Docling高效转换多种文档格式，适合快速开发智能文档应用。
Docling: An Efficient Open-Source Toolkit for AI-driven Document Conversion
- 采用AI模型实现布局与表格结构解析，输出统一结构化数据
- 可在普通硬件上运行，资源占用少，支持快速部署
- 模块化设计易扩展，已集成至LangChain等主流框架
我们推出Docling，一个易于使用、自包含、MIT许可的开源文档转换工具包，可将多种主流文档格式解析为统一的丰富结构化表示。其核心依赖于先进的专用AI模型——布局分析模型DocLayNet和表格结构识别模型TableFormer，可在普通硬件上以小资源开销高效运行。Docling以Python包形式发布，既可通过API调用，也可作为命令行工具使用。其模块化架构和高效的文档表示，便于实现功能扩展、新模型接入与定制化开发。该工具已集成至LangChain、LlamaIndex、spaCy等流行开源框架，是文档处理与高端应用开发的理想选择。发布后一个月内GitHub获10,000颗星，2024年11月成为全球GitHub趋势榜第一名。
原文摘要 · Abstract (English)
We introduce Docling, an easy-to-use, self-contained, MIT-licensed, open-source toolkit for document conversion, that can parse several types of popular document formats into a unified, richly structured representation. It is powered by state-of-the-art specialized AI models for layout analysis (DocLayNet) and table structure recognition (TableFormer), and runs efficiently on commodity hardware in a small resource budget. Docling is released as a Python package and can be used as a Python API or as a CLI tool. Docling's modular architecture and efficient document representation make it easy to implement extensions, new features, models, and customizations. Docling has been already integrated in other popular open-source frameworks (e.g., LangChain, LlamaIndex, spaCy), making it a natural fit for the processing of documents and the development of high-end applications. The open-source community has fully engaged in using, promoting, and developing for Docling, which gathered 10k stars on GitHub in less than a month and was reported as the No. 1 trending repository in GitHub worldwide in November 2024.
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