8838b325fb560af70cf1a512a8e656b9470a7a27
524 Commits
| Author | SHA1 | Message | Date | |
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 bvandeusen
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8838b325fb |
fix(recapture): link on-disk images to their post (#1288)
Recapture disk-skips already-downloaded media, and upsert_post_record only writes Post fields — so a pre-existing image (e.g. one pulled under the old gallery-dl path, imported bare with no post) stays orphaned even after its post record is (re)written. Confirmed on the operator's instance: 329 pixiv images with primary_post_id NULL, 694 pixiv posts with content but no linked images, 0 duplicate posts. Fix: the recapture relink channel now carries the media's post_id (2- → 3-tuple path/url/post_id), and phase 3 calls importer.link_existing_image_to_post — match the on-disk image by path, find its Post by (source, external_post_id), upsert image_provenance + primary_post_id. Factored the provenance-linking out of _apply_sidecar into a shared _attach_provenance so the fresh-import and recapture-backlink paths can't diverge. Idempotent; generic across native platforms (no-op for already-linked Patreon/SubscribeStar). Re-running recapture now repairs orphaned images; future walks never orphan. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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437bf4d37a |
feat(suggestions): group wip/banner/editor under a separate 'system' category
System tags are kind=general, so their suggestions previously landed in the General group. Give them their own 'system' suggestion category so the operator reviews them apart from content tags: _current_heads maps is_system heads to category 'system' (still trained as general heads, still gated by the 0.65 floor). Frontend: CATEGORY_ORDER/LABELS gain 'system'; SuggestionsPanel renders a 'System' group first (small, collapsible, open — false positives easy to spot and reject); the typed-dropdown shows the shield icon for system entries. Safe: system-tag suggestions always carry a canonical_tag_id, so the create-by-kind path (which would send 'system' as a TagKind) is never hit. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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f33808b977 |
fix(pixiv): capture ugoira frame timings in the post record (ordering bug)
The core writes the post record BEFORE extract_media, but the ugoira frame delays were only memoized DURING extract_media — so write_post_record never saw them and ugoira_frames was always empty in the record. Extract a memoized _ugoira_meta (frames + zip url share ONE /v1/ugoira/metadata call regardless of order) and inject client.fetch_ugoira_frames into the downloader (mirrors Patreon's content_fetcher) so write_post_record populates the frames itself. Zero extra API calls — the fetch is shared/memoized with extract_media. A recapture now backfills the timings onto existing ugoira posts. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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6c6e8bdb6d |
feat(heads): surface system-tag suggestions at a flat 0.65 confidence floor
System tags (wip/banner/editor) already get heads (kind=general) and aren't filtered from suggestions, but they surfaced only at each head's precision-tuned suggest_threshold — high enough to hide the borderline/false-positive guesses the operator wants to SEE and REJECT (hard-negative mining: 'negatively reinforce what isn't a system tag'). score_image now uses a flat _SYSTEM_TAG_SUGGEST_FLOOR (0.65, operator-set) for system-tag heads instead of their auto threshold; content-tag heads keep their own, and the typed-dropdown threshold_override still overrides everything. _current_heads carries Tag.is_system into the head meta to drive it. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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c9696a2faf |
fix(subscribestar): route .art creators to .adult; clear source failure on disable
Two pre-merge fixes: 1. SubscribeStar .art age wall: the 18+ cookie doesn't clear the age gate on the .art domain (keeps 302'ing to /age_confirmation_warning even with the cookie — Elasid #54116), but the same creator is reachable on .adult where the cookie works. _normalize_ss_host rewrites subscribestar.art → subscribestar.adult at request time (stored Source.url untouched), logged so it's visible in walk logs. .com/.adult pass through. 2. Disabling a source now clears its failure state (last_error, error_type, consecutive_failures) so subs you pause (not paying for) stop lingering as 'failing'. Only the explicit disable clears — an unrelated edit to an already-disabled source leaves state alone. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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544e30bfb9 |
fix(pixiv): match gallery-dl's exact on-disk filename to avoid re-download at cutover
The native downloader used the Windows-safe sanitize_segment, but gallery-dl on Linux (path-restrict auto→'/', path-remove default control chars, path-strip auto→'') replaces ONLY '/' and deletes control chars — the Windows-forbidden set (<>:"|?*) and trailing dots/spaces stay RAW in on-disk titles. Any pixiv title with those chars would therefore miss the tier-2 disk-skip and re-download the whole work at cutover (seen-ledger starts empty). Replace sanitize_segment with gdl_clean_filename, a byte-exact mirror of gallery-dl 1.32.5 build_filename (verified against path.py). Directory + template already matched; this closes the last parity gap. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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0bbcdee3bd |
feat(pixiv): flip dispatch to the native ingester (#129 step 4)
pixiv joins NATIVE_INGESTER_PLATFORMS: download/verify/preview and the recover/recapture UI actions now route through PixivIngester. Campaign id is parsed straight from the source URL (numeric user id — no network resolver), with a platform-aware resolution-failure message. auth_token now rides the uniform adapter construction (token platforms use it, cookie platforms accept-and-ignore), and the preview endpoint fetches/threads it. The legacy gallery-dl pixiv path is fully removed (PLATFORM_DEFAULTS entry + the refresh-token config branches in download/verify) per no-legacy policy; gallery-dl keeps hentaifoundry/discord/deviantart until they migrate/retire. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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0563b2d750 |
feat(pixiv): ledger models + migration 0076 + PixivIngester adapter (#129 step 3)
pixiv_seen_media / pixiv_failed_media mirror the Patreon/SubscribeStar ledgers (keys are always synthesized <illust_id>:p<num> / <illust_id>:ugoira — pximg URLs carry no content hash). PixivIngester wires client/downloader/ ledgers into ingest_core with drift label 'Pixiv app API' and the new body_canary=False opt-out: caption-less pixiv artists are common, so the zero-bodies #862 alarm would false-positive here — the client's response-shape drift checks cover that failure class instead. auth_token joins the uniform adapter constructor (pixiv is the first token-auth native platform). verify_pixiv_credential = one OAuth refresh, no feed walk. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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7ef2ecd82f |
feat(pixiv): native downloader — gallery-dl layout parity + enriched post record (#129 step 2)
PixivDownloader writes originals to the exact pre-cutover gallery-dl layout
(<artist_slug>/pixiv/pixiv/{id}_{title[:50]}_{NN}.{ext} — flat, double
platform segment) so tier-2 disk-skip recognizes existing files. Post-first:
per-media sidecar is identity-only; the post record (_post_<id>.json — id
suffix because the flat layout would collide a bare _post.json) carries the
enrichment: tags + EN translations, rating from x_restrict, series,
view/bookmark/comment counts, AI flag, dimensions, author, and ugoira frame
delays (the zip has no timings). i.pximg.net media GETs ride the app-header
profile (403 without the app-api Referer).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
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bvandeusen
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86ae396914 |
feat(pixiv): native app-API client — gallery-dl-parity profile, post-first seams (#129 step 1)
PixivClient mirrors gallery-dl 1.32.5's PixivAppAPI request profile exactly (iOS app headers, OAuth refresh with X-Client-Time/X-Client-Hash, /v1/user/illusts pagination via next_url — whose query string doubles as the resumable page cursor). Post-first seams (post_record_key / post_is_gated / post_meta) + extract_media covering multi-page, single-page, ugoira zip (600x600→1920x1080 swap, frame delays memoized for the post record), and limit_* placeholder gating. No PHPSESSID web fallback: FC holds only the refresh token, same effective coverage as the gallery-dl path. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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f77e75147d |
feat(tags): system-tag UI markers + full protection sweep (step 4 of #128)
UI: shield marker + tooltip on TagChip and TagCard; system tags hide rename/merge/delete affordances (chip kebab entirely — set-fandom never applies to their general kind; remove stays, un-tagging is normal use). Aliases stay available: mapping model outputs ONTO a system tag is useful. Directory cards carry is_system. Every destructive path that could take out a system row is now guarded, found by sweeping run 1891s off-by-three failures — each one was a surface that would have eaten the seeded tags: - prune-unused: predicate exempts is_system (they ship with zero applications and matched every unused condition) - reset-content: predicate exempts is_system AND keeps their applications — hygiene flags describe the file, not content tagging - admin tag DELETE: refused with system_tag error - normalize_existing_tags: scan excludes is_system — canonicalization would recase wip -> Wip behind TagService.rename's guard, breaking the name-keyed presentation lookup Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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723f023e6a |
feat(gallery): similar() hides presentation images (banner / editor screenshot)
Step 3 of milestone #128. Presentation-tagged images cluster on UI chrome rather than content, so near any one of them they fill the whole more-like-this grid. Excluded from candidates in the ONE whole-image similarity surface (gallery similar mode, explore walk, and RelatedStrip all ride GalleryService.similar) — the anchor itself may be a banner, and wip stays surfaced: only the training pipelines exclude it. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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e6f128c894 |
feat(ml): training hygiene — system-tagged images are absent from other concepts training
Step 2 of milestone #128. _hygiene_excluded_ids (training_data.py) is the one shared predicate: images carrying any system tag are dropped from every OTHER concepts head training — not positives (a rough wip tagged as a character drags the head toward generic-sketch) and not rejection or sampled negatives (a wip OF character X is not evidence against X). A system tags own head trains on them unfiltered; that is what makes auto-flagging banners work. Selection is split out of train_head as the sklearn-free head_training_ids so CI (no sklearn) can pin the behavior. CCIP: reference prototypes skip hygiene-tagged images — a faceless wip figure region must never become an identity reference — and the ref cache signature now counts hygiene applications, since tagging an image wip changes the reference set without touching character/region counts. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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e9891ee9f3 |
feat(tags): system tags — is_system column, seeded hygiene tags, protection guards
Training hygiene step 1 (milestone #128). Migration 0075 adds tag.is_system and seeds wip / banner / editor screenshot (kind=general), ADOPTING an existing same-(name,kind) tag case-insensitively instead of duplicating. These rows drive the upcoming training exclusions, so they are protected: rename and merge-away refuse system tags (merge-INTO stays allowed — folding an operator's old hygiene tag into the system row is the intended move; merge is the only tag-delete path, so that guard covers deletion). is_system rides every tag serialization. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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b54243a1ff |
fix(subscribestar): inject the 18+ age cookie on every SubscribeStar domain
The cookie was pinned to .subscribestar.adult only; cookies are domain-scoped, so sources on subscribestar.art (Elasid, event #54116) never sent it and every poll 302d to /age_confirmation_warning. Emit one line per domain (.com/.adult/.art) with a per-domain presence check, and admit .art in the platform url_pattern. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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aa12a57f97 |
feat(recovery): surgical re-fetch for deep posts via ExternalLink reset
Operator-flagged: the recovered defective files live DEEP in their artists'
back-catalogues — the normal download cadence (by design, via the seen-gates)
will never re-walk them, so recovery's source re-check alone can't bring them
back. The durable per-post handle is the ExternalLink row, which survives the
image delete:
- services/external_links.refetch_links_for_post: reset settled links to
pending (fresh attempt budget, in-flight left alone) + dispatch their
fetches; sha-dedupe at import discards payload files that still exist, so
only the missing file lands.
- recover_defective_image now captures the image's post ids BEFORE the delete
cascades provenance away and resets those posts' links — future recoveries
are surgical automatically (response gains links_reset; source re-check
stays for gallery-dl-native files within walk reach).
- POST /api/admin/posts/refetch-external {external_post_id, source_id?} — the
manual tool for the three files recovered before this fix existed.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
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bvandeusen
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5b34c9221c |
feat(ia): wave 1 — Import tab dissolves, Maintenance regroups by system, one extension home
Settings IA per the approved A3 design (the old layout was the two-app merge fossilized): - Import tab retired: ImportTriggerPanel + ImportTaskList deleted (manual /import scans stay API-level; imports arrive via downloads/extension, heal via the Layer-2 auto-refetch sweep, and show in Activity). ImportFiltersForm moves to Maintenance → 'Ingestion & filters' and loads its own settings; the import store shrinks to settings-only (no remaining consumers of the scan/task-list machinery). Overview's pending banner now points at Activity. - Maintenance regrouped: Ingestion & filters / GPU agent & embeddings (GpuAgent, Failed processing, CPU embedding backfill) / Tagging (sliders, Heads, Aliases) / Library health (MissingFiles, Thumbnails, DB, Archive re-extract demoted last) / Storage. - One extension home: BrowserExtensionCard moves from Settings → Overview to Subscriptions → Settings, above the API key bar it authenticates. - Single-color import filter WIRED: skip_single_color/threshold existed since FC-2 but nothing read them (the audit module's docstring said as much) — now enforced on both import paths via the audit's canonical predicate (tolerance 30, matching the Cleanup card default; animated images exempt like the transparency check). Default stays off; test added. - Dead weight: PlaceholderView (zero refs) and the permanently-disabled 'Export failed logs (CSV — v2)' menu stub deleted; stale docs fixed (celery queue docstring, threshold comment citing retired tasks, ml package docstring, HeadsCard 'replaces Camie' blurb). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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19b962f1a7 |
feat(b3): ml-worker becomes optional — embed-only role, decoupled GPU coordination, cpu-embed switch
The ml-worker's ONLY processing role is now the CPU whole-image embed fallback (tag_and_embed renamed embed_image — Camie tagging was retired #1189 and the name kept implying otherwise; videos were already handled agent-style: frame sampling + mean-pool). Detection/cropping/CCIP stay GPU-agent-only, and their completion is judged per-pipeline: ccip by gpu_job rows, siglip by concept regions at the current model version — never by image_record.siglip_embedding. A CPU embed therefore can NEVER close crop work for the agent (regression test pins this; only the whole-image 'embed' job, the same artifact, is satisfied). Making removal actually safe (operator will drop the container): - GPU-queue coordination (enqueue_gpu_backfill, recover_orphaned_gpu_jobs, reprocess_gpu_jobs) moved verbatim to tasks/gpu_queue.py on the maintenance quick lane — it lived on the 'ml' queue only by module colocation, which made the ml-worker a hard dependency of the whole agent pipeline. - New ml_settings.cpu_embed_enabled (migration 0074, default ON so agent-less installs keep working): OFF stops the four import hooks queueing embed work nothing will consume and no-ops the manual backfill; switch lives on the renamed 'CPU embedding backfill' card. - NB heads training / auto-apply still run on the ml image (sklearn) — a stack that removes the container gives those up too. Deploy note: in-flight messages under the old task names are dropped by the new workers; the 60s orphan sweep + hourly backfill re-fire under the new names immediately. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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7c19ad91ed |
feat: cap-aware autoscaler + token-gated whole-instance tag reset (operator feedback)
Autoscaler (agent 2026-07-02.5): the buffer-occupancy signal alone would peg downloaders at DL_MAX while the bandwidth CAP — not concurrency — is the real constraint (8 streams sharing 8 MB/s move no more data than 4). Growth is now gated on the pipe having headroom (net < 85% of cap) and a pipe pinned at the cap (>= 95%) sheds streams down to 3; dead band prevents flapping. The UI hint says 'holding at the bandwidth cap' and /status reports bw_capped, so the behavior is legible without tests that need the ML stack. Reset content tagging: stays a FULL-instance reset (operator's call), but now lives in a fenced 'Danger zone' section on Cleanup and the apply is gated by a preview-derived confirm token (mirrors the Tier-C bulk-delete pattern — stale counts are rejected server-side). Copy no longer claims suggestions repopulate: it says plainly the heads' training examples are deleted and re-tagging starts fresh. Moved out of TagMaintenanceCard into DangerZoneCard. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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eaea4308fc |
chore: retire the tag-eval harness — it proved the heads system, job done (operator-approved)
The head-vs-centroid eval (#1130) existed to prove the 'frozen embedding + trained head' spine; the operator accepted the tagging system and dropped the harness. Removed per rule 22: TagEvalCard + store, /api/tag_eval blueprint, tag_eval_run ml task, recover-stalled-tag-eval-runs sweep + beat entry, TagEvalRun model + table (migration 0073), and its tests. The eval's data loaders + metric helpers were NOT eval-specific — the nightly heads trainer runs on them — so they moved verbatim to services/ml/training_data.py (heads.py import updated; behavior unchanged). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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a7abcc41ca |
feat(triage): failed-processing triage — probe errored files, flag defects, recover (#125 C1-C3)
An errored GPU job's stored reason is a suspicion; the file probe is the
verdict. A 15-min beat sweep (triage_gpu_errors) runs verify_integrity's own
probe (sha256 + decode) on each errored image ONCE and writes both verdicts:
ImageRecord.integrity_status and the new GpuJob.triage_status ('defect' |
'file_ok', migration 0072). Every classification logs at WARNING so it
surfaces in Logs/System Activity.
- 'defect' rows are excluded from /retry_errors (re-running a known-bad file
burns agent time re-minting the tombstone); response now reports
defects_kept and the GpuAgentCard toast says so.
- GET /api/gpu/errors: triage view — reason buckets (classify_reason),
probe verdicts, per-job detail. POST /errors/triage runs the sweep now.
- POST /api/gpu/errors/<id>/recover: reuses the Layer-2 refetch pattern —
delete the defective copy + record (full cascade takes the tombstones too)
and re-poll its subscription Source so a fresh copy re-imports and re-enters
the pipeline; 'no_source' when nothing pollable resolves.
- New 'Failed processing' card (GpuTriageCard) in Maintenance: verdict counts,
reason summary, probe-now, defect list with thumbnails + per-image Recover.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
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bvandeusen
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1f27189b8f |
chore: retire ml-backfill-daily beat + the spent purge-legacy action (operator-approved)
- ml-backfill-daily: the CPU tag_and_embed backfill raced the GPU agent's daily embed backfill for the same NULL-embedding images at ~100x the cost (B1 audit verdict, milestone #124). The backfill TASK stays — the manual /api/ml/backfill button remains the deliberate CPU fallback pending B3. - purge-legacy: one-time IR-migration cleanup, dry-run verified 0 targets on the live library before removal (A2 audit, milestone #123). Fully retired per rule 22: tile, store action, route, service fn, tests. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
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bvandeusen
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31c416bc7b |
docs(beat): backfill comments no longer claim errored jobs are retried
Follow-through on the tombstone rule (
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bvandeusen
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09e2772628 |
fix(gpu-jobs): end the error-tombstone loop — deliberate retry semantics + poison-job guards
The hourly ccip backfill's skip-list lacked 'error' (and the daily
siglip/embed variants re-gated failures on their missing results), so every
permanently-bad file got a fresh doomed job each run — ~24 duplicate error
rows/day per file, the perpetual 'unprocessable' flood. An errored job is now
a TOMBSTONE: no backfill re-enqueues it; retry is deliberate-only via
/retry_errors (an errored back-catalogue needs one button press after a
model swap).
One shared set of dedupe DELETEs (services/ml/gpu_jobs.error_dedupe_statements)
runs before every backfill and inside /retry_errors: error rows made moot by a
later pending/leased/done row go first, then older duplicates (newest reason
survives) — so the error count reads as distinct failing files and a retry
can't fan one file out into duplicate pending jobs. /retry_errors now returns
{requeued, pruned} and the toast shows both.
Poison-loop guards (release and lease-expiry burn no attempts, so a job that
stalls its transfer or crashes the agent every time cycled forever —
operator-observed jobs 99044/125288/131594/143131):
- agent: 3 in-session transient bounces (fetch or submit) → fail with the real
reason instead of another release; strikes never count while stopping, and
clear on submit success. Agent build 2026-07-02.3.
- server: the 60s orphan sweep (statements shared between the beat task and
GpuJobService so they can't drift) converts expired leases with >=5 lease
grants and pending jobs with >=10 to 'error', preserving the last stored
failure reason. Backstops old agent builds.
Tests: tombstone rule across all three backfill variants, moot-row pruning,
poison conversions, and the extended /retry_errors dedupe contract.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
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bvandeusen
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686808d3f3 |
feat(gpu): "Retry errored jobs" — scoped requeue of errors only
After an agent-side fix (e.g. the short-video sampler), the errored jobs
(~2.8k) have exhausted their 3 attempts and stay parked: backfill skips
images that already have a job, and /reprocess is the nuclear option (it
resets the 179k DONE jobs too). There was no way to re-run just the errors.
POST /api/gpu/retry_errors resets every status='error' job (all task types)
to pending with attempts=0 and the stored error cleared — a small inline
UPDATE that returns {requeued: n} so the UI toast can show the count.
UI: a "Retry errored jobs" button on the GPU-agent card, right under the
queue tiles; disabled when errored==0. With the agent now logging ffmpeg's
stderr on failure, retrying also reveals which errors were real vs victims
of the fps-filter bug.
Test: retry_errors requeues the errored job (fresh attempts, error cleared)
and leaves done work untouched; asserts via column selects (Core-DML
gotcha), not ORM refresh.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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bvandeusen
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0fe1674753 |
perf(web): stream files in 4 MiB chunks + 4 hypercorn workers (fix 40s downloads)
The image library is on a CIFS/SMB share (mounted rsize=4 MiB, actimeo=1), and Quart's FileBody streams in 8 KiB chunks — so serving one large original was ~19k network round-trips to the storage server, i.e. 30–58s per download (operator-flagged). That's what starved the GPU agent (constant "curator unreachable" backoff) AND slowed the browser: every byte is read off CIFS and streamed through the Python app (no reverse-proxy sendfile), and only 2 hypercorn workers meant the agent + the browser's thumbnail grid queued behind each other. In-container fix, no new service: - Raise FileBody.buffer_size 8 KiB → 4 MiB in create_app, matching the mount's read size: one round-trip per read, ~500× fewer. buffer_size is the MAX read so small thumbnails still read in one gulp, and Range/mime/ETag/conditional handling lives on Response — all preserved. Guarded so a Quart-internal change can't break boot. - HYPERCORN_WORKERS default 2 → 4 so concurrent /images requests stop queuing. Expected: large-file transfers drop from ~40s toward link speed (a few seconds) for the agent and the browser. See issue #1223. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
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c22f37d64d |
feat(gallery): sort by earliest post date across all posts (new default)
The gallery's newest/oldest sort keys off image_record.effective_date = COALESCE(primary post's post_date, created_at). The primary post is often the repost/download the file came from, so the grid led with download dates rather than when content was first posted (operator-flagged). Add a second materialized sort key, earliest_post_date = MIN(post_date) across ALL of an image's provenance posts (every post it appears in), else created_at — the original publish date. Mirrors the effective_date pattern so the sort stays a forward index scan. - alembic 0071: add earliest_post_date + index (DESC, id DESC); backfill created_at baseline then MIN over image_provenance ⋈ post. - importer: recompute earliest_post_date whenever a dated post is linked (MIN over the image's provenance, which now includes the just-added row). - gallery_service: new sorts posted_new / posted_old key off earliest_post_date; cursor + year/month grouping follow the active column transparently. - api: accept posted_new|posted_old; DEFAULT is now posted_new so the grid leads with original publish date. newest/oldest (effective_date) still available. - frontend: sort dropdown gains "Newest/Oldest post date" (default Newest post date); existing effective-date sorts relabelled "Newest/Oldest added". - tests: service test asserts posted_new/posted_old key off earliest_post_date; frontend default-sort omission test updated. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
ef3318aac1 |
feat(explore): more variance in the related rail (stronger MMR diversification)
Operator wants the Explore "related" rail to span more — the #1188 diversifier was tuned conservatively. Push all three knobs so it reaches further across clusters instead of clumping near the anchor: - MMR lam 0.55 → 0.40 — weight the diversity penalty harder (the main dial). - candidate pool min(200, max(limit*5, 60)) → min(400, max(limit*8, 100)) — a wider nearest-cosine pool so MMR has genuinely distinct neighbourhoods to pick from, not just the near-dupes. - pHash dup_threshold 6 → 8 — collapse more near-duplicate reposts/clones, freeing rail slots for distinct picks. Still deterministic (same set per image, just more spread) and relevance-anchored via the lam*sim-to-anchor term. Backend-only; no migration. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
181f1c6a27 |
perf(gpu-queue): partial indexes + two-phase lease so leasing stays O(batch)
The throughput bottleneck was curator-side, not the network. lease() claimed the lowest-id pending/expired jobs with `... ORDER BY id LIMIT n`, but with only a plain `status` index Postgres walked the primary key from id=1, skipping the entire prefix of already done/error rows before reaching pending ones. As `done` grew (69k+), every lease became an O(done) scan — leasing crawled, the DB saturated, and even /status (the queue GROUP BY count) stalled the agent. - Migration 0070 adds two partial indexes over just the live slice: pending rows indexed by id (hot path), and leased rows by lease_expires_at (crash-recovery + orphan sweep). They stay tiny no matter how large the done/error history. - lease() split into two phases so each uses a partial index: claim pending first (id-ordered, O(batch)); reclaim expired leases only when pending can't fill the batch. Same semantics (SKIP LOCKED, attempts++, expired reclaim). - Model __table_args__ declares the indexes so ORM and schema agree. - Test: a done-prefix at low ids must not stop the lease reaching pending. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
359bc5a283 |
feat(ml): default to SigLIP 2 (new installs) + model dropdown, no free-text (#1203)
- Migration 0069: new installs default to SigLIP 2 (so400m, 512px, 1152-d drop-in) — UPDATE applies ONLY where no image is embedded yet (fresh install), so an existing library is NOT silently invalidated; it switches deliberately via the dropdown → Re-embed → Retrain. Column server_defaults moved to SigLIP 2. - GET /api/ml/embedder-models: server-authoritative supported list (SigLIP 2 512 recommended / 384 faster / SigLIP 1 384 original) so the UI never free-types. - GpuAgentCard: the two name/version text fields → a single model dropdown; Save sets name+version from the picked option (the current model is always selectable even if off-list). - embedder.py DEFAULT_MODEL_NAME unchanged (stays the baked local-dir SigLIP 1) to avoid a local-dir/weights mismatch; SigLIP 2 loads by HF name, cached on the ml-worker's persistent HF_HOME. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
80f8eb4756 |
feat(gpu): re-process trigger to apply new crop detectors to the existing library (#1202)
The siglip/ccip backfills skip images that already have current-version regions, so adding crop detectors only affected NEW images — the back-catalogue would never be re-cropped. Add a reprocess trigger that resets every done/error job of a task back to pending, so the agent re-runs the FULL pipeline (figure detection + CCIP + concept/panel crops) over the whole library under the current detectors. - reprocess_gpu_jobs(task='ccip') task + POST /api/gpu/reprocess. - gpu store reprocess() + GpuAgentCard "Re-process library (re-detect + re-crop)" button with a confirm (it's heavy). - Test: a done job resets to pending (attempts cleared). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
d5f29f7056 |
feat(agent): crop proposers — booru_yolo anatomy + COCO person + comic panels (#1202)
Better region PROPOSERS feeding the existing crop→SigLIP→max-over-bag heads (no change to the learned-tagging approach; no per-tag cost — propose once, embed each region, all heads in one matmul). - detectors.py: lazy ultralytics YOLO wrapper, each proposer independently optional + guarded (a bad weight spec / inference error self-disables that one, logged, never breaks the worker). Weights resolve from an ultralytics name | http(s) URL | "hf_repo::file", cached under HF_HOME. NMS merge so a figure two detectors both find collapses to one crop. - worker: figure boxes = imgutils detect_person ∪ general COCO person (merged) → CCIP + concept (anime + Western/realistic coverage); booru_yolo anatomy components (head/cat-head/anatomy/…) → concept crops; comic panels → kind= 'panel' concept crops. Capped per frame (MAX_COMPONENTS/MAX_PANELS). - config + compose: PERSON_WEIGHTS (default yolo11n.pt, works OOB), ANATOMY_WEIGHTS + PANEL_WEIGHTS (operator sets booru_yolo URL + mosesb panel hf::file; empty = off). ultralytics added to requirements. - backend: image_region 'kind' doc notes 'panel'; no migration (free String, and the bag scorer keys on a non-null siglip_embedding, not the kind, so any SigLIP region joins the bag automatically). Agent is outside CI — py-compiled here; operator tests on the GPU and checks Western-vs-anime crop quality via /api/ccip observability. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
3d7f60a6e3 |
fix(lint): use dict() not a dict-comprehension in tag_stats (C416)
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
9a3cda007a |
feat(api): agent-friendly tag analysis endpoints — /tags/top + /tags/<id>/stats (#1136)
Fast, read-only, indexed aggregates shaped for ANALYSIS (not the paged UI directory, which is alphabetical + builds previews and timed out at 10 min on a full count sweep). - GET /api/tags/top — top tags by image count, desc. ?kind, ?limit (cap 500), ?min_count, ?source=all|human|manual|accepted|auto (human=manual+ml_accepted, auto=head_auto+ccip_auto+ml_auto). One GROUP BY over image_tag (indexed on tag_id). - GET /api/tags/<id>/stats — per-tag dataset health: total + per-source counts (manual/accepted/head_auto/ccip_auto), human vs auto rollups, rejection count, and whether a trained head exists. Backs concept-readiness + source-split analysis. Plain-HTTP homelab posture, no auth change. Tests cover ranking, source filter, min_count, the source breakdown, and 404. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
bc6d43d3f2 |
refactor(ml): drop dead tagger/suggestion settings + columns (#1199)
Hygiene follow-up to the Camie retirement (#1189) — these were left inert to bound that change; nothing reads them now. Migration 0068 drops: - ml_settings: tagger_store_floor, tagger_model_version, suggestion_threshold_ character/general (already dead pre-retirement — scoring uses per-head thresholds), video_min_tag_frames (only the deleted video-prediction aggregator used it). - image_record: tagger_model_version (no writer), centroid_scores (dead JSON cache, no reader). Also: ml_admin _EDITABLE/GET/_validate pruned (dropped the store-floor invariant + video_min_tag_frames check); MLThresholdSliders trimmed to a video-embedding card (interval + max frames only); importer no longer resets the dropped cols; download_models drops the Camie fetch; stale CASCADE comments in cleanup_service no longer name the removed tables. Tests updated. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
3d97667f5b |
fix(lint): drop unused select import in tags.py after allowlist removal
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
485387ff0b |
refactor(ml): retire the Camie tagger + allowlist bulk-apply (#1189)
Heads + CCIP are the tag source and head auto-apply is the earned propagation.
The Camie tagger ran only to feed the allowlist bulk-apply (its ImagePrediction
rows had no other consumer), and the allowlist was a SECOND, un-earned auto-apply
path firing in parallel with heads on every accept — exactly the un-earned spray
the v2 pivot replaced. Retire both.
Behavior change: accepting a suggestion now applies the tag to THAT image only
(source='ml_accepted', a head-training positive) — it no longer allowlists +
fans the tag across the library via Camie. Propagation is heads' earned
auto-apply. (Loses instant cold-start propagation for booru-vocab tags; that was
un-earned and bypassed the precision gate.)
- tag_and_embed is now EMBED-ONLY (no Camie load/infer, no ImagePrediction
writes); backfill enqueues it for images with no embedding.
- Removed: services/ml/tagger.py, apply_allowlist_tags + helpers + daily beat +
every enqueue caller (accept/alias/merge/per-image), api/allowlist.py +
blueprint, ImagePrediction + TagAllowlist models/tables (migration 0067),
AllowlistTable.vue + allowlist store, the accept coverage-projection payload.
- AllowlistService gutted to accept/dismiss/undismiss/reject (the rejection store
the rail still needs); accept returns nothing, API returns {accepted, tag_id}.
- tag merge no longer repoints/triggers the allowlist; _keep_as_alias now keys on
ML-applied image_tag sources (incl. head_auto) instead of the allowlist.
- UI: MLBackfillCard relabelled to embedding-only; accept toast simplified;
MaintenancePanel drops the allowlist tile.
Left for a follow-up hygiene pass (now-inert, harmless): the dead settings
columns (tagger_store_floor, tagger_model_version, suggestion_threshold_*,
video_min_tag_frames), image_record.tagger_model_version, MLThresholdSliders
trim, and the Camie model download in download_models.py.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
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bvandeusen
|
3d77a38a25 |
refactor(ml): remove the dead per-tag centroid subsystem (#1189)
The v2 pivot replaced per-tag SigLIP centroids with learned heads + CCIP. Centroids were still recomputed (on every tag merge + a daily beat) but NOTHING read them — suggestions come from heads+CCIP and apply_allowlist_tags applies via Camie predictions, not centroids. Pure dead wiring; remove it. Removed: CentroidService, recompute_centroid/recompute_centroids tasks, the daily beat, POST /api/ml/recompute-centroids, the recompute-on-merge trigger, the tag_reference_embedding table + model, the centroid_similarity_threshold + min_reference_images settings (migration 0066), the CentroidRecomputeCard + its store action + MaintenancePanel tile, and the centroid slider in MLThresholdSliders. _keep_as_alias drops its vestigial has-centroid branch (the allowlist branch already covers "could re-emit"); tag merge no longer clears a table that no longer exists. NOT touched (still live, parallel to heads): the Camie tagger, ImagePrediction, and the allowlist bulk-apply — accepting a suggestion still allowlists + applies it across the library. The tag-eval "centroid" baseline metric is unrelated (in-memory) and stays. (image_record.centroid_scores JSON column also remains — separate legacy field, its own micro-cleanup.) Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
4daa3f2790 |
feat(ml): operator model swap — GPU re-embed + embedder as a setting (#1190)
Make the SigLIP embedder an operator choice (drop-in to SigLIP 2:
google/siglip2-so400m-patch16-512 is a verified 1152-d model at 512px → no
schema change, better small-cue fidelity). A swap = set model + re-embed +
retrain, all operator-driven; the GPU agent does the re-embed so it's fast.
- settings: embedder_model_name is now a setting (migration 0065) alongside the
existing embedder_model_version; both editable + validated (non-empty) in the
ml admin API. The server embedder loads by HF name (AutoImageProcessor/Model,
model-agnostic), preferring the pre-downloaded local dir for the default so
existing deploys don't re-download; rebuilds on a name change.
- agent: new 'embed' job = whole-image SigLIP embedding (mean-pool video frames)
under the lease-announced model → POST /jobs/submit_embedding writes
image_record.siglip_embedding + siglip_model_version. The lease now announces
the model FROM THE SETTING (not a constant).
- re-embed routing: enqueue_gpu_backfill('embed') selects unembedded + stale-
version images; 'siglip' now re-embeds concept crops whose version != current
(so a swap re-triggers crops, not just the never-embedded back-catalogue). The
CPU ml-worker backfill no longer re-embeds on a version mismatch (it can't
churn the library at 512px) — the GPU agent owns version re-embeds. Daily
'embed' + 'siglip' beats self-heal.
- scoring: score_image only bags embeddings in the CURRENT model's space (whole-
image gated by siglip_model_version, concept regions by embedding_version) so a
mid-swap stale vector isn't scored by new-space heads; legacy NULL = current.
- UI: GpuAgentCard "Embedding model (advanced)" — edit name/version, Save, and
"Re-embed library (GPU)" (queues embed + siglip); points at SigLIP 2.
Tests: lease announces model + submit_embedding round-trip; enqueue 'embed'
selects stale/unembedded; stale-version excluded from scoring; embedder model
settable + empty rejected; siglip gate updated to current-version concept.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
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bvandeusen
|
0f472b2f9e |
fix(explore): diversify "more like this" so it stops getting stuck (#1188)
Pure nearest-cosine piled near-identical images into the neighbour grid — a reposted banner filled all 24 slots, and once you wandered into a B&W / comic-panel cluster every neighbour was more of the same with no way back to colour without the Random button (operator-reported, with screenshot). similar() now over-fetches a wide candidate pool (5x the requested limit, cap 200), then diversifies down to `limit`: - pHash near-duplicate collapse: drop candidates within 6 Hamming bits of the anchor or an already-kept candidate, so a repost (and the anchor's own clones) appears at most once. - MMR re-rank: greedily pick for closeness-to-anchor minus similarity-to-already -picked (lambda 0.55), so the result SPANS clusters instead of returning 40 variations of one image. Falls back to nearest-order on any failure / small pool, so existing nearest-first behaviour is unchanged when there's nothing to diversify. Frontend forwardTarget drops the now-redundant skip-nearest-third hack (the list is already diversified server-side) — plain random-over-unvisited gives the variance now. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
c6f38b0dac |
feat(tagging): SigLIP concept crops + max-over-bag scoring (#114)
Lift recall on small/local concepts (glasses, cum, stomach-bulge, xray, lactation) that the whole-image SigLIP vector washes out: the GPU agent now embeds figure crops with SigLIP too, stored as kind='concept' regions, and the suggestion rail scores each image as a BAG (whole-image + every concept crop), taking each head's MAX over the bag. The whole-image vector is always in the bag, so this can never score lower than before. Model-agnostic by construction: the server ANNOUNCES the embedding model (HF name + version) in the lease, so the agent loads whatever the heads were trained in and stays in lock-step — a model swap is a server setting + a re-embed migration, never an agent change. - agent: model-agnostic CropEmbedder (torch/transformers get_image_features, fp16 on CUDA, inference-locked); worker branches on job.task — 'ccip' emits figure(CCIP)+concept(SigLIP) in one pass, 'siglip' emits concept-only so the back-catalogue backfill never churns figure/CCIP regions; torch cu124 + transformers in the image. - server: lease announces embed_model_name/embed_version; score_image is max-over-bag (version-filtered region embeddings); enqueue_gpu_backfill 'siglip' gates on a missing concept region (drains the back-catalogue, retries failures, no double-enqueue); daily siglip-backfill beat; UI button; /api/ccip/overview reports images_with_concept_siglip. - v1 scope: suggestion rail only — auto-apply stays whole-image (conservative; heads' thresholds were calibrated on whole-image). Bulk-apply bag = follow-up. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
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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bvandeusen
|
625336b6b4 |
feat(ccip): tunable match threshold, default 0.85 (#114)
Live data showed the v1 flat 0.75 cosine over-fired — ~64% of matched images got
3-10 character guesses dominated by the most-referenced characters (a 27-ref
character clears a low bar on many images). A sweep showed 0.85 collapses the
noise (noisy multi-matches 47→3) while keeping the confident single-character
matches.
- ml_settings.ccip_match_threshold (migration 0063, default 0.85); match_image
reads it (override still accepted). DEFAULT_SIM_THRESHOLD fallback 0.75→0.85.
- Exposed in GET/PATCH /api/ml/settings (validated 0.5–0.999).
- Slider in the GPU agent card ("Character-match strictness") — tune live, no
redeploy, same observe-and-tune loop as auto-apply.
Test: a ~0.9-cosine figure matches at 0.85, dropped at 0.95.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
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bvandeusen
|
2cb0427868 |
feat(gpu): fast orphan recovery — graceful release + 60s sweep (#114)
So work an agent orphaned gets picked back up quickly, three layers: - GpuJobService.release(): a graceful agent stop hands its still-leased jobs back to pending instantly (POST /api/gpu/jobs/release), no waiting out the lease. - GpuJobService.recover_orphaned() + recover_orphaned_gpu_jobs Celery task on a 60s beat: resets expired leases (a hard-crashed agent) to pending and keeps the queue counts honest even when nothing is leasing. - Lease TTL 300→180s: still well above any single job (a capped-frame video embed is tens of seconds, and a live worker heartbeats), but a hard crash recovers faster once the sweep fires. Tests: release returns-to-pending (token-scoped), recover_orphaned resets only expired leases, release API round-trip. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
60f26247e9 |
style: alphabetize ccip_bp import (ruff I001)
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
de33bab41c |
feat(ccip): read-only observability API for the crop/CCIP work (#114)
So the work can be checked through an API as the agent fills in vectors (same pattern as /api/heads/metrics): - GET /api/ccip/overview: regions by kind, images with figure CCIP vectors, the per-character reference counts (which characters have enough examples to match on), and the embedding versions present. - GET /api/ccip/images/<id>: that image's stored regions (bbox, frame_time, has_ccip/has_siglip, versions) + the CCIP character matches it would get — for spot-checking detector + matcher output. Read-only, no GPU. (Queue depth is already at /api/gpu/status.) Tests: overview coverage counts + per-character refs; per-image regions + matches. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
5faf34a3b5 |
feat(suggestions): overlay CCIP character matches onto the rail (#114)
SuggestionService.for_image now merges CCIP character matches with the SigLIP head suggestions — they're complementary, not exclusive: CCIP is the identity- specialized signal but needs a detected figure; the heads work whole-image but conflate identity with style. Merged by tag: 'both' when they corroborate (higher score wins), 'ccip' / 'head' otherwise. Cheap when no CCIP vectors exist yet (match_image returns early without a figure vector), so it's a no-op until the agent runs. Suggestion.source is now 'head' | 'ccip' | 'both'. Test: a character with a CCIP reference figure surfaces (source='ccip') on a new image whose figure matches. NEXT: the agent container (real CCIP/detector models, hands-on) that produces the vectors this consumes. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
d57ca847e7 |
feat(ccip): few-shot character matcher (#114 slice 5)
The server-side brain that turns stored CCIP vectors into character suggestions
— no GPU. character_references() gathers each character tag's prototype vectors
(figure/face-region CCIP embeddings on images carrying that tag); match_image()
cosine-matches an image's figure vectors against every character (multi-
prototype: best over a character's examples), surfacing those above a tunable
threshold as {tag_id, name, category:'character', score, source:'ccip'},
excluding already-applied characters. v1 = cosine on raw CCIP vectors; the exact
CCIP metric/threshold gets validated against the model in the hands-on eval.
Tests (synthetic vectors): same-character match across images, no-match for an
orthogonal figure, already-applied exclusion, no-figure-vectors empty.
NEXT: merge CCIP character suggestions into the rail; the agent container that
actually produces the vectors (hands-on, GPU — not CI-verifiable).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
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bvandeusen
|
558d965a1c |
fix(gpu): count backfill enqueues via RETURNING, not rowcount
result.rowcount is unreliable for INSERT…SELECT (returned -1), failing the idempotency assert. Use .returning(GpuJob.id) and count the rows. (run 1652) Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
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bvandeusen
|
f247f9247c |
style(gpu): ruff — split as-import, dict(rows) over comprehension
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |