Update app.py

app.py

@@ -11,12 +11,16 @@ def verify_api_key():
         return "ERROR: Mistral API key not found in environment variables"
     return "API key found"
 
-def fetch_nifty_data():
+def fetch_stock_data(symbol):
     try:
         end_date = datetime.now()
-        start_date = end_date - timedelta(days=15)
+        start_date = end_date - timedelta(days=30)  # Changed to 30 days
         
-        url = f"https://query1.finance.yahoo.com/v8/finance/chart/%5ENSEI?period1={int(start_date.timestamp())}&period2={int(end_date.timestamp())}&interval=1d"
+        # Add .NS suffix for NSE stocks if not present
+        if not symbol.endswith('.NS') and not symbol.startswith('^'):
+            symbol = f"{symbol}.NS"
+        
+        url = f"https://query1.finance.yahoo.com/v8/finance/chart/{symbol}?period1={int(start_date.timestamp())}&period2={int(end_date.timestamp())}&interval=1d"
         
         headers = {
             'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
@@ -45,46 +49,54 @@ def fetch_nifty_data():
         print(f"Error fetching data: {str(e)}")
         return pd.DataFrame()
 
-def get_mistral_analysis(df):
+def get_swing_trade_analysis(df, symbol):
     try:
         api_key = os.environ.get('MISTRAL_API_KEY')
         if not api_key:
             return "Error: Mistral API key not found. Please add it to the environment variables."
 
-        # Get last 10 days of data
-        last_10_days = df.tail(10)
+        # Get last 30 days of data
+        last_30_days = df.tail(30)
         
-        # Calculate current price (last close)
-        current_price = last_10_days.iloc[-1]['Close']
+        # Calculate current price and other metrics
+        current_price = last_30_days.iloc[-1]['Close']
+        avg_volume = last_30_days['Volume'].mean()
+        price_change = ((current_price - last_30_days.iloc[0]['Close']) / last_30_days.iloc[0]['Close']) * 100
         
         # Format data for prompt
-        data_str = f"""Based on the following NIFTY 50 price data for the last 10 days, provide only support levels, resistance levels, target price, and trading setup. Format exactly as shown below:
+        data_str = f"""Analyze the following stock data for {symbol} for swing trading suitability.
+Current Price: {current_price}
+30-Day Price Change: {price_change:.2f}%
+Average Daily Volume: {avg_volume:,.0f}
 
-Support Levels:
-- S1: [price] (brief reason)
-- S2: [price] (brief reason)
-- S3: [price] (brief reason)
+Please provide a comprehensive swing trading analysis in the following format:
 
-Resistance Levels:
-- R1: [price] (brief reason)
-- R2: [price] (brief reason)
-- R3: [price] (brief reason)
+Price Action Analysis:
+- Trend Analysis:
+- Key Support Levels:
+- Key Resistance Levels:
+- Volume Analysis:
 
-Today's Target Price:
-- Target ([direction]): [price] (brief reason)
+Swing Trading Suitability:
+- Overall Rating (1-10):
+- Risk Level (Low/Medium/High):
+- Suggested Position Size:
+- Recommended Holding Period:
 
-Trading Setup:
-- Direction: [Bullish/Bearish]
-- Entry Price Range: [range]
-- Stop Loss: [price]
-- Risk/Reward Ratio: [ratio]
+Trading Setup (if suitable):
+- Entry Strategy:
+- Entry Price Range:
+- Stop Loss:
+- Target Prices (multiple levels):
+- Risk/Reward Ratio:
 
-Current price: {current_price}
+Key Observations:
+- List 3-4 critical points about price action and volume patterns
 
-Data:
+Last 30 days data:
 """
-        for _, row in last_10_days.iterrows():
-            data_str += f"{row['Date']}: O:{row['Open']} H:{row['High']} L:{row['Low']} C:{row['Close']}\n"
+        for _, row in last_30_days.iterrows():
+            data_str += f"{row['Date']}: O:{row['Open']} H:{row['High']} L:{row['Low']} C:{row['Close']} V:{row['Volume']:,.0f}\n"
 
         url = "https://api.mistral.ai/v1/chat/completions"
         
@@ -96,11 +108,11 @@ Data:
         data = {
             "model": "mistral-small",
             "messages": [
-                {"role": "system", "content": "You are a price action trader. Provide only the requested levels and setup information in the exact format specified. Do not add any additional analysis or explanation."},
+                {"role": "system", "content": "You are an experienced swing trader specializing in price action analysis. Provide detailed, actionable analysis focusing on price action patterns, volume analysis, and swing trading suitability. Be specific with numbers and levels."},
                 {"role": "user", "content": data_str}
             ],
             "temperature": 0.7,
-            "max_tokens": 500
+            "max_tokens": 1000
         }
         
         response = requests.post(url, headers=headers, json=data)
@@ -113,51 +125,59 @@ Data:
     except Exception as e:
         return f"Error getting analysis: {str(e)}"
 
-def show_nifty_data_and_analysis():
+def analyze_stock(symbol):
     api_status = verify_api_key()
     if api_status.startswith("ERROR"):
         return pd.DataFrame(), api_status
     
-    df = fetch_nifty_data()
-    analysis = get_mistral_analysis(df) if not df.empty else "Unable to fetch data"
+    if not symbol:
+        return pd.DataFrame(), "Please enter a stock symbol"
+    
+    df = fetch_stock_data(symbol)
+    if df.empty:
+        return df, f"Unable to fetch data for symbol: {symbol}"
+    
+    analysis = get_swing_trade_analysis(df, symbol)
     return df, analysis
 
 # Create Gradio interface
 with gr.Blocks() as demo:
     with gr.Column():
-        gr.Markdown("# NIFTY 50 Levels and Setup")
+        gr.Markdown("# Stock Swing Trading Analysis")
+        
+        # Add input for stock symbol
+        stock_input = gr.Textbox(
+            label="Enter Stock Symbol (e.g., RELIANCE, INFY, TATAMOTORS, or ^NSEI for Nifty50)",
+            placeholder="Enter stock symbol...",
+            info="For NSE stocks, you can enter the symbol directly (e.g., RELIANCE). For indices, use ^ prefix (e.g., ^NSEI)"
+        )
         
-        # Add refresh button
-        refresh_btn = gr.Button("Refresh Data", variant="primary")
+        # Add analyze button
+        analyze_btn = gr.Button("Analyze Stock", variant="primary")
         
         # Add outputs
         with gr.Row():
             with gr.Column(scale=1):
-                gr.Markdown("### Market Data")
+                gr.Markdown("### Historical Data (Last 30 Days)")
                 output_table = gr.Dataframe(
                     headers=["Date", "Open", "High", "Low", "Close", "Volume"],
                     wrap=True
                 )
             
             with gr.Column(scale=1):
-                gr.Markdown("### Trading Levels")
+                gr.Markdown("### Swing Trading Analysis")
                 analysis_output = gr.Textbox(
-                    label="Levels and Setup",
-                    lines=15,
+                    label="Analysis Results",
+                    lines=20,
                     elem_classes="analysis"
                 )
     
-    # Set up refresh button click event
-    refresh_btn.click(
-        fn=show_nifty_data_and_analysis,
-        outputs=[output_table, analysis_output],
-    )
-    
-    # Initial load of data
-    demo.load(
-        fn=show_nifty_data_and_analysis,
+    # Set up analyze button click event
+    analyze_btn.click(
+        fn=analyze_stock,
+        inputs=[stock_input],
         outputs=[output_table, analysis_output],
     )
 
-# Launch the app
-demo.launch()
+# Launch the app with sharing enabled
+demo.launch(share=True)