Update app.py

app.py

@@ -1,45 +1,54 @@
-import yfinance as yf
 import gradio as gr
+from langchain_groq import ChatGroq
+import yfinance as yf
 
-# Function to fetch and return data for a given ticker symbol
-def fetch_stock_data(ticker_symbol):
-    try:
-        # Create a Ticker object
-        ticker = yf.Ticker(ticker_symbol)
-
-        # Fetch historical market data
-        historical_data = ticker.history(period="1y")  # data for the last year
-
-        # Fetch basic financials
-        financials = ticker.financials
-
-        # Fetch stock actions like dividends and splits
-        actions = ticker.actions
+# Initialize the ChatGroq model
+llm = ChatGroq(model_name="Llama3-8b-8192", api_key=groq_api_key)
 
-        return historical_data, financials, actions
-    except Exception as e:
-        return f"Error: {e}", None, None
+def fetch_stock_data(company_name):
+    # Fetch stock data using Yahoo Finance
+    ticker = yf.Ticker(company_name)
+    stock_info = ticker.info
+    
+    # Extract relevant information
+    stock_data = {
+        "Company": stock_info.get("longName", "N/A"),
+        "Current Price": stock_info.get("currentPrice", "N/A"),
+        "Market Cap": stock_info.get("marketCap", "N/A"),
+        "PE Ratio": stock_info.get("trailingPE", "N/A"),
+        "Dividend Yield": stock_info.get("dividendYield", "N/A"),
+        "52 Week High": stock_info.get("fiftyTwoWeekHigh", "N/A"),
+        "52 Week Low": stock_info.get("fiftyTwoWeekLow", "N/A"),
+        "Sector": stock_info.get("sector", "N/A"),
+        "Industry": stock_info.get("industry", "N/A")
+    }
+    
+    return stock_data
 
-# Gradio interface
-def create_gradio_interface():
-    # Define the input and output for Gradio
-    ticker_input = gr.Textbox(label="Enter Ticker Symbol")
-    historical_output = gr.Dataframe(label="Historical Data (1 Year)")
-    financials_output = gr.Dataframe(label="Financials")
-    actions_output = gr.Dataframe(label="Stock Actions")
+def respond_to_query(query):
+    # Use the LLM to process the query and fetch relevant data
+    response = llm.invoke(query)
+    return response
 
-    # Define the Gradio interface with explicit submit button
-    interface = gr.Interface(
-        fn=fetch_stock_data,
-        inputs=ticker_input,
-        outputs=[historical_output, financials_output, actions_output],
-        live=False,  # Disable live updates to avoid the interface from triggering automatically
-        title="Stock Data Fetcher",
-        description="Enter a ticker symbol and click 'Submit' to fetch historical data, financials, and stock actions."
-    )
+def main(company_name):
+    # Fetch stock data and generate a response
+    stock_data = fetch_stock_data(company_name)
     
-    # Launch the interface
-    interface.launch()
-
-# Run the Gradio interface
-create_gradio_interface()
+    # Prepare a response string
+    response = f"Here is the data for {company_name}:\n"
+    for key, value in stock_data.items():
+        response += f"{key}: {value}\n"
+        
+    return response
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=main,
+    inputs="text",
+    outputs="text",
+    title="Stock Price Data Fetcher",
+    description="Enter the company name or ticker symbol to get the latest stock price data."
+)
+
+if __name__ == "__main__":
+    iface.launch()