Fixes found by manually testing a fresh install end to end:
- auth: the must-change-password gate returned 403 on public routes
including /api/v1/health, so every fresh install showed a false
"Reconnecting to server" banner on the forced password change
screen. Public routes are now exempt (they need no session at all).
Adds the gate's first direct tests.
- multipart: @fastify/multipart's parts() iterator (9.4.0 and 10.0.0)
ends on the request stream's "close", which on a reused keep-alive
connection fires while an earlier part is still streaming to storage,
silently dropping the parts behind it. The object eraser lost its
mask file on every second POST per connection. Replaced with a
busboy-driven iterator (lib/multipart-parts.ts) that ends on busboy's
own "finish", installed for all routes via a preValidation hook;
the tool-factory field-recovery workaround for the same bug is now
unnecessary and removed.
- eraser: the mask canvas backing store is natural resolution, but
"absolute inset-0" does not stretch replaced elements, so the
canvas rendered at intrinsic size and the brush ring, strokes, and
exported mask were all misscaled on photos larger than the viewport.
The canvas now gets an explicit CSS box at the fitted size.
- compare slider: solid white divider with a dark halo so it stays
visible over light images; still initialised at the painted region.
- tool page: the AI bundle install prompt now centers in the content
area instead of hugging the top.
- api docs: disabled Scalar's cloud features (Ask AI, Generate MCP,
Open API Client, dev toolbar), hid the "Powered by Scalar" footer
link, and set the page title to "SnapOtter API Reference". The docs
CSP blocks those cloud calls by design, so the buttons were dead UI.
- docker: embedded Redis comes from packages.redis.io pinned to the
8.x major (was Debian's 7.0.15), matching the Compose stack and the
documented claim. Build fails fast if the major ever drifts.
- docs: DOCKERHUB.md quick start now leads with the one-command docker
run (matching the README) with Compose as the production path;
README says embedded Postgres 17 + Redis 8.
Claude-Session: https://claude.ai/code/session_01XGB4pGvTvb7sUX4JN745U7
Fixes 15 defects found by a max-effort multi-agent review of the last 6
merged PRs (#388, #390, #391, #392, #393, #394), all adversarially
verified before fixing.
Install queue + dispatcher (the serious cluster):
- features.ts: finalize the installer child exactly once. A failed spawn
fires both "error" and "close", and the second event released the file
lock and active slot that pump() had just handed to the next queued
bundle, letting two pip processes write the same venv concurrently.
Outcome recording now happens before pump() so the next bundle's first
progress frame cannot race the previous install's bookkeeping.
- feature-status.ts: keep failed-install errors in a per-bundle map
instead of the single progress slot. With the queue auto-starting the
next install, the slot was overwritten within seconds and a failed
install vanished without ever surfacing to GET /features.
- bridge.ts: scope child lifecycle per process (stopped-children set +
request generation tags) instead of an instance-wide shuttingDown flag
that the next spawn reset. A stale SIGTERMed child's late close event
could record a phantom crash (5 of which permanently disable the
dispatcher), null out the freshly spawned child, and reject the new
child's pending requests. The request-timeout kill path still counts
as a real crash.
- install_feature.py: the pre-write disk re-check measured ai_dir's
filesystem even when budgeting the cross-filesystem copy that lands on
the venv's disk; now each budget is checked against the filesystem the
bytes actually land on, so ENOSPC cannot strike mid-write and leave
site-packages half overwritten.
Behavior regressions:
- embed-subtitles: preserve pre-existing subtitle tracks (0:s?) and MKV
attachments (0:t?) that the -map 0:v:0/0:a? rewrite silently dropped;
data streams stay unmapped on purpose (the actual MPEG remux fix). The
new subtitle maps first so the language tag hits the right stream.
- usage-survey-overlay: fail closed when the settings fetch fails; the
fail-open path rendered the blocking survey against an unhealthy API
and soft-locked admins, the lock-out class #392 fixed.
- features-store: queued bundles poll instead of each holding an SSE
connection (Install All could pin 7 EventSources and exhaust the
browser's 6-per-origin HTTP/1.1 limit, hanging the whole app);
listenToProgress closes any prior stream and stops any poll before
subscribing; installAll skips bundles already installing or queued.
Contracts, tests, i18n:
- openapi.yaml: add "queued" to the features status enum and document
downloadBytes/installedBytes (Schemathesis conformance).
- feature-lifecycle e2e: queue transcription (~0.5 GB) instead of ocr
(~6 GB) and give the test a budget that covers both install drains
(the stacked waits exceeded the old 900s timeout).
- docker-compose.qa.yml: parameterize the host port (QA_APP_PORT) so
QA_PROJECT_NAME concurrent stacks can actually bind.
- compare + watermark-image: restore per-input error attribution
("Invalid first/second image", "Invalid watermark image") lost in the
shared-handler migration.
- ai-features-section: the "{size} on disk" suffix now goes through
i18n; key added to all 21 locales.
- watermark-image + content-aware-resize: migrate to the shared
inputHandlerFor("image") chain like compare/vectorize/compose, fixing
drift in the inline copies (no SVG sanitize, no RAW extension hint,
no AVIF probe).
Verified: typecheck across 9 workspaces, Biome clean on all changed
files, 584 targeted unit tests and 249 integration tests green
(including real-ffmpeg embed-subtitles runs). One unit test updated to
the new poll-while-queued contract with a single-EventSource assertion.
Claude-Session: https://claude.ai/code/session_017mR1HiHaf3a1BmUtrHX4j3
* 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
* 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.
* 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.
Seven correctness fixes in the admin settings dialog and settings API: AdminSecuritySettings save echoing read-only/redacted keys; the server persisting the ******** mask over real OIDC/SIEM secrets on a settings round trip; the Tools panel missing its settings:write gate; three swallowed errors (ToolsSection save, ApiKeys generate and delete); and generatePassword omitting a special char under passwordRequireSpecial. Adds an integration regression test for the secret-mask no-op.
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.
edit-metadata writes EXIF tags in place and streams the original bytes
back, but the response content-type defaulted to image/jpeg for any
format outside a small map. A BMP/PSD/PPM download then claimed to be a
JPEG, and the nightly tool-x-format matrix tried to Sharp-decode it and
threw "unsupported image format".
Map every format validateImageBuffer can report to its real MIME type,
and switch the matrix's pixel-decode gate from a fragile denylist to an
allowlist of formats this libvips build is guaranteed to decode. Niche
raster types streamed back untouched now carry an honest content-type
we simply don't pixel-verify.
Verified green across all 157 tools x 34 formats with FULL_MATRIX=1.
* 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).
* 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
Tool endpoints (/api/v1/tools/*) now honor the RATE_LIMIT_PER_MIN env var instead of a hardcoded 60/min: `0` disables per-tool limiting, `>0` uses the configured value, and unset falls back to 60. Merged on top of the section-based route refactor (#280).
Fixes#271.
The resolve()+startsWith containment check was correct but CodeQL did not
recognize it. Apply path.basename() to the name in resolveWithinPreviewDir -- a
sanitizer CodeQL recognizes -- so every id-derived preview path is provably a
single filename inside the preview dir. Behaviour is unchanged for valid ids
(already charset-validated); containment check kept as a backstop.
- 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.
All /api/ routes are already covered by the global @fastify/rate-limit
(index.ts:283), but CodeQL doesn't model the global registration and flagged
every route without an explicit per-route limit. Added tuned config.rateLimit
to 45 routes: stricter on auth/credential routes (mfa/saml/oidc/api-keys,
15-30/min), moderate on writes (60/min), generous on reads/polls (300/min =
the global default). Real defense-in-depth on sensitive routes. 3 alerts on
non-route code (a preHandler hook, the rate-limiter's own DB lookup, a test
helper) are documented false-positives covered by the global limiter.
- file-preview.ts: validate the :id URL param against a safe charset and
restrict the original-name extension to alphanumerics before they feed
filesystem paths (closes 9 CodeQL js/path-injection; defense-in-depth on
top of the existing DB lookup).
- media-input.ts: require the SRT/VTT timecode structure to detect a subtitle
rather than a bare '-->' (closes CodeQL js/bad-tag-filter; also rejects
non-subtitle files that merely contain '-->').
#280 left 10 section-prefixed custom-route files mis-indented and one
unsorted import block in the new landing section-index page. Fixed via
biome formatter (api) and manual import sort (landing). No config change
(biome.json is hook-protected); no suppression. pnpm lint + typecheck
now exit 0.
The tool factory created its per-request validation scratch dir at tmpdir()/snapotter-scratch/<jobId> -- the same path the BullMQ worker uses for job processing (worker.ts scratchRoot()/<jobId>) whenever SCRATCH_PATH is unset. For sync tools this is harmless because the factory blocks on the worker before its finally cleanup runs. For "long" tools the factory returns 202 immediately and then rm's that dir, racing the worker that is writing the job's input there -- so tools that stage input in the worker scratch dir (epub-convert, to-epub) intermittently failed with ENOENT. Production never hit this because it sets SCRATCH_PATH, diverging the two paths. Give the factory's validation dir a -prep suffix so its cleanup can never touch the worker's job dir.
acceptedInputs is [.pdf], but pdf-to-image validated by calling mupdf.openDocument(buf, 'application/pdf'); mupdf sniffs the real format and opens JPEGs/PNGs/etc. as 1-page image-documents, returning 200. So non-PDF (incl. truncated/hostile) inputs were accepted, violating the contract and the hostile-input robustness check -- the one pre-existing failure surfaced by the full integration run. Gate all three endpoints (convert/info/preview) on the %PDF- magic bytes. Verified: truncated.jpg -> 400, valid PDF -> 200; the hostile-inputs test passes.
Main already reuses the per-modality input handlers in batch and pipeline
(#244), so the modality-aware reuse from the video QA sweep was redundant.
Port only the remaining unique piece: pass lenient: skipStructuralValidation
to the handler so batched/pipelined PDF tools that opt out of structural
validation behave like the single-file factory path. Keeps main's safer
explicit image-decode chain (HEIC/RAW/SVG/autoOrient) and AI fileId threading.
Add friendlyError() which collapses raw external-tool failure output (ffmpeg/ffprobe/LibreOffice/qpdf/etc.) into one generic sentence while preserving intentional validation messages and scrubbing internal paths. Apply it at every client-facing error surface in the tool factory and job worker (sync 422, async SSE, pipeline + batch finalize). The full error is still recorded server-side via request.log.error / logger.error and telemetry.
GIFs decode to bgra/gbrap (alpha); libvpx-vp9 rejects those pixel formats so the encoder never opened (ffmpeg exit 234), breaking GIF->WebM for essentially every GIF. Flatten to yuv420p in the webm branch, matching what the mp4 branch already does.
* docs: rebrand from image-only to multi-modality across docs and metadata
SnapOtter expanded from image-only to 157 tools across 5 modalities
(image, video, audio, document/PDF, data). Update all product-level
copy, metadata, and i18n that still framed it as an image-only tool.
- README, package.json, root llms.txt: multi-modality framing, 157 tools
- OpenAPI info + tags, generated /llms.txt tagline (docs.ts)
- VitePress docs site: hero, getting-started, architecture, security,
deployment, configuration, developer, supported-formats
- i18n: 10 product keys across all 21 locales (hero, app description,
privacy notes, AI features, progress messages, getting-started)
- web/demo/landing meta + privacy copy, COMMUNITY_GUIDE, .env.example
Stale tool counts (53/50+/52/70+/35) corrected to 157 throughout.
Database/container deployment claims left unchanged (out of scope).
* docs: fix stale post-rebrand test assertions and README language list
- tests/e2e-docs/homepage.spec.ts: assert the current docs homepage (file toolkit, 157 tools, 5 modalities) instead of the old image-only strings
- tests/unit/api/docs-route.test.ts: sync the reproduced llms.txt tagline with docs.ts
- README.md: 21 languages with the correct list (add Swedish and Chinese Traditional, drop Czech which is not supported)
* docs: correct 2.0 architecture references (Postgres 17 + Redis 8, 3-container stack)
The docs and metadata still described the 1.x stack (SQLite, single container, p-queue). Update them to the current 2.0 reality.
- README: replace the broken single-container `docker run` quick-start with the real Docker Compose stack (app + Postgres 17 + Redis 8); fix the "no Redis, no Postgres" feature bullet
- package.json: description no longer claims a single container
- apps/docs: rewrite database.md for Postgres; configuration.md DB_PATH -> DATABASE_URL + REDIS_URL; architecture.md SQLite/p-queue/better-sqlite3 -> Postgres/BullMQ/pg and add media-engine + doc-engine; developer/security/deployment/docker-tags/getting-started/contributing compose examples now include postgres + redis; index.md + api/ai.md AI count 16 -> 19
- SECURITY.md: Drizzle (SQLite) -> (PostgreSQL)
- landing: enterprise/FeatureHighlights single-container wording; TrustSignals/ToolGrid 150+ -> 157 (dynamic); Pricing/FAQ 15 -> 19 AI tools
* docs(api): document all video, audio, document, and data tool endpoints in OpenAPI
The spec covered only image tools; the Scalar UI and the generated /llms.txt and /llms-full.txt inherited that gap. Add the 104 missing tool endpoints so the API docs match the code.
- Video: 29 endpoints (most long/async; auto-subtitles is AI)
- Audio: 17 (transcribe-audio is AI)
- Document/PDF: 36 (ocr-pdf is AI; conversions are long/async)
- Data: 10
- Image: 12 newer tools (background-replace, blur-background AI; histogram/lqip-placeholder/sprite-sheet custom responses; barcode-generate uses a JSON body)
Each schema is derived from the tool's Zod validator and executionHint (fast -> 200, long -> 202+SSE, AI adds 501 FeatureNotInstalledError, multi-file inputs as arrays), referencing the existing shared schemas. Tool path entries: 64 -> 168. Spec parses as valid YAML with no duplicate paths and only known $refs.
SnapOtter spans five modalities now, but several code paths still assumed image input.
- dropzone: default to accept-all when no fileFilter is given (image tools still pass one); neutral "supported file types" error text instead of "image files"
- automate (pipelines): accept any modality in the file pickers and dropzones; render modality-aware previews (video player, audio waveform, document/data card) instead of always using ImageViewer/BeforeAfterSlider
- filename sanitizer: extend the double-extension allowlist beyond image extensions to video/audio/document/data so e.g. "report.csv.php" becomes "report.csv"; add tests
- thumbnail route: return 422 for non-rasterisable files (audio, data, non-PDF docs) instead of attempting a doomed Sharp decode
- pool: unknown tools fall back to the "system" pool, not the image pool
- a11y labels: "Previous/Next image", "Image viewer/area/controls/drop zone" are now modality-neutral, across all 21 locales
- copy: bulk-rename default, find-duplicates ZIP name, SSRF user-agent, fetch-urls fallback name, file-details MIME label, URL-import placeholder, help dialog
Collapses the error_message line introduced in #251 plus the pre-existing
preValidate blocks and the json-xml wrapped assignment that were already
failing apps/api lint on main. Pure formatting, no logic change.
* fix(pdf): never enlarge on compress, honor redact case, hide same-format convert
- compress-pdf: guard both modes so output is never larger than the input; low-DPI scans could be upsampled and grow. Falls back to the original bytes.
- doc_redact.py: caseSensitive=true now filters PyMuPDF's case-insensitive search to exact-case hits, so the toggle works instead of always over-redacting.
- convert-{document,presentation,spreadsheet}: omit the input's own format from the output dropdown; the backend already rejects same-format conversions.
Verified end-to-end against an isolated Docker stack during a full visual QA sweep of all 37 PDF tools.
* fix(ui): show real multi-file preview thumbnails per modality
The bottom multi-file preview strip rendered a raw <img src=blobUrl> for every file, so audio/video/PDF inputs showed a broken-image icon plus the filename. ThumbnailStrip now branches on FileEntry.previewKind: images use <img> (icon fallback on error), video shows a captured first frame, PDF shows a pdf.js page-1 render, and audio/other show a type icon + extension. Fixes the multi-file preview across all modalities.
Verified in the browser for image/PDF/audio/video.
* fix(modality): make pipeline, batch validation, save/upload, previews & UI modality-aware
The app grew up image-only; several paths still assumed image. They now dispatch on the tool/file modality (image/video/audio/document/file):
- pipeline /execute + /batch: validate+decode input via inputHandlerFor(modality) instead of validateImageBuffer, so PDF/audio/video/data pipelines work (were rejected 'Invalid image').
- batch: non-image inputs now get per-modality validation (ffprobe/qpdf) before the worker instead of passing through unchecked.
- files /upload, user-files /save-result + /thumbnail: accept non-image files (MIME from extension; video-poster / pdf-first-page thumbnails).
- postprocess CONTENT_TYPE_TO_EXT: cover video/audio/pdf/text/zip so output extensions are corrected for all modalities.
- worker pipeline-finalize: attach result payload to the complete SSE event so the sync-window-timeout fallback still delivers a download.
- frontend: batch-ZIP blob MIME by extension (not svg-only); modality-neutral fallback labels/filenames; 'smaller file' not 'smaller image'.
Found via a codebase-wide image-only-assumption audit. Verified: PDF/audio/video pipelines + batch now work; image paths unchanged. canBrowserPreview kept image-only by design (non-image is rendered by dedicated displayMode viewers).
* fix(pipeline): generate a modality-aware preview for pipeline results
processPipelineFinalize now derives the output content type from its extension and runs generatePreview (video poster / pdf first page / image thumb), sets previewRef on the result, and surfaces previewUrl in the /execute sync response and the SSE complete event (via buildLegacyResultPayload). Pipeline outputs get a preview like single-tool results instead of always returning previewUrl: undefined.
Verified: PDF pipeline -> previewUrl returns a valid PNG first-page render; png pipeline correctly has no previewUrl; audio/video/multi-step pipelines all 200.
* fix(worker): auto-save a new library version when processing a library file
The worker hardcoded savedFileId = undefined ('No auto-save') even though the whole versioning feature was wired around it: the frontend sends fileId for library files and reads result.savedFileId, tool-factory threads fileId into ToolJobData, and autoSaveToLibrary implements the new-version save -- but the worker never called it (dead code from the tool-first-workflow merge). processToolJob now calls autoSaveToLibrary with data.fileId; without a fileId it is a no-op, so tool-first uploads are unchanged.
Verified: processing a library PDF with fileId creates version 2 (parent linked, toolChain appended, savedFileId returned); processing without fileId saves nothing.
* fix(library): ownership check + modality-aware dimensions in autoSaveToLibrary
- Only create a new version when the requester owns the parent (parent.userId === opts.userId); prevents versioning another user's file via a known fileId.
- Dimensions are modality-aware: sharp for images, ffprobe (probeMedia) for video, null for audio/document. Previously sharp-only, so non-image versions always got null dims.
* fix(ai): thread fileId + real userId through the 16 AI tool routes
AI custom routes parsed neither the fileId multipart field nor the authenticated user (they hardcoded userId: null), so processing a library file via an AI tool never created a new version, and AI jobs were unattributed. Each route now parses fileId like clientJobId and passes getAuthUser(request)?.id as userId to enqueueToolJob.
Verified: ocr-pdf on a library PDF creates a new version (v2); the ownership check still denies cross-user versioning.
* fix(media): mux container-correct codecs in video tools
Video tools hardcoded H.264 (and AAC) while keeping the input's container extension, so a .webm input produced an invalid file (ffmpeg exit 234: H.264 cannot be muxed into WebM). Add shared videoEncodeArgsForContainer/audioEncodeArgsForContainer helpers (vp9+opus for webm, theora+vorbis for ogv, h264+aac otherwise) and apply them across 14 tools; re-encode audio to AAC in burn-subtitles (forced mp4). Adds a webm regression test for change-fps.
* fix(eraser): recover Object Eraser when its progress SSE drops
The eraser used a bespoke EventSource with no recovery, so a dropped SSE left the UI stuck at ~25% forever even though the backend job had finished and saved its result. Add a resilient subscription (reconnect on tab refocus, which replays the cached terminal frame; 5-minute stall timeout) mirroring the standard processor's PR #203/#204 recovery.
* feat(ui): rename the Documents modality to PDF and Data to Files
Updates modality display names, the home-page tabs, the tool-page breadcrumb, and the homePage.documents/data + modalities labels across all 21 locales. URL slugs are unchanged for link stability.
* feat(compress-pdf): add quality and target-size compression modes
Mirror the image Compress tool: a quality slider (1-100) and a target file size, replacing the screen/ebook/printer preset. Adds gsCompressPdfQuality to doc-engine (quality maps to image downsample DPI, the dominant size lever for PDFs); target-size binary-searches the DPI for the highest quality under the target. The frontend reuses the shared CompressControls component, so no new translation strings are needed.
* feat(ocr-pdf): show the PDF preview and extracted text side by side
ocr-pdf fell back to the image viewer, which cannot render a PDF, so the right pane showed 'Preview not available' and the extracted text was only a download. It now uses a custom results view (custom-results display mode) rendering the input PDF via pdf.js (DocumentView gains an inputOnly prop, since the tool's output is a .txt) next to the extracted OCR text, with a copy button.
* feat(ui): link the modality breadcrumb to its tools tab
The modality segment of the tool breadcrumb (PDF, Image, Video, Audio, Files) is now a link to /?modality=<tab>. The home page reads the param, activates the matching tab, and cleans the URL, so it returns to the existing Tools page filtered to that modality without a new page. Handles the file modality whose tab key is 'data'.
* feat(circle-crop): add zoom/offset framing, border, background, and output size
Upgrade the circle-crop tool from a bare centered crop into a framing and
styling tool. New settings (all backward-compatible with the old empty
payload):
- zoom (1-5x) plus offsetX/offsetY (0-1) to control how tight the circle is
and where it sits in the source image
- borderWidth (0-200px) plus borderColor for an optional ring
- background: transparent (clear corners) or a hex fill
- outputSize for a square output; omitted keeps native size
The settings panel gains an inline draggable circular preview that mirrors
the framing live, a zoom slider, a border slider with color, a
transparent/color background toggle, and an output-size field. Adds an
integration test covering output size, border, and a solid background.
* feat(image-tools): flesh out five thin tools (gif-webp, histogram, favicon, color-palette, lqip)
Tier A of the image-tool depth pass. Each of these was as bare as the old
circle-crop (empty settings, opaque or invisible output). Now:
- gif-webp: quality, lossless, and resize-percent controls; shows before/after size
- histogram: returns full per-channel bins + stats; the settings panel renders an
inline interactive histogram with R/G/B/Luma toggles, linear/log scale, and a
mean/median/stdev readout (server PNG still downloadable)
- favicon: background fill, padding, corner-radius, theme color, and a per-size
checklist, with a live preview grid; the route applies the styling and honors
the size filter
- color-palette: count (2-16) and hex/rgb/hsl format controls, median-cut
extraction, a palette strip, and CSS/JSON export
- lqip-placeholder: blur/pixelate/solid strategies, format and quality; the
output panel now surfaces the data URI with copy plus HTML/CSS snippets and a
preview (previously the deliverable was never shown)
Also expose resultPayload from useToolProcessor so a tool can render the route's
extra result fields (histogram bins, lqip data URI) in its own panel. Updates the
five integration tests to cover the new settings.
* feat(image-tools): deepen five thin tools (duotone, vignette, pixelate, background-replace, blur-background)
Tier B of the image-tool depth pass.
- duotone: preset palettes, an intensity slider that blends the duotone with
the original, and a true live duotone preview (a self-contained grayscale +
lighten/darken overlay so the pane filter cannot wash it out)
- vignette: radius, softness, roundness, and center-x/y controls driving a
rebuilt radial gradient, with a matching live overlay
- pixelate: a selection mode that exposes the route's region support via a
draggable box over the image plus width/height sliders, so a face or plate
can be pixelated in isolation
- background-replace: gradient backgrounds, edge feather, and webp output on top
of the existing solid color; now shown before/after
- blur-background: edge feather and webp output; now shown before/after
The live previews for duotone and vignette needed onImageStyle to mount the
overlay branch in image-viewer. The duotone intensity blend and both AI tools'
edge feather were rewritten to splice the alpha channel through raw buffers;
joinChannel did not reliably re-tag the merged channel as alpha and a
raw-without-encoder buffer broke the next decode. Updates the five integration
tests.
* fix(data): rename Files modality to Data + 20 Data-tool bug fixes (#247)
* fix(ui): restore the Data modality name (revert Files rename)
The 'file' modality reverts to the 'Data' label in modality.ts, the home-page tab, and the tools.data + documentsAndFiles i18n keys across all 21 locales. The separate Documents to PDF rename is kept. The URL slug was already /data, so name and slug realign; the tool breadcrumb follows modality.ts automatically.
* fix(create-zip): require at least two files before enabling submit
create-zip enabled its submit button with a single file, but the backend rejects fewer than two files ('Zipping needs at least two files'), producing a 422 error. Gate the button on files.length >= 2 to match the sibling merge-csvs tool. Found during the Data-modality QA sweep.
* fix(data): resolve 17 bugs found in a deeper Data-tool review
Crashes (threw an internal error on otherwise-valid input):
- csv-json: a primitive JSON array like [1,2,3] threw "Unable to serialize"; now a clear error.
- json-xml: a null or primitive JSON root crashed the XML builder; now a clear 4xx.
- yaml-json: an empty or comment-only YAML returned undefined and threw on Buffer.from; now emits null.
Data loss / wrong output:
- csv-json: nested objects rendered as "[object Object]" (now serialized to JSON); heterogeneous objects dropped columns (now the union of all keys).
- xml-to-csv: leaked fast-xml-parser markers ("@_" on attributes, "#text") into CSV headers (now cleaned); a single-record XML failed to tabulate (now a 1-row table); heterogeneous records dropped columns (now the union of all keys).
- csv-excel: xlsx date cells were rendered in the server timezone via Date.toString (now ISO 8601, round-trippable).
- create-zip and extract-zip: filename/basename collisions overwrote zip entries and silently lost a file; dedup now checks generated names and guarantees uniqueness.
- chart-maker: negative values produced invalid/degenerate SVG that Sharp silently dropped; now rejected with a clear message.
Empty output / validation:
- split-csv: a header-only CSV produced an empty zip; now errors with "No data rows to split".
- extract-zip: a directory-only zip produced an empty zip; now errors with "No extractable files found".
- create-zip and merge-csvs: a single-file request fell through to the worker and returned 422; the factory now supports minInputs and returns 400 pre-enqueue.
UI:
- review-panel: the result card showed "Saved +X%" when the output grew; the savings row now appears only when the file is actually smaller (Original/Processed sizes always shown).
Found via two adversarial code-review passes over the 10 Data routes. All 24 fix + regression checks pass against a fresh Docker stack on :1359.
* fix(data): clean 400 for unsafe-zip entries; drop header on split keepHeader=false
- tool-factory: add an opt-in preValidate hook that runs after input prep and
before enqueue. Throwing InputValidationError there returns its statusCode
(400) instead of the worker's generic 422. BullMQ loses the error class across
the job boundary, so InputValidationErrors thrown in the worker cannot be
mapped to their status; pre-enqueue validation can.
- extract-zip: validate entry paths via preValidate, rejecting path-traversal
and absolute-path archives (and unreadable/corrupt zips) with a clear 400. The
processV2 guards remain as defense-in-depth for the pipeline/batch path.
- split-csv: keepHeader=false now drops the header (parts contain only data
rows) instead of keeping it as the first data row of part-1.
Verified against a fresh Docker stack: unsafe / absolute / corrupt zips -> 400,
normal zip still 200; split keepHeader=false drops the header while true repeats
it in each part. No regressions across 51 fix + scenario checks.
* feat(image-tools): deepen image-pad and sprite-sheet, fix sprite-sheet multi-file submit
Tier C of the image-tool depth pass.
- image-pad: a custom W:H ratio alongside the presets, a background mode
(solid color, transparent, or an Instagram-style blurred cover fill), and an
extra padding margin. The settings panel gains a real live preview of the
padded canvas (it previously declared live-preview but rendered nothing) via
onImageStyle + onImageOverlay.
- sprite-sheet: PNG/WebP/JPEG output with a quality control, and the coordinate
map it already computes is now returned and surfaced as Copy CSS (per-frame
background-position rules) and Copy JSON exports.
Also fix a pre-existing sprite-sheet bug: with more than one image the panel
called processAllFiles, fanning out to the per-file batch route (422). It now
calls processFiles, which packs all images into a single sheet request (it is a
MULTI_FILE tool). Updates both integration tests.
* fix(media): preserve source sample rate after loudnorm (#243)
ffmpeg's loudnorm filter runs internally at 192 kHz and emits 192 kHz
unless the chain resamples back. normalize-audio and video-loudnorm
therefore produced 192 kHz output (4.3x larger files) regardless of the
input rate. Append aresample to restore the input's sample rate.
runMediaTool now exposes the input audio sample rate to its args callback.
* fix(color-palette): collapse solid-color images to one swatch
The median-cut bucket selector started bestRange at -1, so a uniform bucket
(range 0) still satisfied the > comparison and kept splitting, yielding N
identical swatches for a solid-color image. Start at 0 so only buckets with
real color spread are split.
* fix(lint): annotate implicit-any lets in saml and user-files
biome noImplicitAnyLet flagged the bare let in saml.ts (profile) and user-files.ts (stream); add derived type annotations (type-only, no behavior change). Latent on main via the turbo lint cache; surfaced when the Data changes busted the apps/api lint cache.
ffmpeg's loudnorm filter runs internally at 192 kHz and emits 192 kHz
unless the chain resamples back, so normalize-audio produced 192 kHz
output (~4.3x larger files) regardless of the input rate. Append
aresample to restore the input's sample rate; runMediaTool now exposes
the input audio sample rate to its args callback.
* fix(ssrf): honor lookup all-option so DNS-pinned fetch works on Node 22
createPinnedAgent's custom lookup always called back in single-address
form. Node 22 invokes the agent lookup with { all: true }, so the address
arrived as undefined and every URL fetch failed with "Invalid IP address:
undefined" -- breaking the URL-import feature entirely. Return the pinned
IP as an array when all is requested; the connection is still pinned to the
SSRF-validated public IP (no DNS-rebinding regression).
* fix(url-import): accept non-image modalities
fetch-urls validated every fetched file as an image and ran a Sharp
preview, so audio/video/document URL imports were rejected. Try image
validation, accept non-image media (typed from the HTTP content-type),
and skip the image preview for non-images. SSRF + size limits unchanged.
* fix(batch): validate non-image inputs by modality
Batch processing ran validateImageBuffer and the image-only decode chain
on every uploaded file, so audio, video, and document tools rejected all
inputs with "Invalid image: Unrecognized image format" and returned
422 "All files failed processing".
Resolve the tool's modality and route non-image files through their own
input handler (inputHandlerFor(modality).prepare), mirroring the
single-file path. The image batch path is unchanged.
* fix(pipeline): validate non-image inputs by modality
The pipeline /execute and /batch routes validated every upload with
validateImageBuffer and ran the image-only decode chain, so audio,
video, and document pipelines were rejected with "Invalid image:
Unrecognized image format".
Resolve the input modality from the first step's tool and route
non-image inputs through their modality handler, mirroring the batch
and single-file paths. Image pipelines are unchanged.
