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/alembic/env.py

@@ -38,7 +38,6 @@ from app.models import (  # noqa: E402, F401
     Tag,
     Heap,
     HeapPhoto,
-    Embedding,
 )
 
 config = context.config

backend/alembic/versions/0012_strip_ai_pipeline.py

@@ -0,0 +1,65 @@
+"""Strip AI pipeline to binary classifier only
+
+Revision ID: 0012_strip_ai
+Revises: 0011_sharing
+Create Date: 2026-04-14
+
+Removes face recognition, OCR, object detection, and semantic embeddings.
+The remaining AI is a single binary 'photography' vs 'other' classifier
+whose output feeds Tag(kind='content_type') and a new Photo.needs_review
+flag.
+
+Drops: embeddings, face_embeddings, ocr_text tables.
+Drops: photo_tags rows produced by 'vision:yolov8n' and 'vision:sface'.
+Drops: tags with kind IN ('object','scene','face_cluster').
+Drops: tags.representative_photo_id column.
+Adds:  photos.needs_review (bool, default false) + partial index.
+"""
+from typing import Sequence, Union
+
+from alembic import op
+
+revision: str = "0012_strip_ai"
+down_revision: Union[str, None] = "0011_sharing"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    # Drop dropped-AI tables. CASCADE clears any lingering FKs/indices.
+    op.execute("DROP TABLE IF EXISTS embeddings CASCADE")
+    op.execute("DROP TABLE IF EXISTS face_embeddings CASCADE")
+    op.execute("DROP TABLE IF EXISTS ocr_text CASCADE")
+
+    # Clear ML-produced photo_tags rows and their parent tags.
+    op.execute(
+        "DELETE FROM photo_tags WHERE source IN ('vision:yolov8n','vision:sface')"
+    )
+    op.execute(
+        "DELETE FROM tags WHERE kind IN ('object','scene','face_cluster')"
+    )
+
+    # Drop the face-cluster representative column.
+    op.execute("ALTER TABLE tags DROP COLUMN IF EXISTS representative_photo_id")
+
+    # Add the needs_review flag.
+    op.execute(
+        "ALTER TABLE photos ADD COLUMN IF NOT EXISTS needs_review "
+        "BOOLEAN NOT NULL DEFAULT false"
+    )
+    op.execute(
+        "CREATE INDEX IF NOT EXISTS ix_photos_needs_review "
+        "ON photos(needs_review) WHERE needs_review"
+    )
+
+
+def downgrade() -> None:
+    # Data is not recoverable on downgrade — only the schema stubs are
+    # put back so a future reinstall of the old pipeline can re-populate.
+    op.execute("DROP INDEX IF EXISTS ix_photos_needs_review")
+    op.execute("ALTER TABLE photos DROP COLUMN IF EXISTS needs_review")
+
+    op.execute(
+        "ALTER TABLE tags ADD COLUMN IF NOT EXISTS representative_photo_id "
+        "VARCHAR REFERENCES photos(id) ON DELETE SET NULL"
+    )

backend/alembic/versions/0013_drop_old_content_types.py

@@ -0,0 +1,35 @@
+"""Drop legacy content_type tags from the 6-category classifier
+
+Revision ID: 0013_drop_old_ct
+Revises: 0012_strip_ai
+Create Date: 2026-04-14
+
+The previous classifier wrote Tag(kind='content_type', name IN
+('photograph','screenshot','document','receipt','meme','artwork')).
+The new binary classifier writes names ('photography','other'). Both
+coexisted after the cutover so users saw duplicate groupings like
+'photography' alongside 'photograph'. Drop the old names — photo_tags
+rows cascade-delete via the FK.
+"""
+from typing import Sequence, Union
+
+from alembic import op
+
+revision: str = "0013_drop_old_ct"
+down_revision: Union[str, None] = "0012_strip_ai"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+LEGACY_NAMES = ('photograph', 'screenshot', 'document', 'receipt', 'meme', 'artwork')
+
+
+def upgrade() -> None:
+    op.execute(
+        "DELETE FROM tags WHERE kind = 'content_type' "
+        f"AND name IN {LEGACY_NAMES}"
+    )
+
+
+def downgrade() -> None:
+    pass