WebAssembly

Extract text, tables, images, and metadata from 62+ file formats including PDF, Office documents, and images. WebAssembly bindings for browsers, Deno, and Cloudflare Workers with portable deployment and multi-threading support.

Installation

$3

Install via one of the supported package managers:

npm:
``bash
npm install @kreuzberg/wasm
`


pnpm:
`bash
pnpm add @kreuzberg/wasm
`


yarn:
`bash
yarn add @kreuzberg/wasm
`

$3

- Modern browser with WebAssembly support, or Deno 1.0+, or Cloudflare Workers
- Optional: Tesseract WASM for OCR functionality

Quick Start

$3

Extract text, metadata, and structure from any supported document format:

`ts
import { extractBytes, initWasm } from "@kreuzberg/wasm";

async function main() {
await initWasm();

const buffer = await fetch("document.pdf").then((r) => r.arrayBuffer());
const bytes = new Uint8Array(buffer);

const result = await extractBytes(bytes, "application/pdf");

console.log("Extracted content:");
console.log(result.content);
console.log("MIME type:", result.mimeType);
console.log("Metadata:", result.metadata);
}

main().catch(console.error);
`

$3

#### Extract with Custom Configuration

Most use cases benefit from configuration to control extraction behavior:


With OCR (for scanned documents):

`ts
import { enableOcr, extractBytes, initWasm } from "@kreuzberg/wasm";

async function extractWithOcr() {
await initWasm();

try {
await enableOcr();
console.log("OCR enabled successfully");
} catch (error) {
console.error("Failed to enable OCR:", error);
return;
}

const bytes = new Uint8Array(await fetch("scanned-page.png").then((r) => r.arrayBuffer()));

const result = await extractBytes(bytes, "image/png", {
ocr: {
backend: "tesseract-wasm",
language: "eng",
},
});

console.log("Extracted text:");
console.log(result.content);
}

extractWithOcr().catch(console.error);
`


#### Table Extraction


See Table Extraction Guide for detailed examples.

#### Processing Multiple Files


`ts
import { extractBytes, initWasm } from "@kreuzberg/wasm";

interface DocumentJob {
name: string;
bytes: Uint8Array;
mimeType: string;
}

async function _processBatch(documents: DocumentJob[], concurrency: number = 3) {
await initWasm();

const results: Record = {};
const queue = [...documents];

const workers = Array(concurrency)
.fill(null)
.map(async () => {
while (queue.length > 0) {
const doc = queue.shift();
if (!doc) break;

try {
const result = await extractBytes(doc.bytes, doc.mimeType);
results[doc.name] = result.content;
} catch (error) {
console.error(Failed to process ${doc.name}:, error);
}
}
});

await Promise.all(workers);
return results;
}
`

#### Async Processing

For non-blocking document processing:

`ts
import { extractBytes, getWasmCapabilities, initWasm } from "@kreuzberg/wasm";

async function extractDocuments(files: Uint8Array[], mimeTypes: string[]) {
const caps = getWasmCapabilities();
if (!caps.hasWasm) {
throw new Error("WebAssembly not supported");
}

await initWasm();

const results = await Promise.all(files.map((bytes, index) => extractBytes(bytes, mimeTypes[index])));

return results.map((r) => ({
content: r.content,
pageCount: r.metadata?.pageCount,
}));
}

const fileBytes = [new Uint8Array([1, 2, 3])];
const mimes = ["application/pdf"];

extractDocuments(fileBytes, mimes)
.then((results) => console.log(results))
.catch(console.error);
`

$3

- Installation Guide - Platform-specific setup
- API Documentation - Complete API reference
- Examples & Guides - Full code examples and usage guides
- Configuration Guide - Advanced configuration options

Features

$3

62+ file formats across 8 major categories with intelligent format detection and comprehensive metadata extraction.

#### Office Documents

| Category | Formats | Capabilities |
|----------|---------|--------------|
| Word Processing | .docx, .odt | Full text, tables, images, metadata, styles |
| Spreadsheets | .xlsx, .xlsm, .xlsb, .xls, .xla, .xlam, .xltm, .ods | Sheet data, formulas, cell metadata, charts |
| Presentations | .pptx, .ppt, .ppsx | Slides, speaker notes, images, metadata |
| PDF | .pdf | Text, tables, images, metadata, OCR support |
| eBooks | .epub, .fb2 | Chapters, metadata, embedded resources |

#### Images (OCR-Enabled)

| Category | Formats | Features |
|----------|---------|----------|
| Raster | .png, .jpg, .jpeg, .gif, .webp, .bmp, .tiff, .tif | OCR, table detection, EXIF metadata, dimensions, color space |
| Advanced | .jp2, .jpx, .jpm, .mj2, .jbig2, .jb2, .pnm, .pbm, .pgm, .ppm | OCR via hayro-jpeg2000 (pure Rust decoder), JBIG2 support, table detection, format-specific metadata |
| Vector | .svg | DOM parsing, embedded text, graphics metadata |

#### Web & Data

| Category | Formats | Features |
|----------|---------|----------|
| Markup | .html, .htm, .xhtml, .xml, .svg | DOM parsing, metadata (Open Graph, Twitter Card), link extraction |
| Structured Data | .json, .yaml, .yml, .toml, .csv, .tsv | Schema detection, nested structures, validation |
| Text & Markdown | .txt, .md, .markdown, .djot, .rst, .org, .rtf | CommonMark, GFM, Djot, reStructuredText, Org Mode |

#### Email & Archives

| Category | Formats | Features |
|----------|---------|----------|
| Email | .eml, .msg | Headers, body (HTML/plain), attachments, threading |
| Archives | .zip, .tar, .tgz, .gz, .7z | File listing, nested archives, metadata |

#### Academic & Scientific

| Category | Formats | Features |
|----------|---------|----------|
| Citations | .bib, .biblatex, .ris, .nbib, .enw, .csl | Structured parsing: RIS (structured), PubMed/MEDLINE, EndNote XML (structured), BibTeX, CSL JSON |
| Scientific | .tex, .latex, .typst, .jats, .ipynb, .docbook | LaTeX, Jupyter notebooks, PubMed JATS |
| Documentation | .opml, .pod, .mdoc, .troff | Technical documentation formats |

Complete Format Reference

$3

- Text Extraction - Extract all text content with position and formatting information
- Metadata Extraction - Retrieve document properties, creation date, author, etc.
- Table Extraction - Parse tables with structure and cell content preservation
- Image Extraction - Extract embedded images and render page previews
- OCR Support - Integrate multiple OCR backends for scanned documents

- Async/Await - Non-blocking document processing with concurrent operations


- Plugin System - Extensible post-processing for custom text transformation


- Batch Processing - Efficiently process multiple documents in parallel
- Memory Efficient - Stream large files without loading entirely into memory
- Language Detection - Detect and support multiple languages in documents
- Configuration - Fine-grained control over extraction behavior

$3

| Format | Speed | Memory | Notes |
|--------|-------|--------|-------|
| PDF (text) | 10-100 MB/s | ~50MB per doc | Fastest extraction |
| Office docs | 20-200 MB/s | ~100MB per doc | DOCX, XLSX, PPTX |
| Images (OCR) | 1-5 MB/s | Variable | Depends on OCR backend |
| Archives | 5-50 MB/s | ~200MB per doc | ZIP, TAR, etc. |
| Web formats | 50-200 MB/s | Streaming | HTML, XML, JSON |

OCR Support

Kreuzberg supports multiple OCR backends for extracting text from scanned documents and images:


- Tesseract-Wasm

$3

`ts
import { enableOcr, extractBytes, initWasm } from "@kreuzberg/wasm";

async function extractWithOcr() {
await initWasm();

try {
await enableOcr();
console.log("OCR enabled successfully");
} catch (error) {
console.error("Failed to enable OCR:", error);
return;
}

const bytes = new Uint8Array(await fetch("scanned-page.png").then((r) => r.arrayBuffer()));

const result = await extractBytes(bytes, "image/png", {
ocr: {
backend: "tesseract-wasm",
language: "eng",
},
});

console.log("Extracted text:");
console.log(result.content);
}

extractWithOcr().catch(console.error);
`

Async Support

This binding provides full async/await support for non-blocking document processing:

`ts
import { extractBytes, getWasmCapabilities, initWasm } from "@kreuzberg/wasm";

async function extractDocuments(files: Uint8Array[], mimeTypes: string[]) {
const caps = getWasmCapabilities();
if (!caps.hasWasm) {
throw new Error("WebAssembly not supported");
}

await initWasm();

const results = await Promise.all(files.map((bytes, index) => extractBytes(bytes, mimeTypes[index])));

return results.map((r) => ({
content: r.content,
pageCount: r.metadata?.pageCount,
}));
}

const fileBytes = [new Uint8Array([1, 2, 3])];
const mimes = ["application/pdf"];

extractDocuments(fileBytes, mimes)
.then((results) => console.log(results))
.catch(console.error);
`

Plugin System

Kreuzberg supports extensible post-processing plugins for custom text transformation and filtering.

For detailed plugin documentation, visit Plugin System Guide.

Batch Processing

Process multiple documents efficiently:

`ts
import { extractBytes, initWasm } from "@kreuzberg/wasm";

interface DocumentJob {
name: string;
bytes: Uint8Array;
mimeType: string;
}

async function _processBatch(documents: DocumentJob[], concurrency: number = 3) {
await initWasm();

const results: Record = {};
const queue = [...documents];

const workers = Array(concurrency)
.fill(null)
.map(async () => {
while (queue.length > 0) {
const doc = queue.shift();
if (!doc) break;

try {
const result = await extractBytes(doc.bytes, doc.mimeType);
results[doc.name] = result.content;
} catch (error) {
console.error(Failed to process ${doc.name}:, error);
}
}
});

await Promise.all(workers);
return results;
}
``

Configuration

For advanced configuration options including language detection, table extraction, OCR settings, and more:

Configuration Guide

Documentation

- Official Documentation
- API Reference
- Examples & Guides

Contributing

Contributions are welcome! See Contributing Guide.

License

MIT License - see LICENSE file for details.

Support

- Discord Community: Join our Discord
- GitHub Issues: Report bugs
- Discussions: Ask questions