Which DSPy versions are compatible with this skill?

This skill is specifically designed for compatibility with DSPy version 3.1.2 and later.

What is MIPROv2 in the context of DSPy?

MIPROv2 is a state-of-the-art optimizer within the DSPy framework that jointly optimizes both the instructions and the few-shot examples using Bayesian search methods.

How much training data do I need to use this skill effectively?

For best results, it is recommended to have at least 200 training examples. This allows the optimizer to accurately evaluate and search for the best program configuration.

Can I optimize only the instructions without using demos?

Yes, this skill supports an 'Instruction-Only Mode' by setting the bootstrap and labeled demo parameters to zero, focusing purely on prompt text optimization.

How long does a typical optimization run take?

Optimization time varies by the selected preset: 'light' is for quick iterations, while 'heavy' can take several hours depending on your dataset size and trial count.

DSPy MIPROv2 Optimizer

Name: DSPy MIPROv2 Optimizer
Author: OmidZamani

byOmidZamani

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データサイエンスとML

Optimizes DSPy programs by jointly tuning instructions and few-shot demonstrations using Bayesian search for maximum model performance.

The DSPy MIPROv2 Optimizer skill provides a sophisticated toolset for developers looking to achieve state-of-the-art performance in their LLM applications. By leveraging a three-stage process involving bootstrapping, instruction proposal, and Bayesian search, it automates the complex task of refining both the prompts and the examples provided to the model. This skill is specifically designed for high-stakes environments where substantial training data is available and peak accuracy is required, making it the premier choice for production-grade RAG pipelines and advanced agentic workflows.

主な機能

01Includes an instruction-only mode for refining zero-shot capabilities.

02Provides 'light', 'medium', and 'heavy' presets to balance speed and performance.

0331 GitHub stars

04Supports multi-threaded execution to handle large-scale optimization runs.

05Employs Bayesian Optimization to efficiently search the prompt-space.

06Jointly optimizes instructions and few-shot demonstrations for maximum synergy.

ユースケース

01Tuning complex agentic systems that require precise instruction following.

02Scaling RAG pipeline accuracy for production environments with 200+ examples.

03Automated prompt engineering for large datasets to replace manual trial-and-error.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add omidzamani/dspy-skills dspy-miprov2-optimizer

For use in Claude.ai and ChatGPT

Download Skill