The #764 in-place prune (rewrite tagger_predictions to >=0.70) is too slow on
100 GB of TOAST and fails at its soft limit (interrupts a query mid-flight ->
'another command is already in progress'). #768 supersedes it: extract only
the >=floor predictions into image_prediction via this set-based backfill,
then drop the column (step 3) — reading 100 GB once + writing ~840k small rows
beats rewriting 100 GB in place.
So this backfill no longer assumes the prune ran: it filters by
ml_settings.tagger_store_floor (default 0.70) itself, handling the full or
partially-pruned JSON identically.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Switch every prediction READER off the JSON column onto the normalized
image_prediction table. Parity by construction: each reader loads the same
{raw_name: {category, confidence}} dict it consumed before (via small
_load_predictions helpers), so all downstream threshold/alias/merge/consensus
logic is byte-identical — only the data source changed.
- suggestions.SuggestionService.for_image (and for_selection via it)
- ml.apply_allowlist_tags (iterates images that have prediction rows)
- importer re-import reset deletes the image's prediction rows
The tagger_predictions JSON column is still dual-written (step 1) so it stays
valid during transition; the backfill task's NULL check still works. Removing
the JSON write + DROP column + retiring the #764 prune is the cleanup
follow-up (needs a quiesced-worker window for the DROP lock).
Tests: shared tests/_prediction_helpers.seed_predictions seeds the table;
read-path tests (suggestions, bulk consensus, allowlist apply, API) seed there
instead of ImageRecord.tagger_predictions.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Normalize tagger predictions out of the image_record.tagger_predictions JSON
blob into a queryable per-prediction table. Step 1 of the cutover (expand):
additive + low-risk — reads still use the JSON, this just adds the table and
keeps it populated.
- ImagePrediction(image_record_id, raw_name, category, score) — stores the
RAW tagger vocab name (not tag_id) so read-time alias→canonical resolution
is unchanged. Indexed for per-image reads + by (raw_name, score).
- Migration 0045: create table + set-based backfill from the JSON via
json_each (fast post-#764-prune). The old column stays (vestigial) and is
dropped in a later follow-up — DROP needs an ACCESS EXCLUSIVE lock on the
hot image_record table, so it waits for a quiesced-worker window.
- tag_and_embed dual-writes the rows (delete-then-insert, idempotent);
tagger_store_floor already applied in infer().
Next: switch suggestion + allowlist reads to the table, then drop the JSON
write. Plan-task #768.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
bvandeusen