Commit Graph
9 Commits
Author SHA1 Message Date
SnapOtter d12b1c0fc6 fix: harden all AI tools against proxy timeouts and filename attacks
Convert all 9 AI tool routes (colorize, restore-photo, remove-background,
enhance-faces, blur-faces, red-eye-removal, erase-object, noise-removal,
upscale) to async 202 processing so none are vulnerable to proxy
connection timeouts.

Also fixes:
- Replace basename() with sanitizeFilename() in all AI tool routes
  (prevents double-extension attacks and adds length truncation)
- Add UUID format validation for clientJobId field
- Fix missing filename sanitization in noise-removal (was using raw
  user-supplied filename with zero sanitization)
- Remove em dash from error message in use-tool-processor
2026-05-01 00:11:03 +08:00
SnapOtter dee9452c48 fix: format preservation, dispatcher stability, and health reporting
Closes #17, #18, #19, #31, #32, #33, #34

Format preservation (#17, #18, #19):
- Add resolveOutputFormat to rotate, resize, text-overlay, watermark-text,
  border, replace-color, blur-faces, upscale, erase-object, restore-photo
- Alpha-aware fallback: border with corner radius/shadow and replace-color
  with makeTransparent fall back to PNG for non-alpha formats (JPEG)
- Python sidecar tools (blur-faces, upscale, erase-object) now convert
  PNG output back to input format, matching restore-photo/colorize pattern
- Upscale and erase-object default to "auto" format detection instead of PNG

Dispatcher stability (#31, #32):
- Add gc.collect() and torch.cuda.empty_cache() after each dispatcher request
- Add configurable max_requests (default 50) for periodic dispatcher restart
- Add exponential backoff to dispatcher crash recovery in bridge.ts
- Circuit breaker: 5 crashes within 60s permanently disables dispatcher
- Reset crash counter on successful dispatcher startup

Health & security (#33, #34):
- Export getDispatcherStatus() from @snapotter/ai with running/ready/failed/
  gpu/pid/consecutiveCrashes fields
- Admin health endpoint now includes full dispatcher status
- Add pip-audit job to CI workflow for Python dependency scanning
2026-04-26 03:22:26 +08:00
SnapOtter 0309e0f680 chore: deploy to Cloudflare Pages and update branding
- 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
2026-04-24 18:06:29 +08:00
AshimandGitHub 97938bdc47 feat: API sync and documentation audit - 100% endpoint coverage (#94)
Code quality:
- Add Zod validation to 14 route handlers that used raw JSON.parse
  (favicon, find-duplicates, barcode-read, upscale, blur-faces,
  erase-object, colorize, enhance-faces, red-eye-removal,
  remove-background/effects, auth, api-keys, roles, teams,
  analytics, settings, user-files)
- Standardize error responses to safeParse + formatZodErrors pattern
- Replace unsafe `as` type casts with schema validation

OpenAPI spec (89 -> 115 operations):
- Add 14 missing tool endpoints (adjust-colors, sharpening,
  optimize-for-web, image-enhancement, noise-removal, red-eye-removal,
  restore-photo, passport-photo, colorize, enhance-faces, image-to-base64)
- Add 12 missing non-tool endpoints (analytics, features, audit-log,
  roles, admin-health)
- Add typed error schemas for 401/403/409 responses
- Add descriptions to all path parameters
- Bump version from 0.9.0 to 1.15.9

Documentation:
- Fix 8 incorrect env var defaults in configuration guide
- Add 15 undocumented env vars to configuration guide
- Fix tool ID mismatch (color-adjustments -> adjust-colors)
- Add 4 new API sections (Roles, Audit Log, Analytics, Features)
- Add image-enhancement to AI engine reference
- Update AI tool count from 13 to 14 across all docs
- Add 6 missing doc links to README
2026-04-23 20:26:58 +08:00
ashim-hq 2aadb66031 feat: add support for JXL, Camera RAW, ICO, TGA, PSD, EXR, HDR image formats
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.
2026-04-21 09:59:57 +08:00
ashim-hq 12c4d4de6f fix: update tool installation checks and refactor stdout JSON parsing in AI modules 2026-04-19 12:13:26 +08:00
ashim-hq 3c3aa74e98 feat: add FEATURE_NOT_INSTALLED guards to API tool routes
Return 501 with structured error when an AI tool's feature bundle
is not installed, preventing Python ImportError crashes. Guards
added to tool-factory, batch, pipeline (both validation loops),
and restore-photo custom route.
2026-04-18 02:40:16 +08:00
Siddharth Kumar Sah 85b1cfc10a chore: rename Stirling-Image to ashim across entire codebase
Complete rebrand from Stirling-Image to ashim following the project
move to https://github.com/ashim-hq/ashim.

Changes across 117 files:
- Package scope: @stirling-image/* → @ashim/*
- GitHub URLs: stirling-image/stirling-image → ashim-hq/ashim
- Docker Hub: stirlingimage/stirling-image → ashimhq/ashim
- GitHub Pages: stirling-image.github.io → ashim-hq.github.io
- All branding text: "Stirling Image" → "ashim"
- Docker service/volumes/user: stirling → ashim
- Database: stirling.db → ashim.db
- localStorage keys: stirling-token → ashim-token
- Environment variables: STIRLING_GPU → ASHIM_GPU
- Python cache dirs: .cache/stirling-image → .cache/ashim
- SVG filter IDs, test prefixes, and all other references
2026-04-14 20:55:42 +08:00
6a43cc1b77 feat: SOTA AI photo restoration with multi-step pipeline (#58) (#62)
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>
2026-04-13 21:57:51 +08:00