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/config.py

@@ -30,19 +30,6 @@ class PerformanceSettings(BaseModel):
     db_pool_max_overflow: int = 10
     db_pool_recycle: int = 3600
 
-class ClassifierSettings(BaseModel):
-    """Binary content classifier (photography vs other)."""
-    min_confidence: float = 0.3
-
-class VisionSettings(BaseModel):
-    """Vision pipeline — one binary classifier (photography vs other)."""
-    enabled: bool = True
-    backend: str = "onnx"
-    models_dir: str = "/data/models"
-    execution_providers: list[str] = ["CPUExecutionProvider"]
-    classifier: ClassifierSettings = ClassifierSettings()
-    worker_concurrency: int = 2
-
 class MulitaConfig(BaseModel):
     """Main configuration from YAML file. Source roots and the discard
     workflow are owned by the database now — only operational settings
@@ -50,13 +37,12 @@ class MulitaConfig(BaseModel):
     thumbnails: ThumbnailSettings = ThumbnailSettings()
     scanner: ScannerSettings = ScannerSettings()
     performance: PerformanceSettings = PerformanceSettings()
-    vision: VisionSettings = VisionSettings()
 
 class Settings(BaseSettings):
     """Application settings"""
-    # Database — Postgres + pgvector by default. The SQLite escape hatch
-    # remains supported via the docker-compose.sqlite.yml override and by
-    # setting DATABASE_URL=sqlite+aiosqlite:///... in .env for local dev.
+    # Database — plain Postgres. The SQLite escape hatch remains
+    # supported via the docker-compose.sqlite.yml override and by setting
+    # DATABASE_URL=sqlite+aiosqlite:///... in .env for local dev.
     database_url: str = Field(
         default="postgresql+asyncpg://mulita:mulita@db:5432/mulita",
         env="DATABASE_URL"
@@ -195,23 +181,6 @@ class Settings(BaseSettings):
     def performance(self) -> PerformanceSettings:
         return self.config.performance
 
-    # ONNX Runtime execution providers, overridable via env var.
-    # Comma-separated: "CUDAExecutionProvider,CPUExecutionProvider"
-    # or "auto" for GPU auto-detection.
-    vision_execution_providers: str = Field(
-        default="CPUExecutionProvider",
-        env="VISION_EXECUTION_PROVIDERS",
-    )
-
-    @property
-    def vision(self) -> VisionSettings:
-        v = self.config.vision
-        # Override execution_providers from env if set.
-        providers = [p.strip() for p in self.vision_execution_providers.split(",") if p.strip()]
-        if providers:
-            v.execution_providers = providers
-        return v
-
     class Config:
         env_file = ".env"
         case_sensitive = False