MIPROv2

Overview

MIPROv2 is one of the most advanced optimizers available in DSPy for automatic prompt optimization. It generates instructions and few-shot examples in each step and uses Bayesian Optimization to effectively search over the space of generation instructions/demonstrations across your modules.

How It Works

MIPROv2 produces optimal instructions for the prompt and can also optimize the set of few-shot demonstrations. The optimization process involves:

1. Generating multiple instruction candidates
2. Creating few-shot example variations
3. Using Bayesian Optimization to search the instruction/demonstration space
4. Evaluating performance against metrics
5. Iteratively improving prompts based on results

Key Features

• Automatic Instruction Generation: Harnesses the idea generation power of LLMs to generate their own prompts
• Few-Shot Optimization: Optimizes both the instructions and the example demonstrations
• Bayesian Search: Uses sophisticated search algorithms to find optimal parameter combinations
• Multi-Module Support: Can optimize across multiple components in complex pipelines

Integration

MIPROv2 is integrated into the DSPy framework and works seamlessly with DSPy signatures and modules. It separates program flow from parameters (prompts and weights) and automatically adjusts these parameters based on desired outcomes.

Use Cases

• RAG pipeline optimization
• Complex multi-step LLM applications
• Question answering systems
• Information extraction pipelines
• Any application requiring systematic prompt optimization

Pricing

Free and open-source as part of the DSPy framework.