LiteParse — Rust document parser của LlamaIndex: PDF/Word/Excel/PPT/image → JSON với bounding boxes. Node.js/Python/WASM bindings. Tesseract OCR bundled, không cần cloud.
Scanned 9/9/2026
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---
name: run-llama--liteparse
description: "LiteParse — Rust document parser của LlamaIndex: PDF/Word/Excel/PPT/image → JSON với bounding boxes. Node.js/Python/WASM bindings. Tesseract OCR bundled, không cần cloud."
allowed-tools: Bash, Read, Write
user-invocable: true
---
LiteParse: fast local document parser viết bằng Rust — PDF + office docs + images → structured JSON với spatial bounding boxes. Zero cloud dependency.
## Install
```bash
# Node.js
npm install liteparse
# Python
pip install liteparse
# Rust
cargo add liteparse
```
## Supported Formats
```
Native: PDF (trực tiếp, không convert)
Office: .doc .docx .odt .ppt .pptx .odp .xls .xlsx .ods .csv .tsv
Images: JPG PNG GIF BMP TIFF WebP SVG
(qua ImageMagick → OCR)
```
## API
```typescript
import { parse } from 'liteparse'
// JSON với bounding boxes
const result = await parse('document.pdf', { format: 'json' })
// result.pages[0].blocks[0].bbox = { x, y, width, height }
// result.pages[0].blocks[0].text = "..."
// Plain text với layout preserved
const text = await parse('report.docx', { format: 'text' })
// Screenshot tại DPI tùy chỉnh
await parse('slide.pptx', { format: 'screenshot', dpi: 300 })
```
```python
from liteparse import parse
result = parse("document.pdf", format="json")
for page in result["pages"]:
for block in page["blocks"]:
print(block["text"], block["bbox"])
```
## Performance
```
Parallel OCR processing — configurable worker threads
Selective OCR — chỉ chạy khi cần (không phải mọi page)
Page-range targeting — parse trang 10-20, skip phần còn lại
Default DPI: 150 — tùy chỉnh được
```
## OCR Options
```
Default: Tesseract (bundled, offline)
HTTP backends: EasyOCR, PaddleOCR (accuracy cao hơn)
Custom: implement theo API spec
```
## CLI
```bash
liteparse document.pdf --format json --pages 1-10 --output result.json
liteparse batch/ --format text --workers 4
```
## Khi nào dùng
- RAG pipeline: parse docs → chunk → embed
- Extract structured data từ PDF reports
- Convert office docs sang Markdown cho LLM context
- OCR images trong batch pipeline
## Source
https://github.com/run-llama/liteparse · Apache-2.0 · +1613⭐/week
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