Update app.py

app.py

@@ -68,7 +68,7 @@ def main():
     data['forecast'] = model.predict(features[model.feature_names_in_])
     
     # Calculate performance metrics
-    latest_data = data.loc[data.index > pd.Timestamp.now(tz='UTC') - pd.Timedelta('1D')]
+    latest_data = data.loc[data.index > pd.Timestamp.now(TIMEZONE) - pd.Timedelta('1D')]
     rmse = np.sqrt((latest_data['power_consumption_kwh'] - latest_data['forecast'])**2).mean()
     mae = (latest_data['power_consumption_kwh'] - latest_data['forecast']).abs().mean()
     current_error = (data['power_consumption_kwh'].iloc[-1] - data['forecast'].iloc[-1]) / data['power_consumption_kwh'].iloc[-1] * 100