feat(ml): DB-backed tagger_store_floor (default 0.70), the ingest confidence floor

Promotes the prediction store-floor from the TAGGER_STORE_FLOOR env (default
0.05) to a DB-backed, Settings-UI-tunable ml_settings column (default 0.70).
Storing every tag down to 0.05 from a ~10k-tag tagger is what grew
image_record's TOAST to ~100 GB; the suggestion path already filters at 0.70
and the centroid/learned path covers lower-confidence preferred tags, so the
sub-0.70 tail is redundant. Foundation for plan-task #764 (backfill + reclaim
land next; this only changes the write gate for NEW imports).

- ml_settings.tagger_store_floor (migration 0044, default 0.70)
- tagger.Tagger.infer(store_floor=...); ml task passes settings.tagger_store_floor
- ML admin GET/PATCH expose it; PATCH rejects a category suggestion threshold
  below the floor (nothing below the floor is stored, so the gap surfaces
  nothing) — server backstop for the UI slider clamp
- Settings → ML: store-floor slider + caption; category sliders min-bound to it

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

tests/test_api_ml_admin.py

@@ -34,6 +34,28 @@ async def test_get_and_patch_settings(client):
     assert (await resp.get_json())["suggestion_threshold_general"] == pytest.approx(0.90)
 
 
+@pytest.mark.asyncio
+async def test_tagger_store_floor_default_and_patch(client):
+    body = await (await client.get("/api/ml/settings")).get_json()
+    assert body["tagger_store_floor"] == pytest.approx(0.70)
+
+    resp = await client.patch("/api/ml/settings", json={"tagger_store_floor": 0.6})
+    assert resp.status_code == 200
+    assert (await resp.get_json())["tagger_store_floor"] == pytest.approx(0.6)
+
+
+@pytest.mark.asyncio
+async def test_suggestion_threshold_below_store_floor_rejected(client):
+    # Invariant (#764): a category threshold can't sit below the store floor —
+    # nothing below the floor is stored, so the gap would surface nothing.
+    # Floor defaults to 0.70; pushing general down to 0.50 must 400.
+    resp = await client.patch(
+        "/api/ml/settings", json={"suggestion_threshold_general": 0.50}
+    )
+    assert resp.status_code == 400
+    assert "tagger_store_floor" in (await resp.get_json())["error"]
+
+
 @pytest.mark.asyncio
 async def test_backfill_and_recompute_trigger(client):
     r1 = await client.post("/api/ml/backfill")

tests/test_ml_tagger.py

@@ -1,14 +1,14 @@
 """Tagger unit tests. The ONNX model isn't available in CI (it's a 1GB
-download into /models), so these test the pure-logic surface: STORE_FLOOR
-constant, SURFACED_CATEGORIES set, TagPrediction dataclass, and the
-load()-missing-file error path. Full inference is exercised by the local
-integration suite against a real /models volume.
+download into /models), so these test the pure-logic surface:
+DEFAULT_STORE_FLOOR constant, SURFACED_CATEGORIES set, TagPrediction
+dataclass, and the load()-missing-file error path. Full inference is
+exercised by the local integration suite against a real /models volume.
 """
 
 import pytest
 
 from backend.app.services.ml.tagger import (
-    STORE_FLOOR,
+    DEFAULT_STORE_FLOOR,
     SURFACED_CATEGORIES,
     Tagger,
     TagPrediction,
@@ -26,8 +26,12 @@ def test_surfaced_categories():
     assert "copyright" not in SURFACED_CATEGORIES
 
 
-def test_store_floor_is_low():
-    assert 0 < STORE_FLOOR < 0.2
+def test_default_store_floor():
+    # Raised 0.05 → 0.70 (plan-task #764): the suggestion path filters at
+    # 0.70 and the centroid path covers lower-confidence preferred tags, so
+    # storing the sub-0.70 tail was redundant (100 GB of TOAST). The live
+    # value is DB-backed (ml_settings.tagger_store_floor); this is the default.
+    assert DEFAULT_STORE_FLOOR == 0.70
 
 
 def test_tag_prediction_dataclass():