* fix(api): correct format/filename/container handling across tool routes
Found during a comprehensive QA sweep exercising every tool against its
full accepted-format matrix:
- watermark-image, compose: preserve the requested output format and a
matching download filename/extension instead of always emitting the
source format
- compose: crop oversized overlays to the visible base area instead of
crashing Sharp's composite, and reject only overlays fully outside the
base image instead of any oversized one
- compare, vectorize: switch to the shared image input handler so
filenames and formats like .svgz/.tga/RAW survive validation instead
of being rejected pre-processing
- tool-factory, images-to-video: normalize frames through Sharp before
handing them to FFmpeg, fixing GIF/AVIF/RAW image-to-video jobs that
previously failed or hung
- media-tool, replace-audio, embed-subtitles: fix legacy container
MIME/codec handling for MPEG sources and subtitle remux cases
- files: expand download MIME mapping for text/data/document/video/audio
outputs that were falling back to a generic content type
- convert-document/presentation/spreadsheet: same-format conversions now
return the original validated file instead of erroring or producing
corrupt tiny output
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(web): dropzone a11y, stale localStorage getter, dead code
- dropzone: stop making the whole drop-zone section clickable/focusable.
A section acting as an interactive element around a real upload button
is a nested-interactive-element anti-pattern that confuses screen
readers; drag-and-drop doesn't need focus semantics, only the button
fallback does. Keeps that button semantic and keyboard-reachable.
Updates the two e2e call sites that clicked the section directly.
- api, use-auth: read through window.localStorage via the existing API
storage helper instead of the bare global, which resolves to Node's
experimental localStorage getter under Vitest and threw
- find-duplicates-settings, info-settings, login-page: remove dead code
(unused zip-download handler, a stale mount-only effect dependency
that left cached info stuck at reused indices, an unused response
variable)
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(i18n): pt-BR, zh-CN, zh-TW were silently falling back to English
The locale loader looked up dynamic-import exports by the raw locale
code (mod["pt-BR"], mod["zh-CN"], mod["zh-TW"]), but those three modules
export camelCased bindings (ptBR, zhCN, zhTW) since identifiers can't
contain hyphens. The lookup returned undefined and every consumer
silently fell back to English for these three locales. Replaces the
generic lookup with explicit per-locale loaders so the mapping can't
drift out of sync again.
Also updates the dropzone helper copy across all 21 locales to match
the drag-only dropzone wording from the previous commit.
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(docs): clear build warnings in the VitePress site
- config.mts: add an onwarn handler for the @vueuse INVALID_ANNOTATION
warnings emitted during the docs build
- deployment.md: the caddyfile code fence language isn't a shiki grammar
VitePress ships with, so it warned on every build; use txt instead
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* test(qa): update QA harness for the drag-only dropzone and regen metadata
- api-sweep, qa-helpers, verify-ai: add JSON-body tools, multi-input
secondary fixtures, async polling for slow valid jobs, 501
FEATURE_NOT_INSTALLED skip handling, and safer per-tool settings
- input-preview, pipeline-ui specs: update upload flow for the
drag-only dropzone surface
- add tests/fixtures/data/valid/chart.json, a valid chart fixture the
updated helpers route to
- regenerate tools-meta.json against current TOOLS[]
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(security): close a login timing side-channel, harden zip-slip tests
Found during a black-box security sweep of the real auth-enabled
production container: a nonexistent username returned 401 in ~3-10ms,
while a wrong password for a real user took ~35-42ms, because scrypt
verification only ran when a user row existed. That timing gap lets an
attacker enumerate valid usernames without ever guessing a password.
Now runs verification against a cached dummy hash on the unknown-user
path too, so both cases cost the same regardless of outcome.
extract-zip already had a relative-traversal regression test
(../evil.txt), but its absolute-path rejection branches
(name.startsWith("/") / startsWith("\\")) had none. Added the three
missing cases: deep relative traversal, absolute Unix path, and
Windows-style absolute path.
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* test(qa): add UI-driven AI bundle install scripts
QA_PROMPT.md's Phase 2 requires installing AI models the way a user
does -- through the UI, on demand from HuggingFace -- and treats the
curl-based admin install endpoint as fallback-only. Nothing in the
harness actually drove that flow; tests/qa/seed-ai-models.sh installs
via docker exec + pip, which is further from a real user than even the
API fallback.
install-ai-bundles-ui.mts logs in, opens Settings > AI Features,
screenshots the pre-install state, clicks Install All, and screenshots
progress -- then exits, since installs continue server-side once
triggered. verify-ai-install-complete.mts polls bundle status,
screenshots the completed state, and runs one real tool per installed
bundle to prove the freshly-downloaded model actually executes.
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(qa): correct the apiToolPath import in the AI verify script
Dynamic import of the package name failed under tsx's module resolution
from apps/api's node_modules context; use the same relative-path import
api-sweep.mts already uses successfully.
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(web): correct AI bundle size estimates shown before install
Measured real downloads during GPU-node QA verification: photo-restoration
pulls ~4.4GB (was advertised as 800MB-1GB, off by 4-5x) and ocr pulls
~5.5GB (was advertised as 3-4GB). Both estimates only accounted for model
weights, not the pip dependencies (torch/paddle) that come down with them.
Updated to reflect actual total download size, since that's what a user
deciding whether they have the disk/bandwidth actually needs to know.
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(web): make desktop Settings reachable when auth is disabled
AvatarDropdown (the only desktop entry point to Settings) was gated
behind `!isMobile && authEnabled`. With AUTH_ENABLED=false the synthetic
anonymous admin user should have full Settings access per how auth.ts
documents this mode -- and the mobile bottom nav already worked this way,
showing Settings unconditionally. Desktop just had a stray extra gate the
component doesn't need: AvatarDropdown already resolves its own username
internally (falling back to "admin") and reads authEnabled itself where
it actually matters (hiding the Logout button). Removed the outer gate;
verified end-to-end against a fresh AUTH_ENABLED=false instance -- avatar
now renders, Settings opens, shows the anonymous/Admin identity correctly.
Also documents (not changes) a related finding in install_feature.py:
detect_arch() always resolves amd64 hosts to the GPU-bundled archive
variant regardless of actual GPU presence, since no CPU-only amd64
archive is published to the bundle repo yet. Left as a code comment
rather than a behavior change, since requesting an unpublished archive
key would hard-fail installs entirely -- worse than the current
oversized-but-working download. Full detail in the QA report.
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(ai): stop logging expected dispatcher reloads as crashes
After each AI bundle install the Python dispatcher reloads because the
venv changed, and after every app shutdown it's SIGTERMed. Both took the
close handler's `code !== 0` branch (SIGTERM makes the exit code null),
so they were counted as crashes -- producing an alarming "crash" line in
the logs and a pointless ~1s recovery backoff after each of 7 installs.
A `stopping` flag set in shutdown() lets the close handler tell an
intentional stop apart from a real crash. The request-timeout kill path
deliberately does not set it, so a genuinely hung script still records a
crash and the 5-in-60s permanent-disable threshold is untouched.
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(api): return a clean message when content-aware resize times out
Carving a very high-resolution image down to a tiny target could exceed
the caire subprocess timeout, and the raw error forwarded to the user was
caire's terminal output -- ANSI color codes and progress-spinner control
characters -- instead of anything actionable. Now: the timeout path
throws a clear "timed out; try a smaller image or larger target" message
(keeping the raw stderr as `cause` for server logs); friendlyError()
strips ANSI/control chars centrally so any subprocess dump surfaced
through the shared sanitizer is plain text; and the content-aware-resize
route (a custom route that bypassed the sanitizer) now routes its error
paths through friendlyError like every other tool.
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(ai): stop bundle installs from exhausting host disk
Installing an AI bundle on a tight-disk host could push the root
filesystem to zero bytes free after the preflight check had already
passed. Two root causes:
- move_tree used copytree+rmtree, so during the move the extracted
payload existed in both staging and the venv at once -- a full
transient doubling on disk. Rewrote it to rename entries (a cheap
metadata op on the same filesystem, no copy), falling back to a copy
only across filesystems.
- the preflight budget used the manifest's extractedSize verbatim, which
is 0 for several archives, collapsing the estimate to just the
compressed size. Added a conservative fallback (3x compressed) so a
missing value can't under-reserve.
Also added a real-on-disk re-check immediately before the first
destructive venv write (measuring the actual extracted payload and
whether the move needs extra space for a cross-filesystem copy), which
also now covers the offline-import path that previously skipped the disk
check entirely; wrapped the moves so an out-of-space failure returns a
clean actionable error instead of a traceback; and made the disk check
resolve the nearest existing ancestor so it never throws on a
not-yet-created venv path.
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* feat(web): show the real per-arch AI bundle download size
The bundle cards and install prompt showed a hardcoded, architecture-blind
estimatedSize string. That's misleading: amd64 hosts always pull the
CUDA-inclusive archive (there's no CPU-only amd64 variant published), so a
bundle labelled "1-2 GB" can actually download several times that, while
arm64 pulls a much smaller archive for the same label. The manifest
already carries the real per-arch compressedSize (and extractedSize where
measured), so surface those: a new optional downloadBytes/installedBytes
on FeatureBundleState, populated in getFeatureStates() for this host's
arch (resolver mirrors install_feature.py detect_arch), shown by the UI
when present with estimatedSize kept as the fallback label. Also nudged
upscale-enhance's fallback string (4-5 -> 5-6 GB) to match its real
compressed size, consistent with the earlier photo-restoration/ocr fixes.
Fields are optional so demo/mock and existing tests stay compiling; the
manifest's extractedSize is 0 for a few archives, which now surfaces as
null rather than a bogus 0.
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(web): move the AI install queue to the server so it survives tab close
Installing multiple bundles could silently lose all but the first. The
server rejected a concurrent install with 409, so the client worked
around it by queueing the rest in browser-local state and only POSTing
each once it saw the previous finish. A single POSTed install is durable
(the installer child is detached from the request), but a queued one had
zero server footprint -- close the tab mid-queue and those installs
vanished with no error, while the UI still showed them "Queued". The
client "mutex" didn't even serialize: the queued bundles' local waits all
resolved at once and raced into concurrent POSTs that 409'd each other.
Now the queue lives on the server (a small in-memory FIFO leaf module).
The install endpoint enqueues instead of 409-ing and returns
202 {jobId, queued}; a pump starts the next bundle when the current one's
child exits (and after an offline import releases the lock), all behind
the existing venv + file locks, which are unchanged. The client just
POSTs every bundle immediately and reflects the server-reported
queued/installing status; Install All fires all POSTs and lets the server
serialize them, keeping the one-shot retry-on-failure. Adds "queued" to
FeatureStatus (the bundle card already rendered that state) and surfaces
it from getFeatureStates. In-memory is deliberate: it matches the
existing contract (survives a tab close, not a server restart, which
already clears the lock on boot).
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
* fix(qa): don't log env-derived credentials in the AI-install script
CodeQL flagged clear-text logging of sensitive information: the login
status line interpolated the QA base URL and username (both read from
the process environment) into a console.log. Replaced with a static
message. QA helper only, but it's a real hygiene issue and cleared the
high-severity code-scanning alert on the PR.
Claude-Session: https://claude.ai/code/session_019fpSXhLGLXWwfyZY2tWhLG
Found and fixed during a full local Docker build validation (amd64/arm64, all
four fleet targets, AI bundle installs, QA harness) and the follow-up bug
sweep requested afterward. None of the affected scripts run in CI, so these
had been silently broken indefinitely.
- docker/feature-manifest.json: pythonVersion was a flat "3.11", but the
amd64 base (Ubuntu 24.04) ships Python 3.12 while arm64 (Debian bookworm)
ships 3.11. Changed to a per-arch object matching the file's existing
convention.
- tests/qa/api-sweep.mts and verify-ai.mts: bare "@snapotter/shared" import
can't resolve since tests/ is not a pnpm workspace member, making both
silently unrunnable via their own documented command on any fresh
checkout. Switched to a relative import.
- tests/qa/generate-ledger.mts: wrote to docs/qa/ without creating the
directory first; docs/ is gitignored except COMMUNITY_GUIDE.md, so a fresh
checkout threw ENOENT.
- Seven QA Playwright spec files (input-preview, settings,
settings-extended, multifile, output-preview, pipeline-ui, smoke) had
~115 fixture() calls using directory names that don't exist. Resolved
every call programmatically against the real fixture tree.
- packages/ai/src/bridge.ts: AI dispatcher restart (happens on every bundle
install) was falsely counted as a crash, risking permanent dispatcher
disable after enough legitimate restarts within the crash window. Added a
shuttingDown flag checked at all three recordCrash() call sites.
- packages/image-engine/src/operations/auto-enhance.ts: image-enhancement
hung 40+ seconds on large RAW photos (confirmed on a real 20.2MP file) in
Sharp's .clahe() step, whose cost scales with total pixel count regardless
of tile size. Added a 16-megapixel cap above which CLAHE is skipped;
verified against the real file (40+s -> 2.0s) with no regression to other
RAW formats or normal-sized images. Fixing this surfaced a second,
smaller bug where the saturation step's CLAHE compensation boost was
keyed off the raw toggle instead of whether CLAHE actually ran.
- Two QA-harness robustness gaps closed per "fix everything, even the small
bugs": the passport-photo/erase-object input-preview tests now skip
cleanly with a clear reason on a container without their AI bundle
installed, and docker-compose.qa.yml's hardcoded project/container name
(the actual root cause of a mid-validation container swap between two
concurrent sessions) is now parameterized via QA_PROJECT_NAME.
Full validation report is local-only per repo convention.
* feat: add usage-survey feedback types and gating function
Claude-Session: https://claude.ai/code/session_01KAC9Lbx8AmebAnj9WQZXHp
* feat: add onboarding usage-survey i18n strings to all locales
Relabels three ambiguous feedback.usageTypes values (personal/team_internal/
business_workflow) and adds a new onboarding namespace (4 keys) across the
reference locale and all 20 translations, so the tree compiles at every
commit instead of only after both locale groups land.
Claude-Session: https://claude.ai/code/session_01KAC9Lbx8AmebAnj9WQZXHp
* feat: add UsageSurveyOverlay component
* feat: mount UsageSurveyOverlay inside AuthGuard
Claude-Session: https://claude.ai/code/session_01KAC9Lbx8AmebAnj9WQZXHp
* fix: use text-start instead of text-left for RTL support in UsageSurveyOverlay
* refactor: drop redundant usage-type field from the admin feedback dialog
Claude-Session: https://claude.ai/code/session_01KAC9Lbx8AmebAnj9WQZXHp
* feat: accept onboarding source and survey id in the feedback route
Claude-Session: https://claude.ai/code/session_01KAC9Lbx8AmebAnj9WQZXHp
* test: cover the onboarding source in the feedback route integration test
Claude-Session: https://claude.ai/code/session_01KAC9Lbx8AmebAnj9WQZXHp
* chore: remove orphaned usageTypeLabel i18n key
* refactor: derive feedback source/survey_id enums from a single source of truth
* perf: skip the settings fetch in UsageSurveyOverlay for non-admin users
Centralizes the sharp format key type into a single `SharpFormat` alias derived from `toFormat()`'s signature (exported from @snapotter/image-engine, imported by the API consumers), replacing the duplicated `keyof FormatEnum` definitions. Adds convert/compress format round-trip tests covering webp/avif/png/jpeg. Part of #325.
Adds a prefilled 'Request a tool' affordance to the home search empty state and beneath weak results. Opens the in-app feedback dialog with a new search_miss source and a structured search_query when analytics is on; links to a prefilled GitHub Discussions (Ideas) post when off, so a request is never silently dropped. Reuses the existing feedback pipe, dialog, and analytics gate; no new storage. i18n across all 21 locales.
Draw, type, or upload a signature and place resizable/rotatable copies across PDF pages; output flattened server-side with PyMuPDF. Visual electronic signature, not cryptographic. New interactive-sign display mode (pdf.js + Konva) and a custom docs-pool route.
PR #364 only changed en/nl; the appDescription and rotating-phrase tool count was still '240' (translated) in the other 19 locales (ar, de, es, fr, hi, id, it, ja, ko, pl, pt-BR, ru, sv, th, tr, uk, vi, zh-CN, zh-TW). Replaces the number in each; surrounding translations untouched. My earlier English-only grep missed these.
* fix(landing): correct PDF tool count to 28 in alternatives copy
The pdf section has 28 tools (section.test.ts asserts bySection('pdf')=28). PR #363 corrected the docs breakdown but the alternatives pages still said 40 PDF tools (the document-modality count, not the pdf section) with 200 for the rest. Update to 28 PDF tools and 212 for the non-PDF remainder.
* chore: use "200+ tools" for the tool-count claim across public surfaces
Replaces the exact '240 tools' count (which drifts as tools are added) with the stable '200+ tools' on README, the Docker Hub overview, landing pages, the docs site (meta, homepage, search), the API self-description, the demo OG tag, llms.txt, package.json, the branding readme, and the en/nl app strings. Per-modality breakdown tables stay exact. Leaves the architecture doc's technical 'tool routes' figure, an internal vitest comment, and a QA report line unchanged. Updates the two tests that assert the docs strings.
Lands five integrated branches: pipeline templates (#355), analytics opt-out (#354), 83 conversion presets bringing the catalog to 240 tools (#356), self-hosted positioning (#353), and e2e modernization (#351).
Integration fixes: aligned stale web analytics tests with the opt-out/allow-list model, closed 3 CodeQL incomplete-sanitization alerts in the i18n generator, resolved settings/index/docs/format-matrix conflicts, and corrected tool counts to 240.
* fix(enterprise): ship enterprise pkg in prod image, full license features, tracing key fallback
docker/Dockerfile: COPY packages/enterprise manifest+src into the production stage.
Without it, apps/api's workspace link to @snapotter/enterprise dangles and every
import() throws (silently caught), so all 19 enterprise features failed closed
(enterprise.active=false) regardless of a valid license.
scripts/generate-license.mjs: sync PLAN_FEATURES with packages/enterprise/src/license.ts
so a --plan enterprise license unlocks all 19 features (was 8) and team unlocks 8.
apps/api/src/tracing.ts: accept SNAPOTTER_LICENSE_KEY as a fallback to LICENSE_KEY so
distributed_tracing activates with the same key as the rest of the app.
* fix(docker): keep scripts/bake-analytics.mjs in build context
.dockerignore excluded the whole scripts/ dir (PR #82, V1 hardening), but
docker/Dockerfile later added 'COPY scripts/bake-analytics.mjs' for the analytics
bake step. A clean production image build therefore fails with
'scripts/bake-analytics.mjs: not found'. The published image build is gated off in
CI so this latent break went unnoticed. Exclude scripts/* but re-include the one
file the Dockerfile needs.
* fix: S3 upload stream, analytics bake reaches API, dedupe retention field, reconcile orphan jobs
storage-s3.ts: wrap the upload AsyncIterable in Readable.from() so @aws-sdk/lib-storage
accepts it. STORAGE_MODE=s3 file uploads failed with 'Body Data is unsupported format'
for every tool because a bare async generator is not a Readable.
docker/Dockerfile: COPY the builder-baked analytics baked.ts into the API runtime stage.
The API re-copied the committed (off) baked.ts from the build context, so the
SNAPOTTER_ANALYTICS build arg had no effect on the API -- and since the SPA reads
/api/v1/config/analytics, analytics was off everywhere regardless of the arg.
settings-dialog.tsx: remove the duplicate tempFileMaxAgeHours control under Data
Retention; it bound the same setting key as the File Management control with a different
default, so editing either silently overwrote the other.
apps/api/src/index.ts: reconcile orphaned job rows (empty tool_id, never enqueued to
BullMQ) at boot so they don't sit in processing/queued forever and inflate the per-user
concurrent-job count and the upgrade-check in-flight gate.
* fix(web): style the SSO login buttons (they referenced undefined theme tokens)
The OIDC/SAML 'Sign in with <provider>' buttons used bg-secondary /
text-secondary-foreground, which the web theme never defines (it has primary,
background, foreground, muted, border, card, primary-subtle). Those classes resolved
to nothing, so the buttons rendered as bare unstyled text on the login page.
Restyle: the optional (non-enforced) buttons become white-card outline buttons with a
key icon and an orange hover tint, secondary to the primary Login button; the
SSO-enforced buttons become solid primary with the icon.
* fix: gate S3 behind license, custom-role enterprise perms, wire retention UI, cleanup
S3 is a licensed feature, but shipping packages/enterprise in every image removed the
implicit gate, so STORAGE_MODE=s3 worked without a license. Enforce
isFeatureEnabled('s3_storage') at boot and fail fast if unlicensed.
Custom roles can now be granted security:manage / compliance:manage / webhooks:manage
(roles.ts ALL_PERMISSIONS + the Roles UI) so admins can build least-privilege
compliance/security roles instead of only the built-in admin role.
retentionSweep now reads the jobsRetentionDays / auditRetentionDays DB settings the
System Settings UI writes (env vars become the fallback default), mirroring how the
temp-file sweep reads tempFileMaxAgeHours. Previously those two UI controls were no-ops.
Cleanup: drop the never-set snapotter_storage_bytes gauge and the unused
MAX_WORKSPACE_SIZE_GB env var; emit tool_client_error to PostHog from the web
ErrorBoundary (client crashes were not reaching analytics); add the Python
OpenTelemetry packages so the innermost sidecar.<script> span exports; fix the stale
'only local storage' line in the docs; delete two e2e-analytics specs that tested the
removed consent UI.
* fix(env): restore MAX_WORKSPACE_SIZE_GB default
security-auth-hardening.test.ts asserts env.MAX_WORKSPACE_SIZE_GB defaults to 10, so
the var is an intentional (tested) default, not dead code. Removing it in the cleanup
commit broke that unit test. Keep the declaration.
* fix(docker): pin CUDA base to 12.6 so the GPU image starts on R560+ drivers
The amd64 base nvidia/cuda:12.9.2-cudnn-runtime bakes a cuda>=12.9 driver gate enforced by nvidia-container-toolkit at container start, so the image fails to launch on common production drivers (e.g. 570.x / CUDA 12.8). The AI bundles are all cu126 wheels and the image installs libcublas-12-6, so 12.9 was misaligned with the workload. Pin to nvidia/cuda:12.6.3-cudnn-runtime-ubuntu24.04 to match the wheels and lower the driver floor to R560+.
* fix(ai): broaden OOM detection so the rembg lighter-model fallback fires
onnxruntime/CUDA allocation failures surface as 'Failed to allocate memory for requested buffer', CUBLAS_STATUS_ALLOC_FAILED, or bad_alloc, not just 'out of memory'. The background-removal and transparency-fixer fallback-to-lighter-model paths only matched the literal 'out of memory', so the fallback was dead code and transparency-fixer (default birefnet-hr-matting) always failed with an allocation error. Add isMemoryAllocError() and use it in both checks.
* fix(ai): use bundled PaddleOCR models so OCR runs offline
ocr.py passed no model dirs to PaddleOCR, so PaddleX resolved models from ~/.paddlex and downloaded them from HuggingFace at runtime (slow first use, broken air-gapped), ignoring the models the OCR bundle ships in MODELS_PATH; it also pulled doc-orientation/unwarping models that are not bundled. Pin detection, recognition and textline models to the bundled dirs in MODELS_PATH (per language) and disable use_doc_orientation_classify / use_doc_unwarping, with per-component fallback when a model is absent. Verified: OCR runs with zero HuggingFace requests.
* fix(docker): add CAP_KILL so container shutdown is graceful
cap_drop: ALL without re-adding KILL meant tini (PID 1, root) could not forward SIGTERM to the gosu-dropped snapotter process (root minus CAP_KILL cannot signal a different UID). docker stop logged '[FATAL tini] forwarding signal: Operation not permitted', never delivered the signal, and fell back to SIGKILL after the 10s timeout. Add KILL to cap_add in both compose files. Verified: docker stop completes in 0s with SIGTERM delivered (exit 143) and no FATAL tini.
* fix(ai): serialize bundle installs against AI jobs to prevent sidecar segfault
A feature bundle install rewrites the shared Python venv (pip + copytree of site-packages/*.so) as a background subprocess, with no coordination against AI tool jobs that dlopen native libs (torch / onnxruntime CUDA) from the same venv; a job loading a shared object while it is overwritten segfaults the sidecar. Add a process-wide async mutex (venv-lock.ts): bridge.run() acquires it before every AI script and the install route holds it across the installer subprocess. Both run in the same Node process so a module-level lock suffices. Verified: concurrent install + AI job produces zero segfaults and the job serializes behind the install.
* fix(ai): make the venv lock read/write so concurrent AI jobs are not serialized
The first cut used an exclusive mutex, which (a) deferred the dispatcher spawn by a microtask and broke unit tests that synchronously drive the mocked spawn, and (b) serialized AI jobs against each other, removing the dispatcher's by-id request multiplexing. Make it a writer-preferring read/write lock: AI jobs are shared readers (with a synchronous fast path so spawn still happens in-tick) and a bundle install is the exclusive writer. Verified: all 764 AI unit tests pass.
* fix(ai): degrade OCR to Tesseract on CPU-only hosts instead of segfaulting
The amd64 AI bundle ships paddlepaddle-gpu, whose native libs dlopen
libcuda.so.1 at import and segfault on a host without a GPU (libcuda is the
driver lib, injected only by nvidia-container-toolkit on GPU hosts). The
segfault crashed the shared long-lived AI dispatcher and, after a few attempts,
tripped the bridge crash-recovery permanent-disable, wedging all AI until a
container restart. The standalone ocr tool defaults to quality=balanced
(PaddleOCR), so it hit this on every CPU-only deployment; ocr-pdf already
hardcoded Tesseract and was unaffected.
ocr.py now gates the PaddleOCR tiers on gpu_available(): balanced/best
transparently fall back to fast (Tesseract, CPU-capable) when no usable GPU is
present, and run_paddleocr_v5/run_paddleocr_vl refuse before importing paddle so
the GPU build is never dlopen'd on CPU. GPU hosts are unchanged.
Verified on a CPU-only Windows/WSL2 box: ocr returns Tesseract text across
repeated runs with the dispatcher staying healthy (no wedge).
The persistent Python dispatcher rejects scripts whose feature bundle is not
installed, but the per-request fallback (used when the dispatcher is down, e.g.
restarting right after a model repair) spawned scripts directly and bypassed
that gate. Behavior was therefore inconsistent: a gated script would fail under
the dispatcher but run under the fallback -- the "works once after a repair"
symptom from the original report.
- add packages/ai/src/feature-gate.ts: SCRIPT_BUNDLE_MAP + missingBundleForScript,
mirroring TOOL_BUNDLE_MAP in dispatcher.py, reading the same installed.json and
failing closed exactly like dispatcher._get_installed_bundles()
- runPerRequest now rejects with "feature_not_installed" (the same message the
dispatcher path surfaces) when a gated script's bundle is not installed
- unit tests for the gate, plus a drift test pinning the TS map to dispatcher.py
Closes#327
* fix(passport-photo): require the face-detection bundle, not just background-removal
Passport Photo runs face-landmark detection (face_landmarks.py, gated to the
face-detection bundle) before background removal (background-removal bundle),
but it was only declared under and guarded against background-removal. A user
who installed only Background Removal passed every JS-side check, then hit a
late "feature_not_installed" from the Python dispatcher gate when the analyze
step ran face landmarks, and the UI never told them Face Detection was needed.
- shared: add TOOL_EXTRA_BUNDLES + getRequiredBundlesForTool so a tool can
declare more than one required bundle (passport-photo needs background-removal
and face-detection). enablesTools is untouched, so the one-tool-per-bundle
invariant still holds.
- api: isToolInstalled() now checks every required bundle; add
getFirstMissingBundleForTool() so the analyze and base routes, pipeline (both
guards) and batch report the bundle the user actually still needs.
- web: the proactive install prompt (tool-page) and features-store treat a tool
as installed only when all required bundles are present, and point the prompt
at the first missing one (sequential install, no new UI).
Refs #327
* test(passport-photo): deterministic integration coverage for the two-bundle guard
Boots the real API with an isolated DATA_DIR and controls installed.json to
prove the HTTP route behavior end-to-end:
- nothing installed -> 501 naming background-removal
- only background-removal installed -> 501 naming face-detection (issue #327)
- both installed -> guard passes (not 501)
- base route reports face-detection too
Refs #327
* feat(web): add pure zoom/pan math module with unit tests
* feat(i18n): add a11y.pan key across all locales (English, matching adjacent zoom labels)
* feat(web): add useZoomPan hook (state + gestures over pure math)
* feat(web): add ZoomToolbar component
* feat(web): zoom & pan in the object eraser canvas
* feat(web): zoom & pan in the split tool preview
* fix(web): synchronous pan-mode refs so drag-pan is race-free under fast input
* test(e2e): zoom & pan acceptance (split always-on, eraser bundle-gated)
Translate the ~950 previously-untranslated Swedish UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated German UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Brazilian Portuguese UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated French UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Spanish UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
The auth.rotatingPhrases and features.progressMessages arrays were skipped by
the main Italian pass (#298) and still had a few missing accents (e.g. verb
e -> è). Diacritic-only fix; wording, placeholders, and key parity unchanged.
Translate the ~950 previously-untranslated Thai UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Indonesian UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Vietnamese UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Hindi UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Turkish UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Arabic UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Ukrainian UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Polish UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Russian UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Dutch UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Korean UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Japanese UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Traditional Chinese UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Translate the ~950 previously-untranslated Simplified Chinese UI strings (tool names,
descriptions, settings labels, dialogs) that were still showing English, and
restore the {size} placeholder dropped from settings.aiFeatures.diskUsage.
Machine-translated and verified: full key parity with en.ts, all {placeholders}
preserved, passes tsc and Biome. Native-speaker review welcome.
Around 35% of Italian strings (903 of 2583) were still English while the
file silently typechecked (key parity was already correct). This translates
them and fixes quality issues in the existing Italian:
- Translate untranslated tool names, descriptions, categories and UI labels;
keep legitimate English terms (formats, URL, Team, Pipeline, device presets)
- Fix accent errors (qualita->qualità, piu->più, Si e->Si è, and similar)
- Restore the {size} placeholder dropped from settings.aiFeatures.diskUsage
- Make role labels consistent Italian: Utente / Editore / Amministratore
- Normalize stray curly apostrophes to the file's straight-quote convention
Based on the Italian translation contributed by @albanobattistella (the issue
author), reconciled against the current en.ts (e.g. the Data->Files rename)
and corrected for accents and a structural error in the source.
Closes#231
* fix(deps): patch gray-matter onto js-yaml 4.2.0 (close js-yaml DoS alert)
js-yaml 3.14.2 (quadratic-complexity DoS in merge-key handling, GHSA
patched only in 4.2.0) was kept in the tree by a scoped pnpm override
"gray-matter>js-yaml": "^3.14.1" that exempted gray-matter from the
global js-yaml>=4.2.0 override. gray-matter is a build-time-only
transitive dep of the docs site (vitepress-plugin-llms,
@sugarat/theme-shared) and pinned 3.x because it calls the removed
yaml.safeLoad / yaml.safeDump APIs.
Remove the exemption so gray-matter resolves js-yaml 4.2.0, and add a
pnpm patch renaming safeLoad->load / safeDump->dump (the 4.x
equivalents; load is safe by default). js-yaml 3.x is now gone from the
lockfile.
Verified: gray-matter parse+stringify smoke test passes on 4.2.0; full
VitePress docs build green (177 pages, llms plugin parses all tool
frontmatter with no safeLoad/safeDump error).
* docs(ai): document rembg 2.0.69 pin and advisory non-reachability
The patched rembg 2.0.75 pulls a numpy 2.x closure (numpy>=2.3,
scipy>=1.16, scikit-image>=0.26) that is incompatible with the
numpy==1.26.4-locked AI stack (realesrgan 0.3.0 and codeformer-pip 0.0.4
break on numpy 2.x). Both open rembg advisories are unreachable in this
codebase: rembg is used purely as a library (never the `rembg s`
server), and new_session() only receives allowlisted model names
(remove_bg.py ALLOWED_MODELS), never user-controlled paths. Record this
rationale next to the pin; the Dependabot alerts are dismissed as
not_used.
- svg-sanitize.ts: strip each dangerous element repeatedly until stable with
whitespace-tolerant end tags, defeating nested/overlapping tags (closes 5
incomplete-multi-character-sanitization + 1 bad-tag-filter; the prior
single-pass regex could leave a residual <script>/<iframe>).
- file-preview.ts: add a resolve()+containment barrier (the path-traversal
guard CodeQL recognizes) on top of the id charset check (closes 9
path-injection).
- metadata.ts: bound the XMP namespace:name key segments so parseXmp cannot
backtrack polynomially (closes js/polynomial-redos).
- analytics-disabled.spec.ts: match analytics by URL host, not substring
(closes 4 incomplete-url-substring-sanitization).
typecheck + lint green; svg (119), preview (22), metadata (164) tests pass.
rembg 2.0.75 requires a numpy incompatible with the pinned numpy==1.26.4
that the rest of the ML stack (onnxruntime etc.) depends on, making
pip-audit's resolution impossible. The rembg <2.0.75 advisory (medium) is
accepted as a residual: it only affects the on-demand background-removal AI
bundle (publishing currently paused) and can't be patched without a numpy
2.x migration across the whole Python sidecar.
