Prompt engineering

DSPy

stanfordnlp/dspy

A framework for programming and optimizing language-model pipelines instead of hand-tuning prompts.

★ 38,6KSterren
⑂ 3,4KForks
361Openstaande problemen
PythonTaal
MITLicentie
Q84Redactionele score

Overzicht

DSPy represents LLM applications as modular programs with typed signatures and predictors, then provides optimizers that can tune prompts or parameters against examples and metrics. It can be used for extraction, classification, RAG, and agent workflows.

Belangrijkste functies

  • Composable LLM modules
  • Typed signatures and predictors
  • Prompt and parameter optimizers
  • Evaluation-driven iteration

Vereisten, installatie en snel aan de slag

Install the Python package with `pip install dspy`; configure a supported language-model provider as described in the docs.

Gebruik

Define task signatures and modules, supply a dataset and metric, then evaluate or optimize the pipeline for the target task.

Modelcompatibiliteit en gebruiksscenario's

Works with multiple providers and local model backends; consult current docs for the integration matrix.

Licentie- en risiconotities

The repository declares the MIT License. Connected model providers and model weights are licensed separately.

Release en onderhoud

See the official repository for current releases and changes.