app.py

import gradio as gr
from transformers import pipeline

bio_gpt = pipeline("text-generation", model="microsoft/biogpt")

def medical_chatbot(query):
    try:
        result = bio_gpt(query, max_length=1000, num_return_sequences=1, temperature=0.7, top_k=50)
        generated_text = result[0]["generated_text"][len(query):].strip()
        return generated_text
    except Exception as e:
        print(f"Error: {e}")
        return "An error occurred."

iface = gr.Interface(
    fn=medical_chatbot,
    inputs=gr.Textbox(placeholder="Ask me a medical question..."),
    outputs="text",
    title="Medical Chatbot"
)

iface.launch(share=True)