Update code to use environment variables and improve error handling

app.py

@@ -1,88 +1,16 @@
-import os
-import chainlit as cl
-from agent_graph import agent_node
-from dotenv import load_dotenv  # Import dotenv
-from typing import List, Dict
 import gradio as gr
 from test_agent import process_query
 import logging
+import os
+from dotenv import load_dotenv
 
-# Load environment variables from .env file
+# Load environment variables
 load_dotenv()
 
-# Ensure your OpenAI API key is set up in environment variables
-openai_api_key = os.getenv("OPENAI_API_KEY")
-
-if not openai_api_key:
-    raise ValueError("OpenAI API key is missing in the .env file")
-
-# Store chat history
-chat_histories: Dict[str, List[Dict[str, str]]] = {}
-
 # Set up logging
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
-@cl.on_chat_start
-async def start_chat():
-    # Initialize empty chat history for this session
-    chat_histories[cl.user_session.get("id")] = []
-    
-    welcome_message = """👋 Welcome to the Stock Price Calculator!
-
-I can help you with:
-• Getting real-time stock prices
-• Calculating how many shares you can buy
-
-Try these examples:
-• Type 'AAPL' to get Apple's stock price
-• Ask 'How many MSFT shares can I buy with $10000?'
-
-What would you like to know?"""
-    
-    await cl.Message(content=welcome_message).send()
-
-@cl.on_message
-async def handle_message(message: cl.Message):
-    try:
-        # Get chat history for this session
-        session_id = cl.user_session.get("id")
-        history = chat_histories.get(session_id, [])
-        
-        # Add current message to history
-        history.append({"role": "user", "content": message.content})
-        
-        # Create state dictionary with history
-        state = {
-            "input": message.content,
-            "chat_history": history
-        }
-        
-        # Process the message with agent_node
-        response = agent_node(state)
-        
-        # Send the response back to the user
-        if isinstance(response, dict) and "output" in response:
-            # Add response to history
-            history.append({"role": "assistant", "content": response["output"]})
-            await cl.Message(content=response["output"]).send()
-        else:
-            await cl.Message(content="Received an invalid response format from the agent.").send()
-            
-        # Update history in storage
-        chat_histories[session_id] = history
-            
-    except Exception as e:
-        print(f"Error occurred: {e}")
-        await cl.Message(content="Sorry, something went wrong while processing your request.").send()
-
-@cl.on_chat_end
-async def end_chat():
-    # Clean up chat history when session ends
-    session_id = cl.user_session.get("id")
-    if session_id in chat_histories:
-        del chat_histories[session_id]
-
 def respond(message, history):
     """Process the user's message and return the response."""
     try:

requirements.txt

@@ -2,4 +2,5 @@ langchain==0.0.267
 openai==0.28.0
 python-dotenv==1.0.0
 yfinance==0.2.18
-gradio==3.50.2
+gradio==3.50.2
+requests==2.31.0