feat: update training workflow and repository management

- Replaced synchronous MinIO repository calls with asynchronous counterparts in the Training class for improved performance.
- Enhanced logging throughout the training process to provide better insights into model metadata loading, parameter validation, and training execution.
- Updated the train_test_split function to enforce DataFrame input type, ensuring consistency in data handling.
- Removed the deprecated model_repository.py file to streamline the codebase.
- Adjusted cleanup schedule logic to improve error handling and logging during schedule reconciliation.
- Updated tests to reflect changes in the training workflow and repository interactions.

tests/schedules/test_cleanup_schedule.py

@@ -125,6 +125,29 @@ async def test_schedule_exists_handles_exception(mock_temporal_client, mock_logg
     assert 'Error checking if schedule exists' in mock_logger.custom_error.call_args[0][0]
 
 
+@pytest.mark.asyncio
+async def test_needs_schedule_reconcile_handles_describe_exception(mock_logger, metadata):
+    """Test _needs_schedule_reconcile returns True and logs when describe fails."""
+    from model_manager.schedules.cleanup_schedule import _needs_schedule_reconcile
+
+    handle = AsyncMock()
+    handle.describe = AsyncMock(side_effect=RuntimeError('describe failed'))
+
+    needs_reconcile = await _needs_schedule_reconcile(
+        schedule_handle=handle,
+        cleanup_task_queue='cleanup_files-model-manager-worker-queue',
+        logger=mock_logger,
+        metadata=metadata,
+    )
+
+    assert needs_reconcile is True
+    mock_logger.custom_error.assert_called_once()
+    assert (
+        'Error describing cleanup schedule for reconcile'
+        in mock_logger.custom_error.call_args[0][0]
+    )
+
+
 # --- create_cleanup_schedule Tests ---