In this report, we introduce DocXChain, a powerful open-source toolchain for
document parsing, which is designed and developed to automatically convert the
rich information embodied in unstructured documents, such as text, tables and
charts, into structured representations that are readable and manipulable by
machines. Specifically, basic capabilities, including text detection, text
recognition, table structure recognition and layout analysis, are provided.
Upon these basic capabilities, we also build a set of fully functional
pipelines for document parsing, i.e., general text reading, table parsing, and
document structurization, to drive various applications related to documents in
real-world scenarios. Moreover, DocXChain is concise, modularized and flexible,
such that it can be readily integrated with existing tools, libraries or models
(such as LangChain and ChatGPT), to construct more powerful systems that can
accomplish more complicated and challenging tasks. The code of DocXChain is
publicly available
at:~https://github.com/AlibabaResearch/AdvancedLiterateMachinery/tree/main/Applications/DocXChain

DocXChain 是一个强大的开源工具链，用于将非结构化文档（如文本、表格和图表）中的丰富信息自动转换为可读取和可操纵的结构化表示，提供了基本功能如文本检测、文本识别、表结构识别和布局分析，并且可以与现有的工具、库或模型轻松集成，以构建更强大的系统，实现更复杂和具有挑战性的任务。