Fix UI inference crash due to missing columns

src/app.py

@@ -139,6 +139,13 @@ def predict_risk(
     df = pd.DataFrame([record])
     from src.features import engineer_features
     df = engineer_features(df)
+    
+    # Ensure all columns expected by the preprocessor are present (fill with NaN if missing)
+    expected_cols = getattr(predictor.preprocessor, "feature_names_in_", [])
+    for col in expected_cols:
+        if col not in df.columns:
+            df[col] = np.nan
+            
     X = predictor.preprocessor.transform(df)
     shap_factors = explain_prediction(
         X, model=predictor.model, feature_names=predictor.feature_names, top_k=8

src/predict.py

@@ -55,6 +55,13 @@ class GridRiskPredictor:
         labels        : np.ndarray  – binary prediction at 0.5 threshold
         """
         df = engineer_features(df)
+        
+        # Ensure that all feature names exist in df
+        expected_cols = getattr(self.preprocessor, "feature_names_in_", [])
+        for col in expected_cols:
+            if col not in df.columns:
+                df[col] = np.nan
+                
         X = self.preprocessor.transform(df)
         probs = self.model.predict_proba(X)[:, 1]
         labels = (probs >= 0.5).astype(int)