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Field DispatchGitHub Trending8 · 2026-05-30

run-llama/liteparse

A fast, helpful, and open-source document parser

Stars
7,193
Today
680
Forks
441
Issues
14
Language
Rust
Updated
2026/05/29
痛点分析发布于 2026/05/29

痛点为 AI 基于上游原始证据的初步提炼;未包含额外中国市场检索。

痛点

用户在处理PDF、扫描件等文档时,需要从中提取结构化文本信息,但现有OCR或解析工具要么速度慢、要么准确率低,导致需要人工反复校对和修正。GitHub上liteparse项目描述为“快速、有用、开源的文档解析器”,且标签包含document-ocr、pdf-parser等,说明用户对解析速度和准确性有明确需求。当文档解析结果不可靠时,后续的数据录入、分析或自动化流程都会出错,造成重复劳动和决策延迟。

README

README summary

LiteParse Docs <img src="https://github.com/user attachments/assets/07ba6a82 6bb1 4dea b0ef cad7df7d1622" alt="out" width="600"

Repository

Repository metadata

Owner
run-llama
License
Apache-2.0
Default branch
main
Days since created
108
Days since last push
0
Signals

Repository signals

Watchers
7,193
Open issues
14
Topics
document-ocrdocument-processingocrocr-recognitionpdfpdf-parsertext-extraction
Contributors

Contributor snapshot

Contributor count
10
Top contributor share
0.748
Top contributors
logan-markewich, AstraBert, AdemBoukhris457, dependabot[bot], github-actions[bot]
源数据· Raw Archive
source
GitHub Trending
upstream_source
github_trending
upstream_item_id
run-llama--liteparse
daily_ranking_item_id
bb6d389e-ada4-4f1d-ba45-f0e13c62e086
rank_date
2026-05-30
rank
8
name
liteparse
tagline
A fast, helpful, and open-source document parser
description
A fast, helpful, and open-source document parser
votes_count
7,193
topics
document-ocrdocument-processingocrocr-recognitionpdfpdf-parsertext-extraction
media / source-specific data
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    "raw_text": "# LiteParse\n\n[![CI](https://github.com/run-llama/liteparse/actions/workflows/ci.yml/badge.svg)](https://github.com/run-llama/liteparse/actions/workflows/ci.yml)\n|\n[![Crates.io version](https://img.shields.io/crates/v/liteparse.svg)](https://crates.io/crates/liteparse)\n|\n[![npm version](https://img.shields.io/npm/v/@llamaindex/liteparse.svg)](https://www.npmjs.com/package/@llamaindex/liteparse)\n|\n[![wasm version](https://img.shields.io/npm/v/@llamaindex/liteparse-wasm.svg)](https://www.npmjs.com/package/@llamaindex/liteparse-wasm)\n|\n[![PyPI version](https://img.shields.io/pypi/v/liteparse.svg)](https://pypi.org/project/liteparse/)\n|\n[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)\n|\n[Docs](https://developers.llamaindex.ai/liteparse/)\n\n<img src=\"https://github.com/user-attachments/assets/07ba6a82-6bb1-4dea-b0ef-cad7df7d1622\" alt=\"out\" width=\"600\">\n\n> Looking for LiteParse V1? Follow this link to [the old code](https://github.com/run-llama/liteparse/tree/logan/liteparse-v1)\n\nLiteParse is a standalone OSS PDF parsing tool focused exclusively on **fast and light** parsing. It provides high-quality spatial text parsing with bounding boxes, without proprietary LLM features or cloud dependencies. Everything runs locally on your machine.\n\n**Hitting the limits of local parsing?**\nFor complex documents (dense tables, multi-column layouts, charts, handwritten text, or\nscanned PDFs), you'll get significantly better results with [LlamaParse](https://developers.llamaindex.ai/python/cloud/llamaparse/?utm_source=github&utm_medium=liteparse),\nour cloud-based document parser built for production document pipelines. LlamaParse handles the\nhard stuff so your models see clean, structured data and markdown.\n\n>  [Sign up for LlamaParse free](https://cloud.llamaindex.ai?utm_source=github&utm_medium=liteparse)\n\n## Overview\n\n- **Fast Text Parsing**: Spatial text parsing using PDFium\n- **Flexible OCR System**:\n  - **Built-in**",
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