DocXChain: A Powerful Open-Source Toolchain for Document Parsing and Beyond

TL;DR

DocXChain is an open-source, modular toolchain that automates the conversion of unstructured documents into structured data, supporting various document parsing tasks and easily integrating with other systems for complex applications.

Contribution

It introduces a flexible, comprehensive toolchain for document parsing that combines basic capabilities with pipelines, enabling easier integration and application in real-world scenarios.

Findings

Provides a complete set of document parsing capabilities

Supports integration with tools like LangChain and ChatGPT

Open-source and publicly available for community use

Abstract

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:~\url{https://github.com/AlibabaResearch/AdvancedLiterateMachinery/tree/main/Applications/DocXChain}