Browser Usage (WASM)

LiteParse ships a WebAssembly package that runs entirely in the browser — no server, no cloud calls. It supports PDF parsing and custom OCR engines implemented in JavaScript.

Install

npm install @llamaindex/liteparse-wasm

Quick start

import init, { LiteParse } from "@llamaindex/liteparse-wasm";

// Load the WASM module
await init();

const parser = new LiteParse({
  ocrEnabled: false,
  outputFormat: "json",
});

// data is a Uint8Array (e.g. from <input type="file"> or fetch)
const bytes = new Uint8Array(await file.arrayBuffer());
const result = await parser.parse(bytes);

console.log(result.text);
console.log(result.pages[0]);

What works in the browser

• PDF parsing from Uint8Array input (use file.arrayBuffer() to get bytes from a file picker for example)
• Custom OCR via the ocrEngine callback interface (see below)
• Text, JSON, and markdown output formats
• Document complexity via parser.isComplex(bytes) — see the complexity guide
• The extraction options — annotations, form fields, structure trees, vector graphics, and the rest. See Extraction options

What doesn’t work

• File path input — pass Uint8Array instead
• DOCX/XLSX/PPTX conversion — requires LibreOffice, which isn’t available in the browser
• Built-in Tesseract or HTTP OCR — use the custom ocrEngine interface instead
• Screenshots — not available in the WASM build
• imageOutputDir — there is no filesystem to write to. Use extractImages and read the bytes from the result instead

OCR in the browser

The native Tesseract and HTTP OCR backends are not available in WASM. To use OCR, pass a custom ocrEngine object with a recognize method:

const parser = new LiteParse({
  ocrEnabled: true,
  ocrLanguage: "eng",
  // Use more than 1 only if the engine supports concurrent jobs.
  numWorkers: 2,
  ocrEngine: {
    /**
     * @param imageData PNG-encoded image bytes
     * @param width  rendered page width in pixels
     * @param height rendered page height in pixels
     * @param language e.g. "eng"
     * @returns array of { text, bbox: [x1, y1, x2, y2], confidence }
     */
    async recognize(imageData, width, height, language) {
      // e.g. call a Web Worker wrapping tesseract.js, or a remote OCR service
      return [
        { text: "Hello", bbox: [10, 20, 80, 40], confidence: 0.98 },
      ];
    },
  },
});

This lets you plug in any OCR implementation — a Web Worker running tesseract.js, a cloud OCR API, or anything else that returns text with bounding boxes.

LiteParse keeps at most numWorkers calls to recognize active. When one call finishes, LiteParse prepares and starts the next page without waiting for the other calls. An OCR engine can send the calls to a Web Worker pool or to concurrent HTTP requests. Results stay assigned to their source pages when jobs finish out of order. Active calls can keep up to numWorkers rendered page rasters in memory, so use a small value for high-DPI documents.

PDF parsing and rendering remain single-threaded in WASM. numWorkers defaults to 1 and limits concurrent OCR calls. LiteParse does not create Web Workers. To process OCR jobs in parallel, supply an engine that supports concurrent jobs.

Config options

All optional, camelCase:

Option	Type	Default	Description
ocrLanguage	string	"eng"	Language code passed to the OCR engine
ocrEnabled	boolean	false	Run OCR on text-sparse pages. Off by default in WASM — there is no built-in engine, so this does nothing without ocrEngine
ocrEngine	object	—	Custom JS-side OCR engine (see above)
numWorkers	number	1	Maximum concurrent OCR calls
ocrFailureFatal	boolean	true	When false, OCR failures return partial results instead of throwing
ocrHedgeDelaysMs	number[]	[]	Request-hedging schedule for a remote ocrEngine
maxPages	number	1000	Stop after this many pages
targetPages	string	—	e.g. "1-5,10,15-20"
dpi	number	150	Render DPI for OCR
outputFormat	"json" | "text" | "markdown"	"json"	Shape of result.text. Also accepts "md". Throws on any other value
preserveVerySmallText	boolean	false	Keep tiny text that’s normally filtered
skipDiagonalText	boolean	false	Drop text more than 2° off the nearest right angle
cropBox	{ top, right, bottom, left }	—	Fraction to crop from each side of every page
pageOrientationCorrections	{ page, angle }[]	—	Counter-rotate listed pages (1-based) by the clockwise angle (0/90/180/270) their content appears rotated
password	string	—	Password for protected PDFs
quiet	boolean	false	Suppress progress logging
imageMode	"off" | "placeholder" | "embed"	"placeholder"	How image references appear in markdown. Also accepts "none" for off
extractLinks	boolean	true	Render [text](url) in markdown
keepHeadersFooters	boolean	false	Keep running header/footer chrome in markdown
emitWordBoxes	boolean	false	Per-word sub-boxes on each text item

The extraction options — extractImages, extractVectorGraphics, extractAnnotations, extractFormFields, extractStructureTree, extractContentBounds, extractXfaPackets, extractTextMetadata, includeComplexity, and renderFormFields — are all available here too, with the same camelCase names and the same false defaults.