fix: harden pipeline — retries, acks_late, time limits, session safety

Addresses 16 robustness, transparency, and performance issues across
the Celery media processing pipeline:

Critical:
- Singleton DB engine in vision tasks (was leaking one per task call)
- acks_late + task_reject_on_worker_lost so crashed workers don't lose tasks
- Global soft/hard time limits (5/10 min) to prevent hung worker slots
- Thumbnail copy-before-resize (in-place mutation degraded larger sizes)
- backfill_vision now checks each task type independently (OCR, faces, etc.)
- Parameterized LIMIT in backfill_vision (was f-string SQL injection)

High:
- try/except + retry(max=3) on all vision inference tasks
- extract_metadata writes processing_error on exiftool failure
- PIL Image handles closed in _load_thumb/_load_original
- Scan progress Redis keys auto-expire after 1 hour
- Watcher lock renewal is wall-clock based (30s) not event-count based
- worker_process_init signal warms up vision models on startup

Medium:
- Explicit task_routes for every task name (wildcards never matched)
- app.services.metadata added to Celery include list
- POST /maintenance/recover-stuck endpoint for photos stuck in processing
- Docker healthchecks for worker-light, worker-vision, and Redis
- Task ID in vision log lines for distributed tracing
- Bare except:pass narrowed to specific exceptions

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
root
2026-04-13 08:57:10 +02:00
parent e974ffbfd2
commit f090a809a9
8 changed files with 366 additions and 110 deletions

View File

@@ -209,21 +209,24 @@ async def _extract_metadata_async(photo_id: str):
cmd,
capture_output=True,
text=True,
timeout=30
timeout=30,
stdin=subprocess.DEVNULL,
)
if result.returncode != 0:
logger.error(f"ExifTool error: {result.stderr}")
photo.processing_error = f"ExifTool: {result.stderr[:500]}"
await session.commit()
return {'status': 'error', 'message': result.stderr}
# Parse JSON output
metadata = json.loads(result.stdout)
if metadata and len(metadata) > 0:
exif_data = metadata[0]
# Store full metadata as JSON
photo.exif_json = json.dumps(exif_data)
# Extract taken_at date
date_fields = [
'EXIF:DateTimeOriginal',
@@ -231,7 +234,7 @@ async def _extract_metadata_async(photo_id: str):
'QuickTime:MediaCreateDate',
'EXIF:ModifyDate'
]
for field in date_fields:
if field in exif_data:
taken_at = parse_exif_datetime(exif_data[field])
@@ -247,7 +250,7 @@ async def _extract_metadata_async(photo_id: str):
photo.has_date_warning = has_date_warning(
photo.filepath, photo.taken_at
)
# Extract dimensions if not already set
if not photo.width:
photo.width = exif_data.get('EXIF:ImageWidth') or exif_data.get('File:ImageWidth')
@@ -262,26 +265,27 @@ async def _extract_metadata_async(photo_id: str):
# Extract and store key metadata for search
key_metadata = extract_key_metadata(exif_data)
# Update FTS table (would be done via trigger in production)
# For now, we'll store it in a comment
await session.commit()
logger.info(f"Metadata extracted for photo {photo_id}")
return {
'status': 'success',
'photo_id': photo_id,
'taken_at': photo.taken_at.isoformat() if photo.taken_at else None
}
except subprocess.TimeoutExpired:
logger.error(f"ExifTool timeout for {photo.filepath}")
photo.processing_error = 'ExifTool timeout'
await session.commit()
return {'status': 'error', 'message': 'ExifTool timeout'}
except json.JSONDecodeError as e:
logger.error(f"Failed to parse ExifTool output: {e}")
photo.processing_error = f"Invalid ExifTool output: {e}"
await session.commit()
return {'status': 'error', 'message': 'Invalid ExifTool output'}
except Exception as e:
logger.error(f"Error extracting metadata for {photo_id}: {e}")
return {'status': 'error', 'message': str(e)}