feat: integrate PluginStore and MinIO repository into model manager activities

- Added PluginStore integration for model management.
- Replaced StorageRepository with MinIORepository in Activities, Cleanup, and Training classes.
- Updated training logic to handle validation files and improved data management.
- Enhanced configuration for MinIO and PluginStore in connectors.
- Removed deprecated model repository and storage repository files.
- Updated environment variable handling for new configurations.
This commit is contained in:
vitor-aignosi
2026-03-11 17:35:05 -03:00
parent 9d71c0cf80
commit cf5111e520
23 changed files with 1480 additions and 4588 deletions

View File

@@ -118,7 +118,6 @@ class TrainModel:
await self._cleanup_resources(
experiment_run_id=experiment_run_id,
run_dir=(train_result.get('run_dir') or ''),
bucket_name=train_params.bucket_name,
file_name=train_params.file_name,
metadata=metadata,
@@ -275,7 +274,6 @@ class TrainModel:
async def _cleanup_resources(
self,
experiment_run_id: int,
run_dir: str,
bucket_name: str,
file_name: str,
metadata: dict[str, Any],
@@ -283,12 +281,11 @@ class TrainModel:
"""
Cleanup resources and delete file from MinIO.
This method removes the temporary run directory via activity and deletes
the training file from MinIO. On success, updates DB status to FILE_DELETED.
This method deletes the training file from MinIO. On success, updates
DB status to FILE_DELETED.
On error, updates DB status to FILE_DELETE_ERROR.
Args:
saved_result: TrainModelResult with run_dir and params information
experiment_run_id: Validated experiment run ID
metadata: Workflow execution metadata
@@ -300,7 +297,6 @@ class TrainModel:
Activities.cleanup_resources,
{
**metadata,
'run_dir': run_dir,
'bucket_name': bucket_name,
'file_name': file_name,
},