File size: 7,776 Bytes
92feab2
 
 
 
 
a0e37e2
92feab2
a0e37e2
 
92feab2
a0e37e2
 
 
 
 
92feab2
c751e97
 
 
 
 
92feab2
 
 
 
 
 
 
 
 
 
c751e97
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a0e37e2
 
 
 
 
 
 
 
 
 
 
22b6a7a
a0e37e2
 
 
 
 
 
 
 
 
92feab2
 
 
a0e37e2
 
92feab2
 
 
 
 
 
a0e37e2
 
92feab2
 
 
 
a0e37e2
d738003
e867f4c
 
 
d738003
e867f4c
 
 
 
 
 
 
 
 
 
 
 
92feab2
 
 
f86d7f2
 
92feab2
a0e37e2
 
 
 
c751e97
a0e37e2
 
92feab2
 
a0e37e2
 
 
 
 
 
92feab2
 
 
 
a0e37e2
92feab2
a0e37e2
92feab2
 
a0e37e2
92feab2
 
 
 
 
c751e97
 
cc80c3d
 
92feab2
 
 
 
 
 
 
 
a0e37e2
 
92feab2
 
c751e97
92feab2
 
 
c751e97
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a0e37e2
c751e97
 
a0e37e2
 
 
 
 
 
 
c751e97
92feab2
a0e37e2
d738003
c751e97
a0e37e2
d738003
a0e37e2
 
92feab2
a0e37e2
 
 
 
 
190ec72
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
from typing import List, Tuple, Dict, TypedDict, Optional, Any
import os

import gradio as gr

from langchain_core.language_models.llms import LLM
from langchain_openai.chat_models import ChatOpenAI
from langchain_aws import ChatBedrock
import boto3

from ask_candid.base.config.rest import OPENAI
from ask_candid.base.config.models import Name2Endpoint
from ask_candid.base.config.data import ALL_INDICES
from ask_candid.utils import format_chat_ag_response
from ask_candid.chat import run_chat

try:
    from feedback import FeedbackApi
except ImportError:
    from demos.feedback import FeedbackApi

ROOT = os.path.dirname(os.path.abspath(__file__))

class LoggedComponents(TypedDict):
    context: List[gr.components.Component]
    found_helpful: gr.components.Component
    will_recommend: gr.components.Component
    comments: gr.components.Component
    email: gr.components.Component


def send_feedback(
    chat_context,
    found_helpful,
    will_recommend,
    comments,
    email
):
    api = FeedbackApi()
    total_submissions = 0

    try:
        response = api(
            context=chat_context,
            found_helpful=found_helpful,
            will_recommend=will_recommend,
            comments=comments,
            email=email
        )
        total_submissions = response.get("response", 0)
        gr.Info("Thank you for submitting feedback")
    except Exception as ex:
        raise gr.Error(f"Error submitting feedback: {ex}")
    return total_submissions


def select_foundation_model(model_name: str, max_new_tokens: int) -> LLM:
    if model_name == "gpt-4o":
        llm = ChatOpenAI(
            model_name=Name2Endpoint[model_name],
            max_tokens=max_new_tokens,
            api_key=OPENAI["key"],
            temperature=0.0,
            streaming=True,
        )
    elif model_name in {"claude-3.5-haiku", "llama-3.1-70b-instruct", "mistral-large", "mixtral-8x7B"}:
        llm = ChatBedrock(
            client=boto3.client("bedrock-runtime", region_name="us-east-1"),
            model=Name2Endpoint[model_name],
            max_tokens=max_new_tokens,
            temperature=0.0
        )
    else:
        raise gr.Error(f"Base model `{model_name}` is not supported")
    return llm


def execute(
    thread_id: str,
    user_input: Dict[str, Any],
    history: List[Dict],
    model_name: str,
    max_new_tokens: int,
    indices: Optional[List[str]] = None,
):
    return run_chat(
        thread_id=thread_id,
        user_input=user_input,
        history=history,
        llm=select_foundation_model(model_name=model_name, max_new_tokens=max_new_tokens),
        indices=indices
    )


def build_rag_chat() -> Tuple[LoggedComponents, gr.Blocks]:
    with gr.Blocks(theme=gr.themes.Soft(), title="Candid's AI assistant") as demo:

        gr.Markdown(
            """
            <h1>Candid's AI assistant</h1>

            <p>
                Please read the <a
                    href='https://info.candid.org/chatbot-reference-guide'
                    target="_blank"
                    rel="noopener noreferrer"
                >guide</a> to get started.
            </p>
            <hr>
            """
        )

        with gr.Accordion(label="Advanced settings", open=False):
            es_indices = gr.CheckboxGroup(
                choices=list(ALL_INDICES),
                # value=[idx for idx in ALL_INDICES if "news" not in idx],
                value=list(ALL_INDICES),
                label="Sources to include",
                interactive=True,
            )
            llmname = gr.Radio(
                label="Language model",
                value="claude-3.5-haiku",
                choices=list(Name2Endpoint.keys()),
                interactive=True,
            )
            max_new_tokens = gr.Slider(
                value=256 * 3,
                minimum=128,
                maximum=2048,
                step=128,
                label="Max new tokens",
                interactive=True,
            )

        with gr.Column():
            chatbot = gr.Chatbot(
                label="AskCandid",
                elem_id="chatbot",
                bubble_full_width=True,
                avatar_images=(
                    None,
                    os.path.join(ROOT, "static", "candid_logo_yellow.png"),
                ),
                height="45vh",
                type="messages",
                show_label=False,
                show_copy_button=True,
                show_share_button=None,
                show_copy_all_button=False,
                autoscroll=True,
                layout="panel",
            )
            msg = gr.MultimodalTextbox(label="Your message", interactive=True)
            thread_id = gr.Text(visible=False, value="", label="thread_id")
            gr.ClearButton(components=[msg, chatbot, thread_id], size="sm")

        # pylint: disable=no-member
        chat_msg = msg.submit(
            fn=execute,
            inputs=[thread_id, msg, chatbot, llmname, max_new_tokens, es_indices],
            outputs=[msg, chatbot, thread_id],
        )
        chat_msg.then(format_chat_ag_response, chatbot, chatbot, api_name="bot_response")
        logged = LoggedComponents(context=chatbot)
    return logged, demo


def build_feedback(components: LoggedComponents) -> gr.Blocks:
    with gr.Blocks(theme=gr.themes.Soft(), title="Candid AI demo") as demo:
        gr.Markdown("<h1>Help us improve this tool with your valuable feedback</h1>")

        with gr.Row():
            with gr.Column():
                found_helpful = gr.Radio(
                    [True, False], label="Did you find what you were looking for?"
                )
                will_recommend = gr.Radio(
                    [True, False],
                    label="Will you recommend this Chatbot to others?",
                )
                comment = gr.Textbox(label="Additional comments (optional)", lines=4)
                email = gr.Textbox(label="Your email (optional)", lines=1)
                submit = gr.Button("Submit Feedback")

                components["found_helpful"] = found_helpful
                components["will_recommend"] = will_recommend
                components["comments"] = comment
                components["email"] = email

                # pylint: disable=no-member
                submit.click(
                    fn=send_feedback,
                    inputs=[
                        components["context"],
                        components["found_helpful"],
                        components["will_recommend"],
                        components["comments"],
                        components["email"]
                    ],
                    outputs=None,
                    show_api=False,
                    api_name=False,
                    preprocess=False,
                )

    return demo


def build_app():
    logger, candid_chat = build_rag_chat()
    feedback = build_feedback(logger)

    with open(os.path.join(ROOT, "static", "chatStyle.css"), "r", encoding="utf8") as f:
        css_chat = f.read()

    demo = gr.TabbedInterface(
        interface_list=[
            candid_chat,
            feedback
        ],
        tab_names=[
            "Candid's AI assistant",
            "Feedback"
        ],
        title="Candid's AI assistant",
        theme=gr.themes.Soft(),
        css=css_chat,
    )
    return demo


if __name__ == "__main__":
    app = build_app()
    app.queue(max_size=5).launch(
        show_api=False,
        auth=[
            (os.getenv("APP_USERNAME"), os.getenv("APP_PASSWORD")),
            (os.getenv("APP_PUBLIC_USERNAME"), os.getenv("APP_PUBLIC_PASSWORD")),
        ],
        auth_message="Login to Candid's AI assistant",
        ssr_mode=False
    )