app.py

from transformers import pipeline, Conversation
import gradio as gr

chatbot = pipeline("text-generation", model="epfl-llm/meditron-7b", use_auth_token=True)


message_list = []
response_list = []

def vanilla_chatbot(message, history):
    conversation = Conversation(text=message, past_user_inputs=message_list, generated_responses=response_list)
    conversation = chatbot(conversation)

    return conversation.generated_responses[-1]

def summarizer_bot(message, history):
    return chatbot(message, min_length=5, max_length=500)[0]['summary_text']

demo_chatbot = gr.ChatInterface(vanilla_chatbot, title="Check medical chatbot", description="Enter question")

# def responseFun(message, history):
#     return history[len(history) - 1]
    
# demo_chatbot = gr.ChatInterface(responseFun, title="Test medical summarization chatbot", description="Enter text to summarize.")

demo_chatbot.launch()