DSPy
Framework for programming, not prompting, language models with automatic prompt optimization
DSPy is an open-source framework from Stanford NLP for building LLM-powered systems through composable Python code rather than manual prompt engineering. It provides three core abstractions: signatures (input/output specs), modules (reusable components), and optimizers that automatically synthesize effective prompts and few-shot examples. DSPy can also fine-tune model weights. It supports building classifiers, RAG pipelines, agent loops, and other LLM applications while making them more reliable and maintainable than hand-crafted prompts.
Pricing: Free
DSPy Alternatives
Explore 31 products in the Frameworks & Stacks category. View all DSPy alternatives.
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