dspy

Name: dspy
Availability: InStock
Author: thisismynewfmail-ui

Build AI systems with declarative DSPy signatures and automatic prompt optimization.

Updated Apr 12, 2026

Search Tags:#prompt optimization #rag #agents #declarative programming #dspy #lm programming

Ready to run

npx skills add https://github.com/thisismynewfmail-ui/Monika-agent --skill dspy-thisismynewfmail-ui

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Many developers struggle with manual prompt engineering and assembling multi‑step AI pipelines, leading to fragile and hard‑to‑maintain systems.

Core Features & Use Cases

Declarative signatures let you define inputs and outputs without writing prompts.
Automatic prompt optimization with built‑in optimizers such as BootstrapFewShot and MIPRO.
Modular pipelines for RAG, agents, and classification that can be composed and reused.
Multi‑provider support for OpenAI, Anthropic, Ollama and others.

Quick Start

Ask the dspy skill to create a simple question‑answering module for the Claude model.

Frequently Asked Questions about dspy

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

FAQPage Schema

How do I stop manually writing prompts for multi-step AI pipelines?▼

Declarative LM programming replaces fragile manual prompt engineering by using declarative signatures to define inputs and outputs, enabling you to build modular AI pipelines without writing prompts.

What is the best way to automate prompt optimization for language models?▼

Automatic prompt optimization is handled by built-in optimizers like BootstrapFewShot and MIPRO, which systematically refine your LM pipelines to improve performance without manual tuning.

Does declarative LM programming work with Anthropic and OpenAI models?▼

Declarative LM programming supports multiple providers including OpenAI, Anthropic, and Ollama, requiring the DSPy package and compatible provider extensions installed in your Python environment.

Can I build RAG pipelines and agents without manually engineering prompts?▼

You can build modular pipelines for RAG, agents, and classification using declarative signatures, which compose and reuse components across different language model providers seamlessly.

Do I need to install specific packages to use declarative LM programming?▼

You need the DSPy package and compatible LM provider extensions installed in your Python environment to apply declarative programming to RAG pipelines, agent creation, and prompt optimization.