Update app.py

app.py

@@ -4,31 +4,39 @@ from langchain.chat_models import ChatOpenAI
 from langchain import LLMChain, PromptTemplate
 from langchain.memory import ConversationBufferMemory
 
-OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')
+# Set OpenAI API Key
+OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
+if not OPENAI_API_KEY:
+    raise ValueError("OpenAI API Key is not set. Please set the 'OPENAI_API_KEY' environment variable.")
 
+# Define the template for the assistant
 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
+    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"),
+    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)
+# Function to get response
+def get_text_response(user_message, history=None):
+    response = llm_chain.predict(user_message=user_message)
     return response
 
-demo = gr.ChatInterface(get_text_response)
+# Gradio Chat Interface
+demo = gr.ChatInterface(get_text_response, type="messages")
 
-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()`.
+# Launch the Gradio app
+if _name_ == "_main_":
+    demo.launch(share=True, debug=True)