Import LiteParse and call parse() with a file path:
import { LiteParse } from '@llamaindex/liteparse';const parser = new LiteParse({ ocrEnabled: true });const result = await parser.parse('document.pdf');console.log(result.text);
result.text contains the full document text with spatial layout preserved across all pages. Per-page data is available in result.pages.
3
Parse from a Buffer or Uint8Array
You can pass raw bytes instead of a file path. PDF bytes go straight to the parser with zero disk I/O; non-PDF bytes are written to a temp file for format conversion.
From disk
From HTTP
import { LiteParse } from '@llamaindex/liteparse';import { readFile } from 'fs/promises';const parser = new LiteParse();const pdfBytes = await readFile('document.pdf');const result = await parser.parse(pdfBytes);console.log(result.text);
import { LiteParse } from '@llamaindex/liteparse';const parser = new LiteParse();const response = await fetch('https://example.com/document.pdf');const buffer = Buffer.from(await response.arrayBuffer());const result = await parser.parse(buffer);console.log(result.text);
4
Get structured JSON output
Set outputFormat: 'json' to receive per-page text items with coordinates and font metadata:
import { LiteParse } from '@llamaindex/liteparse';const parser = new LiteParse({ outputFormat: 'json' });const result = await parser.parse('document.pdf');for (const page of result.json.pages) { console.log(`Page ${page.page}: ${page.textItems.length} text items`); for (const item of page.textItems) { console.log(` "${item.text}" at (${item.x}, ${item.y})`); }}
Each textItem includes text, x, y, width, height, fontName, and fontSize.
OCR is enabled by default using the built-in Tesseract.js engine — no setup required. On the first run, Tesseract downloads language data from the internet. For offline use, set TESSDATA_PREFIX to a directory containing pre-downloaded .traineddata files.
