# LiteParse — Fast Open-Source Document Parser in Rust

> A fast, helpful, and open-source document parser by LlamaIndex that extracts structured text from PDFs and other documents with high speed and accuracy for RAG and AI pipelines.

## Install

Save as a script file and run:

# LiteParse — Fast Open-Source Document Parser in Rust

## Quick Use
```bash
pip install liteparse
liteparse parse document.pdf --output result.md
```

## Introduction
LiteParse is a fast, open-source document parser built in Rust by the LlamaIndex team. It extracts structured text from PDFs and other document formats with a focus on speed and accuracy, making it ideal for RAG pipelines and LLM-powered applications that need to ingest large volumes of documents.

## What LiteParse Does
- Parses PDFs into clean, structured Markdown or JSON output
- Extracts text with layout awareness: headings, paragraphs, tables, and lists
- Processes documents significantly faster than Python-based parsers
- Handles scanned PDFs via integrated OCR capabilities
- Provides both a CLI tool and Python bindings for programmatic use

## Architecture Overview
LiteParse is written in Rust for maximum throughput and compiled into a native binary with Python bindings via PyO3. The parsing pipeline first extracts raw content using a custom PDF reader, then runs layout analysis to classify regions as headings, body text, tables, or figures. A reconstruction step produces clean Markdown or structured JSON preserving the document hierarchy. For scanned pages, an OCR module is invoked automatically.

## Self-Hosting & Configuration
- Install via pip: `pip install liteparse`
- No external services or API keys required
- Configure output format (Markdown, JSON, plain text) via CLI flags
- Adjust OCR sensitivity and language settings for scanned documents
- Use the Python API for integration into existing data pipelines

## Key Features
- Rust-powered speed for processing large document collections
- Layout-aware parsing preserving document structure
- Automatic OCR fallback for scanned or image-based PDFs
- Clean Markdown output ready for LLM consumption
- Python bindings for seamless integration with LlamaIndex and other frameworks

## Comparison with Similar Tools
- **PyPDF/PyMuPDF** — Python PDF libraries with limited layout analysis; LiteParse adds structure-aware extraction
- **Docling** — IBM's document parser; LiteParse is Rust-native and focused on speed
- **Marker** — PDF to Markdown converter; LiteParse is built by the LlamaIndex team for RAG pipeline integration
- **Unstructured.io** — comprehensive document ETL; LiteParse is lighter and faster for the parsing step

## FAQ
**Q: How much faster is it compared to Python parsers?**
A: The Rust core provides significant speed improvements on PDF processing. Benchmarks vary by document complexity.

**Q: Does it work with non-PDF documents?**
A: The primary focus is PDF. Support for additional formats is being added.

**Q: Can I use it without the Python wrapper?**
A: The Rust binary can be used directly from the command line.

**Q: Is it production-ready?**
A: It is actively developed by the LlamaIndex team and used in their production pipelines.

## Sources
- https://github.com/run-llama/liteparse


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Source: https://tokrepo.com/en/workflows/asset-2bc2689f
Author: Script Depot