Update app.py

app.py

@@ -9,41 +9,49 @@ from Gradio_UI import GradioUI
 
 #S&P500 Sentiment StoryTeller
 @tool
-def market_sentiment_story(index:str)-> str: #it's import to specify the return type
-    #Keep this format for the description / args / args description but feel free to modify the tool
-    """A tool that fetches the current price of the a stock exchanges and based on whether the price is up or down generate a short story or explanation for why that might be — even if speculative.
+def market_sentiment_story(index: str) -> str:
+    """Fetches market index data from Financial Modeling Prep and returns a story prompt.
+    
     Args:
-        index: A string representing one of the 3 major exchanges (e.g,'sp500','dowjones', or 'nasdaq')
+        index: One of 'sp500', 'dowjones', or 'nasdaq'.
     """
+    index = index.lower()
+
+    # Mapping user input to FMP-compatible symbols
+    symbols = {
+        "sp500": "^GSPC",
+        "dowjones": "^DJI",
+        "nasdaq": "^IXIC"
+    }
+
+    if index not in symbols:
+        return "Please choose one of: 'sp500', 'dowjones', or 'nasdaq'."
+
+    symbol = symbols[index]
+
     try:
-        # Map user input to Yahoo Finance symbols (I probably can make another function down the line)
-        ticker = {
-            "sp500": "^GSPC",
-            "dowjones": "^DJI",
-            "nasdaq": "^IXIC"
-        }
-        #Get the correct symbol for the requested index
-        ticker = symbols.get(index.lower())
-
-        # 3. Fetch data from Yahoo Finance
-        url = f"https://query1.finance.yahoo.com/v8/finance/chart/{symbol}"
-        data = requests.get(url).json()
-        
-        # 4. Extract current and previous prices
-        result = data["chart"]["result"][0]["meta"]
-        current = result["regularMarketPrice"]
-        previous = result["chartPreviousClose"]
-        change = current - previous
-        percent = (change / previous) * 100
-
-        # 5. Return a prompt for the LLM to generate a story
+        # Use demo API key from FMP
+        url = f"https://financialmodelingprep.com/api/v3/quote/{symbol}?apikey=demo"
+        response = requests.get(url)
+        data = response.json()
+
+        if not data or not isinstance(data, list):
+            return "Could not retrieve market data at the moment."
+
+        price_info = data[0]
+        name = price_info.get("name", index.upper())
+        current_price = price_info["price"]
+        change_percent = price_info["changesPercentage"]
+
+        # Return a prompt for the LLM to expand into a story
         return (
-            f"The {index.upper()} is currently at {current:.2f}, "
-            f"which is a change of {percent:.2f}% from the previous close. "
-            f"Write a short, realistic story that explains why it moved in this direction."
+            f"{name} is currently at {current_price:.2f}, "
+            f"which is a change of {change_percent:.2f}% today. "
+            f"Write a short, realistic story explaining this market movement."
         )
+
     except Exception as e:
-        return f"Error: {str(e)}"
+        return f"Error fetching data: {str(e)}"
 
 
 @tool