# Docling

> Get your documents ready for generative AI

Parses PDF, Office, HTML and images with layout and table understanding into Markdown or JSON for RAG and agents.

- Source: https://github.com/docling-project/docling
- Homepage: https://docling-project.github.io/docling
- License: MIT
- Language: Python
- Stars: 68317
- Forks: 4985
- Contributors: 348
- Last commit: 2026-10-02
- Latest release: v2.132.0 (2026-10-01)
- Purpose: AI & LLM tooling, RAG & vector DBs
- Runs on: CLI, Library / SDK
- For: Personal, Enterprise

## Worth score: 87/100

How much DigGitHub recommends it, from activity, adoption, docs, license and security signals.

- Popularity: 24/25
- Momentum: 10/20
- Maintenance: 25/25
- Community: 13/15
- Readiness: 15/15

## Alternatives

- [MarkItDown](https://diggithub.com/microsoft/markitdown.md): Convert Office files and PDFs to Markdown for LLMs
- [MinerU](https://diggithub.com/opendatalab/MinerU.md): Convert PDFs and Office docs to LLM-ready Markdown
- [Marker](https://diggithub.com/datalab-to/marker.md): Convert PDFs to Markdown and JSON with high accuracy
- [anydoc](https://diggithub.com/firecrawl/anydoc.md): Convert office files and PDFs to Markdown
- [Crawl4AI](https://diggithub.com/unclecode/crawl4ai.md): Web crawler that turns sites into LLM-ready Markdown
- [LightRAG](https://diggithub.com/HKUDS/LightRAG.md): Simple and fast graph-based RAG
- [OpenViking](https://diggithub.com/volcengine/OpenViking.md): Context database for AI agents
- [LlamaIndex](https://diggithub.com/run-llama/llama_index.md): Data framework for LLM applications and agents

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Source page: https://diggithub.com/docling-project/docling
Updated: 2026-10-03