dspy-ruby

Files (9)

• SKILL.md
• config-template.rb · assets/
• module-template.rb · assets/
• signature-template.rb · assets/
• core-concepts.md · references/
• observability.md · references/
• optimization.md · references/
• providers.md · references/
• toolsets.md · references/

SKILL.md (first lines)

# DSPy.rb

> Build LLM apps like you build software. Type-safe, modular, testable.

DSPy.rb brings software engineering best practices to LLM development. Instead of tweaking prompts, define what you want with Ruby types and let DSPy handle the rest.

## Overview

DSPy.rb is a Ruby framework for building language model applications with programmatic prompts. It provides:

- **Type-safe signatures** — Define inputs/outputs with Sorbet types
- **Modular components** — Compose and reuse LLM logic
- **Automatic optimization** — Use data to improve prompts, not guesswork
- **Production-ready** — Built-in observability, testing, and error handling

## Core Concepts

### 1. Signatures

Define interfaces between your app and LLMs using Ruby types:

```ruby
class EmailClassifier < DSPy::Signature
  description "Classify customer support emails by category and priority"

  class Priority < T::Enum
    enums do
      Low = new('low')
      Medium = new('medium')
      High = new('high')
      Urgent = new('urgent')
    end
  end

  input do
    const :email_content, String
    const :sender, String
  end

  output do
    const :category, String
    const :priority, Priority  # Type-safe enum with defined values
    const :confidence, Float
  end
end
```

### 2. Modules

Build complex workflows from simple building blocks:

- **Predict** — Basic LLM calls with signatures
- **ChainOfThought** — Step-by-step reasoning
- **ReAct** — Tool-using agents
- **CodeAct** — Dynamic code generation agents (install the `dspy-code_act` gem)

### 3. Tools & Toolsets

Create type-safe tools for agents with comprehensive Sorbet support:

```ruby
# Enum-based tool with automatic type conversion
class CalculatorTool < DSPy::Tools::Base
  tool_name 'calculator'
  tool_description 'Performs arithmetic operations with type-safe enum inputs'

  class Operation < T::Enum
    enums do
      Add = new('add')
      Subtract = new('subtract')
      Multiply = new('multiply')
      Divide = new('divide')
    end
  end

  sig { params(operation: Operation, num1: Float, num2: Float).returns(T.any(Float, String)) }
  def call(operation:, num1:, num2:)
    case operation
    when Operation::Add then num1 + num2
    when Operation::Subtract then num1 - num2
    when Operation::Multiply then num1 * num2
    when Operation::Divide
      return "Error: Division by zero" if num2 == 0
      num1 / num2
    end
  end
end

# Multi-tool toolset with rich types
class DataToolset < DSPy::Tools::Toolset
  toolset_name "data_processing"

  class Format < T::Enum
    enums do
      JSON = new('json')
      CSV = new('csv')
      XML = new('xml')
    end
  end

  tool :convert, description: "Convert data between formats"
  tool :validate, description: "Validate data structure"

  sig { params(data: String, from: Format, to: Format).returns(String) }
  def convert(data:, from:, to:)
    "Converted from #{from.serialize} to #{to.serialize}"
  end

  sig { params(data: String, format: Format).returns(T::Hash[String, T.any(String, Integer, T::Boolean)]) }
  def validate(data:, format:)
    { valid: true, format: format.serialize, row_count: 42, message: "Data validation passed" }
  end
end
```

### 4. Type System & Discriminators

DSPy.rb uses sophisticated type discrimination for complex data structures:

From sammyjoyce/pi-compound-engineering, MIT.

More from sammyjoyce/pi-compound-engineering