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SWE-agent/SWE-agent

An AI agent that autonomously fixes GitHub issues, finds cybersecurity vulnerabilities, and performs coding tasks using large language models.

Core Features

Automated GitHub issue fixing

Cybersecurity vulnerability detection (EnIGMA mode)

Configurable via a single YAML file

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

Supports various large language models (e.g., GPT-4o, Claude)

Detailed Introduction

SWE-agent is an innovative AI agent developed by researchers from Princeton and Stanford Universities, designed to automate complex software engineering tasks. It leverages the power of large language models to autonomously address a wide range of challenges, including fixing bugs in real GitHub repositories, identifying cybersecurity vulnerabilities through its EnIGMA mode, and tackling competitive coding challenges. With its state-of-the-art performance on benchmarks like SWE-bench, high configurability via a single YAML file, and a design optimized for research, SWE-agent provides a powerful, generalizable, and flexible platform for AI-driven code interaction and development, pushing the boundaries of automated software engineering.