Make on-demand AI feature-bundle installs reliable and self-healing, closing
the failure modes behind most "some tool doesn't work" reports.
Multi-bundle installs: tools needing more than one bundle (Passport Photo,
Enhance Faces) install every required bundle from one action and stay
not-installed until all are present. Verified across all 19 AI tools.
Downloads: self-heal the accelerated Hugging Face (Xet) client so an upgraded
venv no longer silently falls back to slow urllib; restart instead of
corrupting a resumed partial when a proxy ignores Range and returns 200;
verify the completed size; fail fast on disk-full and HTTP 4xx; retry
transient errors five times; add hf_transfer fallback and document Xet egress.
Install integrity: crash-atomic venv writes so a killed or out-of-space
install can no longer tear the shared venv and break other tools; a boot
breadcrumb reseeds a torn venv to a clean state automatically; a post-install
smoke import test refuses to record a bundle whose libraries cannot load; an
install watchdog stops a wedged installer that would otherwise hold the venv
writer lock forever.
Adds unit and end-to-end tests for every failure mode above.
Uninstalling a bundle only deletes its downloaded model weights, never the
shared venv's site-packages, so self-hosters who already hit an AI bundle
conflict (e.g. the scipy ABI strand) have no clean self-service path via
uninstall+reinstall: reinstalling just overlays corrected files on top of
stale ones. Adds POST /api/v1/admin/features/reset, which wipes
/data/ai/{venv,models,pip-cache}, resets installed.json, and reseeds a real
working venv from the image's baked /opt/venv (extracted docker/reseed-ai-venv.sh,
now shared with entrypoint.sh's existing base-venv-upgrade bootstrap instead
of duplicating that logic) -- leaving an empty venv directory here would
make the very next install fail with "spawn .../python3 ENOENT", caught by
testing this live rather than assuming it. Ships with a matching Settings UI
section (inline confirm, same pattern as per-bundle uninstall) and strings
across all 21 locales.
Verified against a real snapotter/snapotter:1.17.2 image migrated to 2.0.0,
with real multi-GB bundles installed (background-removal + OCR): confirmed
the migrated instance's inherited python3.11 venv (2.0.0 itself uses 3.12)
still imports the fixed scipy/numpy/paddleocr correctly, then reset + real
reinstall + actual tool execution (remove-background, verified output image)
all worked end-to-end.
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
* 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
Three production crashes from the snapotter/node Sentry project.
feature-status (NODE-12): a valid-JSON-but-wrong-shape installed.json
crashed boot via Object.keys(data.bundles). readInstalled() now
normalizes any unusable shape to { bundles: {} }, and the boot recovery
call is wrapped so cleanup can never fatal startup.
image-viewer (NODE-15/17/18): drag-to-pan read .x off an undefined
use-gesture memo on pointerUp or a pinch-into-pan. A guarded pure helper
(resolvePanStart) now falls back to the live pan offset.
Fastify (NODE-14): raised pluginTimeout to 60s so slow self-hosted boots
do not fatal at @fastify/static.
- Use /opt/venv directly when --entrypoint bash bypasses entrypoint.sh
- Use sys.executable for all pip calls (not bare pip)
- Override entrypoint in CI workflow to avoid startup banner
- Fix Biome formatting (template literals, try/catch blocks)
Closes the "e2e never runs in CI" hole. Adds per-PR e2e smoke gate,
nightly full-suite workflows, parallel vitest forks (per-fork DBs),
Playwright parallel/serial/visual projects against production builds,
metadata-generated test suites (drift guards, hostile inputs, format
matrix, pairwise settings, property-based fuzz), Stryker mutation
testing, Schemathesis API fuzz, coverage ratchet, and fixes for three
session-poisoning bugs that caused 200+ serial-bucket failures.
Bug fix included: favicon/split/bulk-rename could hang clients forever
when ZIP streaming failed after reply.hijack().
Path resolution for the feature manifest and install script was hardcoded
to /app/..., which only works inside the Docker container. Native installs
(e.g. Proxmox at /opt/snapotter) hit "No such file or directory" errors.
Resolve both paths relative to the source file location via import.meta.url
so they work regardless of where the project is installed.
Also loosen mediapipe==0.10.21 to >=0.10.21 in requirements.txt and
requirements-gpu.txt to match the feature manifest. The exact pin has no
cp313 wheel, so it fails on Python 3.13 (Debian 13 default). mediapipe
0.10.35 ships py3-none universal wheels that resolve cleanly.
Reported-by: MickLesk (community-scripts/ProxmoxVE#14720)
Add support for models defined via downloadFn/args (rembg_session,
hf_snapshot) in bundle verification, recovery, and uninstall paths.
Previously only path-based models were tracked, so bundles using
rembg or HF snapshot downloads appeared broken after install.
Also improve pip install error messages with user-friendly hints for
common failures (basicsr build issues, OOM, disk full) and add better
error context for rembg session download failures.
* feat: add 52 per-tool SEO landing pages and public changelog
- Create individual landing pages for all 52 tools at /tools/{slug}
with search-intent title tags, unique FAQs (156 Q&As), per-tool
features, and rich schema markup (BreadcrumbList, WebApplication,
HowTo, FAQPage)
- Replace static sitemap.xml with dynamic generation including all
tool URLs
- Refactor bento grid to import from @snapotter/shared (eliminates
330 lines of duplicated tool data) and link cards to tool pages
- Add @snapotter/shared as workspace dependency to landing site
- Add public changelog page to docs site with curated release notes
from v1.8 through v1.17
- Update docs nav and sidebar with changelog link
* feat: enhance SEO and performance with updated metadata, robots.txt, and llms.txt
- Add Cloudflare Pages deployment for landing page (snapotter.com) and
docs (docs.snapotter.com)
- Create deploy-landing.yml and update deploy-docs.yml workflows
- Update CI to ignore apps/landing/** paths
- Fix logo transparency (remove white background) across all apps
- Recreate social-preview.png with SnapOtter branding
- Update all docs URLs from GitHub Pages to docs.snapotter.com
- Update VitePress config: light theme default, fix llms.txt paths
- Add .vitepress/cache/ and .env.* to gitignore
- Add 8 new E2E specs for AI tools (upscale, enhance-faces, colorize,
restore-photo, erase-object, smart-crop, passport-photo, red-eye-removal)
closing all HIGH/MEDIUM coverage gaps from the test matrix audit
- Fix ensureAiDirs() crash on non-Docker environments by gating on
isDockerEnvironment() — prevents ENOENT when /data doesn't exist
- Bump torch 2.6.0→2.7.0 and torchvision 0.21.0→0.22.0 in feature
manifest for broader Python version compatibility
- Add Python 3.14 version guard warning in install_feature.py
- Remove duplicate torchvision shims from upscale.py and enhance_faces.py
(dispatcher.py already handles this at startup)
- Remove orphaned tools.batch i18n key and dead pipeline-builder filter
- Regenerate 4 visual regression baselines for current UI state
- Add data-testid to passport-photo generate button for E2E testability
The lock file stored process.pid (Node server PID) which is always
alive. When releaseInstallLock wasn't called (e.g., error path),
the lock persisted forever, making the bundle stuck in "installing"
and blocking all future installs.
Fix: remove PID from lock entirely. Use simple file existence as
mutex. On server startup, unconditionally delete any lock file.
Tracks which AI feature bundles are installed via /data/ai/installed.json
with atomic writes, in-memory caching, file-based install locks, and
startup recovery for interrupted installs.
