Update app.py

app.py

@@ -1,34 +1,46 @@
 import os
 import gradio as gr
-from langchain.chat_models import ChatOpenAI
-from langchain import LLMChain, PromptTemplate
+from langchain_openai import ChatOpenAI
+from langchain.chains import LLMChain
+from langchain.prompts import PromptTemplate
 from langchain.memory import ConversationBufferMemory
 
-OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')
+# Retrieve and validate OpenAI API key
+OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
+if not OPENAI_API_KEY:
+    raise ValueError("OPENAI_API_KEY environment variable is not set.")
 
+# Define the prompt template
 template = """Meet Riya, your youthful and witty personal assistant! At 21 years old, she's full of energy and always eager to help. Riya'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.
 {chat_history}
 User: {user_message}
-Chatbot:"""
+Chatbot: """
 
 prompt = PromptTemplate(
-    input_variables=["chat_history", "user_message"], template=template
+    input_variables=["chat_history", "user_message"], 
+    template=template
 )
 
+# Initialize memory and LLM chain
 memory = ConversationBufferMemory(memory_key="chat_history")
-
 llm_chain = LLMChain(
-    llm=ChatOpenAI(temperature='0.5', model_name="gpt-3.5-turbo"),
+    llm=ChatOpenAI(
+        openai_api_key=OPENAI_API_KEY,
+        temperature=0.5,
+        model_name="gpt-3.5-turbo"
+    ),
     prompt=prompt,
-    verbose=True,
+    verbose=False,  # Set to False for cleaner output
     memory=memory,
 )
 
-def get_text_response(user_message,history):
-    response = llm_chain.predict(user_message = user_message)
+# Define the response function for Gradio
+def get_text_response(user_message, history):
+    response = llm_chain.predict(user_message=user_message)
     return response
 
+# Create and launch Gradio interface
 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()`.
+    demo.launch()  # Add server_name="0.0.0.0" or share=True for specific use cases #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.