The read path: load tagger_predictions, drop unsurfaced categories
(rating/meta/year), apply per-category thresholds, batch-resolve aliases,
skip applied + rejected, augment with centroid hits above the similarity
threshold, merge duplicate signals (take max score, mark source 'both'),
group by category, sort by score DESC. Tests marked integration.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
recompute_for_tag (mean of member embeddings, eligible-kind + min-refs
gated, upsert), list_drifted (the delta-gate: member-count mismatch OR
missing OR wrong model version), find_similar_tags (pgvector cosine
distance, similarity = 1 - distance). Tests marked integration.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
resolve() / resolve_many() (batch, used by the suggestion read path),
idempotent create, remove, list_all. Category-scoped so 'naruto' as
character vs copyright map to different canonicals. Tests marked
integration (real DB).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Direct port of ImageRepo's siglip.py. Lazy torch/transformers import so
the web container can import the module (for enqueue logic) without the
torch cost. EMBED_DIM=1152 asserted against the schema's Vector(1152)
columns. Real inference runs in the local integration suite.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
CPU-only, lazy-loaded, process-singleton ONNX session. Parses Camie's
string-category selected_tags.csv (vs WD14's integer Danbooru ids).
STORE_FLOOR (0.05) keeps the stored predictions JSON compact;
SURFACED_CATEGORIES gates which categories the suggestion UI shows
(meta/rating/year stored but never surfaced).
Inference itself isn't unit-tested (1GB model not in CI); the missing-
model error path and pure-logic surface are. Full inference runs in the
local integration suite.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
bvandeusen