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<div align="center">
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<p>
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<b>📣 New:</b> Meet <a href="https://github.com/SWE-agent/mini-SWE-agent"><code>mini</code></a>, the 100 line AI agent that still gets 65% on SWE-bench verified!
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<b>📣 New: Meet <a href="https://github.com/SWE-agent/mini-SWE-agent"><code>mini</code></a>, the 100 line AI agent that still gets 65% on SWE-bench verified!</b>
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<br/>
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<a href="https://github.com/SWE-agent/SWE-agent"><img src="sweagent_logo_text_below.svg" alt="SWE-agent" height="120px"></a>
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<a href="https://github.com/SWE-bench/sb-cli"><img src="sbcli_logo_text_below.svg" alt="sb-cli" height="120px"></a>
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<div></div>
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<br/>
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<div>Software engineering agents, benchmarks, and models.</div>
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<div>Built and maintained by researchers from Princeton University and Stanford University.</div>
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<br>
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<a href="https://huggingface.co/SWE-bench"><img alt="HuggingFace" src="https://img.shields.io/badge/Hugging%20Face-FFD21E?logo=huggingface&logoColor=000&style=for-the-badge"></a>
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<a href="https://join.slack.com/t/swe-bench/shared_invite/zt-36pj9bu5s-o3_yXPZbaH2wVnxnss1EkQ"><img alt="Slack" src="https://img.shields.io/badge/Slack-4A154B?logo=slack&logoColor=fff&style=for-the-badge"></a>
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<a href="https://huggingface.co/SWE-bench"><img alt="HuggingFace" src="https://img.shields.io/badge/Hugging%20Face-FFD21E?logo=huggingface&logoColor=000&style=for-the-badge"></a>
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<a href="http://youtube.com/@SWE-bench"><img alt="YouTube" src="https://img.shields.io/badge/YouTube-%23FF0000.svg?&logo=YouTube&logoColor=white&style=for-the-badge"></a>
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<details>
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<summary>More information about the projects</summary>
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Main projects:
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* [SWE-agent](https://github.com/SWE-agent/SWE-agent), a system that automatically solves GitHub issues using an LM agent.
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* [mini-SWE-agent](https://github.com/SWE-agent/mini-SWE-agent), a 100 line AI agent that still gets 65% on SWE-bench verified!
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* [SWE-bench](https://github.com/SWE-bench/SWE-bench), a benchmark for evaluating AI systems on real world GitHub issues.
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* [SWE-smith](https://github.com/SWE-smith/SWE-smith), a toolkit for generating SWE training data at scale.
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<details>
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<summary>More information about the projects</summary>
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Main projects:
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* [SWE-agent](https://github.com/SWE-agent/SWE-agent), a system that automatically solves GitHub issues using an LM agent.
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* [mini-SWE-agent](https://github.com/SWE-agent/mini-SWE-agent), a 100 line AI agent that still gets 65% on SWE-bench verified!
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* [SWE-bench](https://github.com/SWE-bench/SWE-bench), a benchmark for evaluating AI systems on real world GitHub issues.
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* [SWE-smith](https://github.com/SWE-smith/SWE-smith), a toolkit for generating SWE training data at scale.
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Also check out the supporting infrastructure for working with SWE-* projects
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* [SWE-ReX](https://github.com/SWE-agent/SWE-ReX), infrastructure supporting sandboxed code execution for AI agents
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* [sb-cli](https://github.com/SWE-bench/sb-cli), a command line interface for running evaluations on the cloud.
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</details>
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</div>
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Also check out the supporting infrastructure for working with SWE-* projects
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* [SWE-ReX](https://github.com/SWE-agent/SWE-ReX), infrastructure supporting sandboxed code execution for AI agents
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* [sb-cli](https://github.com/SWE-bench/sb-cli), a command line interface for running evaluations on the cloud.
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</details>

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