Used in conjunction with the Language Operator for Kubernetes

Interact with PostgreSQL, MySQL, and Oracle databases using natural language. Powered by RubyLLM with a locally-running Ollama model.

Mountable Rails engine that provides hierarchical LLM call tracing and versioned prompt management with Mustache templates.

A Ruby gem for translating Markdown files using AI while preserving formatting

Locallingo extends i18n-tasks with AI translation (via RubyLLM — OpenAI, Anthropic, and more), source-hash drift detection so only missing/changed keys are re-translated, and a static + AI translation-quality linter. Everything app-specific — target locales, provider/model, prompt context and glossary, per-language style guides, which validators and quality rules run, and post-translate hooks — is config-driven via `.locallingo.yml`, with a default block plus optional per-package overrides. Ships the `lingo` CLI.

MARS (Multi-Agent Ruby SDK) provides a comprehensive framework for developers to implementmulti-agent solutions using pure Ruby. It offers a simple API for orchestrating multiple agents.

Mildred power organizer

A Ruby port of mini-swe-agent.

A minimalist AI agent framework with multi-channel support, tool calling, and extensible architecture

An opinionated, drop-in agent harness for RubyLLM. Nexo composes the RubyLLM ecosystem into one coherent front door, adding a Sandbox+Permissions seam and a WorkflowRun lifecycle primitive.

A light agent framework on top of RubyLLM. An agent is an object: its fields are state, its methods are what the model can call, and the methods it declares without a body are written by the model at runtime — the method name and prompt are the specification, the schema is the contract. The model acts by writing Ruby that runs on the agent itself.

Agent framework for Rails: bounded tool-calling loops, fast paths, structured extraction, and (v0.2) durable workflows on ActiveRecord. Built on ruby_llm.

Phronomy is a Ruby AI agent framework that provides composable building blocks — Agents, Workflows, Tools, Filters, and Tracing — for building AI agents in Ruby. Powered by RubyLLM for LLM abstraction.

pikuri-core is the lean, audit-friendly foundation of the pikuri family: Pikuri::Agent (a thin wrapper around ruby_llm's chat loop) with its Configurator + Extension protocol, the strict Pikuri::Tool framework, a listener surface for rendering / budgets / sub-agents, and four bundled stateless tools (calculator, web search, web scrape, fetch). Extensions (skills, MCP, workspace, coding stack, named-agent personas) live in sibling gems so a privacy-conscious user can install just this core and audit a minimal dependency tree. For the convenience bundle that pulls in everything, see the +pikuri+ metagem.

Probatio Diabolica runs custom *_spec.rb files with a DSL inspired by RSpec and supports text/image/PDF reporting.

Under development. Contributors welcome.

Ragents is a pure Ruby, Ractor-based AI agent framework designed for concurrent, isolated agent execution. It provides message-passing architecture, tool-based actions, and provider-agnostic LLM integration without Rails dependencies.

Ragnar is a high-performance RAG system that leverages Rust libraries through Ruby bindings for embeddings, vector search, and topic modeling. It provides a complete CLI for indexing documents and querying with LLMs.

Unified tool definition pipeline for Rails 8 applications using FastMCP and RubyLLM.

RainbowLLM provides intelligent routing and failover capabilities for multiple LLM providers. Automatically tries providers in sequence until one responds successfully, ensuring reliable access to LLM services.