dtoro
574d71371f
Drops face recognition, OCR, object detection, and semantic embeddings. The sole remaining vision task is a CLIP-based binary classifier (photography vs other); photos in "other" get needs_review=true so screenshots, documents, memes and scans can be triaged from a new filter pill in the UI. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
52 lines
1.6 KiB
Python
52 lines
1.6 KiB
Python
"""
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Ensure the OpenCLIP ViT-B/32 visual encoder is present on worker boot.
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Exported via export_models.py if missing.
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"""
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import logging
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from pathlib import Path
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from app.config import settings
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logger = logging.getLogger(__name__)
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REQUIRED = [
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("embed/visual.onnx", "OpenCLIP ViT-B/32 visual encoder"),
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]
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def bootstrap(models_dir: str | None = None):
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base = Path(models_dir or settings.vision.models_dir)
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base.mkdir(parents=True, exist_ok=True)
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missing = [(rel, desc) for rel, desc in REQUIRED if not (base / rel).exists()]
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if missing:
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logger.warning("Missing %d model file(s); attempting automatic export", len(missing))
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try:
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from app.services.vision import export_models
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export_models.export_openclip_visual(base)
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except Exception as e:
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logger.error(
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"Export failed: %s. Run `python -m app.services.vision.export_models "
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"--models-dir %s` manually to retry.",
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e, base,
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)
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still_missing = [(r, d) for r, d in REQUIRED if not (base / r).exists()]
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if still_missing:
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for rel, desc in still_missing:
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logger.error(" still missing: %s — %s", base / rel, desc)
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else:
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logger.info("All model files present in %s", base)
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try:
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import redis as _redis
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_redis.from_url(settings.redis_url).set("mulita:vision:ready", "1")
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logger.info("Set mulita:vision:ready in Redis")
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except Exception as e:
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logger.warning("Could not set vision readiness flag in Redis: %s", e)
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if __name__ == "__main__":
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logging.basicConfig(level=logging.INFO)
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bootstrap()
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