| commit | fab87ffd264033f66c93cc6565f05db7716b419c | [log] [tgz] |
|---|---|---|
| author | elijahbenizzy <elijah_ben_izzy@alumni.brown.edu> | Tue Feb 13 14:50:22 2024 -0800 |
| committer | elijahbenizzy <elijah_ben_izzy@alumni.brown.edu> | Tue Feb 13 14:50:22 2024 -0800 |
| tree | 0fbddf91fa6546bcd4a3ca7dc7e4e41da100612f | |
| parent | ae6cf8e1f5cf86815b3c1af8d6708c28017f1e6d [diff] |
Documentation Updates https://github.com/DAGWorks-Inc/burr/issues/5 A variety of miscelleneous fixes for docs -- clarity + rendering
Burr is a state machine for data/AI projects. You can (and should!) use it for anything where managing state can be hard. Hint: managing state is always hard!
Link to documentation.
Burr can be used for a variety of applications. Burr can build a state machine to orchestrate, express, and track:
And a lot more!
Using hooks and other integrations you can (a) integrate with any of your favorite vendors (LLM observability, storage, etc...), and (b) build custom actions that delegate to your favorite libraries.
Bur will not tell you how to build your models, how to query APIs, or how to manage your data. It will help you tie all these together in a way that scales with your needs and makes following the logic of your system easy. Burr comes out of the box with a host of integrations including tooling to build a UI in streamlit and watch your state machine execute.
Burr is named after Aaron Burr, founding father, third VP of the United States, and murderer/arch-nemesis of Alexander Hamilton. We imagine a world in which Burr and Hamilton lived in harmony and saw through their differences. We originally built Burr as a harness to handle state between executions of Hamilton DAGs, but realized that it has a wide array of applications and decided to release it.
To get started, install from pypi, using your favorite package manager:
pip install burr
Next, see the documentation for getting started, and follow the example. Then read through some of the concepts and write your own application!
