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.

RLM.rb is a Ruby runtime spine for Recursive Language Models. It runs bounded, typed, auditable AI jobs over files, records, and application context. RLM.rb includes RubyLLM provider access, a dspy.rb signature adapter, the recursive prompt loop, file/context mounting, recursive sub-LM calls, typed final output, budget controls, trace events, and a best-effort trace_store hook.

RobotLab is a Ruby framework for building and orchestrating multi-robot LLM workflows. Built on ruby_llm, it provides robots with template-based prompts, tools, and shared memory; networks for coordinating multiple robots with intelligent routing; MCP (Model Context Protocol) integration for external tool servers; and a memory system with Redis backend and semantic caching. Optional gems add Rails integration (robot_lab-rails), durable learning (robot_lab-durable), Ractor concurrency (robot_lab-ractor), document storage (robot_lab-document_store), and OS-level skill-script confinement (robot_lab-sandbox). Core itself imposes no execution limitations.

Standalone background daemon that watches a repo's git activity, Claude Code session transcripts, and terminal commands, then infers the current goal/direction via a one-shot RubyLLM call to a local model. Writes an intent artifact any tool can read — robot_lab-to uses it to seed takeover runs, but nothing here requires RobotLab.

A standalone, self-contained coding and automation agent built on ruby_llm. Provides an agent loop, persistent memory, SQLite sessions, context compaction, a job system, a tool registry, and an extensible UI layer.

Interactive rake tasks to generate context files for AI coding assistants (Claude, Cursor, Windsurf, Codex, llm.txt). Uses RubyLLM to analyze your codebase and create platform-specific context that helps AI understand your project.

RubyCoded is a terminal-based AI coding assistant built in Ruby. It provides a full TUI chat interface with support for multiple LLM providers (OpenAI, Anthropic, etc.), an agent mode with filesystem tools for reading, writing, and editing project files, a plan mode for structured task planning, and a plugin system for extensibility.

Emits the AI SDK UI message stream protocol from RubyLLM chats, so React front ends built with useChat talk to a Ruby backend: text, reasoning, tool calls and approvals.

Talks the native Anthropic Messages format to Bedrock InvokeModel / InvokeModelWithResponseStream, unlocking Anthropic-specific features that the Converse API cannot express — tool search with deferred tool loading, prompt caching via cache_control, and structured outputs — while keeping data inside the AWS boundary. Authenticates with the standard AWS credential chain (IRSA, Pod Identity, instance profiles, env vars) via aws-sdk-core.

RubyLLM Code will provide an AI-powered coding assistant. This is a placeholder release - full implementation coming soon!

A RubyLLM tool that runs model-generated Ruby code inside a secure WebAssembly sandbox (SecurityBox), with explicit read-only and read-write folder mounts so agents can work on host project folders safely.

A RubyLLM provider that invokes the official Codex CLI, reuses local ChatGPT authentication, and maps RubyLLM structured-output schemas to Codex output schemas.

A comprehensive Ruby gem that provides Docker management capabilities through RubyLLM tools. Enables AI assistants to interact with Docker containers, images, networks, and volumes using natural language. Ported from DockerMCP to work directly with RubyLLM without requiring an external MCP server.

LLM evaluation engine for Rails.

Access Claude and GPT models through GitLab Duo via the RubyLLM interface. One provider, automatic routing to Anthropic or OpenAI backends.