One beautiful Ruby API for GPT, Claude, Gemini, and more.

Battle tested at — Your AI coworker

Note

Using RubyLLM? Share your story! Takes 5 minutes.

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Build chatbots, AI agents, RAG applications. Works with OpenAI, xAI, Anthropic, Google, AWS, local models, and any OpenAI-compatible API.

From zero to AI chat app in under two minutes

demo.mp4

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 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.

Show me the code

# Just ask questionschat=RubyLLM.chatchat.ask"What's the best way to learn Ruby?"

# Analyze any file typechat.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 oncechat.ask"Analyze these files",with: ["diagram.png","report.pdf","notes.txt"]

# Stream responseschat.ask"Tell me a story about Ruby"do |chunk|
printchunk.contentend

# Generate imagesRubyLLM.paint"a sunset over mountains in watercolor style"

# Create embeddingsRubyLLM.embed"Ruby is elegant and expressive"

# Transcribe audio to textRubyLLM.transcribe"meeting.wav"

# Moderate content for safetyRubyLLM.moderate"Check if this text is safe"

# Let AI use your codeclassWeather < RubyLLM::Tooldescription"Get current weather"param:latitudeparam:longitudedefexecute(latitude:,longitude:)url="https://api.open-meteo.com/v1/forecast?latitude=#{latitude}&longitude=#{longitude}&current=temperature_2m,wind_speed_10m"JSON.parse(Faraday.get(url).body)endendchat.with_tool(Weather).ask"What's the weather in Berlin?"

# Define an agent with instructions + toolsclassWeatherAssistant < RubyLLM::Agentmodel"gpt-5-nano"instructions"Be concise and always use tools for weather."toolsWeatherendWeatherAssistant.new.ask"What's the weather in Berlin?"

# Get structured outputclassProductSchema < RubyLLM::Schemastring:namenumber:pricearray:featuresdostringendendresponse=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 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
• 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
• Providers: OpenAI, xAI, Anthropic, Gemini, VertexAI, Bedrock, DeepSeek, Mistral, Ollama, OpenRouter, Perplexity, GPUStack, and any OpenAI-compatible API

Installation

Add to your Gemfile:

gem'ruby_llm'

Then bundle install.

Configure your API keys:

# config/initializers/ruby_llm.rbRubyLLM.configuredo |config|
config.openai_api_key=ENV['OPENAI_API_KEY']end

Rails

# 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

classChat < ApplicationRecordacts_as_chatendchat=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

Contributing

See CONTRIBUTING.md.

License

Released under the MIT License.