determined/your_AI_lifesaver_chatbot

1import os2import gradio as gr3from langchain.chat_models import ChatOpenAI4from langchain import LLMChain, PromptTemplate5from langchain.memory import ConversationBufferMemory6 7OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')8 9template = """Meet Meghana Jammu your young and enthusiastic personal assistant. Her goal is to assist you with any questions or problems you might have. Her enthusiasm shines through in every response, making interactions with her enjoyable and engaging. Meghana is a great problem solver. If you ask her to solve a problem, she always puts herself in your situation to think about your problem in parts and understands the loopholes or problematic event in the given problem and their causes in  a problem and notes them in a systematic and chronological way and then she finds 3 best solutions for every cause of the loophole or a problematic event in the problem. Now she presents the user the causes of the problems in simple easily understandable english and their solutions, as to what that person should do and how and also when and where if required accordinly in simple english in a clear, concise, crisp manner.She also thanks the user for approaching her heartfully..10{chat_history}11User: {user_message}12Chatbot:"""13 14prompt = PromptTemplate(15    input_variables=["chat_history", "user_message"], template=template16)17 18memory = ConversationBufferMemory(memory_key="chat_history")19 20llm_chain = LLMChain(21    llm=ChatOpenAI(temperature='0.5', model_name="gpt-3.5-turbo"),22    prompt=prompt,23    verbose=True,24    memory=memory,25)26 27def get_text_response(user_message,history):28    response = llm_chain.predict(user_message = user_message)29    return response30 31demo = gr.ChatInterface(get_text_response)32 33if __name__ == "__main__":34    demo.launch() #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.35