refactor: drop AI/vision pipeline + plain Postgres + full-refresh script

Removes the OpenCLIP-on-ONNX classifier and everything that fed or
consumed it:
  - backend: app/services/vision/, app/tasks/vision.py,
    app/services/feature_flags.py, app/routers/features.py — all
    deleted; admin AI/feature-flag endpoints and the worker-vision
    bootstrap call gone. Photo.needs_review and its index dropped.
  - frontend: AI Settings tab, useFeaturesQuery hook, FeatureFlag
    types, "Needs Review" sidebar entry + filter, needs_review filter
    URL param all gone.
  - infra: worker-vision compose service + models_data volume deleted;
    worker-light command no longer runs bootstrap_models; the db
    image switches from pgvector/pgvector:pg16 to postgres:16; backend
    Dockerfile drops the dedicated torch RUN layer; requirements.txt
    drops torch/torchvision/open-clip-torch/onnxruntime.

Alembic 0019_drop_ai_remnants:
  - drops photos.needs_review + ix_photos_needs_review
  - DROP EXTENSION IF EXISTS vector (must run before the image swap;
    the new postgres:16 doesn't ship pgvector)

New scripts/full_refresh.py: one-shot DB ↔ filesystem reconciliation.
Runs cleanup_data_integrity, scans every active SourceRoot inline
(no celery dependency so the worker can be stopped), hard-prunes
photo + folder rows for files that are gone, removes orphan
/data/thumbs/{user}/{photo}/ directories. New helper
prune_orphan_thumbnails in cleanup.py.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

backend/app/tasks/thumbs.py

@@ -48,11 +48,10 @@ THUMB_SIZES = {
 }
 
 # Sizes the worker writes to /data/thumbs. Empty set since Phase 4 —
-# the API serves all sizes via Nextcloud's /core/preview proxy, and
-# the vision worker also fetches NC previews on demand instead of
-# reading a local cache. generate_thumbnails still runs the decode-
-# and-pHash side-effect (perceptual dedup is mule-only and needs the
-# original-resolution pixels) but no longer touches the disk.
+# the API serves all sizes via Nextcloud's /core/preview proxy.
+# generate_thumbnails still runs the decode-and-pHash side-effect
+# (perceptual dedup is mule-only and needs the original-resolution
+# pixels) but no longer touches the disk.
 WORKER_THUMB_SIZES: set[str] = set()
 
 def get_thumb_path(photo_id: str, size: str, user_id: str = None) -> str:
@@ -396,14 +395,6 @@ async def _generate_thumbnails_async(photo_id: str, task):
 
             logger.info(f"Thumbnails generated for photo {photo_id}")
 
-            # Dispatch vision pipeline only after thumbnails succeeded —
-            # vision tasks need the generated thumbnails to run inference.
-            try:
-                from app.tasks.vision import vision_fanout
-                vision_fanout.delay(photo_id)
-            except Exception as e:
-                logger.warning(f"Could not dispatch vision_fanout for {photo_id}: {e}")
-
             return {'status': 'success', 'photo_id': photo_id}
             
         except Exception as e: