refactor: strip AI pipeline to binary photo/other classifier

Drops face recognition, OCR, object detection, and semantic embeddings.
The sole remaining vision task is a CLIP-based binary classifier
(photography vs other); photos in "other" get needs_review=true so
screenshots, documents, memes and scans can be triaged from a new
filter pill in the UI.

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

backend/app/models/photos.py

@@ -50,6 +50,11 @@ class Photo(Base):
     # rows, and POST /folders/{id}/hide recomputes it on toggle.
     is_hidden = Column(Boolean, nullable=False, default=False, server_default='false', index=True)
 
+    # "Needs review" — set by the content classifier when a photo is
+    # classified as 'other' (screenshot, document, meme, scan, etc.) so
+    # the user can page through non-photographs in the UI and triage them.
+    needs_review = Column(Boolean, nullable=False, default=False, server_default='false', index=True)
+
     # "Capture date is probably wrong" — denormalized from the folder/filename
     # date-guesser. Set at scan time and recomputed on every taken_at edit so
     # the filter bar can query it directly. See services/date_guess.py for
@@ -118,4 +123,5 @@ class Photo(Base):
         Index('ix_photos_media_type', 'media_type'),
         Index('ix_photos_processing_status', 'processing_status'),
         Index('ix_photos_lat_lon', 'latitude', 'longitude'),
+        Index('ix_photos_needs_review', 'needs_review'),
     )