dspy-ruby

You can build type-safe LLM applications in Ruby by defining Sorbet-based signatures for inputs and outputs, which automatically deserialize LLM responses into typed Ruby objects for reliable data contracts.

To get structured output from LLMs in Ruby, you use schema-driven signatures and structured prompts that translate model responses into reliable, typed Ruby objects instead of raw text.

Yes, you can use Ruby to build LLM workflows across multiple providers by configuring LM adapters that support OpenAI, Claude, and Gemini, enabling per-task model selection within your pipelines.

Before configuring LLM adapters in Ruby, you need a Ruby runtime with Sorbet-based types installed, plus provider gems like RubyLLM to translate LLM outputs into typed objects.

Using Sorbet signatures for LLM-driven workflows in Ruby ensures consistent data contracts and strong type safety, making it easier to test modular components like classifiers and agents reliably.

When using Ruby for production-grade LLM pipelines, you are limited to models supported by configured LM adapters, and you must maintain Sorbet type definitions to ensure structured prompt reliability.