Improve AI logic

shared/clients/training_client.py

@@ -127,6 +127,36 @@ class TrainingServiceClient(BaseServiceClient):
             params["start_date"] = start_date
         if end_date:
             params["end_date"] = end_date
-        
+
         result = await self.get(f"training/models/{model_id}/predictions", tenant_id=tenant_id, params=params)
-        return result.get("predictions", []) if result else None
+        return result.get("predictions", []) if result else None
+
+    async def trigger_retrain(
+        self,
+        tenant_id: str,
+        inventory_product_id: str,
+        reason: str = 'manual',
+        metadata: Optional[Dict[str, Any]] = None
+    ) -> Optional[Dict[str, Any]]:
+        """
+        Trigger model retraining for a specific product.
+        Used by orchestrator when forecast accuracy degrades.
+
+        Args:
+            tenant_id: Tenant UUID
+            inventory_product_id: Product UUID to retrain model for
+            reason: Reason for retraining (accuracy_degradation, manual, scheduled, etc.)
+            metadata: Optional metadata (e.g., previous_mape, validation_date, etc.)
+
+        Returns:
+            Training job details or None if failed
+        """
+        data = {
+            "inventory_product_id": inventory_product_id,
+            "reason": reason,
+            "metadata": metadata or {},
+            "include_weather": True,
+            "include_traffic": False,
+            "min_data_points": 30
+        }
+        return await self.post("training/models/retrain", data=data, tenant_id=tenant_id)