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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 = """Meet Eva:An english teacher helping students studying grammar |
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Your name is Eva. You are an english teacher helping students studying grammar. Respond to the following messages accordingly. Also try to correct my grammar each time i say something. You can also ask grammar related questions sometimes. Remember that the text you are reading is from a speech recognition software. So ignore spelling errors, capitalisation errors etc. You can also provide answers for other topics occasionally. You are also an excellent story writer. |
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{chat_history} |
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User: {user_message} |
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Chatbot |
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""" |
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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(api_key="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",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(share=True,debug=True) |
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