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dspy-ruby

Build type-safe DSPy.rb workflows with signatures, modules, and provider configurations.

Updated Jan 16, 2026
Search Tags:#LLM#modules#Ruby#type-safe#providers#signatures#dspy.rb
One-click install
npx skills add https://github.com/8b-is/8b-is-mp --skill dspy-ruby-8b-is
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dspy-ruby
Source: https://github.com/8b-is/8b-is-mp/tree/main/plugins/compound-engineering/skills/dspy-ruby
Command: npx skills add https://github.com/8b-is/8b-is-mp --skill dspy-ruby-8b-is

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps Ruby developers build robust, type-safe LLM workflows by using DSPy.rb's signatures and modules, making AI capabilities more predictable and maintainable.

Core Features & Use Cases

  • Type-Safe Signatures: Define strict input/output contracts for LLM tasks with runtime validation.
  • Composable Modules: Build reusable pipelines that chain predictors and tools for complex tasks.
  • Provider Configuration & Testing: Configure multiple providers and write tests to mock LLM responses.
  • Use Case: Create a small Ruby service that classifies customer inquiries and routes them to teams based on predicted category.

Quick Start

Install DSPy.rb and a provider gem, define a signature and a module, configure a provider, then run a simple forward call to see a result.

Frequently Asked Questions about dspy-ruby

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build type-safe LLM workflows in Ruby?▼

Build type-safe LLM workflows in Ruby by defining strict input and output contracts using DSPy.rb signatures, which provide runtime validation for predictable and maintainable AI capabilities.

How do I configure multiple LLM providers in a Ruby application?▼

Configure multiple LLM providers in a Ruby application by installing provider gems like dspy-openai or dspy-anthropic alongside the DSPy.rb gem, allowing you to switch between models and write tests to mock responses.

What is the best way to chain LLM predictors and tools for complex Ruby tasks?▼

The best way to chain LLM predictors and tools for complex Ruby tasks is using DSPy.rb's composable modules to build reusable pipelines that sequence multiple steps together.

Do I need specific Ruby gems to create LLM agents with tools?▼

Yes, you need a Ruby environment with the DSPy.rb gem installed, plus provider gems like dspy-openai or dspy-anthropic, to create agents with tools and execute forward calls.

How do I test LLM responses in Ruby without making live API calls?▼

Test LLM responses in Ruby without live API calls by using DSPy.rb's provider configuration and testing patterns to mock LLM responses, ensuring your workflows remain predictable during development.

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