dspy-ruby

To build type-safe Ruby LLM applications without brittle prompt engineering, use composable signatures and modules to define clear input and output contracts. This approach replaces manual prompting with testable, maintainable, and type-safe logic.

Yes, you can configure multiple providers including OpenAI, Anthropic, Gemini, Ollama, and OpenRouter with Ruby LLM modules. The framework supports provider switching and multimodal inputs for image-based tasks.

You can test and optimize LLM pipelines in a Ruby application using RSpec validation for testing, VCR-based determinism for recording interactions, and MIPROv2 tuning for automatic prompt and module optimization.

The best way to add observability and tracing to Ruby LLM agents is by integrating OpenTelemetry and Langfuse tracing. This records reasoning steps and monitors classification pipelines for stateful workflows.

You can chain predictors and routing logic for complex AI workflows in Ruby by using composable modules and agents. This approach supports tool use, retries, and stateful workflows for tasks like email triage.

Yes, Sorbet-style type contracts are required for Ruby LLM signatures to ensure type safety. Reusable templates for signatures, modules, and configuration depend on these contracts to maintain reliable application structure.