fix: model weights setup — export scripts, ORT compat, bootstrap

- Add export_models.py for OpenCLIP ViT-B/32 and YOLOv8n ONNX export
- Fix ArgMax(13) ORT ARM64 incompatibility by passing eot_indices as a
  separate ONNX input (computed outside the graph in embed.py)
- Use legacy TorchScript exporter (dynamo=False) for IR version 9 compat
- Upgrade onnxruntime to 1.18.1
- Rewrite bootstrap_models.py with clear separation of auto-downloadable
  models (YuNet, SFace) vs manually-exported ones (OpenCLIP, YOLOv8n)
- Wire bootstrap into worker CMD (runs before Celery)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

docker-compose.yml

@@ -62,7 +62,7 @@ services:
       context: ./backend
       dockerfile: Dockerfile
     container_name: mulita-worker
-    command: celery -A app.tasks.celery worker --loglevel=${LOG_LEVEL:-info} --concurrency=${CELERYD_CONCURRENCY:-4}
+    command: sh -c "python -m app.services.vision.bootstrap_models && celery -A app.tasks.celery worker --loglevel=${LOG_LEVEL:-info} --concurrency=${CELERYD_CONCURRENCY:-4}"
     volumes:
       - ./mulita.yml:/app/config/mulita.yml:ro
       - ${PHOTO_DIRS:-./photos}:/photos:rw