feat: enhance training workflow with model metadata loading and refactor data handling

- Introduced a new activity to load model metadata from the model store.
- Refactored training logic to utilize new model metadata and improved parameter handling.
- Updated the `TrainModelParams` class to include additional fields for model configuration.
- Replaced deprecated utility functions with a custom train-test split implementation.
- Removed unused utility functions and cleaned up the data manager repository.
- Adjusted experiment tracking to include model-specific metadata in notifications.

model_manager/worker/worker.py

@@ -178,6 +178,7 @@ async def main():
             other_workflows=[],
             activities=[
                 activities.update_experiment_run,
+                activities.load_model_metadata,
                 activities.validate_train_params,
                 activities.train_model,
                 activities.cleanup_resources,