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app.py

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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('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')
+
+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()`.