Open SourceAdvanced
DSPy
DSPy is a framework for programming language models rather than prompting them, by composing modular pipelines and automatically optimizing prompts and weights. Developed at Stanford, it replaces brittle prompt engineering with reproducible, testable programs that adapt across different models and tasks.
Overview
"DSPy" is a "Open Source" resource curated by AI Resource Hub, filed under the Frameworks category and suited to Advanced-level learners. It is provided by Stanford NLP, was last updated on 2026-06-26, and holds an editorial score of 4.6/5 from our team. Click "Visit Resource" on the right to open the original page.
Tags
DSPyPrompt OptimizationFrameworkLLM
Key Features
- ▹Program LLMs instead of hand-writing prompts
- ▹Automatic prompt optimization
- ▹Composable, testable modules
Pros
- +Systematic, testable prompting
- +Optimizes prompts for you
- +Turns prompts into compiled, optimizable programs
Cons
- −Different mental model than manual prompting
- −Requires a solid eval set to optimize against
- −Abstraction takes time to learn
FAQ
Visit Resource →
Details
- Pricing
- Free and open source
- Author
- Stanford NLP
- Editorial score
- ★ 4.6 / 5
- Last updated
- Jun 26, 2026