Data & context
Docling
A Python document-processing toolkit that converts varied source formats into structured data for extraction, search, retrieval and agent context.
Overview
Research summary
Docling turns documents into a structured representation suitable for downstream processing and AI applications. Its Python interfaces and command-line tools cover document conversion and extraction across multiple source formats, with features for layout, tables, and other document structure rather than only plain text scraping. Applications can export results into formats such as Markdown or JSON and integrate the converted content into retrieval or agent workflows.
The toolkit can run locally, but specific pipelines may require separately downloaded models or optional processing dependencies. It is a document preparation component, not a coding agent or a guarantee that every complex document will be interpreted correctly. Conversion quality should be checked against the actual source corpus.
The code is MIT licensed; model artifacts, optional components, and source documents retain their own applicable terms.
Repository summary
- Stars
- 66,488
- Open issues
- Unavailable
- Last push
- 2026-09-16
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Version
- Unavailable
Recorded catalogue figures. View repository data and provenance →
Classification
Pricing & services
Paid services unknown
Whether the provider offers paid products or services has not been established.
Licence scope
Implementation
Recorded implementation details and interfaces for Docling.
Implementation details
Python document-conversion library and CLI
- Languages
- Python
- Repository type
- source
Recorded interfaces and capabilities
Licence scope
Repository
Repository snapshots, release information and recorded maintenance signals.
Repository snapshot
- Stars
- 66,488
- Open issues
- Unavailable
- Last push
- 2026-09-16
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Archived
- Not recorded
Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).
Maintenance and provenance
- Catalogue snapshot
- 2026-10-06
- Stars source
- Recorded fallback
- Last push source
- Recorded fallback
Documentation
Recorded references and research provenance for this entry.
Recorded sources 8
- https://github.com/docling-project/docling Project page · Linked repository · Research reference
- https://github.com/docling-project/docling/blob/main/README.md Research reference
- https://github.com/docling-project/docling/blob/main/LICENSE Research reference
- https://github.com/stars/angelcervera/lists/ai Research reference
- https://api.github.com/repos/docling-project/docling Research reference
- https://docling-project.github.io/docling Research reference
- https://docling.ai/community/ Research reference
- https://www.youtube.com/@Docling-AI Research reference
Research metadata
- Research date
- 2026-09-16
- Catalogue snapshot
- 2026-10-06
Community & social 4 channels
Video
- YouTubeDoclingOfficialDemos
Link details for YouTube — Docling
- Access
- Public
- Last checked
Communities
- SlackDocling on LF AI & Data SlackPrimary channelOfficialDiscussionDevelopment
Link details for Slack — Docling on LF AI & Data Slack
- Last checked
- GitHub Discussionsgithub.com/docling-project/docling/discussionsOfficialDiscussion
Link details for GitHub Discussions
- Access
- Public
- Last checked
Social & updates
- LinkedInwww.linkedin.com/company/doclingOfficial
Link details for LinkedIn
- Last checked