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dspy

Build complex AI systems with declarative DSPy signatures.

6|Updated Apr 26, 2026
Search Tags:#optimization#rag#agents#modularity#declarative#dspy#ai-pipelines
One-click install
npx skills add https://github.com/Strategic-Automation/arachne --skill dspy-strategic-automation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dspy
Source: https://github.com/Strategic-Automation/arachne/tree/main/src/arachne/skills/default/mlops/research/dspy
Command: npx skills add https://github.com/Strategic-Automation/arachne --skill dspy-strategic-automation

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Declarative DSPy enables developers to design, compose, and optimize AI workflows as modular pipelines rather than brittle prompts, reducing engineering toil and improving reliability.

Core Features & Use Cases

  • Declarative Signatures and modular pipelines for complex AI tasks
  • RAG systems and agent workflows with optional optimizers
  • Self-healing and dynamic graph weaving for robust production deployments

Quick Start

Create a DSPy module that demonstrates declarative signatures to build a RAG-enabled QA workflow.

Frequently Asked Questions about dspy

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

FAQPage Schema
What are declarative signatures in DSPy used for?▼

Declarative DSPy signatures are used to design and compose modular AI pipelines, replacing brittle prompts to reduce engineering toil and improve system reliability.

How do I build a RAG workflow with DSPy?▼

Build a RAG workflow using DSPy by defining declarative signatures and modular pipelines, optionally applying optimizers to enhance the retrieval-augmented generation system.

Can I use DSPy for both research and production agent workflows?▼

Yes, DSPy supports modular agent workflows across both research and production contexts, utilizing dynamic graph weaving and self-healing mechanisms for robust deployments.

Does DSPy work with OpenAI and Anthropic models?▼

Yes, DSPy integrates with OpenAI and Anthropic dependencies, enabling you to build and optimize complex AI pipelines across different model providers.

What is the best way to optimize AI pipelines without manual prompt engineering?▼

The best way to optimize AI pipelines without manual prompt engineering is using DSPy's declarative signatures and optional optimizers to automate and refine modular task workflows.

Do I need a specific file structure to create a DSPy module?▼

Yes, you need a SKILL.md file containing YAML frontmatter with name and description, a Markdown body for activation instructions, and optional resource directories for extended behavior.

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