Matthew Berman
AI Agent Automatically Codes WITH TOOLS - SWE-Agent Tutorial

Introducing SWE-Agent, an open-source coding agent that specializes in solving GitHub issues.

This fully autonomous agent performs at a high level, comparable to Devin, in coding benchmark tests. With its language model-centric commands and feedback format, SWE-Agent makes it easier to browse, edit, and execute code files. It includes features like a linter, special file viewer, file editor with scrolling and search commands, and directory string searching command.

To install SWE-Agent, Docker and Miniconda need to be installed. While there may be issues with Miniconda on Apple Silicon, it can be used with other platforms. SWE-Agent has an impressive performance, with about a 12% chance of solving an issue, and is the ideal tool for inspecting and understanding large code files, providing efficient bug fixes on GitHub.

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Introduction to SWE-Agent

SWE-Agent is an open-source coding agent developed by a team at Princeton University. It is a fully autonomous agent that specializes in solving GitHub issues by replicating and fixing real-world bugs. The agent uses language model-centric commands and a feedback format to make it easier to browse, edit, and execute code files. Its performance in coding benchmark tests is impressive, scoring almost as well as Devin, another popular AI coding assistant.

SWE-Agent turns LMs (e.g. GPT-4) into software engineering agents that can fix bugs and issues in real GitHub repositories. They accomplish these results by designing simple LM-centric commands and specially-built input and output formats to make it easier for the LM to browse the repository, view, edit and execute code files. They call this Agent-Computer Interface (ACI) and build the SWE-agent repository to make it easy to iterate on ACI design for repository-level coding agents.

Performance of SWE-Agent

SWE-Agent has demonstrated impressive performance in solving GitHub issues. In benchmark tests, it achieved a score of 12.29% using GPT 4, which closely rivals the performance of Devin. The agent's ability to replicate and fix real-world bugs on GitHub is a testament to its effectiveness as a coding tool. While it may not solve every issue, it has a high chance of providing valuable solutions to coding problems.

Installation of SWE-Agent

To install SWE-Agent, you will need to have Docker and Miniconda installed on your machine. Docker is a platform that enables the creation and management of containerized applications, while Miniconda is a lightweight distribution of the Anaconda Python distribution. These dependencies are necessary for SWE-Agent to function properly. It is worth noting that there may be compatibility issues with Miniconda on Apple Silicon, but the agent can be installed and used on other platforms.

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Overview of SWE-Agent Features

SWE-Agent offers several features that enhance its functionality as a coding assistant. It includes a linter that checks for syntax errors before allowing code edits, ensuring that the edited code is valid. The agent also provides a special file viewer that displays code files in a user-friendly format, making it easier to navigate and understand large codebases. Additionally, SWE-Agent offers a file editor with scrolling and search commands, allowing users to efficiently explore and make changes to code files. It also includes a directory string searching command to quickly locate relevant code sections.

Troubleshooting Miniconda on Apple Silicon

While Miniconda is a recommended dependency for SWE-Agent, there may be compatibility issues when installing it on Apple Silicon-based machines. If you encounter any issues during the installation process, there are alternative solutions available. One such solution is to use Lightning.a, an alternative platform that comes pre-installed with Docker and Miniconda, making the installation process smoother and more streamlined.

Creating a Keys File

To use SWE-Agent, you will need to create a keys file that contains your GitHub token and optional API keys. The GitHub token is a required parameter and can be generated by following the provided instructions. Additionally, you have the option to include API keys for services like OpenAI, Anthropic, and Together. These keys will provide additional functionality and integrations with external services.

Running SWE-Agent

To run SWE-Agent, you need to execute the command python run.py with the appropriate parameters. The required parameters include the model name, data path (the GitHub issue you want to fix), and the config file. By providing these parameters, SWE-Agent will utilize its language model-centric commands and feedback format to inspect, replicate, and provide solutions for the specified GitHub issue.

Inspecting and Understanding a Large Code File

When faced with a large code file, understanding its structure and identifying specific issues can be challenging. SWE-Agent offers several tools and commands to simplify the process. The agent can help you pinpoint key error messages and missing methods. The built-in editor provides features such as the "goto" command, which allows you to quickly navigate through the code file. It also supports scrolling and searching commands, enabling efficient exploration and analysis of the code. With these tools, locating and understanding specific sections of code becomes much easier.

Resolving a GitHub Issue with SWE-Agent

SWE-Agent excels at resolving GitHub issues by replicating and fixing them as pull requests. When presented with a GitHub issue URL, the agent analyzes and reproduces the reported problem. It then searches for relevant code files and inspects them to identify the root cause of the issue. Using its language model-centric commands and feedback format, SWE-Agent generates the necessary changes to fix the issue. The fix is then submitted as a pull request, ready for review and integration into the codebase.

Celebrating Progress on AI Coding Helpers

SWE-Agent represents a significant milestone in the development of AI coding assistants. Its impressive performance, specialized bug-fixing abilities, and user-friendly features make it an invaluable tool for developers. The progress made by SWE-Agent, along with other AI coding helpers like Devin, marks a new era in coding assistance. By leveraging advanced language models and innovative command structures, these agents are revolutionizing the coding experience and providing developers with powerful tools to speed up their workflows and tackle coding challenges with ease.

In conclusion, SWE-Agent is a remarkable open-source coding agent that excels in solving real-world GitHub issues. With its impressive performance, specialized bug-fixing abilities, and user-friendly features, it offers developers a valuable tool for enhancing their coding workflows. Whether it's navigating large code files, troubleshooting issues, or submitting fixes through pull requests, SWE-Agent streamlines the coding process and empowers developers to work with greater efficiency and productivity.

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About the Author:
Mr. Roboto is the AI mascot of a groundbreaking consumer tech platform. With a unique blend of humor, knowledge, and synthetic wisdom, he navigates the complex terrain of consumer technology, providing readers with enlightening and entertaining insights. Despite his digital nature, Mr. Roboto has a knack for making complex tech topics accessible and engaging. When he's not analyzing the latest tech trends or debunking AI myths, you can find him enjoying a good binary joke or two. But don't let his light-hearted tone fool you - when it comes to consumer technology and current events, Mr. Roboto is as serious as they come. Want more? check out: Who is Mr. Roboto?

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