dspy

Automate creation, optimization, and deployment of AI systems with DSPy.

1|Updated Jun 9, 2026

Search Tags:#optimization #AI #programming #DSPy #language models

Ready to run

npx skills add https://github.com/lxt070409/hermes-skills --skill dspy-lxt070409

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dspy
Source: https://github.com/lxt070409/hermes-skills/tree/main/mlops/research/dspy
Command: npx skills add https://github.com/lxt070409/hermes-skills --skill dspy-lxt070409

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires dspy, openai, anthropic, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill empowers you to create and optimize modular AI systems, focusing on declarative programming, prompt engineering, and systematic optimization of language models.

Core Features & Use Cases

Declarative AI Programming: Define AI tasks with clear, maintainable signatures.
Prompt Engineering: Automate prompt optimization for better model performance.
Modular AI Pipelines: Assemble complex AI workflows with reusable components.
Use Case: Develop a multi-hop retrieval-augmented generation (RAG) system to answer complex questions by combining information retrieval with generative reasoning.

Quick Start

Load the dspy skill and start building your AI system with the following command:

import dspy

Frequently Asked Questions about dspy

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

FAQPage Schema

What is modular AI programming and how does it help with prompt optimization?▼

Modular AI programming uses declarative signatures to define language model tasks, enabling systematic prompt optimization. This approach automates prompt engineering, replacing manual tuning with maintainable, reusable components for improved model performance.

How do I build a multi-hop retrieval-augmented generation pipeline with DSPy?▼

You build a multi-hop RAG pipeline by assembling modular AI components that combine information retrieval with generative reasoning. DSPy lets you define these complex workflows declaratively using clear, maintainable signatures.

Does this DSPy skill work with both OpenAI and Anthropic language models?▼

Yes, DSPy supports various language model providers including OpenAI and Anthropic. The skill requires the openai and anthropic dependencies to enable full functionality for building and deploying modular AI pipelines.

Why should I use declarative programming instead of manual prompt engineering?▼

Declarative programming automates prompt optimization, yielding better language model performance without manual tuning. It lets you define modular AI pipelines with clear signatures, ensuring your systems remain maintainable and systematically optimized.

What's the best way to optimize AI pipelines for complex generative reasoning tasks?▼

Optimize AI pipelines by defining complex generative reasoning tasks with clear declarative signatures and assembling reusable components. DSPy automates the prompt optimization process to improve language model performance systematically across various providers.