SWE-agent
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SWE-agent is an open-source AI agent framework that uses GPT-4, Claude, and other LMs to autonomously identify bugs, propose fixes, and apply changes directly in real GitHub repositories, streamlining code maintenance and accelerating development workflows.
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SWE-agent is an open-source AI agent framework that uses GPT-4, Claude, and other LMs to autonomously identify bugs, propose fixes, and apply changes directly in real GitHub repositories, streamlining code maintenance and accelerating development workflows.
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What is SWE-agent?
SWE-agent is a developer-focused AI agent framework that integrates with GitHub to autonomously diagnose and resolve code issues. It runs in Docker or GitHub Codespaces, uses your preferred language model, and allows you to configure tool bundles for tasks like linting, testing, and deployment. SWE-agent generates clear action trajectories, applies pull requests with fixes, and provides insights via its trajectory inspector, enabling teams to automate code review, bug fixing, and repository cleanup efficiently.
Who will use SWE-agent?
- Software developers
- DevOps engineers
- Open-source maintainers
- QA engineers
- Engineering managers
How to use the SWE-agent?
- Step1: Install SWE-agent via pip or Docker according to the documentation.
- Step2: Configure your language model API keys in the .env file.
- Step3: Define or select tool bundles for testing, linting, or custom tasks.
- Step4: Run sweagent against a GitHub repository using the CLI or Codespaces.
- Step5: Review the generated trajectory and apply automated fixes via pull request.
Platform
- Linux
- Mac
- Windows
SWE-agent's Core Features & Benefits
The Core Features
- Autonomous code issue detection and fixing
- Integration with GitHub repositories
- Support for GPT-4, Claude, and custom LMs
- Configurable tool bundles
- Docker and Codespaces deployment
- Trajectory inspector for step-by-step output
The Benefits
- Accelerates debugging and maintenance
- Reduces manual code review effort
- Seamless CI/CD pipeline integration
- Customizable to project toolchains
- Improves code quality and consistency
SWE-agent's Main Use Cases & Applications
- Automated bug fixing in pull requests
- Continuous code quality monitoring
- Batch repository cleanup and refactoring
- Automating test and lint workflows
- CI/CD integration for self-healing pipelines
SWE-agent's Pros & Cons
The Pros
State-of-the-art performance on SWE-bench among open-source projects
Enables autonomous language model tool usage for diverse tasks
Highly configurable and fully documented with a simple YAML file
Free-flowing and generalizable design allowing maximum LM agency
Developed and maintained by leading researchers at Princeton and Stanford
Open-source and research-friendly, designed to be hackable
The Cons
No explicit pricing information available
No mention of native mobile or desktop applications
May require technical expertise to install and customize
Limited information about user community or commercial support
FAQs of SWE-agent
SWE-agent Company Information
Analytic of SWE-agent
Visit Over Time
Monthly Visits
15.0k
Avg Visit Duration
00:00:52
Page Per Visit
2.04
Bounce Rate
35.26%
Jun 2026 - Aug 2026 All Traffic
Geography
Top 5 Regions
United States
28.33%
India
19.12%
Brazil
10.39%
Netherlands
8.56%
Singapore
7.59%
Jun 2026 - Aug 2026 Worldwide Desktop Only
Traffic Sources
Direct
40.39%
SearchOrganic
32.06%
Referrals
12.30%
SocialOrganic
5.20%
Mail
2.44%
DisplayAds
2.39%
GenAi
1.88%
Affiliate
1.44%
SearchPaid
1.33%
SocialPaid
0.58%
Jun 2026 - Aug 2026 Desktop Only
Top Keywords
| Keyword | Traffic | Cost Per Click |
|---|---|---|
| mini swe agent | 1.1k | $ -- |
| swe-agent | 2.0k | $ -- |
| swe | 61.1k | $ 2.57 |
| swe ai | 390 | $ -- |
| swe agent | 640 | $ 5.56 |
SWE-agent Reviews
5/5
SWE-agent's Main Competitors and alternatives?
Auto-GPT
LangChain Agents
GitHub Copilot
BabyAGI
OpenAI Function Calling
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