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import os
import gradio as gr
from langchain.chat_models import ChatOpenAI
from langchain import LLMChain, PromptTemplate
from langchain.memory import ConversationBufferMemory
OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')
template = """You are a helpful assistant to answer all user queries.
{chat_history}
User: {user_message}
Chatbot:"""
prompt = PromptTemplate(
input_variables=["chat_history", "user_message"], template=template
)
memory = ConversationBufferMemory(memory_key="chat_history")
llm_chain = LLMChain(
llm=ChatOpenAI(temperature='0.5', model_name="gpt-3.5-turbo"),
prompt=prompt,
verbose=True,
memory=memory,
)
def get_text_response(user_message,history):
response = llm_chain.predict(user_message = user_message)
return response
demo = gr.ChatInterface(get_text_response)
if __name__ == "__main__":
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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