Changelog generation has never been so easy. Fully automate changelog generation - this gem generate changelog file based on tags, issues and merged pull requests from GitHub.

Changelog generation has never been so easy. Fully automate changelog generation - this gem generate changelog file based on tags, issues and merged pull requests from GitHub.

A fast, asynchronous, rack-compatible web server.

Test your rendered HTML files to make sure they're accurate.

Hierarchical persistent memory with semantic search for SwarmSDK AI agents

SwarmSDK is a complete reimagining of Claude Swarm that runs all AI agents in a single process using RubyLLM for LLM interactions. Define collaborative AI agents in simple Markdown files with YAML frontmatter, and orchestrate them without the overhead of multiple processes or MCP inter-process communication. Perfect for building lightweight, efficient AI agent teams with specialized roles and capabilities.

Provides support for asynchonous TCP, UDP, UNIX and SSL sockets.

A HTTP client and server library.

A singleplex and multiplex resource pool for implementing robust clients.

vagrant-dns is a vagrant plugin that manages DNS records associated with local machines.

A Grape API serving a Slack bot to multiple teams.

An easy to use DNS client resolver and server for Ruby.

An adapter for fibered mysql2

Abstract container-based parallelism using threads and processes where appropriate.

A Redis client library.

Featuring full support for the REST, Streaming and Exploits API

This rubygem does not have a description or summary.

ActiveGenie is an enabler for creating reliable GenAI features, offering powerful, model-agnostic tools across any provider. It allows you to settle subjective comparisons with a `ActibeGenie::Comparator` module that stages a political debate, get accurate scores from an AI jury using `ActiveGenie::Scorer`, and rank large datasets using `ActiveGenie::Ranker`'s tournament-style system. This reliability is built on three core pillars: - Custom Benchmarking: Testing for consistency with every new version and model update. - Reasoning Prompting: Utilizing human reasoning techniques (like debate and jury review) to control a model's reasoning. - Overfitting Prompts: Highly specialized, and potentially model-specific, prompt for each module's purpose.

Access postgres without blocking.

The Ruby framework for programming with large language models. DSPy.rb brings structured LLM programming to Ruby developers. Instead of wrestling with prompt strings and parsing responses, you define typed signatures using idiomatic Ruby to compose and decompose AI Worklows and AI Agents.