dspy-skills-marketplace

DSPy Skills Collection

A comprehensive collection of AI-powered skills for programming and optimizing LLM applications using the DSPy framework. These skills enable you to move from manual prompt engineering to systematic, programmatic LLM development.

🎯 What is DSPy?

DSPy is a declarative framework that lets you program language models instead of prompting them. It provides:

• Modular architecture - Compose LLM programs from reusable components
• Automatic optimization - Tune prompts, examples, and weights algorithmically
• Self-improving pipelines - Systems that get better with data

📚 Skills Index

Optimizers

Skill	Description	Best For
dspy-bootstrap-fewshot	Auto-generate few-shot examples	Quick optimization with ~10 examples
dspy-miprov2-optimizer	Bayesian instruction+demo optimization	200+ examples, comprehensive tuning
dspy-gepa-reflective	LLM reflection on execution traces	Agentic systems, complex workflows
dspy-finetune-bootstrap	Fine-tune model weights	Production deployment, efficiency

Pipelines & Components

Skill	Description	Best For
dspy-rag-pipeline	RAG with ColBERTv2 retrieval	Knowledge-grounded generation
dspy-signature-designer	Design type-safe I/O specs	Clean, validated outputs
dspy-evaluation-suite	Metrics and evaluation	Quality assessment
dspy-haystack-integration	DSPy + Haystack pipelines	Existing Haystack projects

📖 Documentation

• DSPy Framework Guide - Complete framework reference

🚀 Installation

pip install dspy-ai

Optional Dependencies

# For ColBERTv2 retrieval
pip install colbert-ai

# For Haystack integration
pip install haystack-ai

# For fine-tuning
pip install transformers datasets

💡 Quick Start

import dspy

# Configure LM
dspy.configure(lm=dspy.LM("openai/gpt-4o-mini"))

# Create a simple classifier
classify = dspy.Predict("text -> sentiment: bool")
result = classify(text="I love this product!")
print(result.sentiment)  # True

📁 Examples

See examples/code-snippets.py for production-ready code.

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Built for the SkillsMP marketplace