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https://github.com/princeton-nlp/SWE-agent

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.47% of bugs in the SWE-bench evaluation set and takes just 1 minute to run.
https://github.com/princeton-nlp/SWE-agent

agent agent-based-model ai developer-tools llm lms

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SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.47% of bugs in the SWE-bench evaluation set and takes just 1 minute to run.

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README

        



swe-agent.com


Website & Demo  |  
Documentation  |  
Discord  |  
Preprint

**SWE-agent turns LMs (e.g. GPT-4) into software engineering agents that can resolve issues in real GitHub repositories.**

On [SWE-bench](https://github.com/princeton-nlp/SWE-bench), SWE-agent resolves 12.47% 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](https://arxiv.org/abs/2405.15793)!

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

![My Movie 3](https://github.com/princeton-nlp/SWE-agent/assets/13602468/fa201621-ec31-4644-b658-c1d0feb92253)

You can use SWE-agent either through a web interface (shown above) or through the command line.

## 🚀 Get started!

👉 Try SWE-agent in your browser: [![Open in GitHub Codespaces](https://img.shields.io/badge/Open_in_GitHub_Codespaces-gray?logo=github)](https://codespaces.new/princeton-nlp/SWE-agent) ([more information](https://princeton-nlp.github.io/SWE-agent/installation/codespaces/))

Read our [documentation][docs] to learn more:

* [Installation](https://princeton-nlp.github.io/SWE-agent/installation/)
* [Command line usage](https://princeton-nlp.github.io/SWE-agent/usage/cl_tutorial/)
* [Using the web UI](https://princeton-nlp.github.io/SWE-agent/usage/web_ui/)
* [Benchmarking on SWE-bench](https://princeton-nlp.github.io/SWE-agent/usage/benchmarking/)
* [Frequently Asked Questions](https://princeton-nlp.github.io/SWE-agent/faq/)



[docs]: https://princeton-nlp.github.io/SWE-agent/

## 💫 Contributions
- If you'd like to ask questions, learn about upcoming features, and participate in future development, join our [Discord community](https://discord.gg/AVEFbBn2rH)!
- If you'd like to contribute to the codebase, we welcome [issues](https://github.com/princeton-nlp/SWE-agent/issues) and [pull requests](https://github.com/princeton-nlp/SWE-agent/pulls)!

Contact person: [John Yang](https://john-b-yang.github.io/) and [Carlos E. Jimenez](http://www.carlosejimenez.com/) (Email: [email protected], [email protected]).

## 📝 Citation
If you found this work helpful, please consider citing it using the following:
```
@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},
eprint={2405.15793},
archivePrefix={arXiv},
primaryClass={cs.SE}
}
```

## 🪪 License
MIT. Check `LICENSE`.

[![Pytest](https://github.com/princeton-nlp/SWE-agent/actions/workflows/pytest.yaml/badge.svg)](https://github.com/princeton-nlp/SWE-agent/actions/workflows/pytest.yaml)
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