dspy

Compile declarative language model calls into self-improving AI pipelines.

Updated Jun 15, 2026

Search Tags:#prompt engineering #AI workflows #declarative programming #modular AI #automated optimization

Ready to run

npx skills add https://github.com/Piaoxuemoli/qoobeeHermes --skill dspy-piaoxuemoli

💬 Prompt for ChatGPT / Claude Chat▼

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

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 simplifies the creation and optimization of AI workflows, allowing users to build complex systems with ease and efficiency.

Core Features & Use Cases

Declarative Programming: Write AI workflows in a natural, declarative style, reducing the need for manual prompt engineering.
Automatic Optimization: Use data-driven methods to optimize prompts and improve model outputs systematically.
Use Case: Imagine you need to build a sophisticated AI system for question answering. With DSPy, you can define the structure of your AI task and let the system automatically optimize the prompts and model outputs for better results.

Quick Start

To get started with DSPy, simply install the package using pip: pip install dspy. You can then define your AI tasks using the provided Signatures and Modules, and let the system handle the rest.

Frequently Asked Questions about dspy

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

FAQPage Schema

How do I automate prompt engineering for complex AI workflows?▼

Declarative AI workflows compile language model calls into self-improving pipelines to automate prompt optimization. This approach uses data-driven methods to systematically improve model outputs, reducing the need for manual prompt engineering.

What is declarative programming for modular AI design?▼

Declarative programming for modular AI design defines task structures using Signatures and Modules instead of manual prompts. The system automatically compiles and optimizes these language model calls into self-improving pipelines for better results.

Do I need OpenAI and Anthropic libraries to build AI pipelines with DSPy?▼

Yes, building automated optimization pipelines requires the dspy package alongside openai and anthropic libraries. These dependencies provide the necessary components for compiling and executing declarative language model calls within your workflows.

What is the best way to optimize language model outputs systematically?▼

The best way to optimize language model outputs systematically is by compiling declarative calls into self-improving pipelines. This data-driven method automatically optimizes prompts to improve model outputs for sophisticated AI tasks like question answering.

How do I get started building declarative AI workflows?▼

To get started building declarative AI workflows, install the dspy package via pip and define your tasks using the provided Signatures and Modules. The system then automatically handles the compilation and optimization of your model calls.