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