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This integration is for the Respan gateway.

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Overview

RubyLLM provides a unified Ruby interface for GPT, Claude, Gemini, and more. Since Respan is OpenAI-compatible, you can route all RubyLLM requests through the Respan gateway by pointing the OpenAI base URL to Respan.

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Quickstart

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Step 1: Get a Respan API key

Create an API key in the Respan dashboard.
Create a Respan API key

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Step 2: Install RubyLLM

gem install ruby_llm
Or add it to your Gemfile: 
gem "ruby_llm"

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Step 3: Configure RubyLLM with Respan

RubyLLM.configure do |config|
  config.openai_api_key = ENV["RESPAN_API_KEY"]
  config.openai_api_base = "https://api.respan.ai/api"
end

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Step 4: Make your first request

chat = RubyLLM.chat(model: "gpt-4o-mini")
response = chat.ask("Hello, world!")
puts response.content
All requests now go through the Respan gateway and are automatically logged.

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Switch models

Since Respan supports 250+ models from all major providers, you can switch models by changing the model name. For OpenAI models, it works out of the box. For non-OpenAI models (Claude, Gemini, etc.), add provider: :openai and assume_model_exists: true to route them through the Respan gateway: 
# OpenAI models — works directly
chat = RubyLLM.chat(model: "gpt-4o")

# Non-OpenAI models — add provider and assume_model_exists
chat = RubyLLM.chat(model: "claude-3-5-haiku-20241022", provider: :openai, assume_model_exists: true)
chat = RubyLLM.chat(model: "gemini-2.0-flash", provider: :openai, assume_model_exists: true)

response = chat.ask("Tell me about artificial intelligence")
puts response.content
For non-OpenAI models, provider: :openai doesn’t mean the model is from OpenAI — it tells RubyLLM to use the OpenAI API protocol to send the request. Without it, RubyLLM would try to call the provider (e.g. Anthropic) directly, bypassing Respan. assume_model_exists: true skips RubyLLM’s local model registry check.See the full model list for all available models.

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Streaming

chat = RubyLLM.chat(model: "gpt-4o-mini")
chat.ask("Explain quantum computing") do |chunk|
  print chunk.content
end

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Multi-tenancy with contexts

Use RubyLLM contexts to isolate per-tenant configuration: 
tenant_ctx = RubyLLM.context do |config|
  config.openai_api_key = tenant.respan_api_key
  config.openai_api_base = "https://api.respan.ai/api"
end

chat = tenant_ctx.chat(model: "gpt-4o-mini")
response = chat.ask("Hello!")

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Rails integration

RubyLLM works with Rails via acts_as_chat. Set your Respan config in an initializer: 
# config/initializers/ruby_llm.rb
RubyLLM.configure do |config|
  config.openai_api_key = ENV["RESPAN_API_KEY"]
  config.openai_api_base = "https://api.respan.ai/api"
end
Then use acts_as_chat as normal — all LLM calls will be routed through Respan.

View your analytics

Access your Respan dashboard to see detailed analytics

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Next Steps

User Management

Track user behavior and patterns

Prompt Management

Manage and version your prompts