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import os |
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import gradio as gr |
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from langchain.chat_models import ChatOpenAI |
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from langchain import LLMChain, PromptTemplate |
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from langchain.memory import ConversationBufferMemory |
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OPENAI_API_KEY=os.getenv('OPENAI_API_KEY') |
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template = """You are a helpful assistant to answer all user queries. |
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{chat_history} |
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User: {user_message} |
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Chatbot:""" |
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prompt = PromptTemplate( |
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input_variables=["chat_history", "user_message"], template=template |
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) |
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memory = ConversationBufferMemory(memory_key="chat_history") |
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llm_chain = LLMChain( |
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llm=ChatOpenAI(temperature='0.5', model_name="gpt-3.5-turbo"), |
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prompt=prompt, |
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verbose=True, |
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memory=memory, |
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) |
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def get_text_response(user_message,history): |
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response = llm_chain.predict(user_message = user_message) |
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return response |
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demo = gr.ChatInterface(get_text_response) |
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if __name__ == "__main__": |
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demo.launch() |
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