SWE-agent

Description

SWE-agent empowers language models to autonomously interact with tools to address issues in real GitHub repositories, identify cybersecurity vulnerabilities, and execute custom tasks. It's designed for research, offering a configurable and fully documented framework. The project is maintained by researchers from Princeton and Stanford Universities.

SWE-agent's development has shifted towards mini-SWE-agent, which offers similar performance with increased simplicity and flexibility. Mini-SWE-agent has become the primary focus, with SWE-agent now in maintenance mode. The FAQ provides more details on the differences between the two versions. SWE-agent has achieved state-of-the-art results on the SWE-bench benchmark among open-source projects.

Key features include free-flowing and generalizable capabilities, allowing language models maximal agency. It is governed by a single YAML file, making it configurable and hackable by design. Recent updates include multimodal support for processing images from GitHub issues and achieving SOTA on SWE-bench with open-weights models. The project also provides user guides and background information to help users understand the features and goals of the agent.

SWE-agent is suitable for researchers, developers, and cybersecurity professionals interested in leveraging AI for software engineering tasks. It provides a platform for experimenting with language models and automating complex processes. The project's focus on research and open-source principles makes it a valuable tool for advancing the field of AI-driven software development.

SWE-agent's Core Features

• Autonomous tool usage

• GitHub issue resolution

• Cybersecurity vulnerability detection

• Custom task execution

• Configurable via YAML file

• Open-source

• State-of-the-art performance on SWE-bench

• Multimodal support for image processing

• Designed for research

• Maintained by researchers from Princeton and Stanford

How to use SWE-agent?

1. 1

   Explore: Review the documentation and user guides.

2. 2

   Install: Follow the installation instructions.

3. 3

   Configure: Set up the agent using the YAML configuration file.

4. 4

   Use: Run the agent to solve GitHub issues or perform custom tasks.

5. 5

   Experiment: Explore different language models and tools.

6. 6

   Optimize: Fine-tune the agent for specific tasks.

SWE-agent's Use Cases

• GitHub Issue Resolution
• Cybersecurity Auditing
• Automated Code Review
• Software Testing
• Code Generation
• Software Maintenance

FAQ from SWE-agent

• What is SWE-agent?

  SWE-agent is an AI agent that uses language models to autonomously fix issues in GitHub repositories, find cybersecurity vulnerabilities, and perform custom tasks.

• Who developed SWE-agent?

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

• What is mini-SWE-agent?

  Mini-SWE-agent is a simpler and more flexible version of SWE-agent that has superseded it.

• What language models does SWE-agent support?

  SWE-agent supports language models like GPT-4o and Claude Sonnet 4.

• Where can I find the documentation?

  The documentation is available on the SWE-agent website.

• What is SWE-bench?

  SWE-bench is a benchmark used to evaluate the performance of AI agents on software engineering tasks.

• Is SWE-agent open source?

  Yes, SWE-agent is open source.

• What are the key benefits of using SWE-agent?

  Key benefits include autonomous tool usage, GitHub issue resolution, and cybersecurity vulnerability detection.

• How do I install SWE-agent?

  Follow the installation instructions provided in the documentation.

• What is the current status of SWE-agent?

  SWE-agent is now in maintenance-only mode, with development efforts focused on mini-SWE-agent.