Generic framework for historical document processing

A full-featured Document Layer for your application, providing the functionality of a flexible document management system, including storage, discovery, processing, and retrieval. Deploys directly into your Amazon Web Services Cloud. 🌟 Star to support our work!

An include filter for Pandoc

⚡ Cloud-native, AI-powered, document processing pipelines on AWS.

Unofficial mirror of git://git.lyx.org/lyx.git (updates daily. not affiliated with lyx.org.)

Semantic extraction from conference proceedings.

A comprehensive list of annotated training datasets classified by use case.

Enhanced Document Understanding on AWS delivers an easy-to-use web application that ingests and analyzes documents, extracts content, identifies and redacts sensitive customer information, and creates search indexes from the analyzed data.

Retrieval of fully structured data made easy. Use LLMs or custom models. Specialized on PDFs and HTML files. Extensive support of tabular data extraction and multimodal queries.

This library builds a graph-representation of the content of PDFs. The graph is then clustered, resulting page segments are classified and returned. Tables are retrieved formatted as a CSV.

tokyo, a REST API, when given any type of document 📄, Identifies mime-type 🧐. Suggests extension 🦔. Alas Extracts text 💪.

A module for creating stopword lists for any language, based on a set of documents.

A Python framework for multi-modal document understanding with Amazon Bedrock

A Python command-line utility intended for automating some copyediting tasks in documents. It allows editing zipped, XML-based files (e.g. docx, odt, or epub), through XSLT stylesheets. Can be rather easily extended with your own custom xsl stylesheets.

An advanced distributed knowledge fabric for intelligent document processing, featuring multi-document agents, optimized query handling, and semantic understanding.

Document Templater is a powerful tool for automated document generation. Streamline the process of creating standard documents, such as contracts, reports, and forms, using predefined templates. This repository contains the source code for Document Templater, allowing you to easily integrate this functionality into your projects and automate docs.

Use data from MongoDB in LangChain, Llama and OpenAI

FileGazer - deep file analysing and categorisation

Text line detection for Urdu OCR (UTRNet)