SIENTIAPDE-1646

Enhance MLFlow reference data handling and testing

- Updated the artifact handling in MLFlow to prioritize 'retrain_input.csv' over 'train_data.csv' when resolving reference data.
- Introduced new methods for resolving artifact names and locating downloaded CSV files.
- Modified the `get_reference_data` method to improve artifact resolution and error handling.
- Expanded unit tests to cover scenarios for missing artifacts and preference logic between retrain and train data CSVs.

laborious/utils/repository/opc_repository.py

@@ -755,9 +755,7 @@ class OpcRepository(SientiaMonitoring):
                 pass
         node_obj.set_value(data, variant_type)
 
-    def _write_reconnect_in_progress(
-        self, metadata: dict[str, Any]
-    ) -> tuple[bool, dict[str, Any]]:
+    def _write_reconnect_in_progress(self, metadata: dict[str, Any]) -> tuple[bool, dict[str, Any]]:
         """
         Fail a write because a background reconnect thread is already running.