Background images, device frames, custom shadows, and watermark text
were not rendering in the right-pane preview. The preview now updates
in real time for all settings: gradient/solid/image backgrounds, macOS/
Windows/Browser frame chrome, iPhone/MacBook/iPad frame indicators,
custom shadow parameters, and watermark text overlay.
Also fixes a React StrictMode effect-ordering race where the parent
tool-page reset cleared preview state set by the child Settings
component on initial mount.
The preview endpoint now returns X-Original-Width/Height headers with
dimensions read from Sharp metadata (or ExifTool for RAW files). The
frontend stores these in FileEntry and the ImageViewer prefers them over
the browser's naturalWidth/naturalHeight, which reflects the resized
preview rather than the original sensor dimensions.
SERVER_PREVIEW_EXTENSIONS was missing TIFF, DDS, DPX, EPS, FITS, JP2,
PBM/PGM/PPM, QOI, SVGZ, CUR, and many RAW variants. The server
already had decoders for all of them but the client never triggered
the preview fetch, so users saw "Preview not available" instead.
The meme generator had everything in one component crammed into the
narrow right sidebar. This splits it into the proper two-panel
architecture (like collage/qr-generate):
- meme-store.ts: shared Zustand store for all meme state and actions
- meme-generator-preview.tsx: ResultsPanel (main area) with gallery,
layout picker, editor preview with CSS text overlay, and result view
- meme-generator-settings.tsx: Settings sidebar with text inputs, font
picker, colors, alignment, and generate button
- tool-registry.tsx: adds ResultsPanel to the meme-generator entry
Also fixes text overlay sizing (reduced from 0.6cqi to 0.45cqi with
smaller stroke width) and moves font injection to a standalone function
callable from either component.
The content-aware-resize tool had a full backend implementation (API route,
caire binary, seam-carving bridge) but was missing from the frontend
toolRegistry Map. Navigating to /content-aware-resize showed "Tool not found"
because ToolPage could not resolve a registry entry for the tool ID.
Added a dedicated ContentAwareResizeSettings component and registered it in
the tool registry with side-by-side display mode. Also added a guard test
that verifies every tool in the shared TOOLS[] array has a matching registry
entry, preventing this class of bug from recurring.
Closes#131
- Fix resize 20% failure rate: add Zod refine requiring at least one
dimension, enforce integer/max constraints, clamp percentage scaling
to minimum 1px, and guard against missing metadata in withoutEnlargement
- Fix PostHog init race condition: move consent check before async import
so frontend events (search, pageview) are no longer silently dropped
- Fix identify() passing nested $set/$set_once wrappers instead of flat
properties, so version person property now appears on PostHog profiles
- Add error_code and error_message to failed tool_used analytics events
for debugging tool failures from PostHog
The production CSP had connect-src/script-src/font-src set to 'self' only,
silently blocking all analytics and error reporting in production while
working fine in dev (where CSP is not applied).
CSP fixes:
- Add PostHog ingest + assets origins to connect-src and script-src
- Add Sentry ingest origin to connect-src
- Add Scalar fonts origin to font-src for API docs pages
- Extract CSP construction into testable buildCsp() function
Silent failure hardening:
- Settings/features stores now set loadError flag and allow retry on
subsequent fetch() calls instead of permanently caching failed state
- Analytics init no longer sets initialized=true before the try block,
allowing retry on failure
- Settings dialog Tools section disables save button when settings
failed to load, preventing accidental config wipe
- Branding logo storage moved from process.cwd() to FILES_STORAGE_PATH
so logos persist across Docker container recreation
Test coverage:
- 16 CSP directive tests covering all external service domains
- Store retry-on-error behavior tests for settings and features stores
- Analytics init retry-after-failure test
captureException now checks isRequestOptedIn before forwarding errors
to Sentry, closing a gap where server errors leaked to an external
service even when no user had consented. The PII scrubbing regex is
also fixed: he[ic]f? failed to match .heic due to word-boundary
behavior and is replaced with hei[cf]? which correctly covers .heic,
.heif, and .hei.
Adds 88 new analytics tests across unit, integration, and e2e layers
proving PostHog/Sentry are never invoked when analytics is disabled or
users have not consented, plus full 7-day reminder lifecycle coverage.
PostHog SDK was initialized on app mount based only on the server-level
config flag, ignoring user consent. This caused network requests to
us-assets.i.posthog.com (config.js, web-vitals.js, dead-clicks-autocapture.js)
even when the user had not opted in or had explicitly declined telemetry.
- Replace static imports of posthog-js and @sentry/react with dynamic
import() so the SDK bundles are not downloaded until consent is granted
- Gate initAnalytics on analyticsConsent.analyticsEnabled === true,
not just server config.enabled
- Add consent re-check after each await import() to handle revocation
during the async load
- Add shutdownAnalytics() that calls opt_out_capturing() + reset()
for mid-session consent revocation
- setAnalyticsConsent(false) now triggers full SDK shutdown automatically
- Rewrite analytics test suite with 44 tests covering init gating,
shutdown lifecycle, consent toggle, race conditions, and Sentry callbacks
Closes#98
- 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
Extends the platform to handle 7 new image format families alongside
the existing AVIF support gap-fill. Uses the established HEIC decoder
pattern (CLI decode → PNG → Sharp) for formats Sharp can't handle
natively: Camera RAW via dcraw_emu/LibRaw, PSD/TGA/EXR/HDR via
ImageMagick. JXL and ICO are Sharp-native. Adds server-side preview
for non-browser-displayable formats and JXL as a new convert output
target. All 27 validateImageBuffer callers updated with filename for
extension-based format detection.
When lazyWithRetry exhausts all retry attempts on a chunk error, also
call setDisconnected() so the reconnecting banner appears alongside the
ErrorBoundary's "Update Available" card.
- Add "unable to preload" pattern to isChunkError for Vite CSS preload failures
- Move ConnectionMonitor and ConnectionBanner outside ErrorBoundary so they
remain visible when the error boundary catches a render crash
- Add test for CSS preload error retry
Add Zustand features store for tracking AI feature bundle state with
fetch, refresh, isToolInstalled, and getBundleForTool methods. Extend
parseApiError to return structured FeatureNotInstalledError objects
when the backend returns FEATURE_NOT_INSTALLED, and handle them in
both tool and pipeline processor hooks with user-friendly messages.
- Replace [object Object] errors with readable messages across all 20+ API
routes by normalizing Zod validation errors to strings (formatZodErrors)
- Add parseApiError() on frontend to defensively handle any details type
- Add global Fastify error handler with full stack traces in logs
- Fix image-to-pdf auth: Object.entries(headers) → headers.forEach()
- Fix passport-photo: safeParse + formatZodErrors, safe error extraction
- Fix OCR silent fallbacks: log exception type/message when falling back,
include actual engine used in API response and Docker logs
- Fix split tool: process all uploaded images, combine into ZIP with
subfolders per image
- Fix batch support for blur-faces, strip-metadata, edit-metadata,
vectorize: add processAllFiles branch for multi-file uploads
- Docker: LOG_LEVEL=debug, PYTHONWARNINGS=default for visibility
- Add Playwright e2e tests verifying all fixes against Docker container
Both routes showed "Tool not found" — the UI was never implemented.
Pipeline functionality already lives at /automate (the Automate page).
Also removed the empty Automation category and unused Workflow/FolderInput
icons from icon-map.ts.
- Fix "Cannot access 'a' before initialization" TDZ error after login
caused by manualChunks splitting react-vendor + lucide icons into
circular ES-module chunks. Removed manualChunks entirely.
- Replace `import * as icons from "lucide-react"` (pulls all ~1000 icons)
with a targeted icon-map of ~50 icons actually used by tool definitions.
Reduces shared icons chunk from 745KB to 62KB (132KB→16KB gzip).
- Exclude static files from @fastify/rate-limit via allowList so rapid
page navigations don't 429 on JS/CSS chunk requests.
- Move Docker auth defaults (AUTH_ENABLED, DEFAULT_USERNAME,
DEFAULT_PASSWORD) from Dockerfile ENV to entrypoint.sh runtime exports
to avoid SecretsUsedInArgOrEnv warnings.
- Fix Docker CMD to use pnpm --filter for workspace-scoped tsx binary.
- Set COREPACK_HOME system-wide so non-root user can access pnpm cache.
- Lazy-load all pages in App.tsx and all controls in
pipeline-step-settings.tsx to keep main bundle under 300KB.
Apply stash from feat/border-redesign branch. Rewrites collage backend
with improved layout engine and adds CollagePreview results panel for
interactive preview. Updates tool registry to use no-dropzone display
mode with the new preview component.
* feat(image-to-base64): register tool in shared constants and i18n
* feat(image-to-base64): add API route with Sharp pipeline and base64 encoding
* feat(image-to-base64): add Zustand store for base64 results
* feat(image-to-base64): add settings panel component
* feat(image-to-base64): add results panel with 6-tab output and batch accordion
* feat(image-to-base64): register tool in frontend tool registry
* fix(image-to-base64): pass through original buffer when no resize/conversion needed
---------
Co-authored-by: stirling-image <stirling-image@users.noreply.github.com>
* feat(passport-photo): add passport specs database and tool constants
* feat(passport-photo): add MediaPipe FaceMesh landmark detection script
* feat(passport-photo): add TypeScript bridge for face landmark detection
* feat(passport-photo): add API routes with analyze and generate endpoints
* fix(passport-photo): accept landmarks from request body and fix pixel coordinate conversion
- Generate endpoint now accepts landmarks + imageWidth/imageHeight in request body
instead of re-running AI face detection (makes generate phase instant)
- Fixed bug where normalized landmark coordinates (0-1) were used directly
as pixel values in crop computation - now properly multiplied by imgW/imgH
- Fixed same bug in pipeline process function
* feat(passport-photo): add UI component with live preview and compliance overlay
---------
Co-authored-by: stirling-image <stirling-image@users.noreply.github.com>
Add comprehensive photo restoration tool that chains multiple AI models:
- Scratch/tear/spot detection via morphological analysis (top-hat/black-hat transforms)
- Damage inpainting via LaMa ONNX model (reuses existing infrastructure)
- Face enhancement via CodeFormer ONNX (~377MB, from facefusion/models-3.0.0)
- Noise reduction via OpenCV NLMeans in LAB color space
- Optional B&W auto-colorization via DDColor (reuses existing model)
Settings: 3 restoration modes (Light/Auto/Heavy), individual feature toggles
for scratch removal, face enhancement (with fidelity slider), denoising
(with strength slider), and auto-colorize. Before/after comparison view.
Handles HEIC, HEIF, and all standard formats. Batch processing supported.
No new Python dependencies - reuses onnxruntime, cv2, mediapipe, PIL.
Co-authored-by: stirling-image <stirling-image@users.noreply.github.com>
* feat(shared): add enhance-faces tool definition and i18n strings
* feat(ai): add face enhancement script with GFPGAN and CodeFormer support
Detects faces via MediaPipe dual-model approach, then enhances using
GFPGAN (proven) or CodeFormer (via codeformer-pip) with auto fallback.
Supports strength-based alpha blending with original image.
* feat(ai): add TypeScript bridge for face enhancement
* feat(api): add enhance-faces route with GFPGAN/CodeFormer support
* feat(web): add enhance-faces settings component and register in tool registry
* feat(docker): add CodeFormer dependency and model download
- Add codeformer-pip to both CPU and GPU requirements
- Download CodeFormer model (~375MB) at Docker build time
- Add CodeFormer to smoke test verification
* fix(enhance-faces): address code review findings
- Skip alpha blend for CodeFormer (strength already applied via fidelity weight)
- Hide "only enhance main face" checkbox when Best (CodeFormer) is selected
- Fix sensitivity slider labels (swap More/Fewer faces to match actual behavior)
- Register EnhanceFacesControls in pipeline step settings
- Remove model names from user-facing descriptions
* fix(enhance-faces): fix CodeFormer integration and Docker setup
- Add codeformer-pip install to Dockerfile with --no-deps to avoid numpy 2.x conflict
- Re-pin numpy==1.26.4 after codeformer-pip install
- Pin codeformer-pip==0.0.4 in requirements files
- Broaden auto-mode fallback to catch any Exception from CodeFormer
---------
Co-authored-by: stirling-image <stirling-image@users.noreply.github.com>
SnapOtter