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SnapOtter 8532f3227b docs: audit all 157 tool pages against live schemas

Reconcile every tool page's parameters, defaults, and response shape against the tool's Zod settings schema and executionHint in code. Notable fixes: color-palette (add count + format params, hex output, median-cut algorithm), favicon (add 5 params, was documented as having none), qr-generate (add logoDataUri), convert (add ppm/eps/tga formats), video-loudnorm (-16 LUFS not -14), smart-crop (async 202 not sync 200), images-to-video (1080x1080 square), and several output-filename and behavior-note corrections.

Also normalize API endpoint paths to /api/v1/tools/<id> (no modality segment) and standardize curl examples on the Docker API port 1349. Verified with a clean docs build.

2026-06-18 14:12:28 +08:00

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description

description
Extract text from PDF documents using AI-powered OCR.

PDF OCR

Extract text from PDF documents using AI-powered optical character recognition. Supports multiple quality tiers and languages. Requires the OCR feature bundle to be installed.

API Endpoint

POST /api/v1/tools/ocr-pdf

Accepts multipart form data with a PDF file and an optional JSON settings field.

Parameters

Parameter	Type	Required	Default	Description
quality	string	No	`"balanced"`	OCR quality tier: `fast`, `balanced`, `best`
language	string	No	`"auto"`	Document language: `auto`, `en`, `de`, `fr`, `es`, `zh`, `ja`, `ko`
pages	string	No	`"all"`	Page selection, e.g. `"all"`, `"1-3"`, `"1,3,5"`

Example Request

curl -X POST http://localhost:1349/api/v1/tools/ocr-pdf \
  -H "Authorization: Bearer si_your-api-key" \
  -F "file=@scanned.pdf" \
  -F 'settings={"quality": "best", "language": "en", "pages": "1-5"}'

Example Response

Returns 202 Accepted. Track progress via SSE at /api/v1/jobs/{jobId}/progress.

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

Notes

Accepted input format: .pdf.
This is an AI tool that requires the OCR feature bundle to be installed. If the bundle is not installed, the API returns 501 Not Implemented.
The fast quality tier uses a lighter model for quicker processing; best uses a more accurate model at the cost of speed.
The auto language setting attempts to detect the document language automatically.
You can target specific pages using ranges ("1-3"), comma-separated lists ("1,3,5"), or "all" for every page.
For PDFs that already contain selectable text, consider using the faster PDF to Text tool instead.

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