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DSPy

Stanford NLP

Stanford framework for programming rather than prompting language models. Typed declarative modules - signatures with Predict, ChainOfThought and ReAct - compose into pipelines, which optimizers such as MIPROv2, BootstrapFewShot and GEPA then auto-tune against a metric, adjusting prompts or weights.

The project sells no commercial service alongside the framework. Verified 2026-08-13 via the stanfordnlp/dspy repository.

Openness

5 high confidence
5.0
license
MIT(OSI)
source
public
core-gated
ungated

Fully MIT with no commercial tier.

  • https://github.com/stanfordnlp/dspy recorded 2026-08-13

    MIT license, full public source for the framework, 37.2k stars and 3.2k forks; no commercial tier or enterprise directory

Adoption

4 high confidence
4.0

6,589,078 PyPI downloads in the trailing 30 days for dspy. Bands at level 4 (1M-10M) on the software and model adoption scale. A widely used prompt-programming framework.

Capability

4 high confidence
4.0

Best-in-class on prompt-optimization/compilation; thinner multi-agent coordination than CrewAI/AutoGen.

  • https://github.com/stanfordnlp/dspy recorded 2026-08-13

    declarative modules and typed signatures, optimizers and compilation, ReAct/CoT/RAG patterns; no benchmark figure published for the framework

Verified 2026-08-12