RAG・知識ベース
MinerU
MinerU — turns PDFs and Office documents into LLM-ready Markdown and JSON for agents and RAG pipelines, Apache-2.0 plus terms
★ 82.5k スターApache-2.0 + terms
ガイドを見る →opendataloader-pdfは、opendataloader-projectが公開しているオープンソースのRAG・知識ベースプロジェクトです（GitHub: opendataloader-project/opendataloader-pdf）。GitHubスターは29,499、フォークは2,809で、Apache-2.0ライセンスの下で公開されています。GitHubでの最終更新は2026年10月8日です。
Turn PDFs into AI-ready data: extract Markdown, JSON and tables — and auto-tag for accessibility
Decide what you want to achieve with opendataloader-pdf and check the README on GitHub for requirements before installing.
Clone the repository from GitHub (or take the packaged install route in step 3 if the README offers one).
Follow the project's documented install commands — the Run section below lists the exact ones — and add any required API keys or models.
Work through the README's quickstart example end to end, then adapt it to your own project or data.
Outputs Markdown, JSON and HTML with tables, headings hierarchy and bounding boxes preserved.
Extracts text in the order a human reads it, including multi-column layouts.
Generates tagged PDFs to support PDF/UA and European Accessibility Act (EAA) workflows.
Complex pages can be routed to an AI-backed mode the project positions for top extraction accuracy.
Pluggable OCR engines (RapidOCR, Tesseract, Apple Vision, Nemotron OCR options) handle image-only pages.
Server-side enrichment can extract formulas as LaTeX and describe charts and images.
Get the parser source and documentation.
git clone https://github.com/opendataloader-project/opendataloader-pdf.git
cd opendataloader-pdfInstall from PyPI (a JVM is used under the hood for conversion).
pip install -U opendataloader-pdfRun the CLI on a file or a whole folder to produce structured output.
opendataloader-pdf file1.pdf file2.pdf folder/opendataloader-pdf is maintained by the opendataloader-project organization/account on GitHub, together with open-source contributors, in the public repository opendataloader-project/opendataloader-pdf.
Yes — the code is open source under the Apache-2.0 license. You can use, modify and redistribute it under that license's terms.
The core parser is free and Apache-2.0 with no API key; the optional hybrid/AI enrichment and PDF/UA export features are positioned as server/enterprise options in the README's capability matrix.
Those extract raw text cheaply but lose layout and reading order; OpenDataLoader focuses on structure — order, tables, headings and tags — that downstream AI actually needs.
Clone the repository from GitHub, follow the install commands in the Run section (taken from the project's README), and complete the documented quickstart example before adapting it to your own use case.
MinerU — turns PDFs and Office documents into LLM-ready Markdown and JSON for agents and RAG pipelines, Apache-2.0 plus terms
Marker — converts PDFs to Markdown and JSON quickly and accurately, with layout, tables and math intact, Apache-2.0
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Knowhere turns documents into structured, hierarchy-native chunks ready for agents and RAG.
LibreAIカタログに掲載されたRAG・知識ベースプロジェクトの中で最もスターの多いもの — opendataloader-pdfが合わなかった場合に検討したい、現実的な候補リストです。
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MinerU — turns PDFs and Office documents into LLM-ready Markdown and JSON for agents and RAG pipelines, Apache-2.0 plus terms
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カタログの中でopendataloader-pdfとスター数が近いRAG・知識ベースプロジェクト — 前後の棚もそのまま見て回れます。
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