SWE-Agent is a cutting-edge AI-driven coding assistant developed by a team at Princeton University. This innovative tool is designed to autonomously resolve bugs and issues within real-world GitHub repositories, significantly enhancing the efficiency and productivity of software development workflows. By leveraging advanced language models like GPT-4, SWE-Agent provides a robust solution for developers to automate the debugging process, reduce time spent on fixing bugs, and improve overall code quality. SWE-Agent boasts a comprehensive set of features aimed at making software development more efficient and effective. Below is a detailed overview of its functionalities: SWE-Agent can be leveraged in various scenarios, including: Getting started with SWE-Agent involves a few straightforward steps:Features
Feature
Description
Autonomous Bug Resolution
Replicates issues from GitHub, identifies root causes, proposes fixes, and submits them as pull requests.
Custom File Viewer and Editor
Displays manageable chunks of code (up to 100 lines) with scrolling and search functionality.
Agent-Computer Interface (ACI)
Enhances interactions between the language model and codebase for efficient browsing and editing.
Integration with Docker and Miniconda
Streamlines setup and usage, simplifying Python environment management.
Built-in Linting Tool
Ensures syntactical correctness of code edits before applying them.
Cost Efficiency
Imposes cost limits on running tasks with GPT-4 to prevent excessive expenditure.
Performance Metrics
Achieved a benchmark score of 12.29% in the SWE-bench test, indicating strong autonomous issue resolution capabilities.
Open-Source and Community Engagement
Allows developers to modify and extend functionality, promoting community involvement and continuous improvement.
Use cases
How to get started
The pricing for SWE-Agent is structured as follows: Note: The technical paper is expected to outline cost optimization strategies in detail, including the average cost per solved task.Pricing for SWE-Agent