【第173期】Docling：开源的文档转换工具包

Seventy3: 用NotebookLM将论文生成播客，让大家跟着AI一起进步。

今天的主题是：

Docling: An Efficient Open-Source Toolkit for AI-driven Document Conversion

Summary

Docling is a new open-source toolkit for document conversion, designed to parse various document formats into a structured representation using AI models for layout analysis and table recognition. It aims to provide an efficient and customizable solution for tasks like document understanding and information extraction, and it supports local execution, integrations with frameworks like LangChain and LlamaIndex. The paper outlines Docling's design, architecture (including pipelines, parser backends, and the DoclingDocument data model), AI models, and performance benchmarks compared to other open-source tools. The toolkit's capabilities make it suitable for generative AI applications, data preparation, and knowledge extraction, with future work planned to include more models and an open-source quality evaluation framework. Docling has attracted significant community interest and is integrated into several open-source projects.

Docling 是一个全新的开源文档转换工具包，旨在通过使用 AI 模型进行布局分析和表格识别，将各种文档格式解析为结构化表示。它旨在为文档理解和信息提取等任务提供高效且可定制的解决方案，支持本地执行，并与像 LangChain 和 LlamaIndex 等框架进行集成。

本文概述了 Docling 的设计与架构，包括管道、解析器后端和 DoclingDocument 数据模型，介绍了所使用的 AI 模型及其与其他开源工具的性能基准对比。该工具包的功能使其非常适合用于生成型 AI 应用、数据准备和知识提取等任务，未来的工作将包括更多模型的引入以及一个开源的质量评估框架。

Docling 已吸引了大量社区关注，并已集成到多个开源项目中。

原文链接：https://www.arxiv.org/abs/2501.17887