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SnapOtter 7db6bb97da docs: add per-tool API documentation and fix parity gaps

- Create 53 per-tool VitePress documentation pages with accurate
  parameters from Zod schemas, example requests, and response formats
- Add root llms.txt for LLM-friendly repo browsing
- Fix OpenAPI spec: add auth and 422 error schemas to
  edit-metadata/inspect and strip-metadata/inspect sub-routes
- Fix tool count inconsistency (52 -> 53) across landing site,
  e2e tests, and local docs
- Rename color-adjustments.ts to adjust-colors.ts to match tool ID
- Update VitePress sidebar with all 8 tool categories and top nav

2026-06-08 11:52:28 +08:00

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Noise Removal

AI-powered noise and grain removal with multi-tier quality options, using the Python sidecar (SCUNet model).

API Endpoint

POST /api/v1/tools/noise-removal

Processing: Asynchronous (returns 202, poll /api/v1/jobs/{jobId}/progress for status via SSE)

Model bundle: upscale-enhance (4-5 GB)

Parameters

Parameter	Type	Required	Default	Description
file	file	Yes	-	Image file (multipart)
tier	string	No	`"balanced"`	Quality tier: `quick`, `balanced`, `quality`, `maximum`
strength	number	No	`50`	Denoising strength (0-100)
detailPreservation	number	No	`50`	How much detail to preserve (0-100). Higher values keep more texture
colorNoise	number	No	`30`	Color noise reduction strength (0-100)
format	string	No	`"original"`	Output format: `original`, `png`, `jpeg`, `webp`, `avif`, `jxl`
quality	number	No	`90`	Output encoding quality (1-100)

Example Request

curl -X POST http://localhost:13490/api/v1/tools/noise-removal \
  -F "file=@noisy-photo.jpg" \
  -F 'settings={"tier":"quality","strength":60,"detailPreservation":70,"colorNoise":40}'

Response

Initial Response (202 Accepted)

{
  "jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "async": true
}

Progress (SSE at `/api/v1/jobs/{jobId}/progress`)

event: progress
data: {"phase":"processing","stage":"Denoising...","percent":65}

Final Result (via SSE)

{
  "phase": "complete",
  "percent": 100,
  "result": {
    "jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "downloadUrl": "/api/v1/download/{jobId}/noisy-photo_denoised.jpg",
    "originalSize": 500000,
    "processedSize": 380000
  }
}

Notes

Requires the upscale-enhance model bundle to be installed (4-5 GB).
Quality tiers trade speed for quality: quick is fastest with basic denoising, maximum uses the most thorough multi-pass approach.
The detailPreservation parameter is critical for textured subjects (fabric, hair, foliage). Higher values prevent the denoiser from smoothing away fine detail.
When format is set to "original", the output format matches the input file format.
Supports HEIC/HEIF, RAW, TGA, PSD, EXR, and HDR input formats via automatic decoding.

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