Deploy PyCaret model baseline_dt_20250426_212853.pkl with fixed indentation

app.py

@@ -173,10 +173,10 @@ else:
             if pred_col_label in predictions.columns:
                 st.success(f"Predicted Label: **{predictions[pred_col_label].iloc[0]}**")
             # Also show score if available for classification
-            if pred_col_score in predictions.columns and pycaret_task_module == 'pycaret.classification':
+            if pred_col_score in predictions.columns and APP_PYCARET_TASK_MODULE  == 'pycaret.classification':
                  st.info(f"Prediction Score: **{predictions[pred_col_score].iloc[0]:.4f}**")
             # Handle regression output (usually just score)
-            elif pred_col_score in predictions.columns and pycaret_task_module == 'pycaret.regression':
+            elif pred_col_score in predictions.columns and APP_PYCARET_TASK_MODULE  == 'pycaret.regression':
                  st.success(f"Predicted Value: **{predictions[pred_col_score].iloc[0]:.4f}**")
             else:
                  # Fallback: Display the last column as prediction if specific ones aren't found