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; a memory system with Redis backend and semantic caching; and Rails integration with generators and ActiveRecord- backed conversation history.

Provider-agnostic LLM evaluation with pluggable metrics, statistical A/B comparison, and test framework integration. Ragas for Ruby, powered by RubyLLM.

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.

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

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.

A Rails engine providing comprehensive observability for LLM-powered applications. Features include session tracking, trace analysis, prompt management, cost monitoring, and optional chat/agent testing UI (with RubyLLM integration).

Adds Pollinations AI support to RubyLLM — chat, image/video generation, TTS/music, and transcription via the Pollinations API. Installs as a standalone gem without modifying RubyLLM core.

A RubyLLM plugin that enables local LLM execution using the Red Candle gem. Run quantized GGUF models directly in Ruby without external API calls. Supports streaming, structured output, and multiple model architectures including Gemma, Llama, Qwen, Mistral, and Phi.

Cache RubyLLM responses based on semantic similarity, not exact string matching. Reduces costs and latency by returning cached responses for semantically equivalent queries.

Route messages to specialized RubyLLM chat agents based on semantic similarity using embeddings and kNN lookup

Provides an adapter to integrate RubyLLM with Sequel ORM.

Provides a RubyLLM::Provider that allows you to stub responses for testing purposes. You can stub individual responses or a sequence of responses, and you can also temporarily stub responses within a block.

Intuitive one-liner utility methods for common LLM tasks like text summarization, translation, data extraction, classification, grammar correction, sentiment analysis, key point extraction, text rewriting, and question answering.

A RubyLLM plugin that integrates Top Secret to automatically filter sensitive information from LLM interactions.

Automatically report AI agent health, response times, and model info to your ups.dev status page.