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bvandeusen b7d4998cdb feat(beat): self-gating schedules for ML backfill, centroids, auto-accept
Promotes three previously-manual maintenance tasks to Celery Beat schedules
so the user doesn't have to remember to run them:

- ml.backfill                              daily
- apply_auto_accept_predictions            daily
- recompute_all_centroids                  weekly

Cadences are env-overridable (ML_BACKFILL_EVERY_SECONDS,
AUTO_ACCEPT_EVERY_SECONDS, CENTROIDS_EVERY_SECONDS).

Each task self-gates so a scheduled run is a no-op when there's nothing
to do:

- ml.backfill: already self-gating — its first paginated query returns
  zero rows when no image is missing predictions/embeddings, the loop
  breaks, and the task returns. No code change.

- apply_auto_accept_predictions: adds a fast-path NOT EXISTS query that
  returns immediately when no WD14 prediction at/above the threshold
  exists for an unattached, non-rejected (image, tag) pair. The full
  walk only fires when fresh predictions have landed since the last run.
  Returns {'skipped_no_candidates': True} on the no-op path.

- recompute_all_centroids: tightens the aggregate query to LEFT JOIN
  tag_reference_embedding and skip tags whose stored reference_count
  already matches current image_tags membership count. Without this gate
  the daily-scheduled sweep would re-enqueue a recompute for every
  eligible tag every run, contending with tag_and_embed on the ml queue.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-28 00:06:09 -04:00

173 lines
6.6 KiB
Python

# app/celery_app.py
"""
Celery application factory and configuration.
Provides task queue functionality for the ImageRepo import pipeline.
"""
import os
from celery import Celery
# Default broker/backend URLs
DEFAULT_BROKER = 'redis://redis:6379/0'
DEFAULT_BACKEND = 'redis://redis:6379/0'
def make_celery(app=None):
"""
Create Celery instance with Flask app context support.
Args:
app: Flask application instance (optional)
Returns:
Configured Celery instance
"""
# Get broker/backend from app config or environment
if app:
broker = app.config.get('CELERY_BROKER_URL', DEFAULT_BROKER)
backend = app.config.get('CELERY_RESULT_BACKEND', DEFAULT_BACKEND)
else:
broker = os.environ.get('CELERY_BROKER_URL', DEFAULT_BROKER)
backend = os.environ.get('CELERY_RESULT_BACKEND', DEFAULT_BACKEND)
celery = Celery(
'imagerepo',
broker=broker,
backend=backend,
include=[
'app.tasks.scan',
'app.tasks.import_file',
'app.tasks.thumbnail',
'app.tasks.sidecar',
'app.tasks.ml',
'app.tasks.maintenance',
]
)
# Worker concurrency from environment
concurrency = int(os.environ.get('CELERY_WORKER_CONCURRENCY', '2'))
celery.conf.update(
# Serialization
task_serializer='json',
accept_content=['json'],
result_serializer='json',
timezone='UTC',
enable_utc=True,
# Concurrency - intentionally low for steady background processing
worker_concurrency=concurrency,
worker_prefetch_multiplier=1, # One task at a time per worker process
# Task routing - separate queues for different task types
# Scheduler handles: maintenance (periodic tasks) + scan (directory scans)
# Worker handles: import, thumbnail, sidecar, default
task_routes={
# Scan tasks - handled by scheduler
'app.tasks.scan.scan_directory': {'queue': 'scan'},
'app.tasks.scan.deep_scan_directory': {'queue': 'scan'},
# Maintenance tasks - handled by scheduler (periodic/lightweight)
'app.tasks.scan.recover_interrupted_tasks': {'queue': 'maintenance'},
'app.tasks.scan.cleanup_old_tasks': {'queue': 'maintenance'},
'app.tasks.scan.update_system_stats': {'queue': 'maintenance'},
'app.tasks.scan.update_batch_stats': {'queue': 'maintenance'},
'app.tasks.maintenance.sweep_blocklisted_tag_from_images': {'queue': 'maintenance'},
'app.tasks.maintenance.sync_character_fandoms_to_images': {'queue': 'maintenance'},
'app.tasks.maintenance.verify_media_integrity': {'queue': 'maintenance'},
'app.tasks.maintenance.verify_unverified_images': {'queue': 'maintenance'},
'app.tasks.maintenance.apply_auto_accept_predictions': {'queue': 'maintenance'},
# Import tasks - handled by worker (heavy processing)
'app.tasks.import_file.*': {'queue': 'import'},
'app.tasks.thumbnail.*': {'queue': 'thumbnail'},
'app.tasks.sidecar.*': {'queue': 'sidecar'},
# ML inference tasks - handled by ml-worker
'app.tasks.ml.*': {'queue': 'ml'},
},
# Task default queue for unrouted tasks
task_default_queue='default',
# Result backend settings
result_expires=86400, # 24 hours
# Task execution settings for resume capability
task_acks_late=True, # Acknowledge after task completes
task_reject_on_worker_lost=True, # Requeue if worker dies
# Time limits (video transcoding may need longer)
task_soft_time_limit=600, # 10 minutes soft limit
task_time_limit=900, # 15 minutes hard limit
# Periodic task schedule (Celery Beat)
beat_schedule={
'periodic-import-scan': {
'task': 'app.tasks.scan.scan_directory',
'schedule': int(os.environ.get('IMPORT_EVERY_SECONDS', '28800')), # 8 hours default
'args': ('/import', '/images'),
},
'recover-interrupted-tasks': {
'task': 'app.tasks.scan.recover_interrupted_tasks',
'schedule': 300, # Every 5 minutes
},
'cleanup-old-tasks': {
'task': 'app.tasks.scan.cleanup_old_tasks',
'schedule': 86400, # Once per day
'args': (7,), # Keep tasks for 7 days
},
'update-system-stats': {
'task': 'app.tasks.scan.update_system_stats',
'schedule': 21600, # Every 6 hours
},
# ML-pipeline self-maintenance. Each is internally self-gating:
# backfill returns immediately when nothing's missing,
# recompute_all_centroids only enqueues for tags whose member
# count changed, and apply_auto_accept_predictions short-circuits
# when no above-threshold predictions are unattached.
'ml-backfill-sweep': {
'task': 'app.tasks.ml.backfill',
'schedule': int(os.environ.get('ML_BACKFILL_EVERY_SECONDS', '86400')), # daily
},
'apply-auto-accept-sweep': {
'task': 'app.tasks.maintenance.apply_auto_accept_predictions',
'schedule': int(os.environ.get('AUTO_ACCEPT_EVERY_SECONDS', '86400')), # daily
},
'recompute-centroids-sweep': {
'task': 'app.tasks.ml.recompute_all_centroids',
'schedule': int(os.environ.get('CENTROIDS_EVERY_SECONDS', '604800')), # weekly
},
},
)
if app:
# Don't pass Flask config directly to Celery - it contains old-style keys
# that conflict with Celery's new lowercase format.
# The broker/backend are already set above from app.config.
# Create a task base class that runs within Flask app context
class ContextTask(celery.Task):
def __call__(self, *args, **kwargs):
with app.app_context():
return self.run(*args, **kwargs)
celery.Task = ContextTask
return celery
def create_celery_with_app():
"""
Create Celery instance with Flask app context for standalone workers.
This is used when running `celery -A app.celery_app:celery worker`.
"""
from app import create_app
flask_app = create_app()
return make_celery(flask_app)
# Create celery instance with Flask app context
# This ensures workers have access to the database and Flask extensions
celery = create_celery_with_app()