SIENTIAPDE-1273

Enhance MLFlowRepository and Activities classes with new methods and metrics

- Added `check_artifact_exists` method to MLFlowRepository for verifying artifact presence in the MLflow Model Registry.
- Implemented `get_prediction_data` method in MLFlowRepository to retrieve prediction data from models.
- Updated Activities class to integrate ModelMetrics for improved metrics handling.
- Enhanced tests for artifact existence checks and prediction data retrieval, ensuring robust coverage for new functionalities.
- Updated various workflows to include `transform_table_name` in input data for better data handling.

laborious/activities/activities.py

@@ -11,9 +11,9 @@ with workflow.unsafe.imports_passed_through():
     from laborious.activities.mlflow import MLFlow
     from laborious.activities.opc import OPC
     from laborious.activities.storage import Storage
+    from laborious.activities.model_metrics import ModelMetrics
 
-
-class Activities(Storage, MLFlow, Gates, OPC):
+class Activities(Storage, MLFlow, Gates, OPC, ModelMetrics):
     """
     Main activities orchestrator for the Laborious system.
 
@@ -108,6 +108,13 @@ class Activities(Storage, MLFlow, Gates, OPC):
             metrics_controller=metrics_controller,
         )
 
+        ModelMetrics.__init__(
+            self,
+            logger=logger,
+            notification_handler=notification_handler,
+            metrics_controller=metrics_controller,
+        )
+
     async def shutdown(self):
         """
         Gracefully shutdown all activities and clean up resources.
@@ -124,3 +131,4 @@ class Activities(Storage, MLFlow, Gates, OPC):
         MLFlow.close(self)
         Gates.close(self)
         await OPC.close(self)
+        ModelMetrics.close(self)