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| import uuid | |
| from typing import List | |
| import gradio as gr | |
| from src.logger import log_feedback | |
| def respond( | |
| message: str, history: List, session_id: str, intent_classifier, retriever | |
| ): | |
| """ | |
| Gradio's main response function | |
| Args: | |
| message: User's message | |
| history: Chat history | |
| session_id: Session identifier | |
| intent_classifier: IntentClassifier instance | |
| retriever: Vector store retriever instance | |
| Returns: | |
| Tuple of (empty string for input box, updated history) | |
| """ | |
| # Import here to avoid circular imports | |
| from app import get_context_and_answer | |
| if not session_id: | |
| session_id = str(uuid.uuid4()) | |
| bot_response = get_context_and_answer( | |
| message, history, session_id, intent_classifier, retriever | |
| ) | |
| history.append([message, bot_response]) | |
| return "", history | |
| def create_interface(intent_classifier, retriever): | |
| """ | |
| Create Gradio interface | |
| Args: | |
| intent_classifier: IntentClassifier instance | |
| retriever: Vector store retriever instance | |
| Returns: | |
| Gradio Blocks interface | |
| """ | |
| with gr.Blocks(theme=gr.themes.Soft()) as demo: | |
| gr.Markdown(""" | |
| # ASKXENO | |
| **Welcome to XENO AI Support!** | |
| I can help you with questions about XENO financial services including: | |
| - Account management and setup | |
| - Transaction processes and fees | |
| - Platform features and troubleshooting | |
| - General service information | |
| *Simply type your question below to get started!* | |
| """) | |
| # Hidden state for session | |
| session_id_box = gr.Textbox( | |
| label="Session ID", value=str(uuid.uuid4()), visible=False | |
| ) | |
| chatbot = gr.Chatbot( | |
| label="XENO Assistant", bubble_full_width=False, height=450 | |
| ) | |
| with gr.Row(): | |
| msg = gr.Textbox( | |
| label="Your Message", | |
| placeholder="Type your question here...", | |
| scale=4, | |
| ) | |
| send_button = gr.Button("Send", variant="primary", scale=1) | |
| # ===== FEEDBACK SECTION ===== | |
| with gr.Row(): | |
| with gr.Accordion("Rate this response / Flag Issue", open=False): | |
| with gr.Row(): | |
| thumbs_up = gr.Button("👍 Good Answer") | |
| thumbs_down = gr.Button("👎 Bad / Flag") | |
| feedback_reason = gr.Textbox( | |
| label="Reason ", placeholder="E.g., Incorrect fees, hallucination," | |
| ) | |
| feedback_status = gr.Label(value="", label="Status", show_label=False) | |
| # Feedback Event Listeners | |
| # Logic: If Thumbs Up is clicked, send 'Positive'. If Textbox is empty, reason defaults to "Good". | |
| thumbs_up.click( | |
| fn=lambda h, s, r: log_feedback("Positive", r if r else "Good", h, s), | |
| inputs=[chatbot, session_id_box, feedback_reason], | |
| outputs=[feedback_status], | |
| ) | |
| # Logic: If Thumbs Down is clicked, send 'Negative' with the content of the textbox. | |
| thumbs_down.click( | |
| fn=lambda r, h, s: log_feedback("Negative", r, h, s), | |
| inputs=[feedback_reason, chatbot, session_id_box], | |
| outputs=[feedback_status], | |
| ) | |
| # ============================= | |
| # Chat Event Listeners - Pass components to respond function | |
| send_button.click( | |
| lambda msg, chat, sid: respond(msg, chat, sid, intent_classifier, retriever), | |
| [msg, chatbot, session_id_box], | |
| [msg, chatbot], | |
| ) | |
| msg.submit( | |
| lambda msg, chat, sid: respond(msg, chat, sid, intent_classifier, retriever), | |
| [msg, chatbot, session_id_box], | |
| [msg, chatbot], | |
| ) | |
| return demo | |