Update app.py

app.py

@@ -20,13 +20,26 @@ def train_predict_wrapper(ticker, start_date, end_date, prediction_days):
     # Download stock data
     data = yf.download(ticker, start=start_date, end=end_date)
     data = data["Close"]
-    
+
+    # Convert dates to a numerical format (days since start date)
+    start_date = pd.to_datetime(start_date)
+    days_since_start = (data.index - start_date).days
+
     # Train linear regression model
-    X = data.index.values[:-prediction_days].reshape(-1, 1)
+    X = days_since_start.values[:-prediction_days].reshape(-1, 1)
     y = data.values[:-prediction_days]
     model = LinearRegression()
     model.fit(X, y)
 
+    # Prepare data for prediction
+    last_date = data.index[-1]
+    future_dates = pd.date_range(start=last_date, periods=prediction_days + 1, closed='right')
+    future_days_since_start = (future_dates - start_date).days
+    X_future = future_days_since_start.values.reshape(-1, 1)
+
+    # Predict future prices
+    predicted_prices = model.predict(X_future)
+
     # Predict future prices
     future_dates = data.index.values[-prediction_days:]
     X_future = future_dates.reshape(-1, 1)