b91a230f12
Works through the optional CCIP ideas + the "keep moving even if I forget" ask:
AUTOMATION (no button needed):
- Hourly beat auto-enqueues CCIP backfill — new images get embedded (and errored
ones retried) on their own; the queue never goes idle waiting for a click.
- CCIP auto-apply: a daily sweep tags confident matches (source='ccip_auto') so
identity tags keep flowing. ON by default (opt-out, like head auto-apply);
ml_settings.ccip_auto_apply_enabled + _threshold (0.92, above the suggest cut),
migration 0064. Vectorized (one matmul + reduceat per image), reversible, skips
already-applied/rejected. Switch + threshold in the GPU agent card; GET/PATCH
/api/ml/settings; auto_applied count in /api/ccip/overview.
REFERENCE QUALITY (the over-fire root cause):
- character_references now draws ONLY from single-character images — on a
multi-character image the tag is image-level, so every figure would otherwise
pollute each character's prototypes (a 2-char image tagged 'Velma' made
Daphne's figure a Velma reference). This is the contamination behind residual
over-firing.
- Cached on a cheap signature (char-tag count + ccip-region count/max-id) so the
reference load isn't redone on every modal open.
Tests: multi-character image not used as a reference; auto-apply tags a confident
match as ccip_auto.
NEXT (not done, confirmed): comic-panel cropping + SigLIP concept crops ("spot
interesting content").
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
144 lines
5.3 KiB
Python
144 lines
5.3 KiB
Python
"""CCIP few-shot character matcher (#114). numpy cosine on stored vectors — no
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model needed, so it runs in CI with synthetic CCIP vectors."""
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import pytest
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from sqlalchemy import select
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from backend.app.models import ImageRecord, ImageRegion, TagKind
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from backend.app.models.tag import image_tag
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from backend.app.services.ml.ccip import match_image
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from backend.app.services.tag_service import TagService
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pytestmark = pytest.mark.integration
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def _ccip(slot: int) -> list[float]:
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v = [0.0] * 768
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v[slot] = 1.0
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return v
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async def _img(db, sha) -> ImageRecord:
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img = ImageRecord(
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path=f"/images/{sha}.jpg", sha256=sha, size_bytes=1, mime="image/jpeg",
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width=1, height=1, origin="imported_filesystem", integrity_status="unknown",
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)
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db.add(img)
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await db.flush()
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return img
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async def _figure(db, image_id, ccip):
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db.add(ImageRegion(
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image_record_id=image_id, kind="figure",
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rx=0.0, ry=0.0, rw=1.0, rh=1.0,
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ccip_embedding=ccip, embedding_version="ccip-test",
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))
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async def _tag_image(db, image_id, tag_id):
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await db.execute(image_tag.insert().values(
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image_record_id=image_id, tag_id=tag_id, source="manual",
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))
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@pytest.mark.asyncio
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async def test_matches_same_character_across_images(db):
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raven = await TagService(db).find_or_create("Raven", TagKind.character)
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ref = await _img(db, "a" * 64) # a tagged example = a prototype
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await _figure(db, ref.id, _ccip(0))
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await _tag_image(db, ref.id, raven.id)
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query = await _img(db, "b" * 64) # untagged, near-identical figure
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await _figure(db, query.id, _ccip(0))
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await db.commit()
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matches = await match_image(db, query.id)
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m = next(x for x in matches if x["tag_id"] == raven.id)
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assert m["source"] == "ccip" and m["category"] == "character"
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assert m["score"] > 0.9
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@pytest.mark.asyncio
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async def test_no_match_for_different_character(db):
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raven = await TagService(db).find_or_create("Raven", TagKind.character)
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ref = await _img(db, "c" * 64)
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await _figure(db, ref.id, _ccip(0))
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await _tag_image(db, ref.id, raven.id)
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query = await _img(db, "d" * 64)
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await _figure(db, query.id, _ccip(5)) # orthogonal → not Raven
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await db.commit()
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assert await match_image(db, query.id) == []
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@pytest.mark.asyncio
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async def test_excludes_already_applied_character(db):
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raven = await TagService(db).find_or_create("Raven", TagKind.character)
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ref = await _img(db, "e" * 64)
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await _figure(db, ref.id, _ccip(0))
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await _tag_image(db, ref.id, raven.id)
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query = await _img(db, "f" * 64)
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await _figure(db, query.id, _ccip(0))
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await _tag_image(db, query.id, raven.id) # already tagged → no re-suggest
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await db.commit()
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assert all(m["tag_id"] != raven.id for m in await match_image(db, query.id))
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@pytest.mark.asyncio
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async def test_no_figure_vectors_means_no_match(db):
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query = await _img(db, "g" * 64)
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await db.commit()
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assert await match_image(db, query.id) == []
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@pytest.mark.asyncio
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async def test_threshold_gates_borderline_match(db):
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# A figure ~0.9 cosine from the reference: matched at 0.85, dropped at 0.95.
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raven = await TagService(db).find_or_create("Raven", TagKind.character)
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ref = await _img(db, "h" * 64)
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await _figure(db, ref.id, _ccip(0)) # e0
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await _tag_image(db, ref.id, raven.id)
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near = [0.0] * 768
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near[0], near[1] = 0.9, 0.4359 # |·|=1, cos(e0)=0.9
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query = await _img(db, "i" * 64)
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await _figure(db, query.id, near)
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await db.commit()
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assert any(m["tag_id"] == raven.id for m in await match_image(db, query.id, 0.85))
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assert await match_image(db, query.id, 0.95) == []
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@pytest.mark.asyncio
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async def test_multi_character_image_not_used_as_reference(db):
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# A figure on a 2-character image is ambiguous (tag is image-level), so it
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# must NOT seed either character's prototypes — else it'd match both.
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raven = await TagService(db).find_or_create("Raven", TagKind.character)
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daphne = await TagService(db).find_or_create("Daphne", TagKind.character)
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multi = await _img(db, "j" * 64)
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await _figure(db, multi.id, _ccip(0))
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await _tag_image(db, multi.id, raven.id)
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await _tag_image(db, multi.id, daphne.id)
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query = await _img(db, "k" * 64)
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await _figure(db, query.id, _ccip(0)) # identical to the ambiguous figure
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await db.commit()
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assert await match_image(db, query.id) == [] # no clean references → nothing
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@pytest.mark.asyncio
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async def test_auto_apply_tags_confident_match(db):
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raven = await TagService(db).find_or_create("Raven", TagKind.character)
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ref = await _img(db, "l" * 64)
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await _figure(db, ref.id, _ccip(0))
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await _tag_image(db, ref.id, raven.id) # single-character reference
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query = await _img(db, "m" * 64)
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await _figure(db, query.id, _ccip(0)) # identical → cosine 1.0
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await db.commit()
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from backend.app.tasks.ml import scheduled_ccip_auto_apply
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assert "applied=" in scheduled_ccip_auto_apply() # sync task, own session
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rows = (await db.execute(
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select(image_tag.c.tag_id, image_tag.c.source).where(
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image_tag.c.image_record_id == query.id
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)
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)).all()
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assert (raven.id, "ccip_auto") in [(t, s) for t, s in rows]
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