Build AI features the Ruby way

A delightful Ruby AI framework that feels at home in Rails. Switch models without rewriting your code, then scale to production with everything from Chats and Tools to Agents, RAG, and Workflows.

Battle tested at [

](https://chatwithwork.com) - *Fully private work AI* [![Gem Version](https://badge.fury.io/rb/ruby_llm.svg)](https://badge.fury.io/rb/ruby_llm) [![Ruby Style Guide](https://img.shields.io/badge/code_style-rubocop-brightgreen.svg)](https://github.com/rubocop/rubocop) [![Gem Downloads](https://img.shields.io/gem/dt/ruby_llm)](https://rubygems.org/gems/ruby_llm) [![codecov](https://codecov.io/gh/crmne/ruby_llm/branch/main/graph/badge.svg)](https://codecov.io/gh/crmne/ruby_llm)

> [!NOTE] > Using RubyLLM? [Share your story](https://tally.so/r/3Na02p)! Takes 5 minutes. --- Build AI features in Ruby: chats, agents, tools, RAG, and agentic workflows. Works with OpenAI, xAI, Anthropic, Google, AWS, local models, and any OpenAI-compatible API. ## Build a working Ruby AI chat in two minutes https://github.com/user-attachments/assets/65422091-9338-47da-a303-92b918bd1345 ## Why RubyLLM? Every AI provider ships their own bloated client. Different APIs. Different response formats. Different conventions. It's exhausting. RubyLLM gives you one beautiful framework for all of them. Same interface whether you're using GPT, Claude, or your local Ollama. Just three dependencies: Faraday, Zeitwerk, and Marcel. That's it. ## Show me the code ```ruby # Just ask questions chat = RubyLLM.chat chat.ask "What's the best way to learn Ruby?" ``` ```ruby # Analyze any file type chat.ask "What's in this image?", with: "ruby_conf.jpg" chat.ask "What's happening in this video?", with: "video.mp4" chat.ask "Describe this meeting", with: "meeting.wav" chat.ask "Summarize this document", with: "contract.pdf" chat.ask "Explain this code", with: "app.rb" ``` ```ruby # Multiple files at once chat.ask "Analyze these files", with: ["diagram.png", "report.pdf", "notes.txt"] ``` ```ruby # Stream responses chat.ask "Tell me a story about Ruby" do |chunk| print chunk.content end ``` ```ruby # Generate images RubyLLM.paint "a sunset over mountains in watercolor style" ``` ```ruby # Create embeddings RubyLLM.embed "Ruby is elegant and expressive" ``` ```ruby # Transcribe audio to text RubyLLM.transcribe "meeting.wav" ``` ```ruby # Turn text into speech speech = RubyLLM.speak "Hello, welcome to RubyLLM!" speech.save "welcome.mp3" ``` ```ruby # Moderate content for safety RubyLLM.moderate "Check if this text is safe" ``` ```ruby # Let AI use your code class Weather < RubyLLM::Tool description "Get current weather" def execute(latitude:, longitude:) url = "https://api.open-meteo.com/v1/forecast?latitude=#{latitude}&longitude=#{longitude}¤t=temperature_2m,wind_speed_10m" JSON.parse(Faraday.get(url).body) end end chat.with_tools(Weather).ask "What's the weather in Berlin?" ``` ```ruby # Define an agent with instructions + tools class WeatherAssistant < RubyLLM::Agent model "gpt-5-nano" instructions "Be concise and always use tools for weather." tools Weather end WeatherAssistant.new.ask "What's the weather in Berlin?" ``` ```ruby # Get structured output class ProductSchema < RubyLLM::Schema string :name number :price array :features do string end end response = chat.with_schema(ProductSchema).ask "Analyze this product", with: "product.txt" ``` ## Features * **Chat:** Conversational AI with `RubyLLM.chat` * **Vision:** Analyze images and videos * **Audio:** Transcribe speech with `RubyLLM.transcribe` and generate it with `RubyLLM.speak` * **Documents:** Extract from PDFs, CSVs, JSON, any file type * **Image generation:** Create images with `RubyLLM.paint` * **Embeddings:** Generate embeddings with `RubyLLM.embed` * **Moderation:** Content safety with `RubyLLM.moderate` * **Tools:** Let AI call your Ruby methods * **Agents:** Reusable assistants with `RubyLLM::Agent` * **Structured output:** JSON schemas that just work * **Streaming:** Real-time responses with blocks * **Rails:** ActiveRecord integration with `acts_as_chat` * **Async:** Fiber-based concurrency * **Model registry:** 800+ models with capability detection and pricing * **Extended thinking:** Control, view, and persist model deliberation * **Citations:** Normalized source citations from documents, search, and grounding * **Batches:** Provider-side batch processing at half price with `RubyLLM.batch` * **Providers:** OpenAI, xAI, Anthropic, Gemini, VertexAI, Bedrock, DeepSeek, Mistral, Ollama, OpenRouter, Perplexity, GPUStack, and any OpenAI-compatible API ## Installation Add to your Gemfile: ```ruby gem 'ruby_llm' ``` Then `bundle install`. Configure your API keys: ```ruby # config/initializers/ruby_llm.rb RubyLLM.configure do |config| config.openai_api_key = ENV['OPENAI_API_KEY'] end ``` ## Rails ```bash # Install Rails Integration bin/rails generate ruby_llm:install bin/rails db:migrate bin/rails ruby_llm:load_models # v1.13+ # Add Chat UI (optional) bin/rails generate ruby_llm:chat_ui ``` ```ruby class Chat < ApplicationRecord acts_as_chat end chat = Chat.create! model: "claude-sonnet-4" chat.ask "What's in this file?", with: "report.pdf" ``` Visit `http://localhost:3000/chats` for a ready-to-use chat interface! ## Documentation [rubyllm.com](https://rubyllm.com) ## Contributing See [CONTRIBUTING.md](CONTRIBUTING.md). ## License Released under the MIT License.