princeton-nlp/SWE-agent
Fork: 1070 Star: 10869 (更新于 2024-05-27 21:29:34)
license: MIT
Language: Python .
SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.29% of bugs in the SWE-bench evaluation set and takes just 1.5 minutes to run.
最后发布版本: v0.4.0 ( 2024-05-09 22:58:44)
Website & Demo | Documentation | Discord | Preprint
👋 Overview
SWE-agent turns LMs (e.g. GPT-4) into software engineering agents that can fix bugs and issues in real GitHub repositories.
On SWE-bench, SWE-agent resolves 12.29% of issues, achieving the state-of-the-art performance on the full test set.
We accomplish our results by designing simple LM-centric commands and feedback formats to make it easier for the LM to browse the repository, view, edit and execute code files. We call this an 🤖 Agent-Computer Interface (ACI). Read more about it in our paper!
SWE-agent is built and maintained by researchers from Princeton University.
If you found this work helpful, please consider using the following citation:
@misc{yang2024sweagent,
title={SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering},
author={John Yang and Carlos E. Jimenez and Alexander Wettig and Kilian Lieret and Shunyu Yao and Karthik Narasimhan and Ofir Press},
year={2024},
}
✨ Use SWE-agent as a dev tool
We provide a command line tool and a graphical web interface:
🚀 Get started!
All information is provided in our documentation:
and many more topics.
💫 Contributions
- If you'd like to ask questions, learn about upcoming features, and participate in future development, join our Discord community!
- If you'd like to contribute to the codebase, we welcome issues and pull requests!
- If you'd like to see a post or tutorial about some topic, please let us know via an issue.
Contact person: John Yang and Carlos E. Jimenez (Email: {jy1682, carlosej}@princeton.edu).
🪪 License
MIT. Check LICENSE
.
最近版本更新:(数据更新于 2024-05-27 21:29:09)
2024-05-09 22:58:44 v0.4.0
2024-05-02 23:47:48 v0.3.0
2024-04-16 03:01:34 v0.2.0
主题(topics):
agent, agent-based-model, ai, developer-tools, llm, lms
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