| | from transformers import pipeline, Conversation |
| | import gradio as gr |
| | import time |
| |
|
| | chatbot = pipeline("text-generation", model="epfl-llm/meditron-7b", use_auth_token=True) |
| | |
| |
|
| | message_list = [] |
| | response_list = [] |
| |
|
| | print("START") |
| | def vanilla_chatbot(message, history): |
| | start = time.perf_counter() |
| | print("start chat") |
| | conversation = Conversation(text=message, past_user_inputs=message_list, generated_responses=response_list) |
| | conversation = chatbot(conversation) |
| | to_return = conversation.generated_responses[-1] |
| | |
| | print ("Answer in %5.1f secs " % (time.perf_counter() - start)) |
| | return to_return |
| |
|
| | def chat_bot(message, history): |
| | start = time.perf_counter() |
| | print("start chat") |
| | to_return = chatbot(message, max_length=500)[0]['generated_text'] |
| |
|
| | print ("Answer in %5.1f secs " % (time.perf_counter() - start)) |
| | return to_return |
| |
|
| | demo_chatbot = gr.ChatInterface(chat_bot, title="Check medical chatbot", description="Enter question") |
| |
|
| | demo_chatbot.launch() |
