RAG & Knowledge
opendataloader-pdf
Turn PDFs into AI-ready data: extract Markdown, JSON and tables — and auto-tag for accessibility
★ 29.5k starsApache-2.0
View guide →Lightweight OCR toolkit turning PDFs and images into structured, LLM-ready data in 100+ languages
PaddleOCR is an open-source rag & knowledge project by PaddlePaddle (PaddlePaddle/PaddleOCR on GitHub). It has 90,781 GitHub stars and 11,456 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 16 September 2026.
Decide what you want from PaddleOCR and check the README and requirements to confirm it fits your setup and Python environment.
Clone the repository from GitHub (github.com/PaddlePaddle/PaddleOCR) or use the documented install channel if you do not need the source.
Follow the README quickstart to install dependencies and set any required configuration or credentials.
Work through the README's first example end to end, then adapt it to your own project or data.
Supports text recognition in over 100 languages for documents and scene images.
PP-Structure and PaddleOCR-VL turn PDFs and images into structured data and Markdown for LLMs.
Scene OCR handles photos and real-world images, not just clean scans.
Includes KIE capabilities for extracting fields from forms and documents.
Part of the PaddlePaddle ecosystem with models, deployment tools and documentation.
Designed as a powerful but lightweight toolkit that runs without a large GPU.
Start by getting the source and entering the project directory.
git clone https://github.com/PaddlePaddle/PaddleOCR.git
cd PaddleOCRInstall the Python package from PyPI (the README's local deployment path).
pip install paddleocrUse the CLI/API on a first document or image after installing.
paddleocr ocr -i ./example.jpg # see README for the exact commandIt is maintained by PaddlePaddle and contributors on GitHub, where the repository github.com/PaddlePaddle/PaddleOCR is the canonical home for code, issues and releases.
Yes — it is open source under the Apache-2.0 license. Read the license in the repository for what is permitted, including any conditions on redistribution or commercial use.
No. PaddleOCR runs locally and needs no API key; optional hosted demos are separate.
Compared with Tesseract: PaddleOCR offers deep-learning models, layout and structure parsing and 100+ languages out of the box, beyond Tesseract's classic OCR engine.
Clone github.com/PaddlePaddle/PaddleOCR, follow the README quickstart to install it, and run the documented first example before adapting it to your own work.
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