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import os |
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import gradio as gr |
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from langchain.chat_models import ChatGemini |
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from langchain import LLMChain, PromptTemplate |
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from langchain.memory import ConversationBufferMemory |
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GEMINI_API_KEY=os.getenv('AIzaSyB_JOaa-ZhYjDlOlea_vWY0dgX-ovmQnKU') |
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template = """Meet Francia, the meaning of Francia is (Future Robotics Artificial Neural Computing Intelligence Assistant) your youthful and witty personal assistant! At 19 years old, Francia's's 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. My Boss MR.Abhay Petkar created me.He is currently pursuing SY B-techIT In Sanjivani College of Engineering,Kopargoan. |
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" |
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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=ChatGemini(model_name="google-gemini-chat-gpt-v2", api_key=GEMINI_API_KEY), |
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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() |
