feat(suggestions): overlay CCIP character matches onto the rail (#114)

SuggestionService.for_image now merges CCIP character matches with the SigLIP
head suggestions — they're complementary, not exclusive: CCIP is the identity-
specialized signal but needs a detected figure; the heads work whole-image but
conflate identity with style. Merged by tag: 'both' when they corroborate
(higher score wins), 'ccip' / 'head' otherwise. Cheap when no CCIP vectors exist
yet (match_image returns early without a figure vector), so it's a no-op until
the agent runs. Suggestion.source is now 'head' | 'ccip' | 'both'.

Test: a character with a CCIP reference figure surfaces (source='ccip') on a new
image whose figure matches.

NEXT: the agent container (real CCIP/detector models, hands-on) that produces the
vectors this consumes.

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

tests/test_ml_suggestions.py

@@ -4,7 +4,7 @@ scikit-learn, ml image only); scoring is numpy-only (available via pgvector)."""
 import pytest
 from sqlalchemy import select
 
-from backend.app.models import ImageRecord, MLSettings, TagHead, TagKind
+from backend.app.models import ImageRecord, ImageRegion, MLSettings, TagHead, TagKind
 from backend.app.models.tag import image_tag
 from backend.app.services.ml.allowlist import AllowlistService
 from backend.app.services.ml.suggestions import SuggestionService
@@ -131,3 +131,35 @@ async def test_rejected_tag_surfaced_flagged_then_reversible(db):
     sl2 = await SuggestionService(db).for_image(img.id)
     s2 = next(x for x in sl2.by_category["general"] if x.canonical_tag_id == tag.id)
     assert s2.rejected is False
+
+
+async def _figure(db, image_id, slot):
+    v = [0.0] * 768
+    v[slot] = 1.0
+    db.add(ImageRegion(
+        image_record_id=image_id, kind="figure",
+        rx=0.0, ry=0.0, rw=1.0, rh=1.0,
+        ccip_embedding=v, embedding_version="ccip-test",
+    ))
+
+
+@pytest.mark.asyncio
+async def test_ccip_character_surfaces_in_rail(db):
+    # A character with a CCIP reference (a tagged figure) is suggested on a new
+    # image whose figure matches — overlaid into the rail alongside the heads.
+    raven = await TagService(db).find_or_create("Raven", TagKind.character)
+    ref = await _img(db, "0" * 64, None)         # the operator's tagged example
+    await _figure(db, ref.id, slot=0)
+    await db.execute(image_tag.insert().values(
+        image_record_id=ref.id, tag_id=raven.id, source="manual",
+    ))
+    query = await _img(db, "1" * 64, None)        # untagged, matching figure
+    await _figure(db, query.id, slot=0)
+    await db.commit()
+
+    sl = await SuggestionService(db).for_image(query.id)
+    m = next(
+        c for c in sl.by_category.get("character", [])
+        if c.canonical_tag_id == raven.id
+    )
+    assert m.source == "ccip"