One beautiful Ruby API for GPT, Claude, Gemini, and more.
Battle tested at 
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Using RubyLLM? Share your story! Takes 5 minutes.
Build chatbots, AI agents, RAG applications. Works with OpenAI, Anthropic, Google, AWS, local models, and any OpenAI-compatible API.
Every AI provider ships their own bloated client. Different APIs. Different response formats. Different conventions. It's exhausting.
RubyLLM gives you one beautiful API 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.
# Just ask questions chat = RubyLLM.chat chat.ask "What's the best way to learn 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"# Multiple files at once chat.ask "Analyze these files", with: ["diagram.png", "report.pdf", "notes.txt"]# Stream responses chat.ask "Tell me a story about Ruby" do |chunk| print chunk.content end# Generate images RubyLLM.paint "a sunset over mountains in watercolor style"# Create embeddings RubyLLM.embed "Ruby is elegant and expressive"# Transcribe audio to text RubyLLM.transcribe "meeting.wav"# Moderate content for safety RubyLLM.moderate "Check if this text is safe"# Let AI use your code class Weather < RubyLLM::Tool description "Get current weather" param :latitude param :longitude 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_tool(Weather).ask "What's the weather in Berlin?"# 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"- Chat: Conversational AI with
RubyLLM.chat - Vision: Analyze images and videos
- Audio: Transcribe and understand speech with
RubyLLM.transcribe - 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
- 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: 500+ models with capability detection and pricing
- Providers: OpenAI, Anthropic, Gemini, VertexAI, Bedrock, DeepSeek, Mistral, Ollama, OpenRouter, Perplexity, GPUStack, and any OpenAI-compatible API
Add to your Gemfile:
gem 'ruby_llm'Then bundle install.
Configure your API keys:
# config/initializers/ruby_llm.rb RubyLLM.configure do |config| config.openai_api_key = ENV['OPENAI_API_KEY'] end# Install Rails Integration rails generate ruby_llm:install # Add Chat UI (optional) rails generate ruby_llm:chat_uiclass 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!
See CONTRIBUTING.md.
Released under the MIT License.