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/sientia/test_exceptions.py

@@ -0,0 +1,9 @@
+"""Unit tests for custom exception aliases."""
+
+from mlflow.exceptions import MlflowException
+
+from model_manager.sientia.exceptions import SientiaMlException
+
+
+def test_sientia_ml_exception_is_mlflow_exception_alias():
+    assert SientiaMlException is MlflowException