dspy

What problem does it solve?

This skill eliminates manual prompt engineering and trial-and-error optimization, allowing you to declaratively program and automatically improve complex AI systems like RAGs and agents. It saves significant development time and systematically improves model reliability and performance.

Core Features & Use Cases

• Declarative LM Programming: Define AI tasks with clear input/output signatures, letting DSPy automatically generate and optimize prompts.
• Automatic Prompt Optimization: Systematically improve model outputs using data-driven optimizers like BootstrapFewShot and MIPRO, ensuring higher accuracy and consistency.
• Modular AI Pipelines: Build complex multi-stage RAG systems and agents with reusable, optimizable components, simplifying development and maintenance.
• Use Case: Develop a robust question-answering system that automatically learns from examples to generate more accurate and reliable answers, without manual prompt tuning or complex prompt engineering.

Quick Start

Help me build a question-answering system using DSPy. I want to define a signature for question -> answer.