import gradio as gr
from medical_chatbot import ColabBioGPTChatbot

# Instantiate and auto-load the medical data
chatbot = ColabBioGPTChatbot(use_gpu=True, use_8bit=True)

medical_file_uploaded = False

try:
    chatbot.load_medical_data("Pediatric_cleaned.txt")
    medical_file_uploaded = True
    startup_status = "✅ Medical file 'Pediatric_cleaned.txt' loaded at startup. Ready to chat!"
except Exception as e:
    startup_status = f"❌ Failed to load 'Pediatric_cleaned.txt': {str(e)}"

def generate_response(user_input):
    if not medical_file_uploaded:
        return "⚠️ Medical data failed to load. Please check the file and restart the app."
    return chatbot.chat(user_input)

with gr.Blocks() as demo:
    gr.Markdown("## 🩺 Pediatric Medical Assistant")
    gr.Markdown(startup_status)

    chatbot_ui = gr.Chatbot(label="🧠 Chat History")
    user_input = gr.Textbox(placeholder="Ask a pediatric health question...", lines=2, show_label=False)
    submit_btn = gr.Button("Send")

    def on_submit(user_message, chat_history):
        bot_response = generate_response(user_message)
        chat_history.append((user_message, bot_response))
        return "", chat_history

    user_input.submit(fn=on_submit, inputs=[user_input, chatbot_ui], outputs=[user_input, chatbot_ui])
    submit_btn.click(fn=on_submit, inputs=[user_input, chatbot_ui], outputs=[user_input, chatbot_ui])

demo.launch(share=True)