Fix inference feature mismatch with training metadata

services/ml/training/train.py

@@ -388,7 +388,28 @@ def train(
             import joblib
             output_model_path = Path(output_model_path)
             output_model_path.parent.mkdir(parents=True, exist_ok=True)
-            joblib.dump(model, output_model_path)
+
+            labels = []
+            try:
+                if hasattr(model, "classes_"):
+                    labels = [str(c) for c in model.classes_]
+                elif hasattr(model, "model") and hasattr(model.model, "classes_"):
+                    labels = [str(c) for c in model.model.classes_]
+            except Exception:
+                labels = []
+
+            model_data = {
+                "model": model,
+                "metadata": {
+                    "model_type": training_config.model_type,
+                    "trained_at": datetime.utcnow().isoformat(),
+                    "run_id": run_id,
+                    "feature_columns": feature_cols,
+                    "feature_engineering_enabled": config.stages.feature_engineering.enabled,
+                    "labels": labels,
+                },
+            }
+            joblib.dump(model_data, output_model_path)
             logger.info(f"Saved model to {output_model_path}")
         
         # Update training run record in PostgreSQL