refactor(ml): DRY pass — shared sweep helpers + table-driven settings (#161)

Consolidate duplication accrued across the ML tagging + settings backend,
behavior-preserving (over-DRY guard applied — the three auto-apply sweep
BODIES stay separate; only their shared inner helpers are extracted).

- _sigmoid / _conflict_scores / _insert_presentation_review (heads.py): the
  score→prob transform (6 inlined sites), the presentation conflict signal
  (2 sites), and the ring-loud PresentationReview insert (2 sites, single-
  sourced so the mode column can't drift on the shared composite PK).
- _applied_or_rejected (training_data.py): the per-tag "applied ∪ rejected"
  skip-set, byte-identical at 3 sweep sites (heads.py x2, tasks/ml.py ccip).
- ccip sweep divergence fixes: import ccip._FIGURE_KINDS + training_data._l2norm
  instead of local copies that silently drift when the canonical changes.
- MLSettings.load / .load_sync classmethods (mirror ImportSettings); route all
  8 scalar_one singleton reads through them (the session.get None-path stays).
- GET serializers for MLSettings + ImportSettings are now table-driven off the
  same _EDITABLE tuples PATCH writes, so a new field can't be silently absent
  from GET (the split that historically dropped fields).
- AUTO_APPLY_THRESHOLD_MIN/MAX constant single-sources the [0.5,0.999] operating
  range across the service clamp + the 5 API validators.
- test_ml_dry_helpers.py pins _applied_or_rejected + _sigmoid.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NsmJSQxnNxGgtM5Yz4GAqi

tests/test_ml_dry_helpers.py

@@ -0,0 +1,59 @@
+"""Shared ML helpers extracted in the DRY pass (milestone #161). These pin the
+single sources the auto-apply sweeps now trust, so a future edit can't silently
+drift them: `_applied_or_rejected` is the skip-set used by auto_apply_sweep,
+system_tag_auto_apply_sweep (heads.py) and scheduled_ccip_auto_apply (tasks/ml.py);
+`_sigmoid` is the head score→prob transform used at every scoring site."""
+import pytest
+
+from backend.app.models import ImageRecord, Tag, TagKind, TagSuggestionRejection
+from backend.app.models.tag import image_tag
+from backend.app.services.ml.training_data import _applied_or_rejected
+
+
+def test_sigmoid_matches_naive_form():
+    import numpy as np
+
+    from backend.app.services.ml.heads import _sigmoid
+
+    z = np.array([-3.0, -0.5, 0.0, 1.5, 12.0], dtype=np.float32)
+    assert np.allclose(_sigmoid(z, np), 1.0 / (1.0 + np.exp(-z)))
+    assert float(_sigmoid(np.array([0.0]), np)[0]) == pytest.approx(0.5)
+
+
+@pytest.mark.integration
+def test_applied_or_rejected_unions_applied_any_source_and_rejected(db_sync):
+    a = Tag(name="dry-helper-a", kind=TagKind.general)
+    b = Tag(name="dry-helper-b", kind=TagKind.general)
+    db_sync.add_all([a, b])
+    db_sync.flush()
+
+    imgs = []
+    for i in range(5):
+        img = ImageRecord(
+            path=f"/images/dryhelp{i}.jpg", sha256=f"{i:064d}", size_bytes=1,
+            mime="image/jpeg", width=1, height=1, origin="imported_filesystem",
+            integrity_status="unknown", siglip_embedding=[0.0] * 1152,
+        )
+        db_sync.add(img)
+        imgs.append(img)
+    db_sync.flush()
+
+    # tag a: applied manually (img0), applied by an AUTO source (img1), rejected (img2).
+    db_sync.execute(image_tag.insert().values(
+        image_record_id=imgs[0].id, tag_id=a.id, source="manual"))
+    db_sync.execute(image_tag.insert().values(
+        image_record_id=imgs[1].id, tag_id=a.id, source="head_auto"))
+    db_sync.add(TagSuggestionRejection(image_record_id=imgs[2].id, tag_id=a.id))
+    # tag b: applied to img3 only.
+    db_sync.execute(image_tag.insert().values(
+        image_record_id=imgs[3].id, tag_id=b.id, source="manual"))
+    db_sync.flush()
+
+    skip = _applied_or_rejected(db_sync, [a.id, b.id])
+
+    # Applied-under-ANY-source (manual + head_auto) ∪ rejected, kept per-tag; the
+    # untouched image (img4) appears under neither tag.
+    assert skip[a.id] == {imgs[0].id, imgs[1].id, imgs[2].id}
+    assert skip[b.id] == {imgs[3].id}
+    assert imgs[4].id not in skip[a.id]
+    assert imgs[4].id not in skip[b.id]