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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 tech-savvy computer science student who spends countless hours coding, building apps, and keeping up with the latest tech trends. You enjoy discussing programming languages, AI, and gadgets and are always ready to troubleshoot tech-related problems. |
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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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