dtoro
649437dc85
Wire the full embedding flow: - Rewrite Embedding model to use pgvector Vector(512) with HNSW index - Add embed_photo, vision_fanout, backfill_vision Celery tasks on dedicated `vision` queue - Hook vision_fanout into generate_thumbnails completion - Add POST /api/v1/photos/search with hybrid RRF ranking (semantic-only for now; FTS leg added in PR5) - Stub ocr_photo, detect_objects, extract_faces tasks for later PRs Migration 0003 drops/recreates the embeddings table (was never populated). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
"""
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Celery configuration and app initialization
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"""
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from celery import Celery
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from app.config import settings
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# Create Celery app
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celery_app = Celery(
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'mulita',
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broker=settings.celery_broker_url,
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backend=settings.celery_result_backend,
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include=['app.tasks.scan', 'app.tasks.thumbs', 'app.tasks.vision']
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)
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# Configure Celery
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celery_app.conf.update(
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task_serializer='json',
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accept_content=['json'],
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result_serializer='json',
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timezone='UTC',
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enable_utc=True,
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task_routes={
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'app.tasks.thumbs.*': {'queue': 'high'},
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'app.tasks.scan.*': {'queue': 'low'},
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'app.tasks.vision.*': {'queue': 'vision'},
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'embed_photo': {'queue': 'vision'},
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'ocr_photo': {'queue': 'vision'},
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'detect_objects': {'queue': 'vision'},
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'extract_faces': {'queue': 'vision'},
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'vision_fanout': {'queue': 'vision'},
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},
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task_default_queue='default',
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task_default_exchange='default',
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task_default_exchange_type='direct',
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task_default_routing_key='default',
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broker_connection_retry_on_startup=True,
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) |