95d2ae1d586ea56d658489bb052713398930ac75
14 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 bvandeusen
|
95d2ae1d58 |
feat(agent): global bandwidth cap — the agent can't saturate the desktop's network
One shared TokenBucket (default 8 MB/s; BANDWIDTH_LIMIT_MB_S, 0 = unlimited; live MB/s dial + net readout in the control UI) is charged by every still download (streamed chunk reads) and every ffmpeg video stream (metered from outside via /proc/<pid>/io and SIGSTOP/SIGCONTed into budget). Why: D1 re-measurement 2026-07-02 — the idle link moves ~38 MB/s, but 8 unthrottled downloaders bufferbloated it to ~1-1.5 MB/s PER STREAM (operator's browser included). Capping the aggregate keeps the desktop usable and still beats the collapsed sweep throughput it replaces. Agent build 2026-07-02.4. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM |
||
|
bvandeusen
|
98b2ac90dd |
refactor(agent): DRY pass on the GPU agent worker package
Consolidate genuine duplication in agent/fc_agent into single-source helpers (behavior-preserving; DRY Pass process #594): worker.py - _fail(jid, image_id, exc, verb) — 4 terminal "fail this job" blocks (downloader HTTP-fault + decode, consumer non-transient + generic). - _release(job_ids) (was _release_owned) — the one lease hand-back path; 6 inline release([jid])+unhold sites now route through it. - _stopped(stop_evt) + _abort_if_stopped(jid, stop_evt) — 4 stop-check -and-release blocks and every bare stop-check. - _timed(stage) contextmanager — ~8 monotonic()/_record() timing pairs; records only on clean exit, matching the old skip-on-raise behavior. - _ewma(prev, x, alpha) module fn — 3 EWMA updates in the autoscaler. client.py - _submit(path, payload) — submit / submit_embedding (retrying session). - _post_quiet(path, payload) — heartbeat / fail / release fire-and-forget. detectors.py - Proposers._top(detector, image, cap) — merges components() and panels(). config.py - _bool_env(name, default) — auto_start / auto_scale env parsing. Left alone (recorded): the xyxy→norm-xywh conversion duplicated across models.py/detectors.py (2 copies, independent wrapper modules — sharing would couple them), and the _ensure_embedder/_ensure_proposers pair (same lock shape, different concepts). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
bvandeusen
|
8a0237eeea |
fix(agent): stream videos via ffmpeg-from-URL instead of downloading the whole file
The failing "poison" jobs were 800MB+ 4K VR videos: the agent pulled the ENTIRE file into memory (r.content) just to sample a few frames, which buffered ~1GB in RAM and — on any slow/contended media store — got cut off mid-download (ChunkedEncodingError), failed, and re-leased forever. Measured the media read at ~4–6 MB/s (raw off the share, curator out of the path), so no serving-layer tweak helps; the file simply shouldn't be fully downloaded. Environment-agnostic fix (works for any deployment, completes even when slow): - media.sample_frames_from_url(): point ffmpeg straight at curator's /images URL. It Range-reads only the video index + up to max_frames of content — never the whole file — and reconnect flags resume a dropped transfer instead of failing. Generous, env-tunable timeout (FFMPEG_TIMEOUT, default 1200s) = completion over speed. Removes the bytes-based sample_frames (dead once videos stream). - worker._download_decode: videos now stream (no fetch_image, no RAM blowup); stills still download+decode. On an ffmpeg miss, probe curator liveness (client.is_reachable) → fail the job if curator is up (unprocessable file, stops the infinite re-lease) vs release if curator is down (transient, survives a redeploy). Auth header passed so it works whether or not /images is gated. Build marker 2026-07-01.6. Refs issue #1225. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
||
|
bvandeusen
|
7cdce0c474 |
feat(agent): temporal video dedup — drop near-duplicate frames before the GPU
Near-static videos are the dominant GPU load: sampled into up to 64 frames, each re-runs the whole detect→CCIP→SigLIP chain on ~identical content. Add a CPU perceptual-hash frame dedup upstream of the GPU so the redundant frames are never processed at all (not just their embeds). - media.dedupe_frames() + _dhash(): 8×8 difference-hash (64-bit) per frame; greedy keep — a frame survives only if its hash differs from every kept frame by >= min_distance bits (Hamming). A static run collapses to one frame; genuinely distinct scenes all survive. Order + frame_time preserved. - Called in worker._download_decode right after sample_frames, so it runs in the decode stage on the downloader thread (CPU) — the GPU consumers only ever see deduped frames, and buffered video items shrink (less RAM too). - Env-tunable FRAME_DEDUPE_DISTANCE (default 8; higher keeps more frames for brief localized changes an 8×8 hash can miss; 0 disables). Logs `video frames N→M` when it drops any, so video load reduction is visible. Complements the spatial per-frame crop dedup (2026-07-01.2); this is the temporal axis. Build marker 2026-07-01.3. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
||
|
bvandeusen
|
eaae896858 |
feat(agent): dedupe near-duplicate crops before the SigLIP embed
Figure boxes are already NMS-merged (iou 0.6) and each YOLO detector self-NMSes, but the combined per-frame crop pile (figure→concept ∪ anatomy component→concept ∪ panel) was embedded with no cross-proposer dedup — so genuine near-duplicates slipped through (a figure box ≈ an anatomy component on a solo bust; overlapping booru head classes on one head), embedding the same region twice and burning a slot against max_regions. Add detectors.dedupe_crops(): a greedy, high-IoU (default 0.85), kind-aware pass over the pending (crop, template) list right before embed_batch — drop boxes that overlap ≥ iou within the same kind, keep the highest score. The high threshold is deliberate: it collapses only true near-identical boxes while preserving intentional nested crops across scopes (a whole figure vs a small head component sit well below it) and distinct kinds (concept vs panel). Env-tunable DEDUPE_IOU (≥1.0 disables). Runs on CPU before the GPU work, so it cuts both embed cost and region count. Temporal (cross-frame) dedup deferred. Build marker 2026-07-01.2. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
||
|
bvandeusen
|
c587ac667c |
fix(agent): cap figures + global region cap + reset active on stop
Three safety/robustness fixes from the operator's run logs: - Cap figures per frame (MAX_FIGURES, default 8) like components/panels already are. Uncapped, a huge/busy image yielded hundreds of figure boxes → hundreds of per-figure CCIP calls + crops → a 38s job AND a submit too big to accept (image 81602 looped on 413). This is the acute fix. - Global per-JOB backstop (MAX_REGIONS, default 128): if total regions still exceed the cap (long video), keep the highest-scoring and log the drop, so a submit body can never blow past curator's limit. - Stale "active" meter: stop() now resets _active to 0 (no slots remain, so the meter must read 0 at once), and _bump clamps at 0 so a slot finishing after the reset can't drive it negative. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
||
|
bvandeusen
|
f01b59f390 |
fix(agent): py3.10 startup crash + submit-path retry; pin agent ruff to py310
The agent container (CUDA base, Python 3.10) crashed on startup with `NameError: name 'Config' is not defined` — an earlier `ruff --fix` unquoted the `from_env(cls) -> Config` self-reference, which is safe on CI's Python 3.14 (PEP 649 lazy annotations) but is evaluated at class-definition time on 3.10. CI lint/compile run on 3.14, so it slipped through. - config.py: `from __future__ import annotations` so the self-referential annotation is a string, never evaluated — works on 3.10 and every version. - agent/ruff.toml: pin the agent to `target-version = "py310"` (its real runtime) and inherit the root rules. Ruff now flags exactly this class as F821, so CI's lint lane catches it instead of shipping a broken image. (CI otherwise lints on 3.14, masking 3.10 issues.) - client.py: submit path now retries in-place. A dedicated session with a urllib3 Retry (connect/read/status, 0.5s backoff, 500/502/503/504, POST) so a momentary blip after the GPU work is done doesn't discard it and force a full re-download + recompute elsewhere. A duplicate submit after a lost response is a harmless 409 no-op. Lease/fetch keep the plain session + loop-level backoff. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
||
|
bvandeusen
|
79269da802 |
fix(agent): prompt stop + lazy curator polling + build marker; add agent to CI
Addresses operator reports: Stop never finishes, the agent polls curator constantly, and stale-cached pages get mistaken for a failed deploy. - Stop is prompt: flip _running BEFORE any lock so /status + worker loops see "stopped" immediately, and add a stop/shrink checkpoint in _process (after decode, before the expensive detect+embed) that releases the job and bails — so a Stop doesn't wait out heavy GPU work. - Lazy curator polling: the queue snapshot is fetched only while a browser is actually watching (a /status hit within UI_IDLE_GRACE) and on a 5s cadence, not a constant background loop. The work loop's own lease/submit is curator's only visitor otherwise — nothing polls just to poll. - Build marker: VERSION is embedded in the page and reported on /status; the UI shows a "reload" banner when they differ, so a browser-cached page can't be mistaken for "the new image didn't deploy" (complements the no-store header). CI: the lint lane now also `ruff check`s agent/ and compileall-parses it, so the GPU agent is linted + syntax-checked before its image builds (build.yml only `docker build`s it). Fixed the agent's pre-existing UP037/B905 so it passes. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
||
|
bvandeusen
|
6d7b17b0b5 |
feat(agent): autoscale the worker count (throughput hill-climb), Auto default-on
The new per-job workload (3 detectors + several SigLIP embeds) is far more GPU-bound than the old I/O-bound CCIP pass, so the right worker count shifted and is hard to guess. Add an Auto mode (default ON) that finds it: - _control_loop samples jobs/sec + GPU util/VRAM every ~6s and hill-climbs the target: grow while throughput keeps improving and VRAM stays under budget, revert a step that doesn't help, back off under memory pressure (VRAM >= 90%), then settle and periodically re-probe (the GPU/IO balance shifts over a run). - A manual concurrency set is an override → leaves Auto; an "Auto" toggle in the control UI re-enables it. status() reports `auto`; the dial reflects the auto-chosen count (read-only) while Auto is on. - AUTO_SCALE env (default on) + compose doc. Agent py-compiled (outside CI). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
||
|
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 |
||
|
bvandeusen
|
55fa4656ff |
feat(agent): survive + auto-recover when curator is unreachable
For redeploying curator while away with nobody to restart the agent: - _process now distinguishes a TRANSPORT error (curator down/redeploying, 5xx, 401/403/408/409/429, or our lease reclaimed mid-flight) from a genuine job fault. On a transport error it hands the job back (best effort) and signals the loop to back off — instead of calling fail(), which would burn the job's server-side attempt budget (MAX_ATTEMPTS=3) and permanently error good jobs across a redeploy. Job-specific 4xx (404 image gone) still fail so they don't re-lease forever. - lease loop retries with capped exponential backoff (poll_idle → 60s) and resets on the first successful lease, so a long outage is gentle and recovery is automatic within ≤60s of curator returning. Sleeps are interruptible so Stop / pool-shrink stays responsive. - AUTO_START env (default on in compose) resumes the worker on container start, so a host reboot / crash-restart (restart: unless-stopped) self-heals with nobody at the desktop. - control UI shows a "waited out" counter + an "curator unreachable, holding work" banner so the recovering state reads as recovery, not failure. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
||
|
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 |
||
|
bvandeusen
|
4a1a9ec5a7 |
feat(agent): GPU load readout + live worker-count tuning (#114)
Control UI gains what the operator asked for: - GPU load (nvidia-smi): util %, VRAM used/total + bar, temp — so you can see how hard the card is working while you're at the desktop. - Worker count is now a live − / + control (POST /concurrency), not just an env: the worker is a pool of independent slots (shared model, so slots add concurrent inference, not N× VRAM). Dial up for speed, down to free the card. Replaces pause/resume with Start/Stop + the worker dial. - Graceful release on stop / pool-shrink: a slot hands its still-leased jobs back via client.release() so they're re-picked immediately (pairs with the server recovery sweep). Not CI-tested (agent/ outside CI) — verified by running. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |
||
|
bvandeusen
|
8419ebd761 |
feat(agent): desktop GPU agent container — CCIP + figure crops over HTTP (#114)
The last piece: a Dockerised desktop-GPU worker that talks to FC ONLY over HTTP (lease → fetch pixels → detect figures + CCIP-embed → submit), so Redis/Postgres stay private. New top-level agent/ (outside CI scope — verified by running it): - fc_agent/worker.py: the lease/compute/submit loop, concurrency 1, start/pause/ stop (stop frees the card; unprocessed leases expire + re-queue). - fc_agent/models.py: imgutils wrappers — detect_person (figures) + CCIP embed. The two API seams to verify against the installed dghs-imgutils (flagged). - fc_agent/media.py: stills + video frame sampling (ffmpeg) at FC's cadence → per-frame instances (the bag). - fc_agent/crops.py: vendored crop primitive. client.py: the FC HTTP client. - fc_agent/app.py: FastAPI localhost control UI (start/pause/stop + progress + queue depth). Dockerfile (CUDA + onnxruntime-gpu + ffmpeg) + requirements + README (token → build → run --gpus all → Start; CPU-fallback path). This completes the CCIP pipeline end to end: agent produces region CCIP vectors → RegionService stores → matcher suggests characters → rail. Verified by running on the desktop (not CI). README calls out the imgutils API + model-string checks. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa |