feat: add vision pipeline scaffolding with ONNX backend

Introduce the app/services/vision/ module with ABC interfaces, ONNX
Runtime backend, model registry, and per-task implementations:
- OpenCLIP ViT-B/32 embedder (image + text, 512-d)
- RapidOCR engine (PP-OCRv4 via ONNX, no PaddlePaddle)
- YOLOv8n object detector (raw ONNX, no ultralytics runtime)
- YuNet + SFace face processor (Apache 2.0, opencv_zoo, 128-d)
- DBSCAN face clustering helper

Add VisionSettings to config (mulita.yml + Pydantic), bootstrap_models.py
for first-boot weight downloads, models_data Docker volume, and ROCm
backend stub for future GPU acceleration.

No Celery tasks wired yet — models load but nothing invokes them.

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

backend/Dockerfile

@@ -30,7 +30,7 @@ RUN pip install --no-cache-dir -r requirements.txt
 COPY . .
 
 # Create necessary directories
-RUN mkdir -p /data/thumbs /data/db /data/proxies /app/config
+RUN mkdir -p /data/thumbs /data/db /data/proxies /data/models /app/config
 
 # Expose port
 EXPOSE 8000