DSPy is a framework for programming language models, allowing for fast iteration on building modular AI systems and optimizing prompts and weights. Instead of using prompts, you write Python code and use DSPy to teach your LM to deliver high-quality outputs.

Key Features:

• Write compositional Python code instead of prompts
• Build modular and optimizable AI systems
• Optimize prompts and weights for LM programs

Use Cases:

• Building simple classifiers
• Creating sophisticated RAG pipelines
• Developing Agent loops

Benefits:

• Fast iteration on AI system design
• Decoupling AI system design from specific LM or prompting strategies
• Community support and contributions via GitHub and Discord