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/worker/test_prepare_worker.py

@@ -3,6 +3,12 @@
 from unittest.mock import MagicMock, patch
 
 
+def test_build_queue_name_without_runtime_uses_default_suffix():
+    from model_manager.worker.prepare_worker import build_queue_name
+
+    assert build_queue_name('TrainModel') == 'train_model-queue'
+
+
 def test_prepare_worker_train_queue_uses_train_limits():
     from model_manager.worker.prepare_worker import prepare_worker
     from model_manager.workflows.train_model import TrainModel