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/routers/library.py

@@ -102,12 +102,6 @@ async def get_library_stats(
         )
     ).scalar() or 0
 
-    needs_review_count = (
-        await db.execute(
-            select(func.count(Photo.id)).where(visible, Photo.needs_review.is_(True))
-        )
-    ).scalar() or 0
-
     # Legacy split (kept for the existing /stats consumers).
     photo_count = (
         await db.execute(
@@ -134,7 +128,6 @@ async def get_library_stats(
         "with_gps": with_gps_count,
         "duplicates": duplicates_count,
         "discarded": discarded_count,
-        "needs_review": needs_review_count,
         "total_photos": photo_count,
         "total_videos": video_count,
         "total_size": size,
@@ -465,8 +458,7 @@ async def get_worker_status(
         r = _redis.Redis.from_url(settings.redis_url, socket_timeout=1.0)
         r.ping()
         broker_ok = True
-        # `vision` runs the content classifier — the only heavy queue.
-        for q in ('default', 'high', 'low', 'vision'):
+        for q in ('default', 'high', 'low'):
             try:
                 queue_depths[q] = int(r.llen(q) or 0)
             except Exception:
@@ -595,17 +587,6 @@ async def get_pipeline_stats(
         )
     )
 
-    # Classified: distinct photos with a content_type tag.
-    classified_done = await scalar_count(
-        select(func.count(func.distinct(photo_tags.c.photo_id)))
-        .select_from(photo_tags)
-        .join(Photo, Photo.id == photo_tags.c.photo_id)
-        .where(not_discarded, photo_tags.c.source == 'vision:clip_classifier')
-    )
-    needs_review_count = await scalar_count(
-        select(func.count(Photo.id)).where(not_discarded, Photo.needs_review.is_(True))
-    )
-
     duplicate_groups = await scalar_count(
         select(func.count(func.distinct(Photo.duplicate_group_id))).where(
             not_discarded, Photo.duplicate_group_id.is_not(None)
@@ -649,13 +630,6 @@ async def get_pipeline_stats(
             "total": total_images,
             "hint": "Feeds duplicate detection.",
         },
-        {
-            "key": "classification",
-            "label": "Content classification (photo vs other)",
-            "done": classified_done,
-            "total": total_images,
-            "hint": f"{needs_review_count} photos flagged for review.",
-        },
         {
             "key": "duplicates",
             "label": "Duplicate groups",