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Implement medical consultation app with LangChain memory management and model integration
031a3f5
import gradio as gr | |
from .handlers import respond, reset_chat | |
def build_interface(): | |
with gr.Blocks(theme="soft") as demo: | |
gr.Markdown("# π₯ Complete Medical Assistant - Me-LLaMA 13B with Memory") | |
gr.Markdown("Comprehensive medical consultation powered by Me-LLaMA 13B with LangChain memory management. One model handles both consultation and medicine suggestions with full context awareness.") | |
with gr.Row(): | |
with gr.Column(scale=4): | |
chatbot = gr.Chatbot(height=500) | |
msg = gr.Textbox( | |
placeholder="Tell me about your symptoms or health concerns...", | |
label="Your Message" | |
) | |
with gr.Column(scale=1): | |
reset_btn = gr.Button("π Start New Consultation", variant="secondary") | |
gr.Markdown("**Memory Features:**\n- Tracks symptoms & timeline\n- Remembers medications & allergies\n- Maintains conversation context\n- Provides comprehensive summaries") | |
gr.Examples( | |
examples=[ | |
"I have a persistent cough and sore throat for 3 days", | |
"I've been having severe headaches and feel dizzy", | |
"My stomach hurts and I feel nauseous after eating" | |
], | |
inputs=msg | |
) | |
msg.submit(respond, [msg, chatbot], [msg, chatbot]) | |
reset_btn.click(reset_chat, [], [chatbot, msg]) | |
return demo |