Update app.py

app.py

@@ -312,8 +312,8 @@ def plot_price_chart(ticker: str):
     
     predicted_price = last_known_price * (1 + predicted_return)
     
- # Plot the data
-    plt.figure(figsize=(10, 5))
+    # Plot the data
+    plt.figure(figsize=(12, 6))  # Increase figure size to give more space for annotations
     plt.plot(historical_dates, historical_prices, label='Historical Prices', marker='o')
     plt.axvline(x=last_known_date, color='gray', linestyle='--', label='Last Known Date')
     plt.plot([last_known_date, predicted_date], [last_known_price, predicted_price], 'r--', label='Predicted Price')
@@ -326,18 +326,24 @@ def plot_price_chart(ticker: str):
     plt.annotate(f'Last Known Price: {last_known_price:.2f}', 
                  xy=(last_known_date, last_known_price), 
                  xytext=(last_known_date, last_known_price * 1.05),
-                 arrowprops=dict(facecolor='black', arrowstyle='->'))
+                 arrowprops=dict(facecolor='black', arrowstyle='->'),
+                 bbox=dict(boxstyle='round,pad=0.5', edgecolor='black', facecolor='white'))
     
     plt.annotate(f'Predicted Price: {predicted_price:.2f}\nPredicted Return: {predicted_return:.2%}', 
                  xy=(predicted_date, predicted_price), 
                  xytext=(predicted_date, predicted_price * 1.05),
-                 arrowprops=dict(facecolor='red', arrowstyle='->'))
+                 arrowprops=dict(facecolor='red', arrowstyle='->'),
+                 bbox=dict(boxstyle='round,pad=0.5', edgecolor='red', facecolor='white'))
     
     plt.xlabel('Date')
     plt.ylabel('Price')
     plt.title(f'{ticker} Price Chart with Predicted Price')
     plt.legend()
     plt.grid(True)
+    
+    # Adjust limits to ensure annotations fit
+    plt.ylim(bottom=min(historical_prices) * 0.95, top=max(historical_prices) * 1.1)
+    plt.xlim(left=min(historical_dates), right=predicted_date + pd.Timedelta(days=10))
 
     # Save plot to a bytes buffer
     buf = BytesIO()