imporve features

services/training/app/ml/hybrid_trainer.py

@@ -7,7 +7,7 @@ import pandas as pd
 import numpy as np
 from typing import Dict, List, Any, Optional, Tuple
 import structlog
-from datetime import datetime
+from datetime import datetime, timezone
 import joblib
 from sklearn.metrics import mean_absolute_error, mean_squared_error, mean_absolute_percentage_error
 from sklearn.model_selection import TimeSeriesSplit
@@ -408,7 +408,7 @@ class HybridProphetXGBoost:
             },
             'tenant_id': tenant_id,
             'inventory_product_id': inventory_product_id,
-            'trained_at': datetime.utcnow().isoformat()
+            'trained_at': datetime.now(timezone.utc).isoformat()
         }
 
     async def predict(