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Update app.py
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app.py
CHANGED
@@ -641,49 +641,51 @@ class AdaptiveMedicalBot:
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logger.error(f"Error updating learning system: {e}")
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def create_demo():
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"""Create Gradio interface with proper
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try:
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bot = AdaptiveMedicalBot()
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def chat(message, history,
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try:
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#
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if
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last_interaction[1],
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1 if feedback == "π" else -1
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)
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# Generate response using the correct method
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response_data = bot.generate_adaptive_response(message, history)
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response = response_data['response']
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#
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history
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return
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except Exception as e:
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logger.error(f"Chat error: {e}")
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return
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# Create Gradio interface with proper
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gr.State([]), # For chat history (input)
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gr.Radio(choices=["π", "π"], label="Was this response helpful?", visible=True, value=None)
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],
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outputs=[
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gr.Chatbot(label="GP Medical Triage Assistant", height=500, type='messages'),
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gr.State([]) # For chat history (output)
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],
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title="GP Medical Triage Assistant - Pearly",
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description="""
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π Hello! I'm Pearly, your GP medical assistant.
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I can help you with:
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@@ -696,14 +698,75 @@ def create_demo():
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For urgent concerns, call 111.
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Please describe your concerns below.
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"""
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["I'm
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return demo
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logger.error(f"Error updating learning system: {e}")
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def create_demo():
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"""Create Gradio interface with proper message formatting"""
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try:
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bot = AdaptiveMedicalBot()
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def chat(message: str, history: List[Dict[str, str]]):
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try:
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# Convert history to the format expected by the bot
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bot_history = [(h["user"], h["bot"]) for h in history] if history else []
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# Generate response
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response_data = bot.generate_adaptive_response(message, bot_history)
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response = response_data['response']
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# Format response for Gradio chat
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history.append({"role": "user", "content": message})
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history.append({"role": "assistant", "content": response})
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return history
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except Exception as e:
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logger.error(f"Chat error: {e}")
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return history + [
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{"role": "user", "content": message},
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{"role": "assistant", "content": "I apologize, but I'm experiencing technical difficulties. For emergencies, please call 999."}
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]
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def process_feedback(feedback: str, history: List[Dict[str, str]]):
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"""Process feedback when received"""
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try:
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if history and len(history) >= 2:
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last_user_msg = history[-2]["content"]
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last_bot_msg = history[-1]["content"]
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bot.update_from_feedback(
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last_user_msg,
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last_bot_msg,
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1 if feedback == "π" else -1
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)
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except Exception as e:
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logger.error(f"Error processing feedback: {e}")
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# Create Gradio interface with proper message handling
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with gr.Blocks(theme="soft") as demo:
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gr.Markdown("""
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# GP Medical Triage Assistant - Pearly
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π Hello! I'm Pearly, your GP medical assistant.
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I can help you with:
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For urgent concerns, call 111.
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Please describe your concerns below.
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""")
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# Initialize chat components
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chatbot = gr.Chatbot(
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value=[{"role": "assistant", "content": "Hello! I'm Pearly, your GP medical assistant. How can I help you today?"}],
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height=500,
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type="messages"
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)
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msg = gr.Textbox(
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label="Your message",
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placeholder="Type your message here...",
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lines=2
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)
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with gr.Row():
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submit = gr.Button("Submit")
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clear = gr.Button("Clear")
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feedback = gr.Radio(
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choices=["π", "π"],
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label="Was this response helpful?",
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visible=True
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)
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# Set up event handlers
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submit.click(
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chat,
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inputs=[msg, chatbot],
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outputs=[chatbot],
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queue=False
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).then(
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lambda: "",
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None,
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msg # Clear input box after sending
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)
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msg.submit(
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chat,
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inputs=[msg, chatbot],
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outputs=[chatbot],
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queue=False
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).then(
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lambda: "",
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None,
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msg # Clear input box after sending
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)
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clear.click(
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lambda: [[], ""],
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None,
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[chatbot, msg],
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queue=False
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)
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feedback.change(
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process_feedback,
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inputs=[feedback, chatbot],
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outputs=[],
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queue=False
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)
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# Add example messages
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gr.Examples(
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examples=[
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"I've been having headaches recently",
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"I need to book a routine checkup",
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"I'm feeling very anxious lately"
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],
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inputs=msg
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)
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return demo
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