A release-readiness QA pass over the whole product. The commits split into
defects a user would hit and gates that were reporting green while measuring
nothing.
## Fixes that change behaviour
Rate limiting was bypassable on every install: TRUST_PROXY defaulted to true, so
request.ip came from a client-set header and a forged X-Forwarded-For got past
the login limiter. The default is now a private-network trust list.
A transient Postgres outage stranded in-flight jobs, leaving finished output on
disk with no row pointing at it. A reconciler now resolves those rows and adopts
the bytes rather than dropping the work.
A Redis connection that moved to a new address wedged every read-blocked
consumer, so completions stopped signalling while health still answered 200.
Socket timeouts plus subscriber pings recover it.
Installing more than one AI bundle left the shared venv multi-versioned and
silently broke three tools. The installer now reconciles distributions to one
version each.
Converting an image to JXL at quality 1 through 4 returned a 500, because
libjxl 0.7 rejects the distance those values compute. The quality is floored at
what the encoder honours. A missing ffmpeg was also reported to the user as a
corrupt upload; it now says the engine is unavailable.
RAW uploads reached an unpatched LibRaw on arm64, so it is built from source at
0.22.2, and the release scan was split so it can fail on an unfixed critical
instead of hiding it behind ignore-unfixed.
## Gates that could not fail
Two mutation lanes ran zero mutants because Stryker crawled the gitignored docs
build; coverage discarded its whole report on any failing test; the lint gate
skipped root tests, scripts, and two workspaces; and several generated matrices
counted a host missing ffmpeg as a passing tool. Each now measures what it
claims.
Full evidence and the outstanding release items are tracked locally and are not
part of this branch.
Adds an opt-in High Quality mode to the Object Eraser, backed by a new inpaint-hq feature bundle (Stable Diffusion 1.5 inpainting via diffusers). The default fast LaMa path is unchanged. Both arch archives are published to deepsafe/feature-bundles and the manifest carries their real sha256/sizes.
Verified end to end: a fresh container pulls the bundle from HuggingFace, checksum-verifies it, extracts torch/diffusers plus the fp16 model, and the HQ sidecar erases a large object with a plausible fill.
Refs #141
Adds a Brush | Lasso toggle to the object eraser. Lasso lets the user drag a freeform loop that auto-closes and fills into the mask, so they select around a subject instead of painting every pixel. Frontend-only; the mask contract is unchanged. Also un-skips the erase-object e2e suite via a shared mockAiFeaturesInstalled helper (7 tests now run; 2 multi-file tests fixme'd for a pre-existing tool-page remount bug). Closes#492.
The spec used the bare /erase-object route (404 under section URLs) and the
old flat fixture path (test-200x150.png moved to image/valid/), so every test
silently skipped. Point it at /image/erase-object and the correct fixture, and
add a 404 guard so future route rot fails loudly instead of skipping.
- Add 8 new E2E specs for AI tools (upscale, enhance-faces, colorize,
restore-photo, erase-object, smart-crop, passport-photo, red-eye-removal)
closing all HIGH/MEDIUM coverage gaps from the test matrix audit
- Fix ensureAiDirs() crash on non-Docker environments by gating on
isDockerEnvironment() — prevents ENOENT when /data doesn't exist
- Bump torch 2.6.0→2.7.0 and torchvision 0.21.0→0.22.0 in feature
manifest for broader Python version compatibility
- Add Python 3.14 version guard warning in install_feature.py
- Remove duplicate torchvision shims from upscale.py and enhance_faces.py
(dispatcher.py already handles this at startup)
- Remove orphaned tools.batch i18n key and dead pipeline-builder filter
- Regenerate 4 visual regression baselines for current UI state
- Add data-testid to passport-photo generate button for E2E testability