A Rails Engine that provides a simple yet effective interface, perfect for admin management.

Doccoli is a modern lightweight rails engine that provides for management of hierarchical documentation.

Docent is a mountable Rails engine to provide your app's users with links to proper support documentation.

Generate documents in various formats based on standard boilerplate and custom content.

Track and report tags of followed Docker images.

Sync and view your DocRaptor log files locally. Prevents having to give out your login to the service to the entire team.

Makes it easy to create PDF documents through the Docmago API.

TO0DO: Description of DocsApi.

a library for docset generation

Docsmith adds snapshot-based versioning to any ActiveRecord model with zero system dependencies. • Full content snapshots (HTML, Markdown, JSON) for instant rollbacks • Format-aware diff engine: word-level diffs for Markdown, tag-atomic diffs for HTML • Document-level and range-anchored comments with threading and version migration • Per-class configuration, debounced auto-save, lifecycle events, and a clean API Perfect for wikis, CMS pages, API specs, legal documents, or any content that needs an audit trail and inline collaboration.

Coverage statistics for Cocoa documentation sets

By adding simple markup to your controllers or routes.rb you can specify your api doc.

Rails engine which takes your markdown documentation stored in your application repository and exposes that as a wiki-style, navigateable wiki.

With this project you will able to analyse your external resources status. You will be able to configure wich database connection to check or all the http urls

Dr. Rails: improving your uptime since 2013.

A Rails plug-in, which checks various services (db, cache, sidekiq, redis, stripe, mailgun, etc.).

It does cool stuff!

Document Number lets you automacally assign number sequences for your rails model

Uses an Active Record as a schema-less document

The Ruby library, Documentrix, is designed to provide a way to build and query vector databases for applications in natural language processing (NLP) and large language models (LLMs). It allows users to store and retrieve dense vector embeddings for text strings.