Update utils.py

utils.py

@@ -136,7 +136,22 @@ def get_fundamental_data(stock):
     try:
         info = stock.info
         history = stock.history(period="1d")
-        fundamental_info = {'name': info.get('longName', 'N/A'), 'current_price': history['Close'].iloc[-1] if not history.empty else 0, 'market_cap': info.get('marketCap', 0), 'pe_ratio': info.get('forwardPE', 0), 'dividend_yield': info.get('dividendYield', 0) * 100 if info.get('dividendYield') else 0, 'volume': history['Volume'].iloc[-1] if not history.empty else 0, 'info': f"Sector: {info.get('sector', 'N/A')}\nIndustry: {info.get('industry', 'N/A')}\nMarket Cap: {info.get('marketCap', 0)}\n52 Week High: {info.get('fiftyTwoWeekHigh', 'N/A')}\n52 Week Low: {info.get('fiftyTwoWeekLow', 'N/A')}\nBeta: {info.get('beta', 'N/A')}\nEPS: {info.get('forwardEps', 'N/A')}\nBook Value: {info.get('bookValue', 'N/A')}\nPrice to Book: {info.get('priceToBook', 'N/A')}"}
+        
+        raw_price = history['Close'].iloc[-1] if not history.empty else 0
+        raw_market_cap = info.get('marketCap', 0)
+        raw_pe = info.get('forwardPE', 0)
+        raw_div_yield = info.get('dividendYield', 0) * 100 if info.get('dividendYield') else 0
+        raw_volume = history['Volume'].iloc[-1] if not history.empty else 0
+
+        fundamental_info = {
+            'name': info.get('longName', 'N/A'), 
+            'current_price': float(raw_price), 
+            'market_cap': int(raw_market_cap), 
+            'pe_ratio': float(raw_pe), 
+            'dividend_yield': float(raw_div_yield), 
+            'volume': int(raw_volume), 
+            'info': f"Sector: {info.get('sector', 'N/A')}\nIndustry: {info.get('industry', 'N/A')}\nMarket Cap: {int(raw_market_cap):,}\n52 Week High: {info.get('fiftyTwoWeekHigh', 'N/A')}\n52 Week Low: {info.get('fiftyTwoWeekLow', 'N/A')}\nBeta: {info.get('beta', 'N/A')}\nEPS: {info.get('forwardEps', 'N/A')}\nBook Value: {info.get('bookValue', 'N/A')}\nPrice to Book: {info.get('priceToBook', 'N/A')}"
+        }
         return fundamental_info
     except:
         return {'name': 'N/A', 'current_price': 0, 'market_cap': 0, 'pe_ratio': 0, 'dividend_yield': 0, 'volume': 0, 'info': 'Unable to fetch fundamental data'}
@@ -160,7 +175,6 @@ def predict_prices(data, model=None, tokenizer=None, prediction_days=30):
         from chronos import BaseChronosPipeline
         pipeline = BaseChronosPipeline.from_pretrained("amazon/chronos-bolt-base", device_map="auto")
         with torch.no_grad():
-            # Fix: Use context_tensor instead of context
             forecast = pipeline.predict(context_tensor=torch.tensor(prices), prediction_length=prediction_days)
         forecast_np = forecast.squeeze().cpu().numpy() if isinstance(forecast, torch.Tensor) else np.array(forecast)
         if forecast_np.ndim > 1:
@@ -215,4 +229,5 @@ def create_technical_chart(data, indicators):
     fig.add_hline(y=70, line_dash="dash", line_color="red", row=2, col=2)
     fig.add_hline(y=30, line_dash="dash", line_color="green", row=2, col=2)
     fig.update_layout(title='Technical Indicators Overview', height=800, showlegend=False, hovermode='x unified')
-    return fig
+    return fig
+