dtoro
94c07b1d0d
Replace OpenCLIP ViT-B/32 (512-d, ~78% recall) with SigLIP2 ViT-B/16 (768-d, ~84% recall) as the default embedding model for significantly better image-text retrieval quality. - New SigLIP2Embedder class with 384px input and SigLIP normalization - ONNX export pipeline for SigLIP2 visual + textual encoders - Migration 0010: resize embeddings.vector from 512 to 768 dimensions - Config-driven model selection: "siglip2_vitb16" (default) or "openclip_vitb32" (legacy) — both models can coexist - Content classifier follows the configured embedder family - Existing embeddings cleared on migration; vision backfill regenerates Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
112 lines
3.7 KiB
Python
112 lines
3.7 KiB
Python
"""
|
|
Download vision model weights on first worker boot.
|
|
|
|
Run as: python -m app.services.vision.bootstrap_models
|
|
|
|
Or called from the vision worker entrypoint before Celery starts.
|
|
Downloads are idempotent — existing files are skipped.
|
|
|
|
For models that require export (OpenCLIP, YOLOv8n), see export_models.py.
|
|
Those must be exported once on any machine with pip, then placed in
|
|
the models volume before the worker starts.
|
|
"""
|
|
import logging
|
|
import os
|
|
from pathlib import Path
|
|
from urllib.request import urlretrieve
|
|
|
|
from app.config import settings
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
# (relative_path, url, description)
|
|
# Models with url=None must be pre-exported via export_models.py.
|
|
# InsightFace (RetinaFace + ArcFace) auto-downloads via the insightface
|
|
# package on first use — no manual download entries needed.
|
|
DOWNLOADS = []
|
|
|
|
# Models that need manual export via export_models.py
|
|
EXPORTS = [
|
|
("embed/visual.onnx", "OpenCLIP ViT-B/32 visual encoder"),
|
|
("embed/textual.onnx", "OpenCLIP ViT-B/32 textual encoder"),
|
|
("embed_siglip2/visual.onnx", "SigLIP2 ViT-B/16 visual encoder"),
|
|
("embed_siglip2/textual.onnx", "SigLIP2 ViT-B/16 textual encoder"),
|
|
("detect/yolov8n.onnx", "YOLOv8n object detector"),
|
|
]
|
|
|
|
|
|
def bootstrap(models_dir: str | None = None):
|
|
"""Ensure all model files are present. Download what we can, warn about
|
|
files that need manual export."""
|
|
base = Path(models_dir or settings.vision.models_dir)
|
|
base.mkdir(parents=True, exist_ok=True)
|
|
|
|
# Download auto-downloadable models
|
|
for rel_path, url, desc in DOWNLOADS:
|
|
dest = base / rel_path
|
|
dest.parent.mkdir(parents=True, exist_ok=True)
|
|
|
|
if dest.exists():
|
|
logger.debug("Already exists: %s (%s)", dest, desc)
|
|
continue
|
|
|
|
logger.info("Downloading %s → %s", desc, dest)
|
|
try:
|
|
urlretrieve(url, str(dest))
|
|
size_kb = dest.stat().st_size / 1024
|
|
logger.info("Downloaded %s (%.0f KB)", desc, size_kb)
|
|
except Exception as e:
|
|
logger.error("Failed to download %s: %s", desc, e)
|
|
if dest.exists():
|
|
dest.unlink()
|
|
|
|
# Check for manually-exported models
|
|
missing = []
|
|
for rel_path, desc in EXPORTS:
|
|
dest = base / rel_path
|
|
if not dest.exists():
|
|
missing.append((rel_path, desc))
|
|
|
|
if missing:
|
|
logger.warning(
|
|
"Missing %d model file(s); attempting automatic export:",
|
|
len(missing),
|
|
)
|
|
for rel_path, desc in missing:
|
|
logger.warning(" %s — %s", base / rel_path, desc)
|
|
|
|
try:
|
|
from app.services.vision import export_models
|
|
|
|
export_models.export_openclip(base)
|
|
export_models.export_siglip2(base)
|
|
export_models.export_yolov8n(base)
|
|
except Exception as e:
|
|
logger.error(
|
|
"Automatic export failed: %s. "
|
|
"Run `python -m app.services.vision.export_models "
|
|
"--models-dir %s` manually before starting the worker.",
|
|
e,
|
|
base,
|
|
)
|
|
return
|
|
|
|
# Re-check what's still missing after the export pass.
|
|
still_missing = [
|
|
(rel_path, desc)
|
|
for rel_path, desc in EXPORTS
|
|
if not (base / rel_path).exists()
|
|
]
|
|
if still_missing:
|
|
for rel_path, desc in still_missing:
|
|
logger.error(" still missing: %s — %s", base / rel_path, desc)
|
|
else:
|
|
logger.info("All model files present in %s", base)
|
|
else:
|
|
logger.info("All model files present in %s", base)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
logging.basicConfig(level=logging.INFO)
|
|
bootstrap()
|