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app.py
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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() #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.
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