#1515th of 50 in Data and scraping for AIFor data and documents, documents and ocr

liteparse

Local PDF and Office document parser with bounding boxes and Markdown output

Stars
13k
License
Apache-2.0
Last commit
Nov 2026
Last release
Nov 2026
Language
Rust
Stars, last 29 weeks+8,619
21 Apr 2026: 4,415 stars28 Apr 2026: 4,845 stars5 May 2026: 4,931 stars12 May 2026: 5,011 stars19 May 2026: 5,091 stars26 May 2026: 5,151 stars2 Jun 2026: 8,837 stars9 Jun 2026: 9,616 stars16 Jun 2026: 9,989 stars23 Jun 2026: 10,708 stars30 Jun 2026: 11,157 stars7 Jul 2026: 11,291 stars14 Jul 2026: 11,406 stars21 Jul 2026: 11,605 stars28 Jul 2026: 11,715 stars4 Aug 2026: 11,805 stars11 Aug 2026: 11,955 stars18 Aug 2026: 12,025 stars25 Aug 2026: 12,082 stars1 Sept 2026: 12,137 stars8 Sept 2026: 12,196 stars15 Sept 2026: 12,243 stars22 Sept 2026: 12,330 stars29 Sept 2026: 12,675 stars6 Oct 2026: 12,755 stars13 Oct 2026: 12,819 stars20 Oct 2026: 12,874 stars27 Oct 2026: 12,920 stars3 Nov 2026: 12,977 stars10 Nov 2026: 13,034 stars

4,415 on 21 Apr 202613,034 on 10 Nov 2026

From GitHub's daily star counts.

Checked on GitHub.

LlamaIndex is hiring: 4 open roles

Overview

LiteParse extracts spatially laid-out text from PDFs using PDFium, at roughly 2-5 ms per page, and converts DOCX, XLSX, PPTX and images through LibreOffice or Rust image crates. It outputs Markdown, JSON with bounding boxes, or plain text, and can run Tesseract or an HTTP OCR server on pages that need it. A Rust core ships with a `lit` CLI plus Node.js, Python and WASM bindings.

Who it is for: Developers feeding PDFs and Office files into RAG pipelines or LLM agents

Strengths

  • No ML model or GPU required; ~2-5 ms per page text extraction via PDFium
  • Bindings for Rust, Node.js, Python and browser WASM, with one `lit` CLI
  • Pluggable OCR: bundled Tesseract or any server following its OCR HTTP API spec
  • Worker pool mode gives parallel parsing and hard per-parse timeouts

Weaknesses

  • Markdown is heuristic and rule-based; complex layouts may render imperfectly
  • Charts score near zero in its own ParseBench results
  • Math is not output as LaTeX; olmOCR-bench math categories score 0%
  • Office formats depend on LibreOffice for conversion

What it needs

  • no GPU
  • Docker
  • Needs LibreOffice (for DOCX/XLSX/PPTX), Optional HTTP OCR server (EasyOCR, PaddleOCR, RapidOCR)
  • Models: Tesseract OCR (bundled), PaddleOCR PP-OCRv5 via HTTP, EasyOCR via HTTP

Quick answers

Is liteparse open source?

Yes. Its code is on GitHub under the Apache-2.0 license.

Can you run liteparse with Docker?

Yes. Its repository has a Docker setup: a Dockerfile, a Compose file or a published image.

Does liteparse need a GPU?

No, it runs without one.

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