blocks):
try:
for g in blocks:
if g in key:
return True
return False
except Exception as e:
raise type(e)(f'failed to is_belong_to_block, due to: {e}')
def filter_consislora(state_dict):
try:
content_lora = {
k: v for k, v in state_dict.items() if is_belong_to_blocks(k, BLOCKS["content"])
}
style_lora = {
k: v for k, v in state_dict.items() if is_belong_to_blocks(k, BLOCKS["style"])
}
return content_lora, style_lora
except Exception as e:
raise type(e)(f'failed to filter_lora, due to: {e}')
def load_pil_image(img_path: str, target_size: int = None):
pil_img = Image.open(img_path).convert('RGB')
print(f"Loaded input image of size ({pil_img.size}) from {img_path}")
if target_size is not None:
resize = transforms.Resize(
size=target_size,
interpolation=transforms.InterpolationMode.BILINEAR
)
pil_img = resize(pil_img)
return pil_img
def unet_lora_state_dict(unet, adapter_name):
lora_state_dict = {}
for name, module in unet.named_modules():
for adapter in adapter_name:
if hasattr(module, adapter):
lora_layer = getattr(module, adapter)
if lora_layer is not None:
current_lora_sd = lora_layer.state_dict()
if "lora_A" in name: name = name.replace("lora_A", "lora.down")
elif "lora_B" in name: name = name.replace("lora_B", "lora.up")
for matrix_name, param in current_lora_sd.items():
lora_state_dict[f"{name}.{matrix_name}"] = param
return lora_state_dict
# Adapted from pipelines.StableDiffusionXLPipeline.encode_prompt
def encode_prompt(text_encoders, tokenizers, prompt, text_input_ids_list=None):
prompt_embeds_list = []
for i, text_encoder in enumerate(text_encoders):
if tokenizers is not None:
tokenizer = tokenizers[i]
text_input_ids = tokenizer(
prompt,
padding="max_length",
max_length=tokenizer.model_max_length,
truncation=True,
return_tensors="pt",
).input_ids
else:
assert text_input_ids_list is not None
text_input_ids = text_input_ids_list[i]
prompt_embeds = text_encoder(
text_input_ids.to(text_encoder.device),
output_hidden_states=True,
)
# We are only ALWAYS interested in the pooled output of the final text encoder
pooled_prompt_embeds = prompt_embeds[0]
prompt_embeds = prompt_embeds.hidden_states[-2]
bs_embed, seq_len, _ = prompt_embeds.shape
prompt_embeds = prompt_embeds.view(bs_embed, seq_len, -1)
prompt_embeds_list.append(prompt_embeds)
prompt_embeds = torch.concat(prompt_embeds_list, dim=-1)
pooled_prompt_embeds = pooled_prompt_embeds.view(bs_embed, -1)
return prompt_embeds, pooled_prompt_embeds
|
000linlin/ConsisLoRA
| 3,474 |
README.md
|
# ConsisLoRA: Enhancing Content and Style Consistency for LoRA-based Style Transfer
<a href='https://ConsisLoRA.github.io/'><img src='https://img.shields.io/badge/Project-Page-green'></a>
<a href='https://arxiv.org/abs/2503.10614'><img src='https://img.shields.io/badge/arXiv-2503.10614-b31b1b.svg'></a>
This repository contains the reference source code for the paper
[ConsisLoRA: Enhancing Content and Style Consistency for LoRA-based Style Transfer](https://arxiv.org/pdf/2503.10614).
## 🔥 News
- **2025/03/24**: We release the inference code and LoRA checkpoints (see [here](https://huggingface.co/chenblin26)).
## ⏳ TODOs
- [x] Release the inference code.
- [ ] Release the training code.
## Getting Started
This code was tested with Python 3.11, Pytorch 2.1 and Diffusers 0.31.
### Installation
```bash
git clone https://github.com/000linlin/ConsisLoRA.git
cd consislora
conda create -n consislora python=3.11
conda activate consislora
pip install -r requirements.txt
```
### 1. Train ConsisLoRA for content and style image
Waiting for training code release.
### 2. Inference
- For style transfer, run:
```
python inference.py \
--prompt "a [c] in the style of [v]" \
--content_image_lora_path "path/to/content" \
--style_image_lora_path "path/to/style" \
--lora_scaling 1. 1. \
--guidance_scale 7.5 \
--output_dir "inference-images" \
--num_images_per_prompt 1 \
--num_steps 30
```
Note that some additional parameters can be set for two guidance (see [Section 4.3](https://arxiv.org/pdf/2503.10614) of our paper).
1. `--content_guidance_scale`, `--style_guidance_scale` for controlling the strength of two guidance. Turning on the guidance will increase the inference time.
2. `--add_positive_content_prompt`, `--add_negative_content_prompt` is positive and negative prompts for content guidance, respectively. e.g, you can set `a [c]` and `a [v]` for them.
3. `--add_positive_style_prompt`, `--add_negative_style_prompt` is positive and negative prompts for style guidance, respectively. e.g, you can set `in the style of [v]` and `in the style of [c]` for them.
- For using the content LoRA separately, run:
```
python inference.py \
--prompt "a [c] in pixel art style" \
--content_image_lora_path "path/to/content" \
--lora_scaling 1. 0.
```
- For using the style LoRA separately, run:
```
python inference.py \
--prompt "a dog in the style of [v]" \
--style_image_lora_path "path/to/style" \
--lora_scaling 0. 1.
```
See the [**inference_demo**][inference] notebook for more details on how to generate stylized images.
## Demos
For more results, please visit our <a href="https://ConsisLoRA.github.io/"><strong>Project page</strong></a>.
## Acknowledgements
Our code mainly bases on [B-LoRA](https://github.com/yardenfren1996/B-LoRA) and [diffusers](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/train_dreambooth_lora_sdxl.py). A huge thank you to the authors for their valuable contributions.
## Citation
If you use this code, please consider citing our paper:
```bibtex
@article{chen2025consislora,
title={ConsisLoRA: Enhancing Content and Style Consistency for LoRA-based Style Transfer},
author={Bolin Chen, Baoquan Zhao, Haoran Xie, Yi Cai, Qing Li and Xudong Mao},
journal={arXiv preprint arXiv:2503.10614},
year={2025}
}
```
[inference]: inference_demo.ipynb
|
000haoji/deep-student
| 11,707 |
src/chat-core/styles/chat.css
|
/**
* Chat Core Styles - 聊天界面核心样式
* 提取自原项目中所有聊天相关的样式
*/
/* ============================================================================
聊天容器 - Chat Container
============================================================================ */
.chat-container {
display: flex;
flex-direction: column;
height: 100%;
background: white;
border-radius: 100px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
overflow: hidden;
transition: all 0.3s ease;
}
.chat-container.chat-fullscreen {
position: fixed;
top: 0;
left: 0;
right: 0;
bottom: 0;
z-index: 1000;
border-radius: 0;
box-shadow: none;
background: white;
}
.chat-header {
padding: 1rem 1.5rem;
border-bottom: 1px solid #e0e0e0;
background: #f8f9fa;
display: flex;
justify-content: space-between;
align-items: center;
min-height: 60px;
}
.chat-header h3,
.chat-header h4 {
margin: 0;
font-size: 1.1rem;
color: #333;
font-weight: 600;
}
.chat-header-actions {
display: flex;
align-items: center;
gap: 10px;
}
.chat-fullscreen-toggle {
background: none;
border: none;
font-size: 1.2rem;
cursor: pointer;
color: #666;
padding: 0.25rem 0.5rem;
border-radius: 4px;
transition: all 0.2s;
}
.chat-fullscreen-toggle:hover {
background-color: #e0e0e0;
color: #333;
}
.chain-indicator {
display: flex;
align-items: center;
gap: 0.5rem;
font-size: 0.9rem;
color: #666;
background: #f0f8ff;
padding: 0.25rem 0.75rem;
border-radius: 12px;
border: 1px solid #e0e7ff;
}
/* ============================================================================
聊天历史 - Chat History
============================================================================ */
.chat-history {
flex: 1;
overflow-y: auto;
padding: 1rem;
display: flex;
flex-direction: column;
gap: 1rem;
max-height: 100vh;
scroll-behavior: smooth;
}
.chat-messages {
flex: 1;
overflow-y: auto;
padding: 1rem;
display: flex;
flex-direction: column;
gap: 1rem;
max-height: 100vh;
}
.empty-chat {
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
padding: 3rem 1rem;
color: #666;
text-align: center;
}
.empty-chat p {
margin: 0.5rem 0;
line-height: 1.5;
}
/* ============================================================================
消息样式 - Message Styles
============================================================================ */
.message {
display: flex;
flex-direction: column;
margin-bottom: 1.5rem;
opacity: 1;
transition: opacity 0.3s ease;
}
.message.user {
align-items: flex-end;
}
.message.assistant {
align-items: flex-start;
}
.message.streaming {
opacity: 1;
}
.message-content {
max-width: 80%;
padding: 1rem 1.25rem;
border-radius: 18px;
word-wrap: break-word;
line-height: 1.5;
font-size: 0.95rem;
position: relative;
}
.message.user .message-content {
background: linear-gradient(135deg, #007bff 0%, #0056b3 100%);
color: white;
border-bottom-right-radius: 8px;
}
.message.assistant .message-content {
background: #f8f9fa;
color: #333;
border: 1px solid #e9ecef;
border-bottom-left-radius: 8px;
}
.message-time {
font-size: 0.75rem;
color: #666;
margin-top: 0.5rem;
padding: 0 0.5rem;
}
.message.user .message-time {
text-align: right;
}
.message.assistant .message-time {
text-align: left;
}
/* ============================================================================
思维链样式 - Thinking Chain Styles
============================================================================ */
.thinking-container {
margin-bottom: 1rem;
border: 1px solid #e0e7ff;
border-radius: 8px;
background: #f8faff;
overflow: hidden;
}
.thinking-header {
padding: 0.75rem 1rem;
background: #f0f8ff;
border-bottom: 1px solid #e0e7ff;
cursor: pointer;
display: flex;
align-items: center;
gap: 0.5rem;
transition: background-color 0.2s;
user-select: none;
}
.thinking-header:hover {
background: #e6f3ff;
}
.thinking-icon {
font-size: 1.1rem;
}
.thinking-title {
font-weight: 500;
color: #4338ca;
font-size: 0.9rem;
}
.thinking-toggle {
margin-left: auto;
color: #6b7280;
font-size: 0.8rem;
transition: transform 0.2s;
}
.thinking-content-box {
padding: 1rem;
background: white;
border-top: 1px solid #e0e7ff;
}
.thinking-status {
display: flex;
align-items: center;
gap: 0.5rem;
font-size: 0.9rem;
color: #666;
margin-bottom: 0.5rem;
}
/* ============================================================================
流式处理样式 - Streaming Styles
============================================================================ */
.streaming-indicator {
display: flex;
align-items: center;
gap: 0.5rem;
color: #007bff;
font-size: 0.9rem;
margin: 0.5rem 0;
}
.streaming-text {
position: relative;
}
.streaming-cursor {
display: inline-block;
width: 2px;
height: 1.2em;
background-color: #007bff;
animation: blink 1s infinite;
margin-left: 2px;
vertical-align: text-bottom;
}
@keyframes blink {
0%, 50% { opacity: 1; }
51%, 100% { opacity: 0; }
}
.typing-indicator {
display: inline-flex;
gap: 4px;
margin-right: 8px;
}
.typing-indicator span {
width: 6px;
height: 6px;
border-radius: 50%;
background-color: #666;
animation: typing 1.4s infinite ease-in-out;
}
.typing-indicator span:nth-child(1) { animation-delay: -0.32s; }
.typing-indicator span:nth-child(2) { animation-delay: -0.16s; }
@keyframes typing {
0%, 80%, 100% {
transform: scale(0.8);
opacity: 0.5;
}
40% {
transform: scale(1);
opacity: 1;
}
}
.partial-math-indicator {
display: inline-block;
margin-left: 4px;
opacity: 0.7;
animation: pulse 1s infinite;
}
@keyframes pulse {
0%, 100% { opacity: 0.7; }
50% { opacity: 1; }
}
/* ============================================================================
聊天输入 - Chat Input
============================================================================ */
.chat-input {
padding: 1rem 1.5rem;
border-top: 1px solid #e0e0e0;
background: white;
display: flex;
flex-direction: column;
gap: 0.75rem;
}
.input-row {
display: flex;
align-items: flex-end;
gap: 0.5rem;
}
.chat-input input[type="text"] {
flex: 1;
padding: 0.75rem 1rem;
border: 1px solid #ddd;
border-radius: 20px;
font-size: 0.95rem;
outline: none;
transition: border-color 0.2s;
resize: none;
min-height: 44px;
max-height: 120px;
}
.chat-input input[type="text"]:focus {
border-color: #007bff;
box-shadow: 0 0 0 3px rgba(0, 123, 255, 0.1);
}
.chat-input input[type="text"]:disabled {
background-color: #f8f9fa;
color: #6c757d;
cursor: not-allowed;
}
.send-button {
background: #007bff;
color: white;
border: none;
border-radius: 50%;
width: 44px;
height: 44px;
cursor: pointer;
transition: all 0.2s;
display: flex;
align-items: center;
justify-content: center;
font-size: 1.1rem;
flex-shrink: 0;
}
.send-button:hover:not(:disabled) {
background: #0056b3;
transform: scale(1.05);
}
.send-button:disabled {
background: #6c757d;
cursor: not-allowed;
transform: none;
}
.image-upload-btn {
background: #f8f9fa;
color: #666;
border: 1px solid #ddd;
border-radius: 50%;
width: 44px;
height: 44px;
cursor: pointer;
transition: all 0.2s;
display: flex;
align-items: center;
justify-content: center;
font-size: 1.1rem;
flex-shrink: 0;
}
.image-upload-btn:hover:not(:disabled) {
background: #e9ecef;
color: #495057;
transform: scale(1.05);
}
.image-upload-btn:disabled {
background: #f8f9fa;
color: #6c757d;
cursor: not-allowed;
transform: none;
}
/* ============================================================================
图片预览 - Image Preview
============================================================================ */
.image-preview-container {
border: 1px solid #e0e0e0;
border-radius: 8px;
padding: 0.75rem;
background: #f8f9fa;
}
.image-preview-header {
font-size: 0.85rem;
color: #666;
margin-bottom: 0.5rem;
font-weight: 500;
}
.image-preview-grid {
display: flex;
gap: 0.5rem;
flex-wrap: wrap;
}
.image-preview-item {
position: relative;
width: 60px;
height: 60px;
border-radius: 6px;
overflow: hidden;
border: 1px solid #ddd;
}
.image-preview-item img {
width: 100%;
height: 100%;
object-fit: cover;
}
.image-preview-info {
position: absolute;
top: 0;
right: 0;
background: rgba(0, 0, 0, 0.7);
color: white;
padding: 2px;
border-radius: 0 0 0 4px;
}
.remove-image-btn {
background: rgba(220, 53, 69, 0.9);
color: white;
border: none;
border-radius: 50%;
width: 18px;
height: 18px;
cursor: pointer;
font-size: 10px;
display: flex;
align-items: center;
justify-content: center;
transition: background-color 0.2s;
}
.remove-image-btn:hover {
background: rgba(220, 53, 69, 1);
}
/* ============================================================================
多模态内容 - Multimodal Content
============================================================================ */
.content-text-part {
margin-bottom: 0.5rem;
}
.content-text-part:last-child {
margin-bottom: 0;
}
.content-image-part {
margin: 0.5rem 0;
}
.content-image-part img {
max-width: 100%;
max-height: 300px;
display: block;
margin: 0 auto;
border-radius: 8px;
border: 1px solid #e5e7eb;
box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
}
.content-unknown {
padding: 1rem;
background: #fff3cd;
color: #856404;
border: 1px solid #ffeaa7;
border-radius: 6px;
font-style: italic;
}
/* ============================================================================
保存按钮 - Save Buttons
============================================================================ */
.save-buttons-row {
margin-top: 0.75rem;
padding-top: 0.75rem;
border-top: 1px solid #e9ecef;
display: flex;
gap: 0.75rem;
flex-wrap: wrap;
}
.save-button-inline,
.save-button-primary,
.save-button-secondary {
padding: 0.5rem 1rem;
border: none;
border-radius: 6px;
font-size: 0.85rem;
font-weight: 500;
cursor: pointer;
transition: all 0.2s;
display: flex;
align-items: center;
gap: 0.5rem;
}
.save-button-inline {
background: #28a745;
color: white;
}
.save-button-inline:hover:not(:disabled) {
background: #218838;
}
.save-button-primary {
background: #007bff;
color: white;
}
.save-button-primary:hover:not(:disabled) {
background: #0056b3;
}
.save-button-secondary {
background: #6c757d;
color: white;
}
.save-button-secondary:hover:not(:disabled) {
background: #545b62;
}
.save-buttons-group {
display: flex;
gap: 0.5rem;
}
/* ============================================================================
响应式设计 - Responsive Design
============================================================================ */
@media (max-width: 768px) {
.chat-container {
border-radius: 0;
height: 100vh;
}
.chat-header {
padding: 0.75rem 1rem;
}
.chat-history {
padding: 0.75rem;
}
.message-content {
max-width: 90%;
padding: 0.75rem 1rem;
font-size: 0.9rem;
}
.chat-input {
padding: 0.75rem 1rem;
}
.input-row {
gap: 0.5rem;
}
.send-button,
.image-upload-btn {
width: 40px;
height: 40px;
font-size: 1rem;
}
.chat-input input[type="text"] {
font-size: 16px; /* 防止iOS缩放 */
}
}
@media (max-width: 480px) {
.message-content {
max-width: 95%;
padding: 0.6rem 0.8rem;
font-size: 0.85rem;
}
.thinking-header {
padding: 0.6rem 0.8rem;
font-size: 0.85rem;
}
.thinking-content-box {
padding: 0.8rem;
}
}
|
000haoji/deep-student
| 16,106 |
src/chat-core/styles/analysis.css
|
/**
* Analysis Styles - 分析相关样式
* 从ReviewAnalysis.css中提取与聊天分析相关的样式
*/
/* ============================================================================
分析容器 - Analysis Container
============================================================================ */
.analysis-container {
width: 100%;
display: flex;
flex-direction: column;
background-color: #f8fafc;
}
.analysis-main {
flex: 1;
padding: 20px;
overflow-y: auto;
}
/* ============================================================================
分析头部 - Analysis Header
============================================================================ */
.analysis-header {
background: white;
border-bottom: 1px solid #e2e8f0;
padding: 16px 24px;
display: flex;
justify-content: space-between;
align-items: center;
}
.analysis-title {
font-size: 20px;
font-weight: 600;
color: #1f2937;
margin: 0;
}
.analysis-back-btn {
padding: 8px 12px;
background: #f3f4f6;
border: none;
border-radius: 6px;
cursor: pointer;
color: #374151;
display: flex;
align-items: center;
gap: 8px;
transition: background-color 0.2s;
}
.analysis-back-btn:hover {
background: #e5e7eb;
}
.analysis-create-btn {
padding: 12px 24px;
background: #3b82f6;
color: white;
border: none;
border-radius: 8px;
cursor: pointer;
font-weight: 500;
transition: background-color 0.2s;
}
.analysis-create-btn:hover {
background: #2563eb;
}
/* ============================================================================
分析步骤指示器 - Analysis Steps
============================================================================ */
.analysis-steps {
display: flex;
align-items: center;
gap: 16px;
margin-bottom: 24px;
padding: 0 20px;
}
.analysis-step {
display: flex;
align-items: center;
gap: 8px;
}
.analysis-step-circle {
width: 32px;
height: 32px;
border-radius: 50%;
display: flex;
align-items: center;
justify-content: center;
font-size: 14px;
font-weight: 500;
}
.analysis-step-circle.active {
background: #3b82f6;
color: white;
}
.analysis-step-circle.completed {
background: #10b981;
color: white;
}
.analysis-step-circle.pending {
background: #e5e7eb;
color: #6b7280;
}
.analysis-step-label {
font-size: 14px;
color: #374151;
}
.analysis-step-divider {
width: 32px;
height: 1px;
background: #d1d5db;
}
/* ============================================================================
分析表单 - Analysis Form
============================================================================ */
.analysis-form-container {
background: white;
border-radius: 12px;
box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1);
border: 1px solid #e5e7eb;
padding: 24px;
margin: 0 20px;
min-height: 400px;
}
.analysis-form-group {
margin-bottom: 20px;
}
.analysis-form-label {
display: block;
font-size: 14px;
font-weight: 500;
color: #374151;
margin-bottom: 8px;
}
.analysis-form-input,
.analysis-form-select,
.analysis-form-textarea {
width: 100%;
padding: 12px;
border: 1px solid #d1d5db;
border-radius: 6px;
font-size: 14px;
transition: border-color 0.2s, box-shadow 0.2s;
}
.analysis-form-input:focus,
.analysis-form-select:focus,
.analysis-form-textarea:focus {
outline: none;
border-color: #3b82f6;
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
}
.analysis-form-input:hover,
.analysis-form-select:hover {
border-color: #9ca3af;
}
.analysis-form-textarea {
resize: vertical;
min-height: 120px;
}
/* ============================================================================
分析模板 - Analysis Templates
============================================================================ */
.analysis-templates {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
gap: 8px;
margin-bottom: 16px;
}
.analysis-template-btn {
text-align: left;
padding: 12px;
font-size: 14px;
border: 1px solid #e5e7eb;
border-radius: 6px;
background: white;
cursor: pointer;
transition: all 0.2s;
}
.analysis-template-btn:hover {
border-color: #3b82f6;
background: #eff6ff;
}
/* ============================================================================
错题选择 - Mistake Selection
============================================================================ */
.analysis-mistakes-grid {
display: grid;
grid-template-columns: repeat(auto-fill, minmax(300px, 1fr));
gap: 16px;
max-height: 400px;
overflow-y: auto;
padding-right: 8px;
}
.analysis-mistake-card {
border: 1px solid #e5e7eb;
border-radius: 8px;
padding: 16px;
cursor: pointer;
transition: all 0.2s;
background: white;
}
.analysis-mistake-card:hover {
border-color: #d1d5db;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
.analysis-mistake-card.selected {
border-color: #3b82f6;
background: #eff6ff;
box-shadow: 0 0 0 1px #3b82f6;
}
.analysis-mistake-header {
display: flex;
align-items: center;
margin-bottom: 8px;
gap: 12px;
}
.analysis-mistake-checkbox {
width: 16px;
height: 16px;
}
.analysis-mistake-subject {
font-size: 12px;
color: #3b82f6;
font-weight: 500;
background: #eff6ff;
padding: 2px 8px;
border-radius: 12px;
}
.analysis-mistake-date {
font-size: 12px;
color: #6b7280;
margin-left: auto;
}
.analysis-mistake-question {
font-weight: 500;
color: #1f2937;
margin-bottom: 8px;
line-height: 1.4;
overflow: hidden;
display: -webkit-box;
-webkit-line-clamp: 2;
-webkit-box-orient: vertical;
}
.analysis-mistake-content {
color: #6b7280;
font-size: 14px;
line-height: 1.4;
margin-bottom: 12px;
overflow: hidden;
display: -webkit-box;
-webkit-line-clamp: 3;
-webkit-box-orient: vertical;
}
.analysis-mistake-tags {
display: flex;
flex-wrap: wrap;
gap: 4px;
}
.analysis-mistake-tag {
background: #f3f4f6;
color: #374151;
padding: 2px 8px;
border-radius: 12px;
font-size: 12px;
}
/* ============================================================================
分析筛选 - Analysis Filters
============================================================================ */
.analysis-filters {
display: grid;
grid-template-columns: 1fr 1fr 2fr;
gap: 20px;
margin-bottom: 24px;
background: white;
padding: 20px;
border-radius: 12px;
box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1);
border: 1px solid #e5e7eb;
}
.analysis-search-group {
grid-column: 1 / -1;
}
.analysis-search-input {
background: white;
}
.analysis-search-input:focus {
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
}
/* ============================================================================
分析库 - Analysis Library
============================================================================ */
.analysis-library-grid {
display: grid;
grid-template-columns: repeat(auto-fill, minmax(400px, 1fr));
gap: 20px;
padding: 20px;
}
.analysis-library-card {
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.06);
border: 1px solid #e5e7eb;
padding: 20px;
cursor: pointer;
transition: all 0.3s ease;
position: relative;
overflow: hidden;
animation: fadeInUp 0.3s ease-out;
}
.analysis-library-card:hover {
transform: translateY(-2px);
box-shadow: 0 8px 24px rgba(0, 0, 0, 0.12);
border-color: #d1d5db;
}
.analysis-library-card:active {
transform: translateY(0);
}
.analysis-library-card:nth-child(odd) {
animation-delay: 0.1s;
}
.analysis-library-card:nth-child(even) {
animation-delay: 0.2s;
}
.analysis-card-header {
display: flex;
justify-content: space-between;
align-items: flex-start;
margin-bottom: 16px;
padding-bottom: 12px;
border-bottom: 1px solid #f3f4f6;
}
.analysis-card-info {
flex: 1;
min-width: 0;
}
.analysis-card-title {
font-size: 16px;
font-weight: 600;
color: #1f2937;
margin: 0 0 4px 0;
line-height: 1.4;
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
}
.analysis-card-id {
font-size: 12px;
color: #9ca3af;
font-family: monospace;
background: #f9fafb;
padding: 2px 6px;
border-radius: 4px;
}
.analysis-card-actions {
display: flex;
align-items: center;
gap: 8px;
flex-shrink: 0;
}
.analysis-status-badge {
font-size: 12px;
font-weight: 500;
padding: 4px 8px;
border-radius: 12px;
white-space: nowrap;
text-shadow: 0 1px 2px rgba(0, 0, 0, 0.1);
border: 1px solid rgba(255, 255, 255, 0.2);
}
.analysis-delete-btn {
background: #f3f4f6;
border: none;
border-radius: 6px;
padding: 6px 8px;
cursor: pointer;
font-size: 14px;
transition: all 0.2s;
color: #6b7280;
}
.analysis-delete-btn:hover {
background: #fee2e2;
color: #dc2626;
}
.analysis-card-content {
display: flex;
flex-direction: column;
gap: 12px;
}
.analysis-meta-row {
display: flex;
flex-wrap: wrap;
gap: 8px;
}
.analysis-meta-item {
font-size: 12px;
padding: 4px 8px;
border-radius: 12px;
white-space: nowrap;
flex-shrink: 0;
transition: all 0.2s ease;
}
.analysis-library-card:hover .analysis-meta-item {
transform: scale(1.05);
}
.analysis-subject-tag {
background: #eff6ff;
color: #1d4ed8;
font-weight: 500;
}
.analysis-mistake-count {
background: #f0fdf4;
color: #166534;
}
.analysis-chat-count {
background: #fef3c7;
color: #92400e;
}
.analysis-target-section,
.analysis-preview-section {
background: #f9fafb;
padding: 12px;
border-radius: 8px;
border-left: 3px solid #3b82f6;
transition: all 0.2s ease;
}
.analysis-library-card:hover .analysis-target-section,
.analysis-library-card:hover .analysis-preview-section {
background: #f3f4f6;
}
.analysis-target-label,
.analysis-preview-label {
font-size: 12px;
font-weight: 600;
color: #374151;
margin-bottom: 4px;
text-transform: uppercase;
letter-spacing: 0.5px;
}
.analysis-target-content,
.analysis-preview-content {
font-size: 14px;
color: #6b7280;
line-height: 1.5;
overflow: hidden;
display: -webkit-box;
-webkit-line-clamp: 2;
-webkit-box-orient: vertical;
}
.analysis-date-section {
display: flex;
align-items: center;
gap: 6px;
padding-top: 8px;
border-top: 1px solid #f3f4f6;
}
.analysis-date-icon {
font-size: 14px;
color: #9ca3af;
}
.analysis-date-text {
font-size: 12px;
color: #6b7280;
font-weight: 500;
}
/* ============================================================================
选中项预览 - Selected Preview
============================================================================ */
.analysis-selected-preview {
background: #f9fafb;
padding: 12px;
border-radius: 6px;
max-height: 120px;
overflow-y: auto;
margin-top: 8px;
}
.analysis-selected-item {
font-size: 14px;
color: #374151;
margin-bottom: 4px;
line-height: 1.4;
}
/* ============================================================================
分析按钮 - Analysis Buttons
============================================================================ */
.analysis-actions {
display: flex;
justify-content: space-between;
padding: 20px;
background: white;
border-top: 1px solid #e5e7eb;
}
.analysis-action-group {
display: flex;
gap: 12px;
}
.analysis-btn {
padding: 12px 24px;
border: none;
border-radius: 8px;
cursor: pointer;
font-size: 14px;
font-weight: 500;
transition: all 0.2s;
}
.analysis-btn-primary {
background: #3b82f6;
color: white;
}
.analysis-btn-primary:hover {
background: #2563eb;
}
.analysis-btn-primary:disabled {
background: #d1d5db;
cursor: not-allowed;
}
.analysis-btn-secondary {
background: #6b7280;
color: white;
}
.analysis-btn-secondary:hover {
background: #4b5563;
}
.analysis-btn-ghost {
background: #f3f4f6;
color: #374151;
}
.analysis-btn-ghost:hover {
background: #e5e7eb;
}
/* ============================================================================
分析状态 - Analysis States
============================================================================ */
.analysis-loading {
display: flex;
justify-content: center;
align-items: center;
height: 200px;
gap: 12px;
opacity: 0;
animation: fadeIn 0.3s ease-in-out forwards;
}
.analysis-loading-spinner {
width: 24px;
height: 24px;
border: 2px solid #e5e7eb;
border-top: 2px solid #3b82f6;
border-radius: 50%;
animation: spin 1s linear infinite;
}
.analysis-loading-text {
color: #6b7280;
font-size: 14px;
}
.analysis-empty {
text-align: center;
padding: 48px 24px;
color: #6b7280;
}
.analysis-empty-icon {
font-size: 48px;
margin-bottom: 16px;
}
.analysis-empty-title {
font-size: 18px;
font-weight: 600;
color: #374151;
margin-bottom: 8px;
}
.analysis-empty-description {
font-size: 14px;
color: #6b7280;
margin-bottom: 4px;
}
.analysis-empty-hint {
font-size: 14px;
color: #9ca3af;
}
/* ============================================================================
分析统计 - Analysis Stats
============================================================================ */
.analysis-library-stats {
display: flex;
flex-direction: column;
align-items: flex-end;
gap: 4px;
}
.analysis-stats-text {
font-size: 16px;
font-weight: 500;
color: #1f2937;
}
.analysis-stats-filter {
font-size: 14px;
color: #6b7280;
}
/* ============================================================================
动画定义 - Animations
============================================================================ */
@keyframes fadeInUp {
from {
opacity: 0;
transform: translateY(20px);
}
to {
opacity: 1;
transform: translateY(0);
}
}
@keyframes fadeIn {
to {
opacity: 1;
}
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
/* ============================================================================
滚动条样式 - Scrollbar
============================================================================ */
.analysis-mistakes-grid::-webkit-scrollbar,
.analysis-selected-preview::-webkit-scrollbar,
.analysis-library-grid::-webkit-scrollbar {
width: 6px;
}
.analysis-mistakes-grid::-webkit-scrollbar-track,
.analysis-selected-preview::-webkit-scrollbar-track,
.analysis-library-grid::-webkit-scrollbar-track {
background: #f1f5f9;
border-radius: 3px;
}
.analysis-mistakes-grid::-webkit-scrollbar-thumb,
.analysis-selected-preview::-webkit-scrollbar-thumb,
.analysis-library-grid::-webkit-scrollbar-thumb {
background: #cbd5e1;
border-radius: 3px;
}
.analysis-mistakes-grid::-webkit-scrollbar-thumb:hover,
.analysis-selected-preview::-webkit-scrollbar-thumb:hover,
.analysis-library-grid::-webkit-scrollbar-thumb:hover {
background: #94a3b8;
}
/* ============================================================================
响应式设计 - Responsive Design
============================================================================ */
@media (max-width: 1024px) {
.analysis-filters {
grid-template-columns: 1fr 1fr;
gap: 16px;
}
.analysis-search-group {
grid-column: 1 / -1;
}
}
@media (max-width: 768px) {
.analysis-filters {
grid-template-columns: 1fr;
padding: 16px;
gap: 12px;
}
.analysis-search-group {
grid-column: 1;
}
.analysis-mistakes-grid {
grid-template-columns: 1fr;
}
.analysis-templates {
grid-template-columns: 1fr;
}
.analysis-actions {
flex-direction: column;
gap: 12px;
}
.analysis-header {
padding: 12px 16px;
flex-direction: column;
gap: 12px;
align-items: flex-start;
}
.analysis-library-stats {
width: 100%;
align-items: flex-start;
}
.analysis-library-grid {
grid-template-columns: 1fr;
gap: 16px;
padding: 16px;
}
.analysis-library-card {
padding: 16px;
}
.analysis-card-header {
flex-direction: column;
gap: 8px;
align-items: flex-start;
}
.analysis-card-actions {
align-self: flex-end;
}
.analysis-library-stats {
align-items: flex-start;
}
}
@media (max-width: 480px) {
.analysis-meta-row {
flex-direction: column;
gap: 6px;
}
.analysis-meta-item {
align-self: flex-start;
}
}
|
000haoji/deep-student
| 9,781 |
src/chat-core/styles/index.css
|
/* Chat Core Styles - 统一样式入口 */
/* 从现有CSS文件中提取和整理的聊天核心样式集合 */
/* 导入核心聊天样式 */
@import './chat.css';
/* 导入Markdown渲染样式 */
@import './markdown.css';
/* 导入分析相关样式 */
@import './analysis.css';
/* ===== 全局聊天相关CSS变量 ===== */
:root {
/* 聊天主色调 */
--chat-primary: #667eea;
--chat-primary-dark: #5a6fd8;
--chat-secondary: #764ba2;
--chat-accent: #f093fb;
/* 聊天背景色 */
--chat-bg: #ffffff;
--chat-bg-light: #f8fafc;
--chat-bg-dark: #edf2f7;
/* 聊天边框色 */
--chat-border: #e2e8f0;
--chat-border-light: #f1f5f9;
--chat-border-dark: #cbd5e0;
/* 聊天文本色 */
--chat-text: #2d3748;
--chat-text-light: #4a5568;
--chat-text-muted: #718096;
/* 用户消息样式 */
--user-message-bg: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
--user-message-text: #ffffff;
/* 助手消息样式 */
--assistant-message-bg: #f8f9fa;
--assistant-message-text: #333333;
--assistant-message-border: #e1e5e9;
/* 流式处理样式 */
--streaming-bg: linear-gradient(135deg, #f0f8ff, #e6f3ff);
--streaming-border: rgba(66, 153, 225, 0.2);
--streaming-text: #2b6cb0;
/* 思维链样式 */
--thinking-bg: linear-gradient(135deg, #fef7e0, #fef3cd);
--thinking-border: #f6cc6d;
--thinking-text: #92400e;
/* RAG来源样式 */
--rag-bg: linear-gradient(135deg, #f0fdf4, #ecfdf5);
--rag-border: #86efac;
--rag-text: #166534;
/* 阴影 */
--chat-shadow-sm: 0 2px 4px rgba(0, 0, 0, 0.05);
--chat-shadow-md: 0 4px 12px rgba(0, 0, 0, 0.1);
--chat-shadow-lg: 0 8px 24px rgba(0, 0, 0, 0.15);
/* 圆角 */
--chat-radius-sm: 6px;
--chat-radius-md: 8px;
--chat-radius-lg: 12px;
--chat-radius-xl: 16px;
/* 间距 */
--chat-spacing-xs: 0.25rem;
--chat-spacing-sm: 0.5rem;
--chat-spacing-md: 1rem;
--chat-spacing-lg: 1.5rem;
--chat-spacing-xl: 2rem;
/* 动画时长 */
--chat-transition-fast: 0.15s;
--chat-transition-normal: 0.3s;
--chat-transition-slow: 0.5s;
}
/* ===== 聊天相关工具类 ===== */
.chat-flex {
display: flex;
}
.chat-flex-col {
flex-direction: column;
}
.chat-flex-1 {
flex: 1;
}
.chat-items-center {
align-items: center;
}
.chat-justify-between {
justify-content: space-between;
}
.chat-gap-sm {
gap: var(--chat-spacing-sm);
}
.chat-gap-md {
gap: var(--chat-spacing-md);
}
.chat-gap-lg {
gap: var(--chat-spacing-lg);
}
.chat-p-sm {
padding: var(--chat-spacing-sm);
}
.chat-p-md {
padding: var(--chat-spacing-md);
}
.chat-p-lg {
padding: var(--chat-spacing-lg);
}
.chat-m-sm {
margin: var(--chat-spacing-sm);
}
.chat-m-md {
margin: var(--chat-spacing-md);
}
.chat-m-lg {
margin: var(--chat-spacing-lg);
}
.chat-rounded-sm {
border-radius: var(--chat-radius-sm);
}
.chat-rounded-md {
border-radius: var(--chat-radius-md);
}
.chat-rounded-lg {
border-radius: var(--chat-radius-lg);
}
.chat-shadow-sm {
box-shadow: var(--chat-shadow-sm);
}
.chat-shadow-md {
box-shadow: var(--chat-shadow-md);
}
.chat-shadow-lg {
box-shadow: var(--chat-shadow-lg);
}
.chat-transition {
transition: all var(--chat-transition-normal) ease;
}
.chat-transition-fast {
transition: all var(--chat-transition-fast) ease;
}
.chat-transition-slow {
transition: all var(--chat-transition-slow) ease;
}
/* ===== 聊天状态指示器 ===== */
.chat-status-online {
color: #22c55e;
}
.chat-status-offline {
color: #ef4444;
}
.chat-status-thinking {
color: #f59e0b;
animation: pulse 2s ease-in-out infinite;
}
.chat-status-streaming {
color: var(--chat-primary);
animation: pulse 2s ease-in-out infinite;
}
/* ===== 聊天加载动画 ===== */
.chat-loading {
display: inline-flex;
align-items: center;
gap: 0.5rem;
}
.chat-loading-dot {
width: 8px;
height: 8px;
border-radius: 50%;
background: var(--chat-primary);
animation: chat-loading-bounce 1.4s ease-in-out infinite both;
}
.chat-loading-dot:nth-child(1) { animation-delay: -0.32s; }
.chat-loading-dot:nth-child(2) { animation-delay: -0.16s; }
.chat-loading-dot:nth-child(3) { animation-delay: 0s; }
@keyframes chat-loading-bounce {
0%, 80%, 100% {
transform: scale(0.8);
opacity: 0.5;
}
40% {
transform: scale(1);
opacity: 1;
}
}
/* ===== 聊天按钮样式 ===== */
.chat-btn {
display: inline-flex;
align-items: center;
justify-content: center;
padding: 0.5rem 1rem;
border: none;
border-radius: var(--chat-radius-md);
font-size: 0.875rem;
font-weight: 500;
cursor: pointer;
transition: all var(--chat-transition-normal) ease;
text-decoration: none;
gap: 0.5rem;
}
.chat-btn:disabled {
opacity: 0.6;
cursor: not-allowed;
}
.chat-btn-primary {
background: var(--user-message-bg);
color: var(--user-message-text);
box-shadow: var(--chat-shadow-sm);
}
.chat-btn-primary:hover:not(:disabled) {
transform: translateY(-1px);
box-shadow: var(--chat-shadow-md);
}
.chat-btn-secondary {
background: var(--chat-bg-dark);
color: var(--chat-text);
border: 1px solid var(--chat-border);
}
.chat-btn-secondary:hover:not(:disabled) {
background: var(--chat-bg-light);
border-color: var(--chat-border-dark);
}
.chat-btn-ghost {
background: transparent;
color: var(--chat-text-light);
}
.chat-btn-ghost:hover:not(:disabled) {
background: var(--chat-bg-light);
}
.chat-btn-sm {
padding: 0.25rem 0.75rem;
font-size: 0.75rem;
}
.chat-btn-lg {
padding: 0.75rem 1.5rem;
font-size: 1rem;
}
/* ===== 聊天输入框样式 ===== */
.chat-input-base {
width: 100%;
padding: 0.75rem 1rem;
border: 2px solid var(--chat-border);
border-radius: var(--chat-radius-md);
font-size: 0.875rem;
font-family: inherit;
background: var(--chat-bg);
color: var(--chat-text);
transition: all var(--chat-transition-normal) ease;
outline: none;
}
.chat-input-base:focus {
border-color: var(--chat-primary);
box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.1);
}
.chat-input-base:disabled {
background: var(--chat-bg-dark);
cursor: not-allowed;
opacity: 0.7;
}
.chat-input-base::placeholder {
color: var(--chat-text-muted);
}
/* ===== 聊天徽章样式 ===== */
.chat-badge {
display: inline-flex;
align-items: center;
padding: 0.25rem 0.75rem;
border-radius: 12px;
font-size: 0.75rem;
font-weight: 500;
white-space: nowrap;
}
.chat-badge-primary {
background: rgba(102, 126, 234, 0.1);
color: var(--chat-primary);
}
.chat-badge-success {
background: rgba(34, 197, 94, 0.1);
color: #166534;
}
.chat-badge-warning {
background: rgba(245, 158, 11, 0.1);
color: #92400e;
}
.chat-badge-error {
background: rgba(239, 68, 68, 0.1);
color: #dc2626;
}
.chat-badge-info {
background: rgba(59, 130, 246, 0.1);
color: #1e40af;
}
/* ===== 聊天分隔符 ===== */
.chat-divider {
height: 1px;
background: var(--chat-border);
margin: var(--chat-spacing-md) 0;
}
.chat-divider-text {
position: relative;
text-align: center;
margin: var(--chat-spacing-lg) 0;
}
.chat-divider-text::before {
content: '';
position: absolute;
top: 50%;
left: 0;
right: 0;
height: 1px;
background: var(--chat-border);
}
.chat-divider-text span {
background: var(--chat-bg);
padding: 0 var(--chat-spacing-md);
color: var(--chat-text-muted);
font-size: 0.875rem;
position: relative;
}
/* ===== 聊天时间戳 ===== */
.chat-timestamp {
font-size: 0.75rem;
color: var(--chat-text-muted);
font-weight: 500;
}
.chat-timestamp-relative {
font-style: italic;
}
/* ===== 聊天头像样式 ===== */
.chat-avatar {
width: 32px;
height: 32px;
border-radius: 50%;
background: var(--chat-bg-dark);
display: flex;
align-items: center;
justify-content: center;
font-weight: 600;
font-size: 0.875rem;
color: var(--chat-text);
flex-shrink: 0;
}
.chat-avatar-sm {
width: 24px;
height: 24px;
font-size: 0.75rem;
}
.chat-avatar-lg {
width: 40px;
height: 40px;
font-size: 1rem;
}
.chat-avatar-user {
background: var(--user-message-bg);
color: var(--user-message-text);
}
.chat-avatar-assistant {
background: var(--chat-primary);
color: white;
}
/* ===== 聊天图标样式 ===== */
.chat-icon {
width: 1em;
height: 1em;
display: inline-block;
vertical-align: middle;
}
.chat-icon-sm {
width: 0.875em;
height: 0.875em;
}
.chat-icon-lg {
width: 1.25em;
height: 1.25em;
}
/* ===== 响应式断点 ===== */
@media (max-width: 768px) {
:root {
--chat-spacing-md: 0.75rem;
--chat-spacing-lg: 1rem;
--chat-spacing-xl: 1.5rem;
}
.chat-btn {
padding: 0.5rem 0.875rem;
font-size: 0.8rem;
}
.chat-input-base {
padding: 0.625rem 0.875rem;
font-size: 0.8rem;
}
.chat-avatar {
width: 28px;
height: 28px;
font-size: 0.8rem;
}
}
@media (max-width: 480px) {
:root {
--chat-spacing-sm: 0.375rem;
--chat-spacing-md: 0.625rem;
--chat-spacing-lg: 0.875rem;
--chat-spacing-xl: 1.25rem;
}
.chat-btn {
padding: 0.375rem 0.75rem;
font-size: 0.75rem;
}
.chat-input-base {
padding: 0.5rem 0.75rem;
font-size: 0.75rem;
}
.chat-avatar {
width: 24px;
height: 24px;
font-size: 0.75rem;
}
}
/* ===== 深色主题支持 ===== */
@media (prefers-color-scheme: dark) {
:root {
--chat-bg: #1a202c;
--chat-bg-light: #2d3748;
--chat-bg-dark: #4a5568;
--chat-border: #4a5568;
--chat-border-light: #718096;
--chat-border-dark: #2d3748;
--chat-text: #e2e8f0;
--chat-text-light: #cbd5e0;
--chat-text-muted: #a0aec0;
--assistant-message-bg: #2d3748;
--assistant-message-text: #e2e8f0;
--assistant-message-border: #4a5568;
}
}
/* ===== 打印样式 ===== */
@media print {
.chat-container {
background: white !important;
border: 1px solid #000 !important;
box-shadow: none !important;
}
.streaming-cursor,
.chat-loading,
.chat-btn {
display: none !important;
}
.message-content {
break-inside: avoid;
}
.thinking-section,
.chain-of-thought,
.rag-sources {
break-inside: avoid;
}
}
|
000haoji/deep-student
| 3,565 |
src/chat-core/styles/README.md
|
# Chat Core Styles
这个目录包含了从现有CSS文件中提取和整理的聊天相关样式，提供了一套完整的聊天界面样式系统。
## 文件结构
```
styles/
├── index.css # 主入口文件，导入所有样式和定义CSS变量
├── chat.css # 聊天界面核心样式
├── markdown.css # Markdown渲染和思维链样式
├── analysis.css # 分析相关样式（回顾分析、错题选择等）
└── README.md # 本文档
```
## 样式文件说明
### 1. index.css
- **主入口文件**，统一导入所有样式
- 定义CSS变量系统，便于主题定制
- 提供工具类和通用组件样式
- 包含响应式断点和深色主题支持
### 2. chat.css
- **聊天界面核心样式**，从App.css和DeepStudent.css中提取
- 包含以下主要样式：
- 聊天容器和布局
- 聊天头部和工具栏
- 消息显示（用户消息、助手消息）
- 流式处理指示器
- 聊天输入区域
- 全屏模式支持
- 聊天界面测试页面样式
### 3. markdown.css
- **Markdown渲染样式**，包含思维链和RAG来源显示
- 包含以下主要样式：
- 基础Markdown元素（标题、段落、列表等）
- 代码块和行内代码
- 表格样式
- 思维链显示（thinking-section）
- 推理链条显示（chain-of-thought）
- RAG来源显示（rag-sources）
- 流式渲染效果
- 特殊内容块（信息框、警告框等）
### 4. analysis.css
- **分析相关样式**，从ReviewAnalysis.css中提取
- 包含以下主要样式：
- 分析容器和布局
- 分析步骤指示器
- 分析表单和输入控件
- 错题选择和筛选界面
- 分析库卡片展示
- 分析结果预览
- 分析模板选择
- 响应式分析界面设计
## 样式提取来源
这些样式主要从以下文件中提取和整理：
1. **App.css** - 主要的聊天界面样式
- 流式聊天界面（.streaming-chat-interface）
- 消息样式（.message, .user-message-content）
- 聊天容器（.chat-container, .chat-header, .chat-input）
- Markdown渲染样式
- 流式处理样式
2. **DeepStudent.css** - 侧边栏和布局样式
- 聊天容器布局和全屏模式
- 聊天头部和操作按钮
3. **ReviewAnalysis.css** - 回顾分析相关样式（已提取到analysis.css）
- 分析容器和布局样式
- 分析步骤指示器
- 错题选择界面
- 分析库卡片展示
- 表单和按钮样式
- 筛选和搜索控件
4. **RagQueryView.css** - RAG查询界面样式
- RAG结果显示
- 查询配置样式
## 主要功能特性
### 1. 响应式设计
- 支持桌面端、平板和移动端
- 自适应布局和字体大小调整
- 移动端优化的交互体验
### 2. 主题支持
- 浅色主题（默认）
- 深色主题支持（通过 prefers-color-scheme）
- CSS变量系统便于主题定制
### 3. 聊天功能
- 用户和助手消息区分显示
- 流式文本渲染效果
- 打字指示器动画
- 全屏聊天模式
- 消息时间戳显示
### 4. 思维链显示
- 思维过程可视化
- 推理步骤展示
- 可折叠的思维内容
- RAG来源信息显示
### 5. Markdown增强
- 完整的Markdown语法支持
- 代码高亮（多语言支持）
- 表格美化
- 数学公式支持
- 特殊内容块（信息、警告、成功、错误）
### 6. 无障碍支持
- 键盘导航支持
- 屏幕阅读器友好
- 高对比度支持
- 焦点指示器
### 7. 动画效果
- 平滑的过渡动画
- 加载指示器
- 悬停效果
- 流式渲染动画
## 使用方法
### 基础使用
```tsx
import './chat-core/styles/index.css';
// 在你的组件中使用样式类
<div className="chat-container">
<div className="chat-header">
<h4>AI 助手</h4>
</div>
<div className="chat-history">
{/* 消息内容 */}
</div>
<div className="chat-input">
{/* 输入区域 */}
</div>
</div>
```
### 思维链使用
```tsx
<div className="thinking-section">
<div className="thinking-header">
🤔 思考过程
</div>
<div className="thinking-content">
<p>让我分析一下这个问题...</p>
</div>
</div>
```
### RAG来源显示
```tsx
<div className="rag-sources">
<div className="rag-sources-header">
📚 参考来源
</div>
<div className="rag-source-item">
<div className="rag-source-header">
<span className="rag-source-title">文档标题</span>
<span className="rag-source-score">0.95</span>
</div>
<div className="rag-source-content">
相关内容摘要...
</div>
</div>
</div>
```
### 工具类使用
```tsx
<div className="chat-flex chat-items-center chat-gap-md">
<button className="chat-btn chat-btn-primary">
发送消息
</button>
<span className="chat-badge chat-badge-success">
在线
</span>
</div>
```
## CSS变量定制
你可以通过重写CSS变量来定制主题：
```css
:root {
--chat-primary: #your-color;
--chat-bg: #your-bg-color;
--chat-text: #your-text-color;
/* 更多变量见 index.css */
}
```
## 注意事项
1. **样式隔离**：所有样式都使用了明确的类名前缀，避免与其他样式冲突
2. **性能优化**：使用了CSS变量和工具类，减少重复代码
3. **兼容性**：支持现代浏览器，包括Chrome、Firefox、Safari、Edge
4. **维护性**：样式按功能分类，便于维护和扩展
## 更新日志
- **v1.0.0** - 初始版本，从现有CSS文件中提取和整理聊天相关样式
- 包含完整的聊天界面、Markdown渲染、思维链显示功能
- 支持响应式设计和深色主题
- 提供丰富的工具类和组件样式
## 贡献指南
如果需要添加新的聊天相关样式：
1. 确定样式的功能分类（聊天界面 vs Markdown渲染）
2. 添加到对应的CSS文件中
3. 遵循现有的命名规范和代码风格
4. 确保添加响应式和深色主题支持
5. 更新本README文档
|
0015/esp_rlottie
| 7,171 |
rlottie/test/test_vpath.cpp
|
#include <gtest/gtest.h>
#include "vpath.h"
class VPathTest : public ::testing::Test {
public:
void SetUp()
{
pathRect.addRect({-10, -20, 100, 100});
pathRoundRect.addRoundRect({0, 0, 100, 100}, 5, 5);
pathRoundRectZeroCorner.addRoundRect({0, 0, 100, 100}, 0, 0);
pathRoundRectHalfCircle.addRoundRect({0, 0, 100, 100}, 60, 60);
pathOval.addOval({0,0,100,50});
pathOvalCircle.addOval({0,0,100,100});
pathCircle.addCircle(0, 0, 100);
pathCircleZeroRadius.addCircle(10, 10, 0);
pathPolygon.addPolygon(10, 50, 5, 0, 0, 0);
pathPolystar.addPolystar(10, 50, 100, 7, 14, 0, 0, 0);
pathPolygonZero.addPolygon(10, 50, 0, 0, 0, 0);
pathPolystarZero.addPolystar(10, 50, 100, 0, 0, 0, 0, 0);
}
void TearDown()
{
}
public:
VPath pathEmpty;
VPath pathRect;
VPath pathRoundRect;
VPath pathRoundRectZeroCorner;
VPath pathRoundRectHalfCircle;
VPath pathOval;
VPath pathOvalCircle;
VPath pathCircle;
VPath pathCircleZeroRadius;
VPath pathPolygon;
VPath pathPolystar;
VPath pathPolygonZero;
VPath pathPolystarZero;
};
TEST_F(VPathTest, emptyPath) {
ASSERT_EQ(sizeof(pathEmpty), sizeof(void *));
ASSERT_TRUE(pathEmpty.empty());
ASSERT_FALSE(pathEmpty.segments());
ASSERT_EQ(pathEmpty.segments() , 0);
ASSERT_EQ(pathEmpty.elements().size() , 0);
ASSERT_EQ(pathEmpty.elements().capacity() , pathEmpty.elements().size());
ASSERT_EQ(pathEmpty.points().size() , 0);
ASSERT_EQ(pathEmpty.points().capacity() , pathEmpty.points().size());
}
TEST_F(VPathTest, reset) {
pathRect.reset();
ASSERT_TRUE(pathRect.empty());
ASSERT_EQ(pathRect.segments() , 0);
ASSERT_GE(pathRect.points().capacity(), 1);
ASSERT_GE(pathRect.elements().capacity(), 1);
}
TEST_F(VPathTest, reserve) {
pathEmpty.reserve(10, 10);
ASSERT_EQ(pathEmpty.points().capacity(), 10);
ASSERT_GE(pathEmpty.elements().capacity(), 10);
ASSERT_EQ(pathEmpty.segments() , 0);
ASSERT_EQ(pathEmpty.points().size(), 0);
ASSERT_GE(pathEmpty.elements().size(), 0);
}
TEST_F(VPathTest, clone) {
VPath pathClone;
pathClone.clone(pathOval);
ASSERT_TRUE(pathClone.unique());
ASSERT_EQ(pathClone.segments(), pathOval.segments());
ASSERT_EQ(pathClone.points().size(), pathOval.points().size());
ASSERT_NE(pathClone.points().data(), pathOval.points().data());
ASSERT_EQ(pathClone.elements().size(), pathOval.elements().size());
ASSERT_NE(pathClone.elements().data(), pathOval.elements().data());
}
TEST_F(VPathTest, copyOnWrite) {
VPath pathCopy;
pathCopy = pathOval;
ASSERT_EQ(pathCopy.segments(), pathOval.segments());
ASSERT_EQ(pathCopy.points().size(), pathOval.points().size());
ASSERT_EQ(pathCopy.points().data(), pathOval.points().data());
ASSERT_EQ(pathCopy.elements().size(), pathOval.elements().size());
ASSERT_EQ(pathCopy.elements().data(), pathOval.elements().data());
}
TEST_F(VPathTest, addRect) {
ASSERT_FALSE(pathRect.empty());
ASSERT_EQ(pathRect.segments() , 1);
ASSERT_EQ(pathRect.elements().capacity() , pathRect.elements().size());
ASSERT_EQ(pathRect.points().capacity() , pathRect.points().size());
}
TEST_F(VPathTest, addRect_N) {
pathEmpty.addRect({});
ASSERT_TRUE(pathEmpty.empty());
ASSERT_EQ(pathEmpty.segments() , 0);
}
TEST_F(VPathTest, addRoundRect) {
ASSERT_FALSE(pathRoundRect.empty());
ASSERT_EQ(pathRoundRect.segments() , 1);
ASSERT_EQ(pathRoundRect.elements().capacity() , pathRoundRect.elements().size());
ASSERT_EQ(pathRoundRect.points().capacity() , pathRoundRect.points().size());
}
TEST_F(VPathTest, addRoundRectZeoCorner) {
ASSERT_FALSE(pathRoundRectZeroCorner.empty());
ASSERT_EQ(pathRoundRectZeroCorner.segments() , 1);
ASSERT_EQ(pathRoundRectZeroCorner.elements().size() , pathRect.elements().size());
ASSERT_EQ(pathRoundRectZeroCorner.elements().capacity() , pathRoundRectZeroCorner.elements().size());
ASSERT_EQ(pathRoundRectZeroCorner.points().size() , pathRect.points().size());
ASSERT_EQ(pathRoundRectZeroCorner.points().capacity() , pathRoundRectZeroCorner.points().size());
}
TEST_F(VPathTest, addRoundRectHalfCircle) {
ASSERT_FALSE(pathRoundRectHalfCircle.empty());
ASSERT_EQ(pathRoundRectHalfCircle.segments() , 1);
ASSERT_EQ(pathRoundRectHalfCircle.elements().capacity() , pathRoundRectHalfCircle.elements().size());
ASSERT_EQ(pathRoundRectHalfCircle.points().capacity() , pathRoundRectHalfCircle.points().size());
}
TEST_F(VPathTest, addOval) {
ASSERT_FALSE(pathOval.empty());
ASSERT_EQ(pathOval.segments() , 1);
ASSERT_EQ(pathOval.elements().capacity() , pathOval.elements().size());
ASSERT_EQ(pathOval.points().capacity() , pathOval.points().size());
}
TEST_F(VPathTest, addOvalCircle) {
ASSERT_FALSE(pathOvalCircle.empty());
ASSERT_EQ(pathOvalCircle.segments() , 1);
ASSERT_EQ(pathOvalCircle.elements().size() , pathOval.elements().size());
ASSERT_EQ(pathOvalCircle.elements().capacity() , pathOvalCircle.elements().size());
ASSERT_EQ(pathOvalCircle.points().size() , pathOval.points().size());
ASSERT_EQ(pathOvalCircle.points().capacity() , pathOvalCircle.points().size());
}
TEST_F(VPathTest, addCircle) {
ASSERT_FALSE(pathCircle.empty());
ASSERT_EQ(pathCircle.segments() , 1);
ASSERT_EQ(pathCircle.elements().size() , pathOval.elements().size());
ASSERT_EQ(pathCircle.elements().capacity() , pathCircle.elements().size());
ASSERT_EQ(pathCircle.points().size() , pathOval.points().size());
ASSERT_EQ(pathCircle.points().capacity() , pathCircle.points().size());
}
TEST_F(VPathTest, addCircleZeroRadius) {
ASSERT_TRUE(pathCircleZeroRadius.empty());
ASSERT_EQ(pathCircleZeroRadius.segments() , 0);
}
TEST_F(VPathTest, length) {
ASSERT_EQ(pathRect.length(), 400);
}
TEST_F(VPathTest, lengthEmptyPath) {
ASSERT_EQ(pathEmpty.length(), 0);
}
TEST_F(VPathTest, addPolygon) {
ASSERT_FALSE(pathPolygon.empty());
ASSERT_EQ(pathPolygon.segments() , 1);
ASSERT_EQ(pathPolygon.elements().size() , pathPolygon.elements().capacity());
ASSERT_EQ(pathPolygon.points().size() , pathPolygon.points().capacity());
}
TEST_F(VPathTest, addPolygonZeroRoundness) {
ASSERT_FALSE(pathPolygonZero.empty());
ASSERT_EQ(pathPolygonZero.segments() , 1);
ASSERT_EQ(pathPolygonZero.elements().size() , pathPolygonZero.elements().capacity());
ASSERT_EQ(pathPolygonZero.points().size() , pathPolygonZero.points().capacity());
}
TEST_F(VPathTest, addPolystar) {
ASSERT_FALSE(pathPolystar.empty());
ASSERT_EQ(pathPolystar.segments() , 1);
ASSERT_EQ(pathPolystar.elements().size() , pathPolystar.elements().capacity());
ASSERT_EQ(pathPolystar.points().size() , pathPolystar.points().capacity());
}
TEST_F(VPathTest, addPolystarZeroRoundness) {
ASSERT_FALSE(pathPolystarZero.empty());
ASSERT_EQ(pathPolystarZero.segments() , 1);
ASSERT_EQ(pathPolystarZero.elements().size() , pathPolystarZero.elements().capacity());
ASSERT_EQ(pathPolystarZero.points().size() , pathPolystarZero.points().capacity());
}
|
0015/esp_rlottie
| 1,131 |
rlottie/test/wasm_test.html
|
<!doctype html>
<html>
<canvas id="rlottie" width="100" height="100"></canvas>
<script>
var Module = {
onRuntimeInitialized: function() {
class Animator {
constructor(){
this.instance = new Module.RlottieWasm();
this.canvas = document.getElementById("rlottie");
this.frames = this.instance.frames();
this.curFrame = 0;
this.tick_cb();
}
tick_cb() {
var context = this.canvas.getContext('2d');
var buffer = this.instance.render(this.curFrame, this.canvas.width, this.canvas.height);
var clampedBuffer = Uint8ClampedArray.from(buffer);
var imageData = new ImageData(clampedBuffer, this.canvas.width, this.canvas.height);
context.putImageData(imageData, 0, 0);
this.curFrame += 1;
if (this.curFrame >= this.frames) this.curFrame = 0;
window.requestAnimationFrame(()=>{ this.tick_cb();});
}
}
var instance = new Animator();
}
};
</script>
<script src="rlottie-wasm.js"></script>
</html>
|
0015/esp_rlottie
| 1,113 |
rlottie/test/meson.build
|
override_default = ['warning_level=2', 'werror=false']
gtest_dep = dependency('gtest')
vector_test_sources = [
'testsuite.cpp',
'test_vrect.cpp',
'test_vpath.cpp',
]
vector_testsuite = executable('vectorTestSuite',
vector_test_sources,
include_directories : inc,
override_options : override_default,
dependencies : [gtest_dep, rlottie_lib_dep],
)
test('Vector Testsuite', vector_testsuite)
animation_test_sources = [
'testsuite.cpp',
'test_lottieanimation.cpp',
'test_lottieanimation_capi.cpp'
]
animation_testsuite = executable('animationTestSuite',
animation_test_sources,
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib,
dependencies : gtest_dep,
)
test('Animation Testsuite', animation_testsuite)
|
000linlin/ConsisLoRA
| 44,336 |
pipeline_demo.py
|
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from diffusers import StableDiffusionXLPipeline
from diffusers.pipelines.stable_diffusion_xl import StableDiffusionXLPipelineOutput
from diffusers.image_processor import PipelineImageInput
from diffusers.callbacks import PipelineCallback, MultiPipelineCallbacks
from diffusers.utils.deprecation_utils import deprecate
import inspect
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from peft.tuners.tuners_utils import BaseTunerLayer
from utils import encode_prompt, filter_consislora
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.retrieve_timesteps
def retrieve_timesteps(
scheduler,
num_inference_steps: Optional[int] = None,
device: Optional[Union[str, torch.device]] = None,
timesteps: Optional[List[int]] = None,
sigmas: Optional[List[float]] = None,
**kwargs,
):
r"""
Calls the scheduler's `set_timesteps` method and retrieves timesteps from the scheduler after the call. Handles
custom timesteps. Any kwargs will be supplied to `scheduler.set_timesteps`.
Args:
scheduler (`SchedulerMixin`):
The scheduler to get timesteps from.
num_inference_steps (`int`):
The number of diffusion steps used when generating samples with a pre-trained model. If used, `timesteps`
must be `None`.
device (`str` or `torch.device`, *optional*):
The device to which the timesteps should be moved to. If `None`, the timesteps are not moved.
timesteps (`List[int]`, *optional*):
Custom timesteps used to override the timestep spacing strategy of the scheduler. If `timesteps` is passed,
`num_inference_steps` and `sigmas` must be `None`.
sigmas (`List[float]`, *optional*):
Custom sigmas used to override the timestep spacing strategy of the scheduler. If `sigmas` is passed,
`num_inference_steps` and `timesteps` must be `None`.
Returns:
`Tuple[torch.Tensor, int]`: A tuple where the first element is the timestep schedule from the scheduler and the
second element is the number of inference steps.
"""
if timesteps is not None and sigmas is not None:
raise ValueError("Only one of `timesteps` or `sigmas` can be passed. Please choose one to set custom values")
if timesteps is not None:
accepts_timesteps = "timesteps" in set(inspect.signature(scheduler.set_timesteps).parameters.keys())
if not accepts_timesteps:
raise ValueError(
f"The current scheduler class {scheduler.__class__}'s `set_timesteps` does not support custom"
f" timestep schedules. Please check whether you are using the correct scheduler."
)
scheduler.set_timesteps(timesteps=timesteps, device=device, **kwargs)
timesteps = scheduler.timesteps
num_inference_steps = len(timesteps)
elif sigmas is not None:
accept_sigmas = "sigmas" in set(inspect.signature(scheduler.set_timesteps).parameters.keys())
if not accept_sigmas:
raise ValueError(
f"The current scheduler class {scheduler.__class__}'s `set_timesteps` does not support custom"
f" sigmas schedules. Please check whether you are using the correct scheduler."
)
scheduler.set_timesteps(sigmas=sigmas, device=device, **kwargs)
timesteps = scheduler.timesteps
num_inference_steps = len(timesteps)
else:
scheduler.set_timesteps(num_inference_steps, device=device, **kwargs)
timesteps = scheduler.timesteps
return timesteps, num_inference_steps
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.rescale_noise_cfg
def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
r"""
Rescales `noise_cfg` tensor based on `guidance_rescale` to improve image quality and fix overexposure. Based on
Section 3.4 from [Common Diffusion Noise Schedules and Sample Steps are
Flawed](https://arxiv.org/pdf/2305.08891.pdf).
Args:
noise_cfg (`torch.Tensor`):
The predicted noise tensor for the guided diffusion process.
noise_pred_text (`torch.Tensor`):
The predicted noise tensor for the text-guided diffusion process.
guidance_rescale (`float`, *optional*, defaults to 0.0):
A rescale factor applied to the noise predictions.
Returns:
noise_cfg (`torch.Tensor`): The rescaled noise prediction tensor.
"""
std_text = noise_pred_text.std(dim=list(range(1, noise_pred_text.ndim)), keepdim=True)
std_cfg = noise_cfg.std(dim=list(range(1, noise_cfg.ndim)), keepdim=True)
# rescale the results from guidance (fixes overexposure)
noise_pred_rescaled = noise_cfg * (std_text / std_cfg)
# mix with the original results from guidance by factor guidance_rescale to avoid "plain looking" images
noise_cfg = guidance_rescale * noise_pred_rescaled + (1 - guidance_rescale) * noise_cfg
return noise_cfg
class StableDiffusionXLPipelineLoraGuidance(StableDiffusionXLPipeline):
@torch.no_grad()
def __call__(
self,
prompt: Union[str, List[str]] = None,
prompt_2: Optional[Union[str, List[str]]] = None,
add_positive_content_prompt: str = None,
add_negative_content_prompt: str = None,
add_positive_style_prompt: str = None,
add_negative_style_prompt: str = None,
lora_scaling: list[float] = [1., 1.], # [content_lora_scaling, style_lora_scaling]
content_guidance_scale: float = 0.,
style_guidance_scale: float = 0.,
height: Optional[int] = None,
width: Optional[int] = None,
num_inference_steps: int = 50,
timesteps: List[int] = None,
sigmas: List[float] = None,
denoising_end: Optional[float] = None,
guidance_scale: float = 5.0,
negative_prompt: Optional[Union[str, List[str]]] = None,
negative_prompt_2: Optional[Union[str, List[str]]] = None,
num_images_per_prompt: Optional[int] = 1,
eta: float = 0.0,
generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None,
latents: Optional[torch.Tensor] = None,
prompt_embeds: Optional[torch.Tensor] = None,
negative_prompt_embeds: Optional[torch.Tensor] = None,
pooled_prompt_embeds: Optional[torch.Tensor] = None,
negative_pooled_prompt_embeds: Optional[torch.Tensor] = None,
ip_adapter_image: Optional[PipelineImageInput] = None,
ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None,
output_type: Optional[str] = "pil",
return_dict: bool = True,
cross_attention_kwargs: Optional[Dict[str, Any]] = None,
guidance_rescale: float = 0.0,
original_size: Optional[Tuple[int, int]] = None,
crops_coords_top_left: Tuple[int, int] = (0, 0),
target_size: Optional[Tuple[int, int]] = None,
negative_original_size: Optional[Tuple[int, int]] = None,
negative_crops_coords_top_left: Tuple[int, int] = (0, 0),
negative_target_size: Optional[Tuple[int, int]] = None,
clip_skip: Optional[int] = None,
callback_on_step_end: Optional[
Union[Callable[[int, int, Dict], None], PipelineCallback, MultiPipelineCallbacks]
] = None,
callback_on_step_end_tensor_inputs: List[str] = ["latents"],
**kwargs,
):
r"""
Function invoked when calling the pipeline for generation.
Args:
prompt (`str` or `List[str]`, *optional*):
The prompt or prompts to guide the image generation. If not defined, one has to pass `prompt_embeds`.
instead.
prompt_2 (`str` or `List[str]`, *optional*):
The prompt or prompts to be sent to the `tokenizer_2` and `text_encoder_2`. If not defined, `prompt` is
used in both text-encoders
height (`int`, *optional*, defaults to self.unet.config.sample_size * self.vae_scale_factor):
The height in pixels of the generated image. This is set to 1024 by default for the best results.
Anything below 512 pixels won't work well for
[stabilityai/stable-diffusion-xl-base-1.0](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0)
and checkpoints that are not specifically fine-tuned on low resolutions.
width (`int`, *optional*, defaults to self.unet.config.sample_size * self.vae_scale_factor):
The width in pixels of the generated image. This is set to 1024 by default for the best results.
Anything below 512 pixels won't work well for
[stabilityai/stable-diffusion-xl-base-1.0](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0)
and checkpoints that are not specifically fine-tuned on low resolutions.
num_inference_steps (`int`, *optional*, defaults to 50):
The number of denoising steps. More denoising steps usually lead to a higher quality image at the
expense of slower inference.
timesteps (`List[int]`, *optional*):
Custom timesteps to use for the denoising process with schedulers which support a `timesteps` argument
in their `set_timesteps` method. If not defined, the default behavior when `num_inference_steps` is
passed will be used. Must be in descending order.
sigmas (`List[float]`, *optional*):
Custom sigmas to use for the denoising process with schedulers which support a `sigmas` argument in
their `set_timesteps` method. If not defined, the default behavior when `num_inference_steps` is passed
will be used.
denoising_end (`float`, *optional*):
When specified, determines the fraction (between 0.0 and 1.0) of the total denoising process to be
completed before it is intentionally prematurely terminated. As a result, the returned sample will
still retain a substantial amount of noise as determined by the discrete timesteps selected by the
scheduler. The denoising_end parameter should ideally be utilized when this pipeline forms a part of a
"Mixture of Denoisers" multi-pipeline setup, as elaborated in [**Refining the Image
Output**](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/stable_diffusion_xl#refining-the-image-output)
guidance_scale (`float`, *optional*, defaults to 5.0):
Guidance scale as defined in [Classifier-Free Diffusion Guidance](https://arxiv.org/abs/2207.12598).
`guidance_scale` is defined as `w` of equation 2. of [Imagen
Paper](https://arxiv.org/pdf/2205.11487.pdf). Guidance scale is enabled by setting `guidance_scale >
1`. Higher guidance scale encourages to generate images that are closely linked to the text `prompt`,
usually at the expense of lower image quality.
negative_prompt (`str` or `List[str]`, *optional*):
The prompt or prompts not to guide the image generation. If not defined, one has to pass
`negative_prompt_embeds` instead. Ignored when not using guidance (i.e., ignored if `guidance_scale` is
less than `1`).
negative_prompt_2 (`str` or `List[str]`, *optional*):
The prompt or prompts not to guide the image generation to be sent to `tokenizer_2` and
`text_encoder_2`. If not defined, `negative_prompt` is used in both text-encoders
num_images_per_prompt (`int`, *optional*, defaults to 1):
The number of images to generate per prompt.
eta (`float`, *optional*, defaults to 0.0):
Corresponds to parameter eta (η) in the DDIM paper: https://arxiv.org/abs/2010.02502. Only applies to
[`schedulers.DDIMScheduler`], will be ignored for others.
generator (`torch.Generator` or `List[torch.Generator]`, *optional*):
One or a list of [torch generator(s)](https://pytorch.org/docs/stable/generated/torch.Generator.html)
to make generation deterministic.
latents (`torch.Tensor`, *optional*):
Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
tensor will ge generated by sampling using the supplied random `generator`.
prompt_embeds (`torch.Tensor`, *optional*):
Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
provided, text embeddings will be generated from `prompt` input argument.
negative_prompt_embeds (`torch.Tensor`, *optional*):
Pre-generated negative text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt
weighting. If not provided, negative_prompt_embeds will be generated from `negative_prompt` input
argument.
pooled_prompt_embeds (`torch.Tensor`, *optional*):
Pre-generated pooled text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting.
If not provided, pooled text embeddings will be generated from `prompt` input argument.
negative_pooled_prompt_embeds (`torch.Tensor`, *optional*):
Pre-generated negative pooled text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt
weighting. If not provided, pooled negative_prompt_embeds will be generated from `negative_prompt`
input argument.
ip_adapter_image: (`PipelineImageInput`, *optional*): Optional image input to work with IP Adapters.
ip_adapter_image_embeds (`List[torch.Tensor]`, *optional*):
Pre-generated image embeddings for IP-Adapter. It should be a list of length same as number of
IP-adapters. Each element should be a tensor of shape `(batch_size, num_images, emb_dim)`. It should
contain the negative image embedding if `do_classifier_free_guidance` is set to `True`. If not
provided, embeddings are computed from the `ip_adapter_image` input argument.
output_type (`str`, *optional*, defaults to `"pil"`):
The output format of the generate image. Choose between
[PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.
return_dict (`bool`, *optional*, defaults to `True`):
Whether or not to return a [`~pipelines.stable_diffusion_xl.StableDiffusionXLPipelineOutput`] instead
of a plain tuple.
cross_attention_kwargs (`dict`, *optional*):
A kwargs dictionary that if specified is passed along to the `AttentionProcessor` as defined under
`self.processor` in
[diffusers.models.attention_processor](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
guidance_rescale (`float`, *optional*, defaults to 0.0):
Guidance rescale factor proposed by [Common Diffusion Noise Schedules and Sample Steps are
Flawed](https://arxiv.org/pdf/2305.08891.pdf) `guidance_scale` is defined as `φ` in equation 16. of
[Common Diffusion Noise Schedules and Sample Steps are Flawed](https://arxiv.org/pdf/2305.08891.pdf).
Guidance rescale factor should fix overexposure when using zero terminal SNR.
original_size (`Tuple[int]`, *optional*, defaults to (1024, 1024)):
If `original_size` is not the same as `target_size` the image will appear to be down- or upsampled.
`original_size` defaults to `(height, width)` if not specified. Part of SDXL's micro-conditioning as
explained in section 2.2 of
[https://huggingface.co/papers/2307.01952](https://huggingface.co/papers/2307.01952).
crops_coords_top_left (`Tuple[int]`, *optional*, defaults to (0, 0)):
`crops_coords_top_left` can be used to generate an image that appears to be "cropped" from the position
`crops_coords_top_left` downwards. Favorable, well-centered images are usually achieved by setting
`crops_coords_top_left` to (0, 0). Part of SDXL's micro-conditioning as explained in section 2.2 of
[https://huggingface.co/papers/2307.01952](https://huggingface.co/papers/2307.01952).
target_size (`Tuple[int]`, *optional*, defaults to (1024, 1024)):
For most cases, `target_size` should be set to the desired height and width of the generated image. If
not specified it will default to `(height, width)`. Part of SDXL's micro-conditioning as explained in
section 2.2 of [https://huggingface.co/papers/2307.01952](https://huggingface.co/papers/2307.01952).
negative_original_size (`Tuple[int]`, *optional*, defaults to (1024, 1024)):
To negatively condition the generation process based on a specific image resolution. Part of SDXL's
micro-conditioning as explained in section 2.2 of
[https://huggingface.co/papers/2307.01952](https://huggingface.co/papers/2307.01952). For more
information, refer to this issue thread: https://github.com/huggingface/diffusers/issues/4208.
negative_crops_coords_top_left (`Tuple[int]`, *optional*, defaults to (0, 0)):
To negatively condition the generation process based on a specific crop coordinates. Part of SDXL's
micro-conditioning as explained in section 2.2 of
[https://huggingface.co/papers/2307.01952](https://huggingface.co/papers/2307.01952). For more
information, refer to this issue thread: https://github.com/huggingface/diffusers/issues/4208.
negative_target_size (`Tuple[int]`, *optional*, defaults to (1024, 1024)):
To negatively condition the generation process based on a target image resolution. It should be as same
as the `target_size` for most cases. Part of SDXL's micro-conditioning as explained in section 2.2 of
[https://huggingface.co/papers/2307.01952](https://huggingface.co/papers/2307.01952). For more
information, refer to this issue thread: https://github.com/huggingface/diffusers/issues/4208.
callback_on_step_end (`Callable`, `PipelineCallback`, `MultiPipelineCallbacks`, *optional*):
A function or a subclass of `PipelineCallback` or `MultiPipelineCallbacks` that is called at the end of
each denoising step during the inference. with the following arguments: `callback_on_step_end(self:
DiffusionPipeline, step: int, timestep: int, callback_kwargs: Dict)`. `callback_kwargs` will include a
list of all tensors as specified by `callback_on_step_end_tensor_inputs`.
callback_on_step_end_tensor_inputs (`List`, *optional*):
The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
`._callback_tensor_inputs` attribute of your pipeline class.
Examples:
Returns:
[`~pipelines.stable_diffusion_xl.StableDiffusionXLPipelineOutput`] or `tuple`:
[`~pipelines.stable_diffusion_xl.StableDiffusionXLPipelineOutput`] if `return_dict` is True, otherwise a
`tuple`. When returning a tuple, the first element is a list with the generated images.
"""
self.content_block = self.unet.get_submodule('up_blocks.0.attentions.0')
self.style_block = self.unet.get_submodule('up_blocks.0.attentions.1')
self._cnt_lora_names = ["content_lora", "neg_cnt_lora"]
self._sty_lora_names = ["style_lora", "neg_sty_lora"]
# self._all_lora_names = self._cnt_lora_names + self._sty_lora_names
callback = kwargs.pop("callback", None)
callback_steps = kwargs.pop("callback_steps", None)
if callback is not None:
deprecate(
"callback",
"1.0.0",
"Passing `callback` as an input argument to `__call__` is deprecated, consider use `callback_on_step_end`",
)
if callback_steps is not None:
deprecate(
"callback_steps",
"1.0.0",
"Passing `callback_steps` as an input argument to `__call__` is deprecated, consider use `callback_on_step_end`",
)
if isinstance(callback_on_step_end, (PipelineCallback, MultiPipelineCallbacks)):
callback_on_step_end_tensor_inputs = callback_on_step_end.tensor_inputs
# 0. Default height and width to unet
height = height or self.default_sample_size * self.vae_scale_factor
width = width or self.default_sample_size * self.vae_scale_factor
original_size = original_size or (height, width)
target_size = target_size or (height, width)
# 1. Check inputs. Raise error if not correct
self.check_inputs(
prompt,
prompt_2,
height,
width,
callback_steps,
negative_prompt,
negative_prompt_2,
prompt_embeds,
negative_prompt_embeds,
pooled_prompt_embeds,
negative_pooled_prompt_embeds,
ip_adapter_image,
ip_adapter_image_embeds,
callback_on_step_end_tensor_inputs,
)
self._guidance_scale = guidance_scale
self._guidance_rescale = guidance_rescale
self._clip_skip = clip_skip
self._cross_attention_kwargs = cross_attention_kwargs
self._denoising_end = denoising_end
self._interrupt = False
# 2. Define call parameters
if prompt is not None and isinstance(prompt, str):
batch_size = 1
elif prompt is not None and isinstance(prompt, list):
batch_size = len(prompt)
else:
batch_size = prompt_embeds.shape[0]
device = self._execution_device
# 3. Encode input prompt
lora_scale = (
self.cross_attention_kwargs.get("scale", None) if self.cross_attention_kwargs is not None else None
)
(
prompt_embeds,
negative_prompt_embeds,
pooled_prompt_embeds,
negative_pooled_prompt_embeds,
) = self.encode_prompt(
prompt=prompt,
prompt_2=prompt_2,
device=device,
num_images_per_prompt=num_images_per_prompt,
do_classifier_free_guidance=self.do_classifier_free_guidance,
negative_prompt=negative_prompt,
negative_prompt_2=negative_prompt_2,
prompt_embeds=prompt_embeds,
negative_prompt_embeds=negative_prompt_embeds,
pooled_prompt_embeds=pooled_prompt_embeds,
negative_pooled_prompt_embeds=negative_pooled_prompt_embeds,
lora_scale=lora_scale,
clip_skip=self.clip_skip,
)
# 4. Prepare timesteps
timesteps, num_inference_steps = retrieve_timesteps(
self.scheduler, num_inference_steps, device, timesteps, sigmas
)
# 5. Prepare latent variables
num_channels_latents = self.unet.config.in_channels
latents = self.prepare_latents(
batch_size * num_images_per_prompt,
num_channels_latents,
height,
width,
prompt_embeds.dtype,
device,
generator,
latents,
)
# 6. Prepare extra step kwargs. TODO: Logic should ideally just be moved out of the pipeline
extra_step_kwargs = self.prepare_extra_step_kwargs(generator, eta)
# 7. Prepare added time ids & embeddings
add_text_embeds = pooled_prompt_embeds
if self.text_encoder_2 is None:
text_encoder_projection_dim = int(pooled_prompt_embeds.shape[-1])
else:
text_encoder_projection_dim = self.text_encoder_2.config.projection_dim
add_time_ids = self._get_add_time_ids(
original_size,
crops_coords_top_left,
target_size,
dtype=prompt_embeds.dtype,
text_encoder_projection_dim=text_encoder_projection_dim,
)
if negative_original_size is not None and negative_target_size is not None:
negative_add_time_ids = self._get_add_time_ids(
negative_original_size,
negative_crops_coords_top_left,
negative_target_size,
dtype=prompt_embeds.dtype,
text_encoder_projection_dim=text_encoder_projection_dim,
)
else:
negative_add_time_ids = add_time_ids
if self.do_classifier_free_guidance:
prompt_embeds = torch.cat([negative_prompt_embeds, prompt_embeds], dim=0)
add_text_embeds = torch.cat([negative_pooled_prompt_embeds, add_text_embeds], dim=0)
add_time_ids = torch.cat([negative_add_time_ids, add_time_ids], dim=0)
prompt_embeds = prompt_embeds.to(device)
add_text_embeds = add_text_embeds.to(device)
add_time_ids = add_time_ids.to(device).repeat(batch_size * num_images_per_prompt, 1)
if ip_adapter_image is not None or ip_adapter_image_embeds is not None:
image_embeds = self.prepare_ip_adapter_image_embeds(
ip_adapter_image,
ip_adapter_image_embeds,
device,
batch_size * num_images_per_prompt,
self.do_classifier_free_guidance,
)
# 8. Denoising loop
num_warmup_steps = max(len(timesteps) - num_inference_steps * self.scheduler.order, 0)
# 8.1 Apply denoising_end
if (
self.denoising_end is not None
and isinstance(self.denoising_end, float)
and self.denoising_end > 0
and self.denoising_end < 1
):
discrete_timestep_cutoff = int(
round(
self.scheduler.config.num_train_timesteps
- (self.denoising_end * self.scheduler.config.num_train_timesteps)
)
)
num_inference_steps = len(list(filter(lambda ts: ts >= discrete_timestep_cutoff, timesteps)))
timesteps = timesteps[:num_inference_steps]
# 9. Optionally get Guidance Scale Embedding
timestep_cond = None
if self.unet.config.time_cond_proj_dim is not None:
guidance_scale_tensor = torch.tensor(self.guidance_scale - 1).repeat(batch_size * num_images_per_prompt)
timestep_cond = self.get_guidance_scale_embedding(
guidance_scale_tensor, embedding_dim=self.unet.config.time_cond_proj_dim
).to(device=device, dtype=latents.dtype)
"""
Implementation of two inference guidance. Begin with some prep work.
"""
if isinstance(lora_scaling, list) and len(lora_scaling) == 2:
content_lora_scaling, style_lora_scaling = lora_scaling
else:
raise ValueError("lora_scaling must be a list = [content_lora_scaling, style_lora_scaling]")
# if lora_scaling = [0., 0.], we close two inference guidance
if content_lora_scaling == 0 and style_lora_scaling == 0:
content_guidance_scale = style_guidance_scale = 0
# If using two guidance, we check whether the corresponding LoRA adapter has been loaded.
if content_guidance_scale > 0:
if not all(lora in self.lora_names for lora in self._cnt_lora_names):
raise ValueError(
f"Content guidance requires lora adapter names {self._cnt_lora_names}, but now is {self.lora_names}"
)
if style_guidance_scale > 0:
if not all(lora in self.lora_names for lora in self._sty_lora_names):
raise ValueError(
f"Style guidance requires lora adapter names {self._sty_lora_names}, but now is {self.lora_names}"
)
# Prepare additional prompt embeds for two guidance (content guidance and style guidance)
def get_add_embeds(add_prompt: str):
if add_prompt is not None:
add_prompt_embeds, add_pooled_prompt_embeds = encode_prompt(
text_encoders=[self.text_encoder, self.text_encoder_2],
tokenizers=[self.tokenizer, self.tokenizer_2],
prompt=add_prompt
)
add_prompt_embeds = add_prompt_embeds.repeat(num_images_per_prompt, 1, 1).to(device)
add_pooled_prompt_embeds = add_pooled_prompt_embeds.repeat(num_images_per_prompt, 1).to(device)
_time_ids = add_time_ids[num_images_per_prompt:]
else:
add_prompt_embeds = prompt_embeds[:num_images_per_prompt]
add_pooled_prompt_embeds = pooled_prompt_embeds[:num_images_per_prompt]
_time_ids = add_time_ids[:num_images_per_prompt]
_added_cond_kwargs = {
"text_embeds": add_pooled_prompt_embeds,
"time_ids": _time_ids,
}
return add_prompt_embeds, _added_cond_kwargs
add_positive_content_prompt_embeds, content_positive_added_cond_kwargs = get_add_embeds(add_positive_content_prompt)
add_negative_content_prompt_embeds, content_negative_added_cond_kwargs = get_add_embeds(add_negative_content_prompt)
add_positive_style_prompt_embeds, style_positive_added_cond_kwargs = get_add_embeds(add_positive_style_prompt)
add_negative_style_prompt_embeds, style_negative_added_cond_kwargs = get_add_embeds(add_negative_style_prompt)
self._num_timesteps = len(timesteps)
with self.progress_bar(total=num_inference_steps) as progress_bar:
for i, t in enumerate(timesteps):
if self.interrupt:
continue
# expand the latents if we are doing classifier free guidance
latent_model_input = torch.cat([latents] * 2) if self.do_classifier_free_guidance else latents
latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)
# predict the noise residual
added_cond_kwargs = {
"text_embeds": add_text_embeds,
"time_ids": add_time_ids
}
if ip_adapter_image is not None or ip_adapter_image_embeds is not None:
added_cond_kwargs["image_embeds"] = image_embeds
self._set_lora_scale(content_lora_scaling, style_lora_scaling, 0., 0.)
noise_pred = self.unet(
latent_model_input,
t,
encoder_hidden_states=prompt_embeds,
timestep_cond=timestep_cond,
cross_attention_kwargs=self.cross_attention_kwargs,
added_cond_kwargs=added_cond_kwargs,
return_dict=False,
)[0]
# perform classifier-free guidance
if self.do_classifier_free_guidance:
noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)
noise_pred_orig = noise_pred_uncond + self.guidance_scale * (noise_pred_text - noise_pred_uncond)
# perform two inference guidance (see Section 4.3 of https://arxiv.org/pdf/2503.10614)
noise_pred_content = noise_pred_style = 0.
if content_guidance_scale > 0:
self._set_lora_scale(1, 0, 0, 0)
noise_pred_content_positive = self.unet(
latent_model_input[num_images_per_prompt:],
t,
encoder_hidden_states=add_positive_content_prompt_embeds,
timestep_cond=timestep_cond,
cross_attention_kwargs=self.cross_attention_kwargs,
added_cond_kwargs=content_positive_added_cond_kwargs,
return_dict=False,
)[0]
self._set_lora_scale(0, 0, 1, 0)
noise_pred_content_negative = self.unet(
latent_model_input[:num_images_per_prompt],
t,
encoder_hidden_states=add_negative_content_prompt_embeds,
timestep_cond=timestep_cond,
cross_attention_kwargs=self.cross_attention_kwargs,
added_cond_kwargs=content_negative_added_cond_kwargs,
return_dict=False,
)[0]
noise_pred_content = content_guidance_scale * (
noise_pred_content_positive - noise_pred_content_negative
)
if style_guidance_scale > 0:
self._set_lora_scale(0, 1, 0, 0)
noise_pred_style_positive = self.unet(
latent_model_input[num_images_per_prompt:],
t,
encoder_hidden_states=add_positive_style_prompt_embeds,
timestep_cond=timestep_cond,
cross_attention_kwargs=self.cross_attention_kwargs,
added_cond_kwargs=style_positive_added_cond_kwargs,
return_dict=False,
)[0]
self._set_lora_scale(0, 0, 0, 1)
noise_pred_style_negative = self.unet(
latent_model_input[:num_images_per_prompt],
t,
encoder_hidden_states=add_negative_style_prompt_embeds,
timestep_cond=timestep_cond,
cross_attention_kwargs=self.cross_attention_kwargs,
added_cond_kwargs=style_negative_added_cond_kwargs,
return_dict=False,
)[0]
noise_pred_style = style_guidance_scale * (
noise_pred_style_positive - noise_pred_style_negative
)
noise_pred = noise_pred_orig + noise_pred_content + noise_pred_style
if self.do_classifier_free_guidance and self.guidance_rescale > 0.0:
# Based on 3.4. in https://arxiv.org/pdf/2305.08891.pdf
noise_pred = rescale_noise_cfg(noise_pred, noise_pred_text, guidance_rescale=self.guidance_rescale)
# compute the previous noisy sample x_t -> x_t-1
latents_dtype = latents.dtype
latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwargs, return_dict=False)[0]
if latents.dtype != latents_dtype:
if torch.backends.mps.is_available():
# some platforms (eg. apple mps) misbehave due to a pytorch bug: https://github.com/pytorch/pytorch/pull/99272
latents = latents.to(latents_dtype)
if callback_on_step_end is not None:
callback_kwargs = {}
for k in callback_on_step_end_tensor_inputs:
callback_kwargs[k] = locals()[k]
callback_outputs = callback_on_step_end(self, i, t, callback_kwargs)
latents = callback_outputs.pop("latents", latents)
prompt_embeds = callback_outputs.pop("prompt_embeds", prompt_embeds)
negative_prompt_embeds = callback_outputs.pop("negative_prompt_embeds", negative_prompt_embeds)
add_text_embeds = callback_outputs.pop("add_text_embeds", add_text_embeds)
negative_pooled_prompt_embeds = callback_outputs.pop(
"negative_pooled_prompt_embeds", negative_pooled_prompt_embeds
)
add_time_ids = callback_outputs.pop("add_time_ids", add_time_ids)
negative_add_time_ids = callback_outputs.pop("negative_add_time_ids", negative_add_time_ids)
# call the callback, if provided
if i == len(timesteps) - 1 or ((i + 1) > num_warmup_steps and (i + 1) % self.scheduler.order == 0):
progress_bar.update()
if callback is not None and i % callback_steps == 0:
step_idx = i // getattr(self.scheduler, "order", 1)
callback(step_idx, t, latents)
# if XLA_AVAILABLE:
# xm.mark_step()
if not output_type == "latent":
# make sure the VAE is in float32 mode, as it overflows in float16
needs_upcasting = self.vae.dtype == torch.float16 and self.vae.config.force_upcast
if needs_upcasting:
self.upcast_vae()
latents = latents.to(next(iter(self.vae.post_quant_conv.parameters())).dtype)
elif latents.dtype != self.vae.dtype:
if torch.backends.mps.is_available():
# some platforms (eg. apple mps) misbehave due to a pytorch bug: https://github.com/pytorch/pytorch/pull/99272
self.vae = self.vae.to(latents.dtype)
# unscale/denormalize the latents
# denormalize with the mean and std if available and not None
has_latents_mean = hasattr(self.vae.config, "latents_mean") and self.vae.config.latents_mean is not None
has_latents_std = hasattr(self.vae.config, "latents_std") and self.vae.config.latents_std is not None
if has_latents_mean and has_latents_std:
latents_mean = (
torch.tensor(self.vae.config.latents_mean).view(1, 4, 1, 1).to(latents.device, latents.dtype)
)
latents_std = (
torch.tensor(self.vae.config.latents_std).view(1, 4, 1, 1).to(latents.device, latents.dtype)
)
latents = latents * latents_std / self.vae.config.scaling_factor + latents_mean
else:
latents = latents / self.vae.config.scaling_factor
image = self.vae.decode(latents, return_dict=False)[0]
# cast back to fp16 if needed
if needs_upcasting:
self.vae.to(dtype=torch.float16)
else:
image = latents
if not output_type == "latent":
# apply watermark if available
if self.watermark is not None:
image = self.watermark.apply_watermark(image)
image = self.image_processor.postprocess(image, output_type=output_type)
# Offload all models
self.maybe_free_model_hooks()
if not return_dict:
return (image,)
return StableDiffusionXLPipelineOutput(images=image)
def _set_lora_scale(
self,
content_lora_scale: float,
style_lora_scale: float,
negative_content_lora_scale: float,
negative_style_lora_scale: float,
):
for _, module in self.content_block.named_modules():
if isinstance(module, BaseTunerLayer):
module.set_scale("content_lora", content_lora_scale)
module.set_scale("neg_cnt_lora", negative_content_lora_scale)
for _, module in self.style_block.named_modules():
if isinstance(module, BaseTunerLayer):
module.set_scale("style_lora", style_lora_scale)
module.set_scale("neg_sty_lora", negative_style_lora_scale)
def load_lora_checkpoint(
self,
content_image_lora_path: str = None,
style_image_lora_path: str = None,
):
self.lora_names = []
if content_image_lora_path is not None:
lora_dict, _ = self.lora_state_dict(content_image_lora_path)
content_lora, neg_style_lora = filter_consislora(lora_dict)
self.load_lora_weights(content_lora, adapter_name="content_lora")
self.load_lora_weights(neg_style_lora, adapter_name="neg_sty_lora")
self.lora_names.extend(["content_lora", "neg_sty_lora"])
print(f"Loaded lora weights of the content image from {content_image_lora_path}")
if style_image_lora_path is not None:
lora_dict, _ = self.lora_state_dict(style_image_lora_path)
neg_content_lora, style_lora = filter_consislora(lora_dict)
self.load_lora_weights(style_lora, adapter_name="style_lora")
self.load_lora_weights(neg_content_lora, adapter_name="neg_cnt_lora")
self.lora_names.extend(["style_lora", "neg_cnt_lora"])
print(f"Loaded lora weights of the style image from {style_image_lora_path}")
self.set_adapters(self.lora_names)
def unload_lora_checkpoint(self):
self.unload_lora_weights()
self.lora_names = []
|
0015/esp_rlottie
| 14,830 |
rlottie/vs2019/rlottie.vcxproj.filters
|
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|
0015/esp_rlottie
| 11,630 |
rlottie/inc/rlottie_capi.h
|
/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef _RLOTTIE_CAPI_H_
#define _RLOTTIE_CAPI_H_
#include <stddef.h>
#include <stdint.h>
#include "rlottiecommon.h"
#ifdef __cplusplus
extern "C" {
#endif
typedef enum {
LOTTIE_ANIMATION_PROPERTY_FILLCOLOR, /*!< Color property of Fill object , value type is float [0 ... 1] */
LOTTIE_ANIMATION_PROPERTY_FILLOPACITY, /*!< Opacity property of Fill object , value type is float [ 0 .. 100] */
LOTTIE_ANIMATION_PROPERTY_STROKECOLOR, /*!< Color property of Stroke object , value type is float [0 ... 1] */
LOTTIE_ANIMATION_PROPERTY_STROKEOPACITY, /*!< Opacity property of Stroke object , value type is float [ 0 .. 100] */
LOTTIE_ANIMATION_PROPERTY_STROKEWIDTH, /*!< stroke with property of Stroke object , value type is float */
LOTTIE_ANIMATION_PROPERTY_TR_ANCHOR, /*!< Transform Anchor property of Layer and Group object , value type is int */
LOTTIE_ANIMATION_PROPERTY_TR_POSITION, /*!< Transform Position property of Layer and Group object , value type is int */
LOTTIE_ANIMATION_PROPERTY_TR_SCALE, /*!< Transform Scale property of Layer and Group object , value type is float range[0 ..100] */
LOTTIE_ANIMATION_PROPERTY_TR_ROTATION, /*!< Transform Scale property of Layer and Group object , value type is float. range[0 .. 360] in degrees*/
LOTTIE_ANIMATION_PROPERTY_TR_OPACITY /*!< Transform Opacity property of Layer and Group object , value type is float [ 0 .. 100] */
}Lottie_Animation_Property;
typedef struct Lottie_Animation_S Lottie_Animation;
/**
* @brief Runs lottie initialization code when rlottie library is loaded
* dynamically.
*
*
* This api should be called before any other api when rlottie library
* is loaded using dlopen() or equivalent.
*
* @see lottie_shutdown()
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API void lottie_init(void);
/**
* @brief Runs lottie teardown code when rlottie library is loaded
* dynamically.
*
* This api should be called before unloading the rlottie library for
* proper cleanup of the resource without doing so will result in undefined
* behaviour.
*
* @see lottie_init()
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API void lottie_shutdown(void);
/**
* @brief Constructs an animation object from file path.
*
* @param[in] path Lottie resource file path
*
* @return Animation object that can build the contents of the
* Lottie resource represented by file path.
*
* @see lottie_animation_destroy()
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API Lottie_Animation *lottie_animation_from_file(const char *path);
/**
* @brief Constructs an animation object from JSON string data.
*
* @param[in] data The JSON string data.
* @param[in] key the string that will be used to cache the JSON string data.
* @param[in] resource_path the path that will be used to load external resource needed by the JSON data.
*
* @return Animation object that can build the contents of the
* Lottie resource represented by JSON string data.
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API Lottie_Animation *lottie_animation_from_data(const char *data, const char *key, const char *resource_path);
/**
* @brief Free given Animation object resource.
*
* @param[in] animation Animation object to free.
*
* @see lottie_animation_from_file()
* @see lottie_animation_from_data()
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API void lottie_animation_destroy(Lottie_Animation *animation);
/**
* @brief Returns default viewport size of the Lottie resource.
*
* @param[in] animation Animation object.
* @param[out] w default width of the viewport.
* @param[out] h default height of the viewport.
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API void lottie_animation_get_size(const Lottie_Animation *animation, size_t *width, size_t *height);
/**
* @brief Returns total animation duration of Lottie resource in second.
* it uses totalFrame() and frameRate() to calculate the duration.
* duration = totalFrame() / frameRate().
*
* @param[in] animation Animation object.
*
* @return total animation duration in second.
* @c 0 if the Lottie resource has no animation.
*
* @see lottie_animation_get_totalframe()
* @see lottie_animation_get_framerate()
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API double lottie_animation_get_duration(const Lottie_Animation *animation);
/**
* @brief Returns total number of frames present in the Lottie resource.
*
* @param[in] animation Animation object.
*
* @return frame count of the Lottie resource.*
*
* @note frame number starts with 0.
*
* @see lottie_animation_get_duration()
* @see lottie_animation_get_framerate()
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API size_t lottie_animation_get_totalframe(const Lottie_Animation *animation);
/**
* @brief Returns default framerate of the Lottie resource.
*
* @param[in] animation Animation object.
*
* @return framerate of the Lottie resource
*
* @ingroup Lottie_Animation
* @internal
*
*/
RLOTTIE_API double lottie_animation_get_framerate(const Lottie_Animation *animation);
/**
* @brief Get the render tree which contains the snapshot of the animation object
* at frame = @c frame_num, the content of the animation in that frame number.
*
* @param[in] animation Animation object.
* @param[in] frame_num Content corresponds to the @p frame_num needs to be drawn
* @param[in] width requested snapshot viewport width.
* @param[in] height requested snapshot viewport height.
*
* @return Animation snapshot tree.
*
* @note: User has to traverse the tree for rendering.
*
* @see LOTLayerNode
* @see LOTNode
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API const LOTLayerNode *lottie_animation_render_tree(Lottie_Animation *animation, size_t frame_num, size_t width, size_t height);
/**
* @brief Maps position to frame number and returns it.
*
* @param[in] animation Animation object.
* @param[in] pos position in the range [ 0.0 .. 1.0 ].
*
* @return mapped frame numbe in the range [ start_frame .. end_frame ].
* @c 0 if the Lottie resource has no animation.
*
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API size_t lottie_animation_get_frame_at_pos(const Lottie_Animation *animation, float pos);
/**
* @brief Request to render the content of the frame @p frame_num to buffer @p buffer.
*
* @param[in] animation Animation object.
* @param[in] frame_num the frame number needs to be rendered.
* @param[in] buffer surface buffer use for rendering.
* @param[in] width width of the surface
* @param[in] height height of the surface
* @param[in] bytes_per_line stride of the surface in bytes.
*
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API void lottie_animation_render(Lottie_Animation *animation, size_t frame_num, uint32_t *buffer, size_t width, size_t height, size_t bytes_per_line);
/**
* @brief Request to render the content of the frame @p frame_num to buffer @p buffer asynchronously.
*
* @param[in] animation Animation object.
* @param[in] frame_num the frame number needs to be rendered.
* @param[in] buffer surface buffer use for rendering.
* @param[in] width width of the surface
* @param[in] height height of the surface
* @param[in] bytes_per_line stride of the surface in bytes.
*
* @note user must call lottie_animation_render_flush() to make sure render is finished.
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API void lottie_animation_render_async(Lottie_Animation *animation, size_t frame_num, uint32_t *buffer, size_t width, size_t height, size_t bytes_per_line);
/**
* @brief Request to finish the current async renderer job for this animation object.
* If render is finished then this call returns immidiately.
* If not, it waits till render job finish and then return.
*
* @param[in] animation Animation object.
*
* @warning User must call lottie_animation_render_async() and lottie_animation_render_flush()
* in pair to get the benefit of async rendering.
*
* @return the pixel buffer it finished rendering.
*
* @ingroup Lottie_Animation
* @internal
*/
RLOTTIE_API uint32_t *lottie_animation_render_flush(Lottie_Animation *animation);
/**
* @brief Request to change the properties of this animation object.
* Keypath should conatin object names separated by (.) and can handle globe(**) or wildchar(*)
*
* @usage
* To change fillcolor property of fill1 object in the layer1->group1->fill1 hirarchy to RED color
*
* lottie_animation_property_override(animation, LOTTIE_ANIMATION_PROPERTY_FILLCOLOR, "layer1.group1.fill1", 1.0, 0.0, 0.0);
*
* if all the color property inside group1 needs to be changed to GREEN color
*
* lottie_animation_property_override(animation, LOTTIE_ANIMATION_PROPERTY_FILLCOLOR, "**.group1.**", 1.0, 0.0, 0.0);
*
* @param[in] animation Animation object.
* @param[in] type Property type. (@p Lottie_Animation_Property)
* @param[in] keypath Specific content of target.
* @param[in] ... Property values.
*
* @ingroup Lottie_Animation
* @internal
* */
RLOTTIE_API void lottie_animation_property_override(Lottie_Animation *animation, const Lottie_Animation_Property type, const char *keypath, ...);
/**
* @brief Returns list of markers in the Lottie resource
* @p LOTMarkerList has a @p LOTMarker list and size of list
* @p LOTMarker has the marker's name, start frame, and end frame.
*
* @param[in] animation Animation object.
*
* @return The list of marker. If there is no marker, return null.
*
* @ingroup Lottie_Animation
* @internal
* */
RLOTTIE_API const LOTMarkerList* lottie_animation_get_markerlist(Lottie_Animation *animation);
/**
* @brief Configures rlottie model cache policy.
*
* Provides Library level control to configure model cache
* policy. Setting it to 0 will disable
* the cache as well as flush all the previously cached content.
*
* @param[in] cacheSize Maximum Model Cache size.
*
* @note to disable Caching configure with 0 size.
* @note to flush the current Cache content configure it with 0 and
* then reconfigure with the new size.
*
* @internal
*/
RLOTTIE_API void lottie_configure_model_cache_size(size_t cacheSize);
#ifdef __cplusplus
}
#endif
#endif //_RLOTTIE_CAPI_H_
|
0015/esp_rlottie
| 5,193 |
rlottie/inc/rlottiecommon.h
|
/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef _RLOTTIE_COMMON_H_
#define _RLOTTIE_COMMON_H_
#if defined _WIN32 || defined __CYGWIN__
#ifdef RLOTTIE_BUILD
#define RLOTTIE_API __declspec(dllexport)
#else
#define RLOTTIE_API __declspec(dllimport)
#endif
#else
#ifdef RLOTTIE_BUILD
#define RLOTTIE_API __attribute__ ((visibility ("default")))
#else
#define RLOTTIE_API
#endif
#endif
/**
* @defgroup Lottie_Animation Lottie_Animation
*
* Lottie Animation is a modern style vector based animation design. Its animation
* resource(within json format) could be generated by Adobe After Effect using
* bodymovin plugin. You can find a good examples in Lottie Community which
* shares many free resources(see: www.lottiefiles.com).
*
* This Lottie_Animation is a common engine to manipulate, control Lottie
* Animation from the Lottie resource - json file. It provides a scene-graph
* node tree per frames by user demand as well as rasterized frame images.
*
*/
/**
* @ingroup Lottie_Animation
*/
typedef enum
{
BrushSolid = 0,
BrushGradient
} LOTBrushType;
typedef enum
{
FillEvenOdd = 0,
FillWinding
} LOTFillRule;
typedef enum
{
JoinMiter = 0,
JoinBevel,
JoinRound
} LOTJoinStyle;
typedef enum
{
CapFlat = 0,
CapSquare,
CapRound
} LOTCapStyle;
typedef enum
{
GradientLinear = 0,
GradientRadial
} LOTGradientType;
typedef struct LOTGradientStop
{
float pos;
unsigned char r, g, b, a;
} LOTGradientStop;
typedef enum
{
MaskAdd = 0,
MaskSubstract,
MaskIntersect,
MaskDifference
} LOTMaskType;
typedef struct LOTMask {
struct {
const float *ptPtr;
size_t ptCount;
const char* elmPtr;
size_t elmCount;
} mPath;
LOTMaskType mMode;
unsigned char mAlpha;
}LOTMask;
typedef enum
{
MatteNone = 0,
MatteAlpha,
MatteAlphaInv,
MatteLuma,
MatteLumaInv
} LOTMatteType;
typedef struct LOTMarker {
char *name;
size_t startframe;
size_t endframe;
} LOTMarker;
typedef struct LOTMarkerList {
LOTMarker *ptr;
size_t size;
} LOTMarkerList;
typedef struct LOTNode {
#define ChangeFlagNone 0x0000
#define ChangeFlagPath 0x0001
#define ChangeFlagPaint 0x0010
#define ChangeFlagAll (ChangeFlagPath & ChangeFlagPaint)
struct {
const float *ptPtr;
size_t ptCount;
const char *elmPtr;
size_t elmCount;
} mPath;
struct {
unsigned char r, g, b, a;
} mColor;
struct {
unsigned char enable;
float width;
LOTCapStyle cap;
LOTJoinStyle join;
float miterLimit;
float *dashArray;
int dashArraySize;
} mStroke;
struct {
LOTGradientType type;
LOTGradientStop *stopPtr;
size_t stopCount;
struct {
float x, y;
} start, end, center, focal;
float cradius;
float fradius;
} mGradient;
struct {
unsigned char *data;
size_t width;
size_t height;
unsigned char mAlpha;
struct {
float m11; float m12; float m13;
float m21; float m22; float m23;
float m31; float m32; float m33;
} mMatrix;
} mImageInfo;
int mFlag;
LOTBrushType mBrushType;
LOTFillRule mFillRule;
const char *keypath;
} LOTNode;
typedef struct LOTLayerNode {
struct {
LOTMask *ptr;
size_t size;
} mMaskList;
struct {
const float *ptPtr;
size_t ptCount;
const char *elmPtr;
size_t elmCount;
} mClipPath;
struct {
struct LOTLayerNode **ptr;
size_t size;
} mLayerList;
struct {
LOTNode **ptr;
size_t size;
} mNodeList;
LOTMatteType mMatte;
int mVisible;
unsigned char mAlpha;
const char *keypath;
} LOTLayerNode;
/**
* @}
*/
#endif // _RLOTTIE_COMMON_H_
|
0015/esp_rlottie
| 17,630 |
rlottie/inc/rlottie.h
|
/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef _RLOTTIE_H_
#define _RLOTTIE_H_
#include <future>
#include <vector>
#include <memory>
#if defined _WIN32 || defined __CYGWIN__
#ifdef RLOTTIE_BUILD
#define RLOTTIE_API __declspec(dllexport)
#else
#define RLOTTIE_API __declspec(dllimport)
#endif
#else
#ifdef RLOTTIE_BUILD
#define RLOTTIE_API __attribute__ ((visibility ("default")))
#else
#define RLOTTIE_API
#endif
#endif
class AnimationImpl;
struct LOTNode;
struct LOTLayerNode;
namespace rlottie {
/**
* @brief Configures rlottie model cache policy.
*
* Provides Library level control to configure model cache
* policy. Setting it to 0 will disable
* the cache as well as flush all the previously cached content.
*
* @param[in] cacheSize Maximum Model Cache size.
*
* @note to disable Caching configure with 0 size.
* @note to flush the current Cache content configure it with 0 and
* then reconfigure with the new size.
*
* @internal
*/
RLOTTIE_API void configureModelCacheSize(size_t cacheSize);
struct Color {
Color() = default;
Color(float r, float g , float b):_r(r), _g(g), _b(b){}
float r() const {return _r;}
float g() const {return _g;}
float b() const {return _b;}
private:
float _r{0};
float _g{0};
float _b{0};
};
struct Size {
Size() = default;
Size(float w, float h):_w(w), _h(h){}
float w() const {return _w;}
float h() const {return _h;}
private:
float _w{0};
float _h{0};
};
struct Point {
Point() = default;
Point(float x, float y):_x(x), _y(y){}
float x() const {return _x;}
float y() const {return _y;}
private:
float _x{0};
float _y{0};
};
struct FrameInfo {
explicit FrameInfo(uint32_t frame): _frameNo(frame){}
uint32_t curFrame() const {return _frameNo;}
private:
uint32_t _frameNo;
};
enum class Property {
FillColor, /*!< Color property of Fill object , value type is rlottie::Color */
FillOpacity, /*!< Opacity property of Fill object , value type is float [ 0 .. 100] */
StrokeColor, /*!< Color property of Stroke object , value type is rlottie::Color */
StrokeOpacity, /*!< Opacity property of Stroke object , value type is float [ 0 .. 100] */
StrokeWidth, /*!< stroke width property of Stroke object , value type is float */
TrAnchor, /*!< Transform Anchor property of Layer and Group object , value type is rlottie::Point */
TrPosition, /*!< Transform Position property of Layer and Group object , value type is rlottie::Point */
TrScale, /*!< Transform Scale property of Layer and Group object , value type is rlottie::Size. range[0 ..100] */
TrRotation, /*!< Transform Rotation property of Layer and Group object , value type is float. range[0 .. 360] in degrees*/
TrOpacity /*!< Transform Opacity property of Layer and Group object , value type is float [ 0 .. 100] */
};
struct Color_Type{};
struct Point_Type{};
struct Size_Type{};
struct Float_Type{};
template <typename T> struct MapType;
class RLOTTIE_API Surface {
public:
/**
* @brief Surface object constructor.
*
* @param[in] buffer surface buffer.
* @param[in] width surface width.
* @param[in] height surface height.
* @param[in] bytesPerLine number of bytes in a surface scanline.
*
* @note Default surface format is ARGB32_Premultiplied.
*
* @internal
*/
Surface(uint32_t *buffer, size_t width, size_t height, size_t bytesPerLine);
/**
* @brief Sets the Draw Area available on the Surface.
*
* Lottie will use the draw region size to generate frame image
* and will update only the draw rgion of the surface.
*
* @param[in] x region area x position.
* @param[in] y region area y position.
* @param[in] width region area width.
* @param[in] height region area height.
*
* @note Default surface format is ARGB32_Premultiplied.
* @note Default draw region area is [ 0 , 0, surface width , surface height]
*
* @internal
*/
void setDrawRegion(size_t x, size_t y, size_t width, size_t height);
/**
* @brief Returns width of the surface.
*
* @return surface width
*
* @internal
*
*/
size_t width() const {return mWidth;}
/**
* @brief Returns height of the surface.
*
* @return surface height
*
* @internal
*/
size_t height() const {return mHeight;}
/**
* @brief Returns number of bytes in the surface scanline.
*
* @return number of bytes in scanline.
*
* @internal
*/
size_t bytesPerLine() const {return mBytesPerLine;}
/**
* @brief Returns buffer attached tp the surface.
*
* @return buffer attaced to the Surface.
*
* @internal
*/
uint32_t *buffer() const {return mBuffer;}
/**
* @brief Returns drawable area width of the surface.
*
* @return drawable area width
*
* @note Default value is width() of the surface
*
* @internal
*
*/
size_t drawRegionWidth() const {return mDrawArea.w;}
/**
* @brief Returns drawable area height of the surface.
*
* @return drawable area height
*
* @note Default value is height() of the surface
*
* @internal
*/
size_t drawRegionHeight() const {return mDrawArea.h;}
/**
* @brief Returns drawable area's x position of the surface.
*
* @return drawable area's x potition.
*
* @note Default value is 0
*
* @internal
*/
size_t drawRegionPosX() const {return mDrawArea.x;}
/**
* @brief Returns drawable area's y position of the surface.
*
* @return drawable area's y potition.
*
* @note Default value is 0
*
* @internal
*/
size_t drawRegionPosY() const {return mDrawArea.y;}
/**
* @brief Default constructor.
*/
Surface() = default;
private:
uint32_t *mBuffer{nullptr};
size_t mWidth{0};
size_t mHeight{0};
size_t mBytesPerLine{0};
struct {
size_t x{0};
size_t y{0};
size_t w{0};
size_t h{0};
}mDrawArea;
};
using MarkerList = std::vector<std::tuple<std::string, int , int>>;
/**
* @brief https://helpx.adobe.com/after-effects/using/layer-markers-composition-markers.html
* Markers exported form AE are used to describe a segmnet of an animation {comment/tag , startFrame, endFrame}
* Marker can be use to devide a resource in to separate animations by tagging the segment with comment string ,
* start frame and duration of that segment.
*/
using LayerInfoList = std::vector<std::tuple<std::string, int , int>>;
using ColorFilter = std::function<void(float &r , float &g, float &b)>;
class RLOTTIE_API Animation {
public:
/**
* @brief Constructs an animation object from file path.
*
* @param[in] path Lottie resource file path
* @param[in] cachePolicy whether to cache or not the model data.
* use only when need to explicit disabl caching for a
* particular resource. To disable caching at library level
* use @see configureModelCacheSize() instead.
*
* @return Animation object that can render the contents of the
* Lottie resource represented by file path.
*
* @internal
*/
static std::unique_ptr<Animation>
loadFromFile(const std::string &path, bool cachePolicy=true);
/**
* @brief Constructs an animation object from JSON string data.
*
* @param[in] jsonData The JSON string data.
* @param[in] key the string that will be used to cache the JSON string data.
* @param[in] resourcePath the path will be used to search for external resource.
* @param[in] cachePolicy whether to cache or not the model data.
* use only when need to explicit disabl caching for a
* particular resource. To disable caching at library level
* use @see configureModelCacheSize() instead.
*
* @return Animation object that can render the contents of the
* Lottie resource represented by JSON string data.
*
* @internal
*/
static std::unique_ptr<Animation>
loadFromData(std::string jsonData, const std::string &key,
const std::string &resourcePath="", bool cachePolicy=true);
/**
* @brief Constructs an animation object from JSON string data and update.
* the color properties using ColorFilter.
* @param[in] jsonData The JSON string data.
* @param[in] resourcePath the path will be used to search for external resource.
* @param[in] filter The color filter that will be applied for each color property
* found during parsing.
* @return Animation object that can render the contents of the
* Lottie resource represented by JSON string data.
*
* @internal
*/
static std::unique_ptr<Animation>
loadFromData(std::string jsonData, std::string resourcePath, ColorFilter filter);
/**
* @brief Returns default framerate of the Lottie resource.
*
* @return framerate of the Lottie resource
*
* @internal
*
*/
double frameRate() const;
/**
* @brief Returns total number of frames present in the Lottie resource.
*
* @return frame count of the Lottie resource.
*
* @note frame number starts with 0.
*
* @internal
*/
size_t totalFrame() const;
/**
* @brief Returns default viewport size of the Lottie resource.
*
* @param[out] width default width of the viewport.
* @param[out] height default height of the viewport.
*
* @internal
*
*/
void size(size_t &width, size_t &height) const;
/**
* @brief Returns total animation duration of Lottie resource in second.
* it uses totalFrame() and frameRate() to calculate the duration.
* duration = totalFrame() / frameRate().
*
* @return total animation duration in second.
* @retval 0 if the Lottie resource has no animation.
*
* @see totalFrame()
* @see frameRate()
*
* @internal
*/
double duration() const;
/**
* @brief Returns frame number for a given position.
* this function helps to map the position value retuned
* by the animator to a frame number in side the Lottie resource.
* frame_number = lerp(start_frame, endframe, pos);
*
* @param[in] pos normalized position value [0 ... 1]
*
* @return frame numer maps to the position value [startFrame .... endFrame]
*
* @internal
*/
size_t frameAtPos(double pos);
/**
* @brief Renders the content to surface Asynchronously.
* it gives a future in return to get the result of the
* rendering at a future point.
* To get best performance user has to start rendering as soon as
* it finds that content at {frameNo} has to be rendered and get the
* result from the future at the last moment when the surface is needed
* to draw into the screen.
*
*
* @param[in] frameNo Content corresponds to the @p frameNo needs to be drawn
* @param[in] surface Surface in which content will be drawn
* @param[in] keepAspectRatio whether to keep the aspect ratio while scaling the content.
*
* @return future that will hold the result when rendering finished.
*
* for Synchronus rendering @see renderSync
*
* @see Surface
* @internal
*/
std::future<Surface> render(size_t frameNo, Surface surface, bool keepAspectRatio=true);
/**
* @brief Renders the content to surface synchronously.
* for performance use the async rendering @see render
*
* @param[in] frameNo Content corresponds to the @p frameNo needs to be drawn
* @param[in] surface Surface in which content will be drawn
* @param[in] keepAspectRatio whether to keep the aspect ratio while scaling the content.
*
* @internal
*/
void renderSync(size_t frameNo, Surface surface, bool keepAspectRatio=true);
/**
* @brief Returns root layer of the composition updated with
* content of the Lottie resource at frame number @p frameNo.
*
* @param[in] frameNo Content corresponds to the @p frameNo needs to be extracted.
* @param[in] width content viewbox width
* @param[in] height content viewbox height
*
* @return Root layer node.
*
* @internal
*/
const LOTLayerNode * renderTree(size_t frameNo, size_t width, size_t height) const;
/**
* @brief Returns Composition Markers.
*
*
* @return returns MarkerList of the Composition.
*
* @see MarkerList
* @internal
*/
const MarkerList& markers() const;
/**
* @brief Returns Layer information{name, inFrame, outFrame} of all the child layers of the composition.
*
*
* @return List of Layer Information of the Composition.
*
* @see LayerInfoList
* @internal
*/
const LayerInfoList& layers() const;
/**
* @brief Sets property value for the specified {@link KeyPath}. This {@link KeyPath} can resolve
* to multiple contents. In that case, the callback's value will apply to all of them.
*
* Keypath should conatin object names separated by (.) and can handle globe(**) or wildchar(*).
*
* @usage
* To change fillcolor property of fill1 object in the layer1->group1->fill1 hirarchy to RED color
*
* player->setValue<rlottie::Property::FillColor>("layer1.group1.fill1", rlottie::Color(1, 0, 0);
*
* if all the color property inside group1 needs to be changed to GREEN color
*
* player->setValue<rlottie::Property::FillColor>("**.group1.**", rlottie::Color(0, 1, 0);
*
* @internal
*/
template<Property prop, typename AnyValue>
void setValue(const std::string &keypath, AnyValue value)
{
setValue(MapType<std::integral_constant<Property, prop>>{}, prop, keypath, value);
}
/**
* @brief default destructor
*
* @internal
*/
~Animation();
private:
void setValue(Color_Type, Property, const std::string &, Color);
void setValue(Float_Type, Property, const std::string &, float);
void setValue(Size_Type, Property, const std::string &, Size);
void setValue(Point_Type, Property, const std::string &, Point);
void setValue(Color_Type, Property, const std::string &, std::function<Color(const FrameInfo &)> &&);
void setValue(Float_Type, Property, const std::string &, std::function<float(const FrameInfo &)> &&);
void setValue(Size_Type, Property, const std::string &, std::function<Size(const FrameInfo &)> &&);
void setValue(Point_Type, Property, const std::string &, std::function<Point(const FrameInfo &)> &&);
/**
* @brief default constructor
*
* @internal
*/
Animation();
std::unique_ptr<AnimationImpl> d;
};
//Map Property to Value type
template<> struct MapType<std::integral_constant<Property, Property::FillColor>>: Color_Type{};
template<> struct MapType<std::integral_constant<Property, Property::StrokeColor>>: Color_Type{};
template<> struct MapType<std::integral_constant<Property, Property::FillOpacity>>: Float_Type{};
template<> struct MapType<std::integral_constant<Property, Property::StrokeOpacity>>: Float_Type{};
template<> struct MapType<std::integral_constant<Property, Property::StrokeWidth>>: Float_Type{};
template<> struct MapType<std::integral_constant<Property, Property::TrRotation>>: Float_Type{};
template<> struct MapType<std::integral_constant<Property, Property::TrOpacity>>: Float_Type{};
template<> struct MapType<std::integral_constant<Property, Property::TrAnchor>>: Point_Type{};
template<> struct MapType<std::integral_constant<Property, Property::TrPosition>>: Point_Type{};
template<> struct MapType<std::integral_constant<Property, Property::TrScale>>: Size_Type{};
} // namespace lotplayer
#endif // _RLOTTIE_H_
|
0015/esp_rlottie
| 27,441 |
rlottie/example/gif.h
|
//
// gif.h
// by Charlie Tangora
// Public domain.
// Email me : ctangora -at- gmail -dot- com
//
// This file offers a simple, very limited way to create animated GIFs directly in code.
//
// Those looking for particular cleverness are likely to be disappointed; it's pretty
// much a straight-ahead implementation of the GIF format with optional Floyd-Steinberg
// dithering. (It does at least use delta encoding - only the changed portions of each
// frame are saved.)
//
// So resulting files are often quite large. The hope is that it will be handy nonetheless
// as a quick and easily-integrated way for programs to spit out animations.
//
// Only RGBA8 is currently supported as an input format. (The alpha is ignored.)
//
// If capturing a buffer with a bottom-left origin (such as OpenGL), define GIF_FLIP_VERT
// to automatically flip the buffer data when writing the image (the buffer itself is
// unchanged.
//
// USAGE:
// Create a GifWriter struct. Pass it to GifBegin() to initialize and write the header.
// Pass subsequent frames to GifWriteFrame().
// Finally, call GifEnd() to close the file handle and free memory.
//
#ifndef gif_h
#define gif_h
#include <stdio.h> // for FILE*
#include <string.h> // for memcpy and bzero
#include <stdint.h> // for integer typedefs
// Define these macros to hook into a custom memory allocator.
// TEMP_MALLOC and TEMP_FREE will only be called in stack fashion - frees in the reverse order of mallocs
// and any temp memory allocated by a function will be freed before it exits.
// MALLOC and FREE are used only by GifBegin and GifEnd respectively (to allocate a buffer the size of the image, which
// is used to find changed pixels for delta-encoding.)
#ifndef GIF_TEMP_MALLOC
#include <stdlib.h>
#define GIF_TEMP_MALLOC malloc
#endif
#ifndef GIF_TEMP_FREE
#include <stdlib.h>
#define GIF_TEMP_FREE free
#endif
#ifndef GIF_MALLOC
#include <stdlib.h>
#define GIF_MALLOC malloc
#endif
#ifndef GIF_FREE
#include <stdlib.h>
#define GIF_FREE free
#endif
const int kGifTransIndex = 0;
struct GifPalette
{
int bitDepth;
uint8_t r[256];
uint8_t g[256];
uint8_t b[256];
// k-d tree over RGB space, organized in heap fashion
// i.e. left child of node i is node i*2, right child is node i*2+1
// nodes 256-511 are implicitly the leaves, containing a color
uint8_t treeSplitElt[255];
uint8_t treeSplit[255];
};
// max, min, and abs functions
int GifIMax(int l, int r) { return l>r?l:r; }
int GifIMin(int l, int r) { return l<r?l:r; }
int GifIAbs(int i) { return i<0?-i:i; }
// walks the k-d tree to pick the palette entry for a desired color.
// Takes as in/out parameters the current best color and its error -
// only changes them if it finds a better color in its subtree.
// this is the major hotspot in the code at the moment.
void GifGetClosestPaletteColor(GifPalette* pPal, int r, int g, int b,
int32_t& bestInd, int32_t& bestDiff,
int treeRoot = 1)
{
// base case, reached the bottom of the tree
if(treeRoot > (1<<pPal->bitDepth)-1)
{
int ind = treeRoot-(1<<pPal->bitDepth);
if(ind == kGifTransIndex) return;
// check whether this color is better than the current winner
int r_err = r - ((int32_t)pPal->r[ind]);
int g_err = g - ((int32_t)pPal->g[ind]);
int b_err = b - ((int32_t)pPal->b[ind]);
int diff = GifIAbs(r_err)+GifIAbs(g_err)+GifIAbs(b_err);
if(diff < bestDiff)
{
bestInd = ind;
bestDiff = diff;
}
return;
}
// take the appropriate color (r, g, or b) for this node of the k-d tree
int comps[3]; comps[0] = r; comps[1] = g; comps[2] = b;
int splitComp = comps[pPal->treeSplitElt[treeRoot]];
int splitPos = pPal->treeSplit[treeRoot];
if(splitPos > splitComp)
{
// check the left subtree
GifGetClosestPaletteColor(pPal, r, g, b, bestInd, bestDiff, treeRoot*2);
if( bestDiff > splitPos - splitComp )
{
// cannot prove there's not a better value in the right subtree, check that too
GifGetClosestPaletteColor(pPal, r, g, b, bestInd, bestDiff, treeRoot*2+1);
}
}
else
{
GifGetClosestPaletteColor(pPal, r, g, b, bestInd, bestDiff, treeRoot*2+1);
if( bestDiff > splitComp - splitPos )
{
GifGetClosestPaletteColor(pPal, r, g, b, bestInd, bestDiff, treeRoot*2);
}
}
}
void GifSwapPixels(uint8_t* image, int pixA, int pixB)
{
uint8_t rA = image[pixA*4];
uint8_t gA = image[pixA*4+1];
uint8_t bA = image[pixA*4+2];
uint8_t aA = image[pixA*4+3];
uint8_t rB = image[pixB*4];
uint8_t gB = image[pixB*4+1];
uint8_t bB = image[pixB*4+2];
uint8_t aB = image[pixA*4+3];
image[pixA*4] = rB;
image[pixA*4+1] = gB;
image[pixA*4+2] = bB;
image[pixA*4+3] = aB;
image[pixB*4] = rA;
image[pixB*4+1] = gA;
image[pixB*4+2] = bA;
image[pixB*4+3] = aA;
}
// just the partition operation from quicksort
int GifPartition(uint8_t* image, const int left, const int right, const int elt, int pivotIndex)
{
const int pivotValue = image[(pivotIndex)*4+elt];
GifSwapPixels(image, pivotIndex, right-1);
int storeIndex = left;
bool split = 0;
for(int ii=left; ii<right-1; ++ii)
{
int arrayVal = image[ii*4+elt];
if( arrayVal < pivotValue )
{
GifSwapPixels(image, ii, storeIndex);
++storeIndex;
}
else if( arrayVal == pivotValue )
{
if(split)
{
GifSwapPixels(image, ii, storeIndex);
++storeIndex;
}
split = !split;
}
}
GifSwapPixels(image, storeIndex, right-1);
return storeIndex;
}
// Perform an incomplete sort, finding all elements above and below the desired median
void GifPartitionByMedian(uint8_t* image, int left, int right, int com, int neededCenter)
{
if(left < right-1)
{
int pivotIndex = left + (right-left)/2;
pivotIndex = GifPartition(image, left, right, com, pivotIndex);
// Only "sort" the section of the array that contains the median
if(pivotIndex > neededCenter)
GifPartitionByMedian(image, left, pivotIndex, com, neededCenter);
if(pivotIndex < neededCenter)
GifPartitionByMedian(image, pivotIndex+1, right, com, neededCenter);
}
}
// Builds a palette by creating a balanced k-d tree of all pixels in the image
void GifSplitPalette(uint8_t* image, int numPixels, int firstElt, int lastElt, int splitElt, int splitDist, int treeNode, bool buildForDither, GifPalette* pal)
{
if(lastElt <= firstElt || numPixels == 0)
return;
// base case, bottom of the tree
if(lastElt == firstElt+1)
{
if(buildForDither)
{
// Dithering needs at least one color as dark as anything
// in the image and at least one brightest color -
// otherwise it builds up error and produces strange artifacts
if( firstElt == 1 )
{
// special case: the darkest color in the image
uint32_t r=255, g=255, b=255;
for(int ii=0; ii<numPixels; ++ii)
{
r = (uint32_t)GifIMin((int32_t)r, image[ii * 4 + 0]);
g = (uint32_t)GifIMin((int32_t)g, image[ii * 4 + 1]);
b = (uint32_t)GifIMin((int32_t)b, image[ii * 4 + 2]);
}
pal->r[firstElt] = (uint8_t)r;
pal->g[firstElt] = (uint8_t)g;
pal->b[firstElt] = (uint8_t)b;
return;
}
if( firstElt == (1 << pal->bitDepth)-1 )
{
// special case: the lightest color in the image
uint32_t r=0, g=0, b=0;
for(int ii=0; ii<numPixels; ++ii)
{
r = (uint32_t)GifIMax((int32_t)r, image[ii * 4 + 0]);
g = (uint32_t)GifIMax((int32_t)g, image[ii * 4 + 1]);
b = (uint32_t)GifIMax((int32_t)b, image[ii * 4 + 2]);
}
pal->r[firstElt] = (uint8_t)r;
pal->g[firstElt] = (uint8_t)g;
pal->b[firstElt] = (uint8_t)b;
return;
}
}
// otherwise, take the average of all colors in this subcube
uint64_t r=0, g=0, b=0;
for(int ii=0; ii<numPixels; ++ii)
{
r += image[ii*4+0];
g += image[ii*4+1];
b += image[ii*4+2];
}
r += (uint64_t)numPixels / 2; // round to nearest
g += (uint64_t)numPixels / 2;
b += (uint64_t)numPixels / 2;
r /= (uint64_t)numPixels;
g /= (uint64_t)numPixels;
b /= (uint64_t)numPixels;
pal->r[firstElt] = (uint8_t)r;
pal->g[firstElt] = (uint8_t)g;
pal->b[firstElt] = (uint8_t)b;
return;
}
// Find the axis with the largest range
int minR = 255, maxR = 0;
int minG = 255, maxG = 0;
int minB = 255, maxB = 0;
for(int ii=0; ii<numPixels; ++ii)
{
int r = image[ii*4+0];
int g = image[ii*4+1];
int b = image[ii*4+2];
if(r > maxR) maxR = r;
if(r < minR) minR = r;
if(g > maxG) maxG = g;
if(g < minG) minG = g;
if(b > maxB) maxB = b;
if(b < minB) minB = b;
}
int rRange = maxR - minR;
int gRange = maxG - minG;
int bRange = maxB - minB;
// and split along that axis. (incidentally, this means this isn't a "proper" k-d tree but I don't know what else to call it)
int splitCom = 1;
if(bRange > gRange) splitCom = 2;
if(rRange > bRange && rRange > gRange) splitCom = 0;
int subPixelsA = numPixels * (splitElt - firstElt) / (lastElt - firstElt);
int subPixelsB = numPixels-subPixelsA;
GifPartitionByMedian(image, 0, numPixels, splitCom, subPixelsA);
pal->treeSplitElt[treeNode] = (uint8_t)splitCom;
pal->treeSplit[treeNode] = image[subPixelsA*4+splitCom];
GifSplitPalette(image, subPixelsA, firstElt, splitElt, splitElt-splitDist, splitDist/2, treeNode*2, buildForDither, pal);
GifSplitPalette(image+subPixelsA*4, subPixelsB, splitElt, lastElt, splitElt+splitDist, splitDist/2, treeNode*2+1, buildForDither, pal);
}
// Finds all pixels that have changed from the previous image and
// moves them to the fromt of th buffer.
// This allows us to build a palette optimized for the colors of the
// changed pixels only.
int GifPickChangedPixels( const uint8_t* lastFrame, uint8_t* frame, int numPixels )
{
int numChanged = 0;
uint8_t* writeIter = frame;
for (int ii=0; ii<numPixels; ++ii)
{
if(lastFrame[0] != frame[0] ||
lastFrame[1] != frame[1] ||
lastFrame[2] != frame[2])
{
writeIter[0] = frame[0];
writeIter[1] = frame[1];
writeIter[2] = frame[2];
++numChanged;
writeIter += 4;
}
lastFrame += 4;
frame += 4;
}
return numChanged;
}
// Creates a palette by placing all the image pixels in a k-d tree and then averaging the blocks at the bottom.
// This is known as the "modified median split" technique
void GifMakePalette( const uint8_t* lastFrame, const uint8_t* nextFrame, uint32_t width, uint32_t height, int bitDepth, bool buildForDither, GifPalette* pPal )
{
pPal->bitDepth = bitDepth;
// SplitPalette is destructive (it sorts the pixels by color) so
// we must create a copy of the image for it to destroy
size_t imageSize = (size_t)(width * height * 4 * sizeof(uint8_t));
uint8_t* destroyableImage = (uint8_t*)GIF_TEMP_MALLOC(imageSize);
memcpy(destroyableImage, nextFrame, imageSize);
int numPixels = (int)(width * height);
if(lastFrame)
numPixels = GifPickChangedPixels(lastFrame, destroyableImage, numPixels);
const int lastElt = 1 << bitDepth;
const int splitElt = lastElt/2;
const int splitDist = splitElt/2;
GifSplitPalette(destroyableImage, numPixels, 1, lastElt, splitElt, splitDist, 1, buildForDither, pPal);
GIF_TEMP_FREE(destroyableImage);
// add the bottom node for the transparency index
pPal->treeSplit[1 << (bitDepth-1)] = 0;
pPal->treeSplitElt[1 << (bitDepth-1)] = 0;
pPal->r[0] = pPal->g[0] = pPal->b[0] = 0;
}
// Implements Floyd-Steinberg dithering, writes palette value to alpha
void GifDitherImage( const uint8_t* lastFrame, const uint8_t* nextFrame, uint8_t* outFrame, uint32_t width, uint32_t height, GifPalette* pPal )
{
int numPixels = (int)(width * height);
// quantPixels initially holds color*256 for all pixels
// The extra 8 bits of precision allow for sub-single-color error values
// to be propagated
int32_t *quantPixels = (int32_t *)GIF_TEMP_MALLOC(sizeof(int32_t) * (size_t)numPixels * 4);
for( int ii=0; ii<numPixels*4; ++ii )
{
uint8_t pix = nextFrame[ii];
int32_t pix16 = int32_t(pix) * 256;
quantPixels[ii] = pix16;
}
for( uint32_t yy=0; yy<height; ++yy )
{
for( uint32_t xx=0; xx<width; ++xx )
{
int32_t* nextPix = quantPixels + 4*(yy*width+xx);
const uint8_t* lastPix = lastFrame? lastFrame + 4*(yy*width+xx) : NULL;
// Compute the colors we want (rounding to nearest)
int32_t rr = (nextPix[0] + 127) / 256;
int32_t gg = (nextPix[1] + 127) / 256;
int32_t bb = (nextPix[2] + 127) / 256;
// if it happens that we want the color from last frame, then just write out
// a transparent pixel
if( lastFrame &&
lastPix[0] == rr &&
lastPix[1] == gg &&
lastPix[2] == bb )
{
nextPix[0] = rr;
nextPix[1] = gg;
nextPix[2] = bb;
nextPix[3] = kGifTransIndex;
continue;
}
int32_t bestDiff = 1000000;
int32_t bestInd = kGifTransIndex;
// Search the palete
GifGetClosestPaletteColor(pPal, rr, gg, bb, bestInd, bestDiff);
// Write the result to the temp buffer
int32_t r_err = nextPix[0] - int32_t(pPal->r[bestInd]) * 256;
int32_t g_err = nextPix[1] - int32_t(pPal->g[bestInd]) * 256;
int32_t b_err = nextPix[2] - int32_t(pPal->b[bestInd]) * 256;
nextPix[0] = pPal->r[bestInd];
nextPix[1] = pPal->g[bestInd];
nextPix[2] = pPal->b[bestInd];
nextPix[3] = bestInd;
// Propagate the error to the four adjacent locations
// that we haven't touched yet
int quantloc_7 = (int)(yy * width + xx + 1);
int quantloc_3 = (int)(yy * width + width + xx - 1);
int quantloc_5 = (int)(yy * width + width + xx);
int quantloc_1 = (int)(yy * width + width + xx + 1);
if(quantloc_7 < numPixels)
{
int32_t* pix7 = quantPixels+4*quantloc_7;
pix7[0] += GifIMax( -pix7[0], r_err * 7 / 16 );
pix7[1] += GifIMax( -pix7[1], g_err * 7 / 16 );
pix7[2] += GifIMax( -pix7[2], b_err * 7 / 16 );
}
if(quantloc_3 < numPixels)
{
int32_t* pix3 = quantPixels+4*quantloc_3;
pix3[0] += GifIMax( -pix3[0], r_err * 3 / 16 );
pix3[1] += GifIMax( -pix3[1], g_err * 3 / 16 );
pix3[2] += GifIMax( -pix3[2], b_err * 3 / 16 );
}
if(quantloc_5 < numPixels)
{
int32_t* pix5 = quantPixels+4*quantloc_5;
pix5[0] += GifIMax( -pix5[0], r_err * 5 / 16 );
pix5[1] += GifIMax( -pix5[1], g_err * 5 / 16 );
pix5[2] += GifIMax( -pix5[2], b_err * 5 / 16 );
}
if(quantloc_1 < numPixels)
{
int32_t* pix1 = quantPixels+4*quantloc_1;
pix1[0] += GifIMax( -pix1[0], r_err / 16 );
pix1[1] += GifIMax( -pix1[1], g_err / 16 );
pix1[2] += GifIMax( -pix1[2], b_err / 16 );
}
}
}
// Copy the palettized result to the output buffer
for( int ii=0; ii<numPixels*4; ++ii )
{
outFrame[ii] = (uint8_t)quantPixels[ii];
}
GIF_TEMP_FREE(quantPixels);
}
// Picks palette colors for the image using simple thresholding, no dithering
void GifThresholdImage( const uint8_t* lastFrame, const uint8_t* nextFrame, uint8_t* outFrame, uint32_t width, uint32_t height, GifPalette* pPal )
{
uint32_t numPixels = width*height;
for( uint32_t ii=0; ii<numPixels; ++ii )
{
// if a previous color is available, and it matches the current color,
// set the pixel to transparent
if(lastFrame &&
lastFrame[0] == nextFrame[0] &&
lastFrame[1] == nextFrame[1] &&
lastFrame[2] == nextFrame[2])
{
outFrame[0] = lastFrame[0];
outFrame[1] = lastFrame[1];
outFrame[2] = lastFrame[2];
outFrame[3] = kGifTransIndex;
}
else
{
// palettize the pixel
int32_t bestDiff = 1000000;
int32_t bestInd = 1;
GifGetClosestPaletteColor(pPal, nextFrame[0], nextFrame[1], nextFrame[2], bestInd, bestDiff);
// Write the resulting color to the output buffer
outFrame[0] = pPal->r[bestInd];
outFrame[1] = pPal->g[bestInd];
outFrame[2] = pPal->b[bestInd];
outFrame[3] = (uint8_t)bestInd;
}
if(lastFrame) lastFrame += 4;
outFrame += 4;
nextFrame += 4;
}
}
// Simple structure to write out the LZW-compressed portion of the image
// one bit at a time
struct GifBitStatus
{
uint8_t bitIndex; // how many bits in the partial byte written so far
uint8_t byte; // current partial byte
uint32_t chunkIndex;
uint8_t chunk[256]; // bytes are written in here until we have 256 of them, then written to the file
};
// insert a single bit
void GifWriteBit( GifBitStatus& stat, uint32_t bit )
{
bit = bit & 1;
bit = bit << stat.bitIndex;
stat.byte |= bit;
++stat.bitIndex;
if( stat.bitIndex > 7 )
{
// move the newly-finished byte to the chunk buffer
stat.chunk[stat.chunkIndex++] = stat.byte;
// and start a new byte
stat.bitIndex = 0;
stat.byte = 0;
}
}
// write all bytes so far to the file
void GifWriteChunk( FILE* f, GifBitStatus& stat )
{
fputc((int)stat.chunkIndex, f);
fwrite(stat.chunk, 1, stat.chunkIndex, f);
stat.bitIndex = 0;
stat.byte = 0;
stat.chunkIndex = 0;
}
void GifWriteCode( FILE* f, GifBitStatus& stat, uint32_t code, uint32_t length )
{
for( uint32_t ii=0; ii<length; ++ii )
{
GifWriteBit(stat, code);
code = code >> 1;
if( stat.chunkIndex == 255 )
{
GifWriteChunk(f, stat);
}
}
}
// The LZW dictionary is a 256-ary tree constructed as the file is encoded,
// this is one node
struct GifLzwNode
{
uint16_t m_next[256];
};
// write a 256-color (8-bit) image palette to the file
void GifWritePalette( const GifPalette* pPal, FILE* f )
{
fputc(0, f); // first color: transparency
fputc(0, f);
fputc(0, f);
for(int ii=1; ii<(1 << pPal->bitDepth); ++ii)
{
uint32_t r = pPal->r[ii];
uint32_t g = pPal->g[ii];
uint32_t b = pPal->b[ii];
fputc((int)r, f);
fputc((int)g, f);
fputc((int)b, f);
}
}
// write the image header, LZW-compress and write out the image
void GifWriteLzwImage(FILE* f, uint8_t* image, uint32_t left, uint32_t top, uint32_t width, uint32_t height, uint32_t delay, GifPalette* pPal)
{
// graphics control extension
fputc(0x21, f);
fputc(0xf9, f);
fputc(0x04, f);
fputc(0x05, f); // leave prev frame in place, this frame has transparency
fputc(delay & 0xff, f);
fputc((delay >> 8) & 0xff, f);
fputc(kGifTransIndex, f); // transparent color index
fputc(0, f);
fputc(0x2c, f); // image descriptor block
fputc(left & 0xff, f); // corner of image in canvas space
fputc((left >> 8) & 0xff, f);
fputc(top & 0xff, f);
fputc((top >> 8) & 0xff, f);
fputc(width & 0xff, f); // width and height of image
fputc((width >> 8) & 0xff, f);
fputc(height & 0xff, f);
fputc((height >> 8) & 0xff, f);
//fputc(0, f); // no local color table, no transparency
//fputc(0x80, f); // no local color table, but transparency
fputc(0x80 + pPal->bitDepth-1, f); // local color table present, 2 ^ bitDepth entries
GifWritePalette(pPal, f);
const int minCodeSize = pPal->bitDepth;
const uint32_t clearCode = 1 << pPal->bitDepth;
fputc(minCodeSize, f); // min code size 8 bits
GifLzwNode* codetree = (GifLzwNode*)GIF_TEMP_MALLOC(sizeof(GifLzwNode)*4096);
memset(codetree, 0, sizeof(GifLzwNode)*4096);
int32_t curCode = -1;
uint32_t codeSize = (uint32_t)minCodeSize + 1;
uint32_t maxCode = clearCode+1;
GifBitStatus stat;
stat.byte = 0;
stat.bitIndex = 0;
stat.chunkIndex = 0;
GifWriteCode(f, stat, clearCode, codeSize); // start with a fresh LZW dictionary
for(uint32_t yy=0; yy<height; ++yy)
{
for(uint32_t xx=0; xx<width; ++xx)
{
#ifdef GIF_FLIP_VERT
// bottom-left origin image (such as an OpenGL capture)
uint8_t nextValue = image[((height-1-yy)*width+xx)*4+3];
#else
// top-left origin
uint8_t nextValue = image[(yy*width+xx)*4+3];
#endif
// "loser mode" - no compression, every single code is followed immediately by a clear
//WriteCode( f, stat, nextValue, codeSize );
//WriteCode( f, stat, 256, codeSize );
if( curCode < 0 )
{
// first value in a new run
curCode = nextValue;
}
else if( codetree[curCode].m_next[nextValue] )
{
// current run already in the dictionary
curCode = codetree[curCode].m_next[nextValue];
}
else
{
// finish the current run, write a code
GifWriteCode(f, stat, (uint32_t)curCode, codeSize);
// insert the new run into the dictionary
codetree[curCode].m_next[nextValue] = (uint16_t)++maxCode;
if( maxCode >= (1ul << codeSize) )
{
// dictionary entry count has broken a size barrier,
// we need more bits for codes
codeSize++;
}
if( maxCode == 4095 )
{
// the dictionary is full, clear it out and begin anew
GifWriteCode(f, stat, clearCode, codeSize); // clear tree
memset(codetree, 0, sizeof(GifLzwNode)*4096);
codeSize = (uint32_t)(minCodeSize + 1);
maxCode = clearCode+1;
}
curCode = nextValue;
}
}
}
// compression footer
GifWriteCode(f, stat, (uint32_t)curCode, codeSize);
GifWriteCode(f, stat, clearCode, codeSize);
GifWriteCode(f, stat, clearCode + 1, (uint32_t)minCodeSize + 1);
// write out the last partial chunk
while( stat.bitIndex ) GifWriteBit(stat, 0);
if( stat.chunkIndex ) GifWriteChunk(f, stat);
fputc(0, f); // image block terminator
GIF_TEMP_FREE(codetree);
}
struct GifWriter
{
FILE* f;
uint8_t* oldImage;
bool firstFrame;
};
// Creates a gif file.
// The input GIFWriter is assumed to be uninitialized.
// The delay value is the time between frames in hundredths of a second - note that not all viewers pay much attention to this value.
bool GifBegin( GifWriter* writer, const char* filename, uint32_t width, uint32_t height, uint32_t delay, int32_t bitDepth = 8, bool dither = false )
{
(void)bitDepth; (void)dither; // Mute "Unused argument" warnings
#if defined(_MSC_VER) && (_MSC_VER >= 1400)
writer->f = 0;
fopen_s(&writer->f, filename, "wb");
#else
writer->f = fopen(filename, "wb");
#endif
if(!writer->f) return false;
writer->firstFrame = true;
// allocate
writer->oldImage = (uint8_t*)GIF_MALLOC(width*height*4);
fputs("GIF89a", writer->f);
// screen descriptor
fputc(width & 0xff, writer->f);
fputc((width >> 8) & 0xff, writer->f);
fputc(height & 0xff, writer->f);
fputc((height >> 8) & 0xff, writer->f);
fputc(0xf0, writer->f); // there is an unsorted global color table of 2 entries
fputc(0, writer->f); // background color
fputc(0, writer->f); // pixels are square (we need to specify this because it's 1989)
// now the "global" palette (really just a dummy palette)
// color 0: black
fputc(0, writer->f);
fputc(0, writer->f);
fputc(0, writer->f);
// color 1: also black
fputc(0, writer->f);
fputc(0, writer->f);
fputc(0, writer->f);
if( delay != 0 )
{
// animation header
fputc(0x21, writer->f); // extension
fputc(0xff, writer->f); // application specific
fputc(11, writer->f); // length 11
fputs("NETSCAPE2.0", writer->f); // yes, really
fputc(3, writer->f); // 3 bytes of NETSCAPE2.0 data
fputc(1, writer->f); // JUST BECAUSE
fputc(0, writer->f); // loop infinitely (byte 0)
fputc(0, writer->f); // loop infinitely (byte 1)
fputc(0, writer->f); // block terminator
}
return true;
}
// Writes out a new frame to a GIF in progress.
// The GIFWriter should have been created by GIFBegin.
// AFAIK, it is legal to use different bit depths for different frames of an image -
// this may be handy to save bits in animations that don't change much.
bool GifWriteFrame( GifWriter* writer, const uint8_t* image, uint32_t width, uint32_t height, uint32_t delay, int bitDepth = 8, bool dither = false )
{
if(!writer->f) return false;
const uint8_t* oldImage = writer->firstFrame? NULL : writer->oldImage;
writer->firstFrame = false;
GifPalette pal;
GifMakePalette((dither? NULL : oldImage), image, width, height, bitDepth, dither, &pal);
if(dither)
GifDitherImage(oldImage, image, writer->oldImage, width, height, &pal);
else
GifThresholdImage(oldImage, image, writer->oldImage, width, height, &pal);
GifWriteLzwImage(writer->f, writer->oldImage, 0, 0, width, height, delay, &pal);
return true;
}
// Writes the EOF code, closes the file handle, and frees temp memory used by a GIF.
// Many if not most viewers will still display a GIF properly if the EOF code is missing,
// but it's still a good idea to write it out.
bool GifEnd( GifWriter* writer )
{
if(!writer->f) return false;
fputc(0x3b, writer->f); // end of file
fclose(writer->f);
GIF_FREE(writer->oldImage);
writer->f = NULL;
writer->oldImage = NULL;
return true;
}
#endif
|
0015/esp_rlottie
| 4,938 |
rlottie/example/lottieperf.cpp
|
#include <memory>
#include <vector>
#include <dirent.h>
#include <algorithm>
#include <chrono>
#include <iostream>
#include <cstring>
#include <rlottie.h>
static bool isJsonFile(const char *filename) {
const char *dot = strrchr(filename, '.');
if(!dot || dot == filename) return false;
return !strcmp(dot + 1, "json");
}
static std::vector<std::string>
jsonFiles(const std::string &dirName)
{
DIR *d;
struct dirent *dir;
std::vector<std::string> result;
d = opendir(dirName.c_str());
if (d) {
while ((dir = readdir(d)) != NULL) {
if (isJsonFile(dir->d_name))
result.push_back(dirName + dir->d_name);
}
closedir(d);
}
std::sort(result.begin(), result.end(), [](auto & a, auto &b){return a < b;});
return result;
}
class Renderer
{
public:
explicit Renderer(const std::string& filename)
{
_animation = rlottie::Animation::loadFromFile(filename);
_frames = _animation->totalFrame();
_buffer = std::make_unique<uint32_t[]>(100 * 100);
_surface = rlottie::Surface(_buffer.get(), 100, 100, 100 * 4);
}
void render()
{
if (_cur >= _frames) _cur = 0;
_animation->renderSync(_cur++, _surface);
}
void renderAsync()
{
if (_cur >= _frames) _cur = 0;
_future = _animation->render(_cur++, _surface);
}
void get()
{
if (_future.valid()) _future.get();
}
private:
std::unique_ptr<uint32_t[]> _buffer;
std::unique_ptr<rlottie::Animation> _animation;
size_t _frames{0};
size_t _cur{0};
rlottie::Surface _surface;
std::future<rlottie::Surface> _future;
};
class PerfTest
{
public:
explicit PerfTest(size_t resourceCount, size_t iterations):
_resourceCount(resourceCount), _iterations(iterations)
{
_resourceList = jsonFiles(std::string(DEMO_DIR));
}
void test(bool async)
{
setup();
std::cout<<" Test Started : .... \n";
auto start = std::chrono::high_resolution_clock::now();
benchmark(async);
std::chrono::duration<double> secs = std::chrono::high_resolution_clock::now() - start;
std::chrono::duration<double, std::milli> millisecs = secs;
std::cout<< " Test Finished.\n";
std::cout<< " \nPerformance Report: \n\n";
std::cout<< " \t Resource Rendered per Frame : "<< _resourceCount <<"\n";
std::cout<< " \t Render Buffer Size : (100 X 100) \n";
std::cout<< " \t Render Mode : "<< (async ? "Async" : "Sync")<<"\n";
std::cout<< " \t Total Frames Rendered : "<< _iterations<<"\n";
std::cout<< " \t Total Render Time : "<< secs.count()<<"sec\n";
std::cout<< " \t Avrage Time per Resource : "<< millisecs.count() / (_iterations * _resourceCount)<<"ms\n";
std::cout<< " \t Avrage Time Per Frame : "<< millisecs.count() / _iterations <<"ms\n";
std::cout<< " \t FPS : "<< _iterations / secs.count() <<"fps\n\n";
}
private:
void setup()
{
for (auto i = 0u; i < _resourceCount; i++) {
auto index = i % _resourceList.size();
_renderers.push_back(std::make_unique<Renderer>(_resourceList[index]));
}
}
void benchmark(bool async)
{
for (auto i = 0u; i < _iterations; i++) {
if (async) {
for (const auto &e : _renderers) e->renderAsync();
for (const auto &e : _renderers) e->get();
} else {
for (const auto &e : _renderers) e->render();
}
}
}
private:
size_t _resourceCount;
size_t _iterations;
std::vector<std::string> _resourceList;
std::vector<std::unique_ptr<Renderer>> _renderers;
};
static int help()
{
std::cout<<"\nUsage : ./perf [--sync] [-c] [resource count] [-i] [iteration count] \n";
std::cout<<"\nExample : ./perf -c 50 -i 100 \n";
std::cout<<"\n\t runs perf test for 100 iterations. renders 50 resource per iteration\n\n";
return 0;
}
int
main(int argc, char ** argv)
{
bool async = true;
size_t resourceCount = 250;
size_t iterations = 500;
auto index = 0;
while (index < argc) {
const char* option = argv[index];
index++;
if (!strcmp(option,"--help") || !strcmp(option,"-h")) {
return help();
} else if (!strcmp(option,"--sync")) {
async = false;
} else if (!strcmp(option,"-c")) {
resourceCount = (index < argc) ? atoi(argv[index]) : resourceCount;
index++;
} else if (!strcmp(option,"-i")) {
iterations = (index < argc) ? atoi(argv[index]) : iterations;
index++;
}
}
PerfTest obj(resourceCount, iterations);
obj.test(async);
return 0;
}
|
0015/esp_rlottie
| 3,952 |
rlottie/example/uxsampletest.cpp
|
/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include"evasapp.h"
#include "lottieview.h"
#include <memory>
#include<vector>
#include<string>
class UxSampleTest
{
public:
UxSampleTest(EvasApp *app, bool renderMode) {
mApp = app;
mRenderMode = renderMode;
mResourceList = EvasApp::jsonFiles(std::string(DEMO_DIR) + "UXSample_1920x1080/");
mRepeatMode = LottieView::RepeatMode::Restart;
}
void showPrev() {
if (mResourceList.empty()) return;
mCurIndex--;
if (mCurIndex < 0)
mCurIndex = mResourceList.size() - 1;
show();
}
void showNext() {
if (mResourceList.empty()) return;
mCurIndex++;
if (mCurIndex >= int(mResourceList.size()))
mCurIndex = 0;
show();
}
void resize() {
if (mView) {
mView->setSize(mApp->width(), mApp->height());
}
}
private:
void show() {
mView = std::make_unique<LottieView>(mApp->evas(), Strategy::renderCAsync);
mView->setFilePath(mResourceList[mCurIndex].c_str());
mView->setPos(0, 0);
mView->setSize(mApp->width(), mApp->height());
mView->show();
mView->play();
mView->loop(true);
mView->setRepeatMode(mRepeatMode);
}
public:
EvasApp *mApp;
bool mRenderMode = false;
int mCurIndex = -1;
std::vector<std::string> mResourceList;
std::unique_ptr<LottieView> mView;
LottieView::RepeatMode mRepeatMode;
};
static void
onExitCb(void *data, void */*extra*/)
{
UxSampleTest *view = (UxSampleTest *)data;
delete view;
}
static void
onKeyCb(void *data, void *extra)
{
UxSampleTest *view = (UxSampleTest *)data;
char *keyname = (char *)extra;
if (!strcmp(keyname, "Right") || !strcmp(keyname, "n")) {
view->showNext();
} else if (!strcmp(keyname, "Left") || !strcmp(keyname, "p")) {
view->showPrev();
} else if (!strcmp(keyname,"r")) {
if (view->mRepeatMode == LottieView::RepeatMode::Restart) {
view->mRepeatMode = LottieView::RepeatMode::Reverse;
} else
view->mRepeatMode = LottieView::RepeatMode::Restart;
if (view->mView)
view->mView->setRepeatMode(view->mRepeatMode);
}
}
static void
onResizeCb(void *data, void */*extra*/)
{
UxSampleTest *view = (UxSampleTest *)data;
view->resize();
}
int
main(int argc, char **argv)
{
EvasApp *app = new EvasApp(800, 800);
app->setup();
bool renderMode = true;
if (argc > 1) {
if (!strcmp(argv[1],"--disable-render"))
renderMode = false;
}
UxSampleTest *view = new UxSampleTest(app, renderMode);
view->showNext();
app->addExitCb(onExitCb, view);
app->addKeyCb(onKeyCb, view);
app->addResizeCb(onResizeCb, view);
app->run();
delete app;
return 0;
}
|
0015/esp_rlottie
| 2,107 |
rlottie/example/meson.build
|
override_default = ['warning_level=2', 'werror=false']
common_source = files('evasapp.cpp')
common_source += files('lottieview.cpp')
demo_sources = files('demo.cpp')
demo_sources += common_source
executable('lottie2gif',
'lottie2gif.cpp',
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib)
if host_machine.system() != 'windows'
executable('perf',
'lottieperf.cpp',
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib)
endif
demo_dep = dependency('elementary', required : false, disabler : true)
executable('demo',
demo_sources,
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib,
dependencies : demo_dep)
demo_marker_sources = files('demo_marker.cpp')
demo_marker_sources += common_source
executable('demo_marker',
demo_marker_sources,
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib,
dependencies : demo_dep)
lottieview_test_src = files('lottieviewtest.cpp')
lottieview_test_src += common_source
executable('lottieviewTest',
lottieview_test_src,
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib,
dependencies : demo_dep)
uxsample_test_src = files('uxsampletest.cpp')
uxsample_test_src += common_source
executable('uxsampleTest',
uxsample_test_src,
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib,
dependencies : demo_dep)
lottieviewer_sources = files('lottieviewer.cpp')
lottieviewer_sources += common_source
executable('lottieviewer',
lottieviewer_sources,
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib,
dependencies : demo_dep)
|
0015/esp_rlottie
| 9,226 |
rlottie/example/demo.cpp
|
/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "evasapp.h"
#include "lottieview.h"
#include<iostream>
#include <stdio.h>
#include <fstream>
#include <sstream>
using namespace std;
class Demo
{
public:
Demo(EvasApp *app, std::string &filePath) {
Demo1(app, filePath);
Demo2(app, filePath);
Demo3(app, filePath);
Demo4(app, filePath);
Demo5(app, filePath);
Demo6(app, filePath);
Demo7(app, filePath);
Demo8(app, filePath);
}
void Demo1(EvasApp *app, std::string &filePath) {
/* Fill Color */
view1.reset(new LottieView(app->evas()));
view1->setFilePath(filePath.c_str());
if (view1->player()) {
view1->player()->setValue<rlottie::Property::FillColor>("Shape Layer 1.Ellipse 1.Fill 1",
[](const rlottie::FrameInfo& info) {
if (info.curFrame() < 60 )
return rlottie::Color(0, 0, 1);
else {
return rlottie::Color(1, 0, 0);
}
});
}
view1->setPos(0, 0);
view1->setSize(300, 300);
view1->show();
view1->play();
view1->loop(true);
view1->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo2(EvasApp *app, std::string &filePath) {
/* Stroke Opacity */
view2.reset(new LottieView(app->evas()));
view2->setFilePath(filePath.c_str());
if (view2->player()) {
view2->player()->setValue<rlottie::Property::StrokeOpacity>("Shape Layer 2.Shape 1.Stroke 1",
[](const rlottie::FrameInfo& info) {
if (info.curFrame() < 60 )
return 20;
else {
return 100;
}
});
}
view2->setPos(300, 0);
view2->setSize(300, 300);
view2->show();
view2->play();
view2->loop(true);
view2->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo3(EvasApp *app, std::string &filePath) {
/* Stroke Opacity */
view3.reset(new LottieView(app->evas()));
view3->setFilePath(filePath.c_str());
if (view3->player()) {
view3->player()->setValue<rlottie::Property::StrokeWidth>("**",
[](const rlottie::FrameInfo& info) {
if (info.curFrame() < 60 )
return 1.0;
else {
return 5.0;
}
});
}
view3->setPos(600, 0);
view3->setSize(300, 300);
view3->show();
view3->play();
view3->loop(true);
view3->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo4(EvasApp *app, std::string &filePath) {
/* Transform position */
view4.reset(new LottieView(app->evas()));
view4->setFilePath(filePath.c_str());
if (view4->player()) {
view4->player()->setValue<rlottie::Property::TrPosition>("Shape Layer 1.Ellipse 1",
[](const rlottie::FrameInfo& info) {
return rlottie::Point(-20 + (double)info.curFrame()/2.0,
-20 + (double)info.curFrame()/2.0);
});
}
view4->setPos(900, 0);
view4->setSize(300, 300);
view4->show();
view4->play();
view4->loop(true);
view4->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo5(EvasApp *app, std::string &filePath) {
/* Transform position */
view5.reset(new LottieView(app->evas()));
view5->setFilePath(filePath.c_str());
if (view5->player()) {
view5->player()->setValue<rlottie::Property::TrPosition>("Shape Layer 2.Shape 1",
[](const rlottie::FrameInfo& info) {
return rlottie::Point(-20 + (double)info.curFrame()/2.0,
-20 + (double)info.curFrame()/2.0);
});
}
view5->setPos(1200, 0);
view5->setSize(300, 300);
view5->show();
view5->play();
view5->loop(true);
view5->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo6(EvasApp *app, std::string &filePath) {
/* Transform scale */
view6.reset(new LottieView(app->evas()));
view6->setFilePath(filePath.c_str());
if (view6->player()) {
view6->player()->setValue<rlottie::Property::TrScale>("Shape Layer 1.Ellipse 1",
[](const rlottie::FrameInfo& info) {
return rlottie::Size(100 - info.curFrame(),
50);
});
}
view6->setPos(1500, 0);
view6->setSize(300, 300);
view6->show();
view6->play();
view6->loop(true);
view6->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo7(EvasApp *app, std::string &filePath) {
/* Transform rotation */
view7.reset(new LottieView(app->evas()));
view7->setFilePath(filePath.c_str());
if (view7->player()) {
view7->player()->setValue<rlottie::Property::TrRotation>("Shape Layer 2.Shape 1",
[](const rlottie::FrameInfo& info) {
return info.curFrame() * 20;
});
}
view7->setPos(1800, 0);
view7->setSize(300, 300);
view7->show();
view7->play();
view7->loop(true);
view7->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo8(EvasApp *app, std::string &filePath) {
/* Transform + color */
view8.reset(new LottieView(app->evas()));
view8->setFilePath(filePath.c_str());
if (view8->player()) {
view8->player()->setValue<rlottie::Property::TrRotation>("Shape Layer 1.Ellipse 1",
[](const rlottie::FrameInfo& info) {
return info.curFrame() * 20;
});
view8->player()->setValue<rlottie::Property::TrScale>("Shape Layer 1.Ellipse 1",
[](const rlottie::FrameInfo& info) {
return rlottie::Size(50, 100 - info.curFrame());
});
view8->player()->setValue<rlottie::Property::TrPosition>("Shape Layer 1.Ellipse 1",
[](const rlottie::FrameInfo& info) {
return rlottie::Point(-20 + (double)info.curFrame()/2.0,
-20 + (double)info.curFrame()/2.0);
});
view8->player()->setValue<rlottie::Property::FillColor>("Shape Layer 1.Ellipse 1.Fill 1",
[](const rlottie::FrameInfo& info) {
if (info.curFrame() < 60 )
return rlottie::Color(0, 0, 1);
else {
return rlottie::Color(1, 0, 0);
}
});
}
view8->setPos(2100, 0);
view8->setSize(300, 300);
view8->show();
view8->play();
view8->loop(true);
view8->setRepeatMode(LottieView::RepeatMode::Reverse);
}
private:
std::unique_ptr<LottieView> view1;
std::unique_ptr<LottieView> view2;
std::unique_ptr<LottieView> view3;
std::unique_ptr<LottieView> view4;
std::unique_ptr<LottieView> view5;
std::unique_ptr<LottieView> view6;
std::unique_ptr<LottieView> view7;
std::unique_ptr<LottieView> view8;
};
static void
onExitCb(void *data, void */*extra*/)
{
Demo *demo = (Demo *)data;
delete demo;
}
int
main(void)
{
EvasApp *app = new EvasApp(2400, 300);
app->setup();
std::string filePath = DEMO_DIR;
filePath +="done.json";
auto demo = new Demo(app, filePath);
app->addExitCb(onExitCb, demo);
app->run();
delete app;
return 0;
}
|
0015/esp_rlottie
| 5,437 |
rlottie/example/lottieviewtest.cpp
|
/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "evasapp.h"
#include "lottieview.h"
#include<iostream>
#include <dirent.h>
#include <stdio.h>
#include <chrono>
using namespace std;
static Eina_Bool onTestDone(void *data);
/*
* To check the frame rate with rendermode off run
* ECORE_EVAS_FPS_DEBUG=1 ./lottieviewTest --disable-render
*
* To check the frame rate with render backend
* ECORE_EVAS_FPS_DEBUG=1 ./lottieviewTest
*
*/
class LottieViewTest
{
public:
LottieViewTest(EvasApp *app, Strategy st, double timeout) {
mStartTime = std::chrono::high_resolution_clock::now();
mStrategy = st;
mApp = app;
if (timeout > 0) {
ecore_timer_add(timeout, onTestDone, mApp);
}
// work around for 60fps
ecore_animator_frametime_set(1.0f/120.0f);
}
void show(int numberOfImage) {
auto resource = EvasApp::jsonFiles(std::string(DEMO_DIR));
if (resource.empty()) return;
int count = numberOfImage;
int colums = (int) ceil(sqrt(count));
int offset = 3;
int vw = (mApp->width() - (offset * colums))/colums;
int vh = vw;
int posx = offset;
int posy = offset;
int resourceSize = resource.size();
for (int i = 0 ; i < numberOfImage; i++) {
int index = i % resourceSize;
std::unique_ptr<LottieView> view(new LottieView(mApp->evas(), mStrategy));
view->setFilePath(resource[index].c_str());
view->setPos(posx, posy);
view->setSize(vw, vh);
view->show();
view->play();
view->loop(true);
//view->setRepeatMode(LottieView::RepeatMode::Reverse);
posx += vw+offset;
if ((mApp->width() - posx) < vw) {
posx = offset;
posy = posy + vh + offset;
}
mViews.push_back(std::move(view));
}
}
~LottieViewTest() {
const auto frames = mViews.empty() ? 0 : mViews[0]->renderCount();
const double secs = std::chrono::duration<double>(std::chrono::high_resolution_clock::now() - mStartTime).count();
std::cout<<"\tTestTime : "<< secs<<" sec \n\tTotalFrames : "<<frames<<"\n\tFramesPerSecond : "<< frames / secs <<" fps\n";
}
static int help() {
printf("Usage ./lottieviewTest [-s] [strategy] [-t] [timeout] [-c] [count]\n");
printf("\n \t-t : timeout duration in seconds\n");
printf("\n \t-c : number of resource in the grid\n");
printf("\n \t-s : Rendering Strategy\n");
printf("\t\t 0 - Test Lottie SYNC Renderer with CPP API\n");
printf("\t\t 1 - Test Lottie ASYNC Renderer with CPP API\n");
printf("\t\t 2 - Test Lottie SYNC Renderer with C API\n");
printf("\t\t 3 - Test Lottie ASYNC Renderer with C API\n");
printf("\t\t 4 - Test Lottie Tree Api using Efl VG Render\n");
printf(" Default : ./lottieviewTest -s 1 \n");
return 0;
}
public:
EvasApp *mApp;
Strategy mStrategy;
std::vector<std::unique_ptr<LottieView>> mViews;
std::chrono::high_resolution_clock::time_point mStartTime;
};
static void
onExitCb(void *data, void */*extra*/)
{
LottieViewTest *view = (LottieViewTest *)data;
delete view;
}
static Eina_Bool
onTestDone(void *data)
{
EvasApp *app = (EvasApp *)data;
app->exit();
return ECORE_CALLBACK_CANCEL;
}
int
main(int argc, char **argv)
{
Strategy st = Strategy::renderCppAsync;
auto index = 0;
double timeOut = 0;
size_t itemCount = 250;
while (index < argc) {
const char* option = argv[index];
index++;
if (!strcmp(option,"--help") || !strcmp(option,"-h")) {
return LottieViewTest::help();
} else if (!strcmp(option,"-s")) {
st = (index < argc) ? static_cast<Strategy>(atoi(argv[index])) : Strategy::renderCppAsync;
index++;
} else if (!strcmp(option,"-t")) {
timeOut = (index < argc) ? atoi(argv[index]) : 10;
index++;
} else if (!strcmp(option,"-c")) {
itemCount = (index < argc) ? atoi(argv[index]) : 10;
index++;
}
}
EvasApp *app = new EvasApp(800, 800);
app->setup();
LottieViewTest *view = new LottieViewTest(app, st, timeOut);
view->show(itemCount);
app->addExitCb(onExitCb, view);
app->run();
delete app;
return 0;
}
|
0015/esp_rlottie
| 2,957 |
rlottie/example/evasapp.h
|
/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef EVASAPP_H
#define EVASAPP_H
#ifndef EFL_BETA_API_SUPPORT
#define EFL_BETA_API_SUPPORT
#endif
#ifndef EFL_EO_API_SUPPORT
#define EFL_EO_API_SUPPORT
#endif
#include <Eo.h>
#include <Efl.h>
#include <Evas.h>
#include <Ecore.h>
#include <Ecore_Evas.h>
#include <Ecore_Input.h>
#include<vector>
#include<string>
typedef void (*appCb)(void *userData, void *extra);
class EvasApp
{
public:
EvasApp(int w, int h);
void setup();
void resize(int w, int h);
int width() const{ return mw;}
int height() const{ return mh;}
void run();
Ecore_Evas * ee() const{return mEcoreEvas;}
Evas * evas() const {return mEvas;}
void addExitCb(appCb exitcb, void *data) {mExitCb = exitcb; mExitData = data;}
void addResizeCb(appCb resizecb, void *data) {mResizeCb = resizecb; mResizeData = data;}
void addKeyCb(appCb keycb, void *data) {mKeyCb = keycb; mKeyData = data;}
void addRenderPreCb(appCb renderPrecb, void *data) {mRenderPreCb = renderPrecb; mRenderPreData = data;}
void addRenderPostCb(appCb renderPostcb, void *data) {mRenderPostCb = renderPostcb; mRenderPostData = data;}
void exit();
static std::vector<std::string> jsonFiles(const std::string &dir, bool recurse=false);
public:
int mw{0};
int mh{0};
Ecore_Evas *mEcoreEvas{nullptr};
Evas *mEvas{nullptr};
Evas_Object *mBackground{nullptr};
appCb mResizeCb{nullptr};
void *mResizeData{nullptr};
appCb mExitCb{nullptr};
void *mExitData{nullptr};
appCb mKeyCb{nullptr};
void *mKeyData{nullptr};
appCb mRenderPreCb{nullptr};
void *mRenderPreData{nullptr};
appCb mRenderPostCb{nullptr};
void *mRenderPostData{nullptr};
};
#endif //EVASAPP_H
|
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