2 Commits

Include renames

Author	SHA1	Message	Date
bvandeusen	5e1996e77f	db: reconcile the models with the deployed schema (#3275) ... Milestone 328's acceptance test compared a database built by the real 0001..0087 chain against one built from the models, and found ~130 places where they disagree. This closes them. Almost all were the MODEL being wrong, so almost all of this is model edits with no DDL — the database already had these things, nothing in it changes, and no deploy is needed for this part: * 92 columns gained server_default. The models carried Python-side `default=` only, so the ORM filled the value and the column had no database default. Anything inserting outside the ORM behaved differently from production. * Eleven indexes that existed only in migrations are now declared: the three backup_run reporting indexes, the two date-ordered image_record browse indexes, import_task and presentation_review, and the three task_run history indexes. All use text() for their DESC ordering and postgresql_where for the partial one. * Two UNIQUE indexes that autogenerate silently proposed DROPPING, because neither is expressible as a UniqueConstraint: uq_tag_name_kind_fandom — an EXPRESSION index over (name, kind, COALESCE(fandom_id, 0)) uq_post_artist_external_id_null_source — PARTIAL, WHERE source_id IS NULL post.py already had a comment describing the second one. The comment was right; nothing declared it. * The two external_link enum CHECKs (host, status) — rule 36 territory, and absent from the model entirely. * Two indexes were named explicitly. A bare index=True generated ix_tag_alias_canonical_tag_id where the database has ix_tag_alias_canonical, so autogenerate proposed a drop+create of an index that was already there under another name. Same for tag_suggestion_rejection. Only ONE thing needed DDL, as 0088: tag.fandom_id is declared index=True but no migration ever created that index. Deliberately NOT here: image_record.sha256. The model says unique=True; 0001 created a plain index. Duplicates are possible today and the ORM believes otherwise. The fix depends on whether duplicates already exist — if they do, that is a dedupe decision, not a constraint — so it waits on an answer about live data. The real severity of #3275 is not the squash. It is that --autogenerate has been unsafe on this project: run against the old models it would have proposed dropping eleven indexes and two uniqueness guarantees.	2026-08-30 14:42:30 -04:00
bvandeusenandClaude Opus 4.8	48c8811d69	feat(heads): auto-apply observability + on by default (#114 auto-apply B) ... Auto-apply is now ON by default (operator-asked: opt-OUT, not opt-in) — migration 0059 + model default flipped. The support (>=30) + measured-precision gates keep it safe and every auto-tag is reversible. Observability so the operator can tune from real data: - MISFIRE = an auto-applied (source='head_auto') tag the operator later removes. UNDER-FIRE = a tag with a head the operator adds by hand (the head missed it). Both captured at correction time in TagService.add_to_image/remove_from_image (source is lost on delete) into durable per-tag counters (head_metric), keyed by tag so they survive head retrain/prune. - Daily snapshot_head_metrics writes a per-concept time-series point (head_metrics_snapshot): auto-applied volume + cumulative misfires/under-fires + head quality; 180-day retention; daily beat. - GET /api/heads/metrics: per-concept current counts + realized misfire rate + head quality, plus the snapshot time-series — the report to tune the precision target + support floor. Migration 0060. Tests: misfire/under-fire counting (and the negatives — manual removal isn't a misfire, headless manual add isn't an under-fire), snapshot time-series, metrics API. What's the autofire threshold? There's no single number — each graduated head derives its OWN probability cutoff from its PR curve: the operating point that holds precision >= head_auto_apply_precision (0.97) at max recall. The global knobs are that target + the >=30 support floor. NEXT (slice 3): UI — enable toggle, dry-run preview, per-concept trends. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa	2026-06-29 00:36:58 -04:00