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import gradio as gr
import threading
import os
import shutil
import tempfile
import time
from util import process_image_edit, get_country_info_safe, get_location_info_safe, contains_chinese
from nfsw import NSFWDetector

# 配置参数
NSFW_TIME_WINDOW = 5  # 时间窗口:5分钟
NSFW_LIMIT = 6        # 限制次数:6次

IP_Dict = {}
NSFW_Dict = {}  # 记录每个IP的NSFW违规次数
NSFW_Time_Dict = {}  # 记录每个IP在特定时间窗口的NSFW检测次数,键格式: "ip_timestamp"

def get_current_time_window():
    """
    获取当前的整点时间窗口
    
    Returns:
        tuple: (窗口开始时间戳, 窗口结束时间戳)
    """
    current_time = time.time()
    # 获取当前时间的分钟数
    current_struct = time.localtime(current_time)
    current_minute = current_struct.tm_min
    
    # 计算当前5分钟时间窗口的开始分钟
    window_start_minute = (current_minute // NSFW_TIME_WINDOW) * NSFW_TIME_WINDOW
    
    # 构建窗口开始时间
    window_start_struct = time.struct_time((
        current_struct.tm_year, current_struct.tm_mon, current_struct.tm_mday,
        current_struct.tm_hour, window_start_minute, 0,
        current_struct.tm_wday, current_struct.tm_yday, current_struct.tm_isdst
    ))
    
    window_start_time = time.mktime(window_start_struct)
    window_end_time = window_start_time + (NSFW_TIME_WINDOW * 60)
    
    return window_start_time, window_end_time

def check_nsfw_rate_limit(client_ip):
    """
    检查IP的NSFW检测频率限制(基于整点时间窗口)
    
    Args:
        client_ip (str): 客户端IP地址
    
    Returns:
        tuple: (是否超过限制, 剩余等待时间)
    """
    current_time = time.time()
    window_start_time, window_end_time = get_current_time_window()
    
    # 清理不在当前时间窗口的记录
    current_window_key = f"{client_ip}_{int(window_start_time)}"
    
    # 如果没有当前窗口的记录,创建新的
    if current_window_key not in NSFW_Time_Dict:
        NSFW_Time_Dict[current_window_key] = 0
    
    # 清理旧的窗口记录(保持内存清洁)
    keys_to_remove = []
    for key in NSFW_Time_Dict:
        if key.startswith(client_ip + "_"):
            window_time = int(key.split("_")[1])
            if window_time < window_start_time:
                keys_to_remove.append(key)
    
    for key in keys_to_remove:
        del NSFW_Time_Dict[key]
    
    # 检查当前窗口是否超过限制
    if NSFW_Time_Dict[current_window_key] >= NSFW_LIMIT:
        # 计算到下一个时间窗口的等待时间
        wait_time = window_end_time - current_time
        return True, max(0, wait_time)
    
    return False, 0

def record_nsfw_detection(client_ip):
    """
    记录IP的NSFW检测时间(基于整点时间窗口)
    
    Args:
        client_ip (str): 客户端IP地址
    """
    window_start_time, _ = get_current_time_window()
    current_window_key = f"{client_ip}_{int(window_start_time)}"
    
    # 增加当前窗口的计数
    if current_window_key not in NSFW_Time_Dict:
        NSFW_Time_Dict[current_window_key] = 0
    NSFW_Time_Dict[current_window_key] += 1
    
    # 记录到NSFW_Dict中(兼容现有逻辑)
    if client_ip not in NSFW_Dict:
        NSFW_Dict[client_ip] = 0
    NSFW_Dict[client_ip] += 1

def get_current_window_info(client_ip):
    """
    获取当前窗口的统计信息(用于调试)
    
    Args:
        client_ip (str): 客户端IP地址
        
    Returns:
        dict: 当前窗口的统计信息
    """
    window_start_time, window_end_time = get_current_time_window()
    current_window_key = f"{client_ip}_{int(window_start_time)}"
    
    current_count = NSFW_Time_Dict.get(current_window_key, 0)
    
    # 格式化时间显示
    start_time_str = time.strftime("%H:%M:%S", time.localtime(window_start_time))
    end_time_str = time.strftime("%H:%M:%S", time.localtime(window_end_time))
    
    return {
        "window_start": start_time_str,
        "window_end": end_time_str,
        "current_count": current_count,
        "limit": NSFW_LIMIT,
        "window_key": current_window_key
    }

# 初始化NSFW检测器(从Hugging Face下载)
try:
    nsfw_detector = NSFWDetector()  # 自动从Hugging Face下载falconsai_yolov9_nsfw_model_quantized.pt
    print("✅ NSFW检测器初始化成功")
except Exception as e:
    print(f"❌ NSFW检测器初始化失败: {e}")
    nsfw_detector = None

def edit_image_interface(input_image, prompt, request: gr.Request, progress=gr.Progress()):
    """
    Interface function for processing image editing
    """
    # 提取用户IP
    client_ip = request.client.host
    x_forwarded_for = dict(request.headers).get('x-forwarded-for')
    if x_forwarded_for:
        client_ip = x_forwarded_for   
    if client_ip not in IP_Dict:
        IP_Dict[client_ip] = 0
    IP_Dict[client_ip] += 1

    # 获取IP属地信息
    country_info = get_country_info_safe(client_ip)
    location_info = get_location_info_safe(client_ip)
    
    # # 检查IP是否因NSFW违规过多而被屏蔽 3 
    # if client_ip in NSFW_Dict and NSFW_Dict[client_ip] >= 5:
    #     print(f"❌ IP blocked due to excessive NSFW violations - IP: {client_ip}({country_info}), violations: {NSFW_Dict[client_ip]}")
        
    #     # 检查是否需要特殊处理(中文prompt或中国IP)
    #     has_chinese = contains_chinese(prompt.strip()) if prompt else False
    #     is_china_ip = location_info.get("country", "").lower() == "中国"
        
    #     if has_chinese or is_china_ip:
    #         # 构建特殊警告信息
    #         prov = location_info.get("prov", "未知省份")
    #         city = location_info.get("city", "未知城市")
    #         isp = location_info.get("isp", "Unknown")
            
    #         # 处理城市名称
    #         city_name = city.replace("市", "") if city != "未知城市" else "当地"
            
    #         # 处理ISP名称,去掉"中国"前缀
    #         isp_name = isp.replace("中国", "") if isp != "Unknown" else "未知"
            
    #         warning_msg = f"您的ip地址为{client_ip},地点为{prov}-{city},您的网络服务商为{isp_name},检测到您目前正在浏览,制作淫秽内容,已经上报给 {city_name}市公安局,已加急处理,请耐心等待警察上门调查"
    #         return None, f"❌ {warning_msg}"
    #     else:
    #         return None, f"❌ Your ip {client_ip}, your region has been blocked for too much nsfw content"
    
    if input_image is None:
        return None, "Please upload an image first"
    
    if not prompt or prompt.strip() == "":
        return None, "Please enter editing prompt"
    
    # 检查prompt长度是否大于3个字符
    if len(prompt.strip()) <= 3:
        return None, "❌ Editing prompt must be more than 3 characters"
    
    # 检查图片是否包含NSFW内容
    nsfw_result = None
    if nsfw_detector is not None and input_image is not None:
        try:
            # 直接使用PIL Image对象进行检测,避免文件路径问题
            nsfw_result = nsfw_detector.predict_pil_label_only(input_image)
            
            
            if nsfw_result.lower() == "nsfw":
                print(f"🔍 NSFW检测结果: ❌❌❌ {nsfw_result} - IP: {client_ip}({country_info})")
                # 检查NSFW频率限制
                is_rate_limited, wait_time = check_nsfw_rate_limit(client_ip)
                
                if is_rate_limited:
                    # 超过频率限制,显示等待提示并阻止继续
                    wait_minutes = int(wait_time / 60) + 1  # 向上取整到分钟
                    window_info = get_current_window_info(client_ip)
                    print(f"⚠️ NSFW频率限制 - IP: {client_ip}({country_info})")
                    print(f"   时间窗口: {window_info['window_start']} - {window_info['window_end']}")
                    print(f"   当前计数: {window_info['current_count']}/{NSFW_LIMIT}, 需要等待 {wait_minutes} 分钟")
                    return None, f"❌ Please wait {wait_minutes} minutes before generating again"
                else:
                    # 未超过频率限制,记录此次检测但允许继续处理
                    record_nsfw_detection(client_ip)
                    window_info = get_current_window_info(client_ip)
                    # print(f"🔍 NSFW检测记录 - IP: {client_ip}({country_info})")
                    # print(f"   时间窗口: {window_info['window_start']} - {window_info['window_end']}")
                    # print(f"   当前计数: {window_info['current_count']}/{NSFW_LIMIT}, 允许继续处理")
                    # 不return,允许继续处理图片编辑
            else:
                print(f"🔍 NSFW检测结果: ✅✅✅ {nsfw_result} - IP: {client_ip}({country_info})")
                
        except Exception as e:
            print(f"⚠️ NSFW检测失败: {e}")
            # 检测失败时允许继续处理
    
    if IP_Dict[client_ip]>10 and country_info.lower() in ["印度", "巴基斯坦"]:
        print(f"❌ Content not allowed - IP: {client_ip}({country_info}), count: {IP_Dict[client_ip]}, prompt: {prompt.strip()}")
        return None, "❌ Content not allowed. Please modify your prompt"
    # if IP_Dict[client_ip]>18 and country_info.lower() in ["中国"]:
    #     print(f"❌ Content not allowed - IP: {client_ip}({country_info}), count: {IP_Dict[client_ip]}, prompt: {prompt.strip()}")
    #     return None, "❌ Content not allowed. Please modify your prompt"
    # if client_ip.lower() in ["221.194.171.230", "101.126.56.37", "101.126.56.44"]:
    #     print(f"❌ Content not allowed - IP: {client_ip}({country_info}), count: {IP_Dict[client_ip]}, prompt: {prompt.strip()}")
    #     return None, "❌ Content not allowed. Please modify your prompt"
    

    result_url = None
    status_message = ""
    
    def progress_callback(message):
        nonlocal status_message
        status_message = message
        progress(0.5, desc=message)
    
    try:
        # 打印成功访问的信息
        print(f"✅ Processing started - IP: {client_ip}({country_info}), count: {IP_Dict[client_ip]}, prompt: {prompt.strip()}", flush=True)
        
        # Call image editing processing function
        result_url, message = process_image_edit(input_image, prompt.strip(), progress_callback)
        
        if result_url:
            print(f"✅ Processing completed successfully - IP: {client_ip}({country_info}), result_url: {result_url}", flush=True)
            progress(1.0, desc="Processing completed")
            return result_url, "✅ " + message
        else:
            print(f"❌ Processing failed - IP: {client_ip}({country_info}), error: {message}", flush=True)
            return None, "❌ " + message
            
    except Exception as e:
        return None, f"❌ Error occurred during processing: {str(e)}"

# Create Gradio interface
def create_app():
    with gr.Blocks(
        title="AI Image Editor",
        theme=gr.themes.Soft(),
        css="""
        .main-container {
            max-width: 1200px;
            margin: 0 auto;
        }
        .upload-area {
            border: 2px dashed #ccc;
            border-radius: 10px;
            padding: 20px;
            text-align: center;
        }
        .result-area {
            margin-top: 20px;
            padding: 20px;
            border-radius: 10px;
            background-color: #f8f9fa;
        }
        """
    ) as app:
        
        gr.Markdown(
            """
            # 🎨 AI Image Editor
            """,
            elem_classes=["main-container"]
        )
        
        with gr.Row():
            with gr.Column(scale=1):
                gr.Markdown("### 📸 Upload Image")
                input_image = gr.Image(
                    label="Select image to edit",
                    type="pil",
                    height=400,
                    elem_classes=["upload-area"]
                )
                
                gr.Markdown("### ✍️ Editing Instructions")
                prompt_input = gr.Textbox(
                    label="Enter editing prompt",
                    placeholder="For example: change background to beach, add rainbow, remove background, etc...",
                    lines=3,
                    max_lines=5
                )
                
                edit_button = gr.Button(
                    "🚀 Start Editing",
                    variant="primary",
                    size="lg"
                )
            
            with gr.Column(scale=1):
                gr.Markdown("### 🎯 Editing Result")
                output_image = gr.Image(
                    label="Edited image",
                    height=400,
                    elem_classes=["result-area"]
                )
                
                status_output = gr.Textbox(
                    label="Processing status",
                    lines=2,
                    max_lines=3,
                    interactive=False
                )
        
        # Example area
        gr.Markdown("### 💡 Prompt Examples")
        with gr.Row():
            example_prompts = [
                "Change the character's background to a sunny seaside with blue waves.",
                "Change the character's background to New York at night with neon lights.",
                "Change the character's background to a fairytale castle with bright colors.",
                "Change background to forest",
                "Change background to snow mountain"
            ]
            
            for prompt in example_prompts:
                gr.Button(
                    prompt,
                    size="sm"
                ).click(
                    lambda p=prompt: p,
                    outputs=prompt_input
                )
        
        # Bind button click event
        edit_button.click(
            fn=edit_image_interface,
            inputs=[input_image, prompt_input],
            outputs=[output_image, status_output],
            show_progress=True
        )
    
    return app

if __name__ == "__main__":
    app = create_app()
    app.queue()  # Enable queue to handle concurrent requests
    app.launch()