- heads.py: conf_map = dict(conf) instead of a dict comprehension (ruff C416).
- postCard.spec.js: the modal-playlist rename (postImageIds→playlistIds) missed
this frontend test (grep was src-only); update the expected call args.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
The confirm-UI change added source + confirmed to serialize_tag; two exact-dict
unit tests in test_tag_query.py failed on the new keys. Add them (default
None/False for rows without image scope).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
The image modal cycled GLOBAL neighbours; now the gallery hands it a snapshot of
the currently-filtered, ordered id list so prev/next moves through exactly what
you're viewing — the filtered-playlist behaviour lost in the ImageRepo→FC move.
Generalized the modal store's post-scoped cycle into a `playlistIds` playlist
reused by both GalleryView and PostCard (falls back to global neighbours when no
playlist is passed, e.g. Explore's "open full viewer").
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
Completes "no self-training": unconfirmed auto-applied character tags no longer
seed CCIP references — character_references + the prototype builder
(_current_fingerprints/_rebuild_one) gain a shared _positive_char_tag filter
(human-applied OR operator-confirmed), mirroring the head-positive exclusion.
Confirming a tag also has to move the change-detectors, or an incremental
refresh/Retrain right after a confirm wouldn't fold the tag in (only the nightly
full pass would): the CCIP global gate now counts character confirmations, and
the head training fingerprint counts confirmations. Test for the CCIP path.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
Auto-applied tags are provisional (they don't train the model + can be retracted
until confirmed), so surface and confirm them:
- Backend: list_for_image + get_image_with_tags now include `source` + a
`confirmed` flag on each applied tag (via serialize_tag, image-scoped; defaulted
for autocomplete/directory callers).
- Frontend: TagChip badges an unconfirmed auto-tag with an "auto" pill + a
one-click Keep/confirm (✓) → POST /images/<id>/tags/<id>/confirm, which promotes
it to a training positive and shields it from the retraction sweep; TagPanel
reloads so the badge + button drop once confirmed.
Contract test for the source/confirmed payload.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
The keystroke debounce cleared the timer but not an already-fired fetch, so a
slower earlier-prefix response ("s") could land after "sex" and overwrite the
dropdown with wrong-prefix matches (operator-flagged with a "sex"→Stockings/
Super Mario screenshot). Gate each autocomplete response on a useInflightToken
(cancel on every keystroke, isCurrent() after the await) so only the latest
query's results are applied.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
Milestone 139 raised head_auto_apply_precision 0.97→0.98; operator confirmed the
general-tag confidence was already well tuned, so revert that. The support floor
(min_positives 30→50) and CCIP match confidence (0.92→0.95) stay. Migration 0081
(not yet deployed) edited to drop the precision bump.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
Each category section header gets a subtle "Reject rest" action that dismisses
every still-unhandled suggestion in it at once (store.dismissRemaining, parallel
dispatch). Canonical tags persist a rejection and stay flagged (reversible,
one-click un-reject); raw creates-new-tag rows drop client-side. Shows only when
the section has unhandled items. No confirm dialog — it's fully reversible.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
Makes auto-apply truly "soft" for heads: _ids_with_tag (head positives) and
_eligible_tag_ids (graduation count) now count human-applied + operator-confirmed
tags only, via a shared _AUTO_SOURCES (head_auto/ccip_auto/ml_auto) exclusion.
Unconfirmed auto-applied tags no longer train the head that judges them, so a
misfire can't reinforce itself and the retraction sweep can actually drop it.
Confirming a tag (TagPositiveConfirmation) promotes it to a positive AND protects
it from retraction. sklearn-free tests. CCIP reference exclusion is the companion
piece, next.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
The stricter head_auto_apply_min_positives (30→50, migration 0081) dropped the
_head helper's default n_pos=30 below the support floor, so the "supported head"
sweep tests saw the head as ineligible (n_applied 0). Move the default to 60; the
explicit n_pos=5 under-supported test stays correct.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
Daily scheduled_retract_auto_tags re-scores standing auto-applied tags and drops
the ones the model no longer supports:
- retract_auto_applied_heads: per graduated head, re-score its source='head_auto'
images (bounded — only the images already carrying the auto-tag, not the whole
library) and remove ones now < auto_apply_threshold.
- retract_auto_applied_ccip: per source='ccip_auto' character tag, max-cosine the
image's figure vectors vs that character's prototypes; remove ones now below the
ccip auto-apply threshold.
Both SKIP operator-confirmed tags (TagPositiveConfirmation) and are SILENT — a low
score isn't proof the tag was wrong, so no hard negative is recorded (that's
reserved for an operator removal). No-op unless the relevant auto-apply switch is
on. New daily beat. sklearn-free tests for both paths + the disabled no-op.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
head_auto_apply_precision 0.97→0.98, head_auto_apply_min_positives 30→50,
ccip_auto_apply_threshold 0.92→0.95 (operator-asked). Model defaults change for
fresh installs; migration 0081 bumps the existing singleton row IFF still at the
old default (won't clobber a deliberate operator change). ml_admin bounds already
permit these. Fixed a stale comment in the auto-apply test.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
bvandeusen