dspy — проект с открытым исходным кодом из категории «ИИ-агенты» от stanfordnlp (stanfordnlp/dspy на GitHub). У него 38 554 звезды на GitHub и 3 406 форков, он распространяется по лицензии MIT и последний раз обновлялся на GitHub 7 октября 2026.
Program language models with code and compilers — not fragile prompts.
Choose one concrete task — narrow beats ambitious for a first run.
Fetch the source and skim the docs folder.
Set the environment variables or keys the project needs.
Execute the example workflow and watch what happens.
LM behavior as code with signatures.
Compile and tune programs with data.
Not tied to a single provider.
Build complex pipelines from simple parts.
Measure what your tuning actually did.
From Stanford NLP, with papers behind it.
Download the source and move into the project folder.
git clone https://github.com/stanfordnlp/dspy.git
cd dspyIsolate dependencies, then install requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtLaunch using the entry point shown in the README.
python -m dspy # check README for the exact commandIt is an open-source project at stanfordnlp/dspy with 3406 forks. Check the contributors tab and recent commits to judge how active maintenance is.
Yes — it's MIT licensed: free to use, modify, and ship commercially. Just keep the license notice in copies.
Some — DSPy is a programming framework with optimizers, aimed at engineers comfortable with data-driven iteration.
Many major providers; programs are model-agnostic by design. Check the docs for the current list.
Clone the repo and follow the README quickstart — the docs at https://dspy.ai walk through setup.
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Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.