It is an AI-powered tool called SWE-agent that takes a GitHub issue and attempts to automatically fix it using a language model like GPT-4 or another model of choice.
It is an AI-powered tool called SWE-agent that takes a GitHub issue and attempts to automatically fix it using a language model like GPT-4 or another model of choice. Additionally, it can be used for offensive cybersecurity tasks, such as capture-the-flag challenges, or competitive coding problems. SWE-agent operates by using configurable agent-computer interfaces (ACIs) to interact with isolated computer environments, enabling autonomous tool usage. It is built and maintained by researchers from Princeton University and Stanford University.
SWE-agent includes a mode called EnIGMA, specifically designed for solving offensive cybersecurity challenges, achieving state-of-the-art results on multiple benchmarks. EnIGMA introduces features like a debugger, server connection tools, and a summarizer to handle long outputs, which are available across all modes of SWE-agent. The tool is an academic project initiated at Princeton University by a team including John Yang, Carlos E. Jimenez, Alexander Wettig, Kilian Lieret, Shunyu Yao, Karthik Narasimhan, and Ofir Press.
The project is open-source under the MIT license, and users are encouraged to cite the work if they find it helpful. SWE-agent is actively developed, with version 0.7 currently recommended while updates for version 1.0 are underway. For more information, users can refer to the documentation, try SWE-agent in their browser, or contact the team via email.
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It is an AI-powered tool called SWE-agent that takes a GitHub issue and attempts to automatically fix it using a language model like GPT-4 or another model of choice.
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