feat(fc2b): add tag_and_embed + backfill Celery tasks

tag_and_embed: Camie + SigLIP on one image (video → 10-frame sample,
max-pool tags, mean-pool embeddings), stores predictions/embedding with
model versions, then enqueues per-image allowlist apply. backfill:
keyset-paginated discovery of images missing predictions/embeddings for
the current model versions (restart-safe). apply_allowlist_tags stub
included so .delay() resolves between commits (filled in Task 9).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

tests/test_tasks_ml.py

@@ -0,0 +1,54 @@
+"""tag_and_embed / backfill task tests. Models aren't in CI, so we test
+the pure helpers (_maxpool_predictions, _is_video) as unit tests, and the
+DB-touching backfill query as an integration test with monkeypatched
+inference.
+"""
+
+from pathlib import Path
+
+import pytest
+
+from backend.app.services.ml.tagger import TagPrediction
+from backend.app.tasks.ml import _is_video, _maxpool_predictions
+
+
+def test_is_video():
+    assert _is_video(Path("a.mp4")) is True
+    assert _is_video(Path("a.MKV")) is True
+    assert _is_video(Path("a.jpg")) is False
+
+
+def test_maxpool_predictions():
+    f1 = {"smile": TagPrediction("smile", "general", 0.6)}
+    f2 = {
+        "smile": TagPrediction("smile", "general", 0.9),
+        "sword": TagPrediction("sword", "general", 0.7),
+    }
+    merged = _maxpool_predictions([f1, f2])
+    assert merged["smile"]["confidence"] == 0.9
+    assert merged["sword"]["confidence"] == 0.7
+
+
+@pytest.mark.integration
+@pytest.mark.asyncio
+async def test_backfill_enqueues_missing(db, monkeypatch):
+    from backend.app.models import ImageRecord
+    from backend.app.tasks import ml as ml_tasks
+
+    calls = []
+    monkeypatch.setattr(
+        ml_tasks.tag_and_embed, "delay", lambda image_id: calls.append(image_id)
+    )
+
+    img = ImageRecord(
+        path="/images/n.jpg", sha256="n" * 64, size_bytes=1,
+        mime="image/jpeg", width=1, height=1,
+        origin="imported_filesystem", integrity_status="unknown",
+        tagger_predictions=None, siglip_embedding=None,
+    )
+    db.add(img)
+    await db.commit()
+
+    count = ml_tasks.backfill()
+    assert count >= 1
+    assert img.id in calls