Docling: Document Parsing for Generative AI

Repositorydocling-project/doclingTool

Docling is an open-source Python tool designed to parse documents across multiple formats—such as PDF, office files, audio, and HTML—to prepare them for generative AI workflows.

Key points

  1. Parses formats including PDF, DOCX, PPTX, XLSX, HTML, EPUB, emails (EML, MSG), LaTeX, images, and audio files (WAV, MP3).
  2. Features advanced PDF understanding for page layouts, reading order, table structures, code, formulas, and image classification.
  3. Built with Python, Pydantic v2, uv, and Ruff under the MIT License.
  4. Supported by the LF AI & Data Foundation, complies with OpenSSF Best Practices, and references an arXiv research paper (2408.09869).

Why it matters

Raw, unstructured files are often a bottleneck in generative AI and retrieval workflows. Docling addresses layout and table extraction across diverse formats to provide structured data for language models.

Analysis

Docling targets developers and data practitioners building generative AI and document processing systems. With over 66,000 GitHub stars, LF AI & Data Foundation backing, OpenSSF Best Practices certification, and a modern Python stack, the project demonstrates a very high level of maturity.

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Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.

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Locations

  • Mattersburg
    Johann Nepomuk Bergerstraße 7/2/14
    7210 Mattersburg, Austria
  • Vienna
    Ungargasse 64-66/3/404
    1030 Wien, Austria

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