# RubyLLM Documentation

> Developer documentation for RubyLLM 1.x.

The canonical source is [crmne/ruby_llm](https://github.com/crmne/ruby_llm).

## Full Documentation

- [Complete documentation](https://rubyllm.com/llms-full.txt): All canonical pages in one Markdown document.

## Overview

- [RubyLLM](https://rubyllm.com/): A single, beautiful Ruby framework for all major AI providers. Easily build chatbots, AI agents, RAG applications, content generators, and every AI workflow you can think of.

## Pages

- [About RubyLLM](https://rubyllm.com/about/): RubyLLM is an open source Ruby gem for building AI applications across major AI providers with one consistent Ruby framework.

## Getting Started

- [Getting Started](https://rubyllm.com/getting-started/): Start building AI apps in Ruby in 5 minutes. Chat, generate images, create embeddings - all with one gem.
- [Overview](https://rubyllm.com/overview/): Understand how RubyLLM works and how its components fit together
- [Configuration](https://rubyllm.com/configuration/): Configure once, use everywhere. API keys, defaults, timeouts, and multi-tenant contexts made simple.

## Core Features

- [Chat](https://rubyllm.com/chat/): Learn how to have conversations with AI models, work with different providers, and handle multi-modal inputs
- [Tools](https://rubyllm.com/tools/): Let AI call your Ruby code. Connect to databases, APIs, or any external system with function calling.
- [Stream Responses](https://rubyllm.com/streaming/): Learn how to display AI responses in real-time as they're generated
- [Embeddings](https://rubyllm.com/embeddings/): Transform text into numerical vectors for semantic search, recommendations, and content similarity
- [Image Generation](https://rubyllm.com/image-generation/): Generate images from text descriptions using AI models like DALL-E 3 and Imagen
- [Agents](https://rubyllm.com/agents/): Define reusable AI assistants with class-based configuration, runtime context, and prompt conventions
- [Audio Transcription](https://rubyllm.com/audio-transcription/): Convert speech to text with support for multiple languages and speaker diarization
- [Moderation](https://rubyllm.com/moderation/): Identify potentially harmful content in text using AI moderation models before sending to LLMs
- [Extended Thinking](https://rubyllm.com/thinking/): Give reasoning models more time and budget to deliberate, with optional access to thinking output

## Advanced

- [Rails Integration](https://rubyllm.com/rails/): Rails + AI made simple. Persist chats with ActiveRecord. Stream with Hotwire. Deploy with confidence.
- [Scale with Async](https://rubyllm.com/async/): Handle hundreds of concurrent AI requests on modest hardware. Ruby's async ecosystem meets AI.
- [Error Handling](https://rubyllm.com/error-handling/): Learn how to handle errors gracefully when working with AI providers
- [Model Registry](https://rubyllm.com/models/): Access hundreds of AI models from all major AI providers with one Ruby framework
- [Instrumentation](https://rubyllm.com/instrumentation/): Observe RubyLLM requests, chats, tool calls, embeddings, and model refreshes
- [Agentic Workflows](https://rubyllm.com/agentic-workflows/): Build workflow-oriented AI systems with plain Ruby orchestration, from routing and parallelization to RAG
- [Upgrading](https://rubyllm.com/upgrading/): Upgrade guides for changes in data formats

## Reference

- [RubyLLM Ecosystem](https://rubyllm.com/ecosystem/): Extend RubyLLM with MCP servers, structured schemas, instrumentation, monitoring and community-built tools for production AI apps.