Fix new services implementation 5

services/training/app/ml/trainer.py

@@ -92,9 +92,27 @@ class EnhancedBakeryMLTrainer:
                 
                 # Get unique products from the sales data
                 products = sales_df['inventory_product_id'].unique().tolist()
-                logger.info("Training enhanced models",
+                
+                # Debug: Log sales data details to understand why only one product is found
+                total_sales_records = len(sales_df)
+                sales_by_product = sales_df.groupby('inventory_product_id').size().to_dict()
+                
+                logger.info("Enhanced training pipeline - Sales data analysis",
+                           total_sales_records=total_sales_records,
                            products_count=len(products),
-                           products=products)
+                           products=products,
+                           sales_by_product=sales_by_product)
+                
+                if len(products) == 1:
+                    logger.warning("Only ONE product found in sales data - this may indicate a data fetching issue",
+                                 tenant_id=tenant_id,
+                                 single_product_id=products[0],
+                                 total_sales_records=total_sales_records)
+                elif len(products) == 0:
+                    raise ValueError("No products found in sales data")
+                else:
+                    logger.info("Multiple products detected for training",
+                               products_count=len(products))
                 
                 self.status_publisher.products_total = len(products)
                 
@@ -512,7 +530,7 @@ class EnhancedBakeryMLTrainer:
                        from_column='quantity_sold',
                        to_column='quantity')
         
-        required_columns = ['date', 'product_name', 'quantity']
+        required_columns = ['date', 'inventory_product_id', 'quantity']
         missing_columns = [col for col in required_columns if col not in sales_df.columns]
         if missing_columns:
             raise ValueError(f"Missing required columns: {missing_columns}")
@@ -541,7 +559,7 @@ class EnhancedBakeryMLTrainer:
         try:
             logger.info("Enhanced model evaluation starting",
                        tenant_id=tenant_id,
-                       product_name=product_name)
+                       inventory_product_id=inventory_product_id)
             
             # Get database session and repositories
             async with self.database_manager.get_session() as db_session: