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SWE-agent/SWE-agent

Fork: 1412 Star: 13921 (更新于 2024-12-13 07:21:54)

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 can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]

最后发布版本: v0.7.0 ( 2024-09-25 22:45:14)

官方网址 GitHub网址

swe-agent.com

Documentation  |   Discord  |   Paper

SWE-agent lets your language model of choice (e.g. GPT-4o or Claude Sonnet 3.5) autonomously use tools to:

It does so by using configurable agent-computer interfaces (ACIs) to interact with isolated computer environments.

SWE-agent is built and maintained by researchers from Princeton University and Stanford University.

🚀 Get started!

👉 Try SWE-agent in your browser: Open in GitHub Codespaces (more information)

Read our documentation to learn more:

SWE-agent for offensive cybersecurity (EnIGMA)

SWE-agent: EnIGMA is a mode for solving offensive cybersecurity (capture the flag) challenges. EnIGMA achieves state-of-the-art results on multiple cybersecurity benchmarks (see leaderboard). The EnIGMA project introduced multiple features that are available in all modes of SWE-agent, such as the debugger and server connection tools and a summarizer to handle long outputs. Please use SWE-agent 0.7 while we update EnIGMA for 1.0.

About

SWE-agent is an academic project started at Princeton University by John Yang*, Carlos E. Jimenez*, Alexander Wettig, Kilian Lieret, Shunyu Yao, Karthik Narasimhan, and Ofir Press. Contact person: John Yang, Carlos E. Jimenez, and Kilian Lieret (Email: johnby@stanford.edu, carlosej@princeton.edu, kl5675@princeton.edu).

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!

Citation

If you found this work helpful, please consider citing it using the following:

@inproceedings{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 R Narasimhan and Ofir Press},
  booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
  year={2024},
  url={https://arxiv.org/abs/2405.15793}
}

If you used the summarizer, interactive commands or the offensive cybersecurity capabilities in SWE-agent, please also consider citing:

@misc{abramovich2024enigmaenhancedinteractivegenerative,
      title={EnIGMA: Enhanced Interactive Generative Model Agent for CTF Challenges},
      author={Talor Abramovich and Meet Udeshi and Minghao Shao and Kilian Lieret and Haoran Xi and Kimberly Milner and Sofija Jancheska and John Yang and Carlos E. Jimenez and Farshad Khorrami and Prashanth Krishnamurthy and Brendan Dolan-Gavitt and Muhammad Shafique and Karthik Narasimhan and Ramesh Karri and Ofir Press},
      year={2024},
      eprint={2409.16165},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2409.16165},
}

🪪 License

MIT. Check LICENSE.

Pytest Release to dockerhub (nightly) Release to dockerhub (release) build-docs codecov pre-commit.ci status Markdown links

最近版本更新:(数据更新于 2024-10-28 13:34:39)

2024-09-25 22:45:14 v0.7.0

2024-06-20 23:21:51 v0.6.1

2024-06-05 21:16:40 v0.6.0

2024-05-29 01:14:15 v0.5.0

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, cybersecurity, developer-tools, llm, lms

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