SIENTIAPDE-1717: Remove MinIO cleanup functionality and associated components. This change streamlines the cleanup workflow to focus solely on local temporary directories, removes the ModelTrainingError exception, and updates related configurations, documentation, and tests.

scripts/run_cleanup_test.py

@@ -45,14 +45,8 @@ async def main(argv: list[str]) -> None:
     temporal_host = os.getenv('TEMPORAL_HOST')
     temporal_namespace = os.getenv('TEMPORAL_NAMESPACE')
     task_queue = os.getenv('CLEANUP_TASK_QUEUE')
-    default_bucket = os.getenv('DEFAULT_CLEANUP_BUCKET')
     use_tls = os.getenv('TEMPORAL_USE_TLS', 'false').lower() == 'true'
 
-    # Optional CLI: bucket name override
-    bucket_name = default_bucket
-    if argv:
-        bucket_name = argv[0]
-
     print(f'Connecting to Temporal at {temporal_host} (namespace={temporal_namespace})...')
     client = await Client.connect(
         target_host=temporal_host,
@@ -61,7 +55,6 @@ async def main(argv: list[str]) -> None:
     )
 
     input_data: dict[str, Any] = {
-        'bucket_name': bucket_name,
     }
 
     workflow_id = f'cleanup-files-manual-{int(asyncio.get_event_loop().time())}'
@@ -69,8 +62,7 @@ async def main(argv: list[str]) -> None:
     print(
         f'Starting cleanup_files workflow once...\n'
         f'  workflow_id = {workflow_id}\n'
-        f'  task_queue  = {task_queue}\n'
-        f'  bucket_name = {bucket_name}'
+        f'  task_queue  = {task_queue}'
     )
 
     handle = await client.start_workflow(