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>

backend/app/api/ml_admin.py

@@ -13,6 +13,7 @@ _EDITABLE = (
     "suggestion_threshold_general",
     "centroid_similarity_threshold",
     "min_reference_images",
+    "tagger_store_floor",
 )
 
 
@@ -30,6 +31,7 @@ async def get_settings():
             "suggestion_threshold_general": s.suggestion_threshold_general,
             "centroid_similarity_threshold": s.centroid_similarity_threshold,
             "min_reference_images": s.min_reference_images,
+            "tagger_store_floor": s.tagger_store_floor,
             "tagger_model_version": s.tagger_model_version,
             "embedder_model_version": s.embedder_model_version,
         }
@@ -47,13 +49,45 @@ async def patch_settings():
         s = (
             await session.execute(select(MLSettings).where(MLSettings.id == 1))
         ).scalar_one()
+
+        # Merge the patch over current values, then validate the result as a
+        # whole — the store-floor invariant couples three fields, so they
+        # can't be checked one at a time.
+        proposed = {f: getattr(s, f) for f in _EDITABLE}
         for field in _EDITABLE:
             if field in body:
-                setattr(s, field, body[field])
+                proposed[field] = body[field]
+
+        err = _validate(proposed)
+        if err is not None:
+            return jsonify({"error": err}), 400
+
+        for field in _EDITABLE:
+            setattr(s, field, proposed[field])
         await session.commit()
     return await get_settings()
 
 
+def _validate(p: dict) -> str | None:
+    """Returns an error string if the proposed settings are invalid, else None.
+
+    Invariant (plan-task #764): the per-category suggestion thresholds can't
+    drop below tagger_store_floor — nothing below the floor is stored, so a
+    lower threshold would silently surface nothing in that gap. The UI clamps
+    the sliders to the floor; this is the server-side backstop.
+    """
+    floor = p["tagger_store_floor"]
+    if not (0.0 <= floor <= 1.0):
+        return "tagger_store_floor must be between 0 and 1"
+    for cat in ("character", "general"):
+        if p[f"suggestion_threshold_{cat}"] < floor:
+            return (
+                f"suggestion_threshold_{cat} cannot be below tagger_store_floor "
+                f"({floor}) — predictions below the floor are not stored"
+            )
+    return None
+
+
 @ml_admin_bp.route("/backfill", methods=["POST"])
 async def trigger_backfill():
     from ..tasks.ml import backfill