refactor(ml): retire the Camie tagger + allowlist bulk-apply (#1189)

Heads + CCIP are the tag source and head auto-apply is the earned propagation.
The Camie tagger ran only to feed the allowlist bulk-apply (its ImagePrediction
rows had no other consumer), and the allowlist was a SECOND, un-earned auto-apply
path firing in parallel with heads on every accept — exactly the un-earned spray
the v2 pivot replaced. Retire both.

Behavior change: accepting a suggestion now applies the tag to THAT image only
(source='ml_accepted', a head-training positive) — it no longer allowlists +
fans the tag across the library via Camie. Propagation is heads' earned
auto-apply. (Loses instant cold-start propagation for booru-vocab tags; that was
un-earned and bypassed the precision gate.)

- tag_and_embed is now EMBED-ONLY (no Camie load/infer, no ImagePrediction
  writes); backfill enqueues it for images with no embedding.
- Removed: services/ml/tagger.py, apply_allowlist_tags + helpers + daily beat +
  every enqueue caller (accept/alias/merge/per-image), api/allowlist.py +
  blueprint, ImagePrediction + TagAllowlist models/tables (migration 0067),
  AllowlistTable.vue + allowlist store, the accept coverage-projection payload.
- AllowlistService gutted to accept/dismiss/undismiss/reject (the rejection store
  the rail still needs); accept returns nothing, API returns {accepted, tag_id}.
- tag merge no longer repoints/triggers the allowlist; _keep_as_alias now keys on
  ML-applied image_tag sources (incl. head_auto) instead of the allowlist.
- UI: MLBackfillCard relabelled to embedding-only; accept toast simplified;
  MaintenancePanel drops the allowlist tile.

Left for a follow-up hygiene pass (now-inert, harmless): the dead settings
columns (tagger_store_floor, tagger_model_version, suggestion_threshold_*,
video_min_tag_frames), image_record.tagger_model_version, MLThresholdSliders
trim, and the Camie model download in download_models.py.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa

tests/test_phash_dedup.py

@@ -11,7 +11,6 @@ from PIL import Image
 from sqlalchemy import func, select
 
 from backend.app.models import (
-    ImagePrediction,
     ImageProvenance,
     ImageRecord,
     ImportSettings,
@@ -119,11 +118,6 @@ def test_smaller_existing_is_superseded(importer, import_layout):
             image_record_id=eid, tag_id=tag.id, source="manual"
         )
     )
-    importer.session.add(
-        ImagePrediction(
-            image_record_id=eid, raw_name="x", category="general", score=0.9
-        )
-    )
     old.siglip_embedding = [0.0] * 1152
     old.integrity_status = "ok"
     importer.session.commit()
@@ -141,11 +135,6 @@ def test_smaller_existing_is_superseded(importer, import_layout):
     assert row.path != old_path
     assert row.phash is not None
     assert row.integrity_status == "unknown"
-    # #768: re-import clears the normalized predictions too
-    assert importer.session.execute(
-        select(func.count()).select_from(ImagePrediction)
-        .where(ImagePrediction.image_record_id == eid)
-    ).scalar_one() == 0
     assert row.siglip_embedding is None
     linked = importer.session.execute(
         select(image_tag.c.tag_id).where(