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6959e1220c |
Revert "db: collapse alembic 0001..0087 into one baseline"
This reverts
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2529b516e6 |
db: collapse alembic 0001..0087 into one baseline (milestone 328 step 1)
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87 revisions narrating this project's build-out become one file that creates the schema in a single step. They cost nothing at runtime — all 86 upgrade steps ran in 0.2s (note #3260) — so this is a presentation change, not a performance one: a new installer should not inherit our development history to stand up a database. Deleted: 87 revisions (6,052 lines), the 10 tests/test_migration_*.py files (483 lines) that asserted intermediate states and backfills which no longer exist, and backend/app/utils/artist_backfill.py — the only live module a migration imported, with no other consumer anywhere. That last one satisfies the operator's separate request to inline it into 0008 and delete the module; the squash removes both outright. THE REVISION ID IS "0087", NOT "0001", ON PURPOSE. It is the id of the last revision collapsed, so an existing database is already at head and `alembic upgrade head` does nothing. The alternative is `alembic stamp` against live data, and stamp validates NOTHING — it writes a version string whether or not the schema matches, so a wrong baseline surfaces later, via the next real migration, with no clean way back. This removes that operation rather than making it safe. Future revisions run from 0088. Four things are hand-written because SQLAlchemy metadata does not carry them, and none fail at generation time: 1. CREATE EXTENSION vector — the VECTOR columns cannot be created without it, so it is ordered first in upgrade(). 2. CREATE EXTENSION tsm_system_rows — surfaces only when the random sample query runs. 3. the HNSW index on image_record.siglip_embedding, raw SQL because create_index cannot express USING hnsw (... vector_cosine_ops). The quietest of the four: everything works, similarity search just stops using an index. 4. import pgvector.sqlalchemy.vector — autogenerate EMITS pgvector.sqlalchemy.vector.VECTOR references without importing it, so the generated file dies with NameError on first run. The candidate came out of CI (run 4967) as checksummed base64 rather than a plain cat, because run 4964's cat was truncated mid-line inside a column definition with the step still green — 29 tables instead of 42, and it looked entirely plausible. Verified here: 56,582 bytes, sha256 471acfca69c0…, 42 tables, 66 indexes, 42 drops. NOT YET PROVEN against the old chain. baseline.yml does that, and it is step 2's gate; this commit does not claim the schemas match. |
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b91a230f12 |
feat(ccip): automation + reference quality — keep identity flowing hands-free (#114)
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
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