L

liteparse

by @run-llamav1.0.0
4.5(40)

本地解析 PDF、DOCX、PPTX、XLSX 等非结构化文档,快速轻量,无需云端依赖或 LLM 支持

document-parsingdata-extractionpdf-processingGitHub
安装方式
npx skills add run-llama/llamaparse-agent-skills --skill liteparse
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Before / After 效果对比

1
使用前

手动从 PDF 或 Word 文档中复制粘贴文本,处理复杂格式时需要反复调整,一个 50 页的报告需要 2 小时才能完成内容整理

使用后

一键上传文档自动提取结构化文本,保留段落格式和表格结构,50 页报告在 2 分钟内完成解析并输出可编辑的 Markdown

description SKILL.md

liteparse

LiteParse Skill

Parse unstructured documents (PDF, DOCX, PPTX, XLSX, images, and more) locally with LiteParse: fast, lightweight, no cloud dependencies or LLM required.

Initial Setup

When this skill is invoked, respond with:

I'm ready to use LiteParse to parse files locally. Before we begin, please confirm that:

- `@llamaindex/liteparse` is installed globally (`npm i -g @llamaindex/liteparse`)
- The `lit` CLI command is available in your terminal

If both are set, please provide:

1. One or more files to parse (PDF, DOCX, PPTX, XLSX, images, etc.)
2. Any specific options: output format (json/text), page ranges, OCR preferences, DPI, etc.
3. What you'd like to do with the parsed content.

I will produce the appropriate `lit` CLI command or TypeScript script, and once approved, report the results.

Then wait for the user's input.

Step 0 — Install LiteParse (if needed)

If liteparse is not yet installed, install it globally:

npm i -g @llamaindex/liteparse

Verify installation:

lit --version

For Office document support (DOCX, PPTX, XLSX), LibreOffice is required:

# macOS
brew install --cask libreoffice

# Ubuntu/Debian
apt-get install libreoffice

For image parsing, ImageMagick is required:

# macOS
brew install imagemagick

# Ubuntu/Debian
apt-get install imagemagick

Step 1 — Produce the CLI Command or Script

Parse a Single File

# Basic text extraction
lit parse document.pdf

# JSON output saved to a file
lit parse document.pdf --format json -o output.json

# Specific page range
lit parse document.pdf --target-pages "1-5,10,15-20"

# Disable OCR (faster, text-only PDFs)
lit parse document.pdf --no-ocr

# Use an external HTTP OCR server for higher accuracy
lit parse document.pdf --ocr-server-url http://localhost:8828/ocr

# Higher DPI for better quality
lit parse document.pdf --dpi 300

Batch Parse a Directory

lit batch-parse ./input-directory ./output-directory

# Only process PDFs, recursively
lit batch-parse ./input ./output --extension .pdf --recursive

Generate Page Screenshots

Screenshots are useful for LLM agents that need to see visual layout.

# All pages
lit screenshot document.pdf -o ./screenshots

# Specific pages
lit screenshot document.pdf --pages "1,3,5" -o ./screenshots

# High-DPI PNG
lit screenshot document.pdf --dpi 300 --format png -o ./screenshots

# Page range
lit screenshot document.pdf --pages "1-10" -o ./screenshots

Step 3 — Key Options Reference

OCR Options

Option Description

(default) Tesseract.js — zero setup, built-in

--ocr-language fra Set OCR language (ISO code)

--ocr-server-url <url> Use external HTTP OCR server (EasyOCR, PaddleOCR, custom)

--no-ocr Disable OCR entirely

Output Options

Option Description

--format json Structured JSON with bounding boxes

--format text Plain text (default)

-o <file> Save output to file

Performance / Quality Options

Option Description

--dpi <n> Rendering DPI (default: 150; use 300 for high quality)

--max-pages <n> Limit pages parsed

--target-pages <pages> Parse specific pages (e.g. "1-5,10")

--no-precise-bbox Disable precise bounding boxes (faster)

--skip-diagonal-text Ignore rotated/diagonal text

--preserve-small-text Keep very small text that would otherwise be dropped

Step 4 — Using a Config File

For repeated use with consistent options, generate a liteparse.config.json:

{
  "ocrLanguage": "en",
  "ocrEnabled": true,
  "maxPages": 1000,
  "dpi": 150,
  "outputFormat": "json",
  "preciseBoundingBox": true,
  "skipDiagonalText": false,
  "preserveVerySmallText": false
}

For an HTTP OCR server:

{
  "ocrServerUrl": "http://localhost:8828/ocr",
  "ocrLanguage": "en",
  "outputFormat": "json"
}

Use with:

lit parse document.pdf --config liteparse.config.json

Step 5 — HTTP OCR Server API (Advanced)

If the user wants to plug in a custom OCR backend, the server must implement:

  • Endpoint: POST /ocr

  • Accepts: file (multipart) and language (string) parameters

  • Returns:

{
  "results": [
    { "text": "Hello", "bbox": [x1, y1, x2, y2], "confidence": 0.98 }
  ]
}

Ready-to-use wrappers exist for EasyOCR and PaddleOCR in the LiteParse repo.

Supported Input Formats

Category Formats

PDF .pdf

Word .doc, .docx, .docm, .odt, .rtf

PowerPoint .ppt, .pptx, .pptm, .odp

Spreadsheets .xls, .xlsx, .xlsm, .ods, .csv, .tsv

Images .jpg, .jpeg, .png, .gif, .bmp, .tiff, .webp, .svg

Office documents require LibreOffice; images require ImageMagick. LiteParse auto-converts these formats to PDF before parsing. Weekly Installs332Repositoryrun-llama/llama…t-skillsGitHub Stars26First Seen8 days agoSecurity AuditsGen Agent Trust HubPassSocketPassSnykPassInstalled onopencode329codex328github-copilot326cursor326gemini-cli325kimi-cli325

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统计数据

安装量819
评分4.5 / 5.0
版本1.0.0
更新日期2026年3月28日
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创建2026年3月28日
最后更新2026年3月28日