Fix new services implementation 3

services/forecasting/app/api/forecasts.py

@@ -56,7 +56,7 @@ async def create_enhanced_single_forecast(
         
         logger.info("Generating enhanced single forecast",
                    tenant_id=tenant_id,
-                   product_name=request.product_name,
+                   inventory_product_id=request.inventory_product_id,
                    forecast_date=request.forecast_date.isoformat())
         
         # Record metrics
@@ -124,13 +124,13 @@ async def create_enhanced_batch_forecast(
         
         logger.info("Generating enhanced batch forecasts",
                    tenant_id=tenant_id,
-                   products_count=len(request.products),
-                   forecast_dates_count=len(request.forecast_dates))
+                   products_count=len(request.inventory_product_ids),
+                   forecast_dates_count=request.forecast_days)
         
         # Record metrics
         if metrics:
             metrics.increment_counter("enhanced_batch_forecasts_total")
-            metrics.histogram("enhanced_batch_forecast_products_count", len(request.products))
+            metrics.histogram("enhanced_batch_forecast_products_count", len(request.inventory_product_ids))
         
         # Generate batch forecasts using enhanced service
         batch_result = await enhanced_forecasting_service.generate_batch_forecasts(
@@ -174,7 +174,7 @@ async def create_enhanced_batch_forecast(
 @track_execution_time("enhanced_get_forecasts_duration_seconds", "forecasting-service")
 async def get_enhanced_tenant_forecasts(
     tenant_id: str = Path(..., description="Tenant ID"),
-    product_name: Optional[str] = Query(None, description="Filter by product name"),
+    inventory_product_id: Optional[str] = Query(None, description="Filter by inventory product ID"),
     start_date: Optional[date] = Query(None, description="Start date filter"),
     end_date: Optional[date] = Query(None, description="End date filter"),
     skip: int = Query(0, description="Number of records to skip"),
@@ -203,7 +203,7 @@ async def get_enhanced_tenant_forecasts(
         # Get forecasts using enhanced service
         forecasts = await enhanced_forecasting_service.get_tenant_forecasts(
             tenant_id=tenant_id,
-            product_name=product_name,
+            inventory_product_id=inventory_product_id,
             start_date=start_date,
             end_date=end_date,
             skip=skip,
@@ -218,7 +218,7 @@ async def get_enhanced_tenant_forecasts(
             "forecasts": forecasts,
             "total_returned": len(forecasts),
             "filters": {
-                "product_name": product_name,
+                "inventory_product_id": inventory_product_id,
                 "start_date": start_date.isoformat() if start_date else None,
                 "end_date": end_date.isoformat() if end_date else None
             },

services/forecasting/app/api/predictions.py

@@ -59,14 +59,14 @@ async def generate_enhanced_realtime_prediction(
         
         logger.info("Generating enhanced real-time prediction",
                    tenant_id=tenant_id,
-                   product_name=prediction_request.get("product_name"))
+                   inventory_product_id=prediction_request.get("inventory_product_id"))
         
         # Record metrics
         if metrics:
             metrics.increment_counter("enhanced_realtime_predictions_total")
         
         # Validate required fields
-        required_fields = ["product_name", "model_id", "features"]
+        required_fields = ["inventory_product_id", "model_id", "features"]
         missing_fields = [field for field in required_fields if field not in prediction_request]
         if missing_fields:
             raise HTTPException(
@@ -91,7 +91,7 @@ async def generate_enhanced_realtime_prediction(
         
         return {
             "tenant_id": tenant_id,
-            "product_name": prediction_request["product_name"],
+            "inventory_product_id": prediction_request["inventory_product_id"],
             "model_id": prediction_request["model_id"],
             "prediction": prediction_result,
             "generated_at": datetime.now().isoformat(),
@@ -205,7 +205,7 @@ async def generate_enhanced_batch_predictions(
 @track_execution_time("enhanced_get_prediction_cache_duration_seconds", "forecasting-service")
 async def get_enhanced_prediction_cache(
     tenant_id: str = Path(..., description="Tenant ID"),
-    product_name: Optional[str] = Query(None, description="Filter by product name"),
+    inventory_product_id: Optional[str] = Query(None, description="Filter by inventory product ID"),
     skip: int = Query(0, description="Number of records to skip"),
     limit: int = Query(100, description="Number of records to return"),
     request_obj: Request = None,
@@ -232,7 +232,7 @@ async def get_enhanced_prediction_cache(
         # Get cached predictions using enhanced service
         cached_predictions = await enhanced_forecasting_service.get_cached_predictions(
             tenant_id=tenant_id,
-            product_name=product_name,
+            inventory_product_id=inventory_product_id,
             skip=skip,
             limit=limit
         )
@@ -245,7 +245,7 @@ async def get_enhanced_prediction_cache(
             "cached_predictions": cached_predictions,
             "total_returned": len(cached_predictions),
             "filters": {
-                "product_name": product_name
+                "inventory_product_id": inventory_product_id
             },
             "pagination": {
                 "skip": skip,
@@ -271,7 +271,7 @@ async def get_enhanced_prediction_cache(
 @track_execution_time("enhanced_clear_prediction_cache_duration_seconds", "forecasting-service")
 async def clear_enhanced_prediction_cache(
     tenant_id: str = Path(..., description="Tenant ID"),
-    product_name: Optional[str] = Query(None, description="Clear cache for specific product"),
+    inventory_product_id: Optional[str] = Query(None, description="Clear cache for specific inventory product ID"),
     request_obj: Request = None,
     current_tenant: str = Depends(get_current_tenant_id_dep),
     enhanced_forecasting_service: EnhancedForecastingService = Depends(get_enhanced_forecasting_service)
@@ -296,7 +296,7 @@ async def clear_enhanced_prediction_cache(
         # Clear cache using enhanced service
         cleared_count = await enhanced_forecasting_service.clear_prediction_cache(
             tenant_id=tenant_id,
-            product_name=product_name
+            inventory_product_id=inventory_product_id
         )
         
         if metrics:
@@ -305,13 +305,13 @@ async def clear_enhanced_prediction_cache(
         
         logger.info("Enhanced prediction cache cleared",
                    tenant_id=tenant_id,
-                   product_name=product_name,
+                   inventory_product_id=inventory_product_id,
                    cleared_count=cleared_count)
         
         return {
             "message": "Prediction cache cleared successfully",
             "tenant_id": tenant_id,
-            "product_name": product_name,
+            "inventory_product_id": inventory_product_id,
             "cleared_count": cleared_count,
             "enhanced_features": True,
             "repository_integration": True