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.
Workflow Automation
Web Tools
Search Technology
Software Testing
#AI code assistant
#automated debugging
#GitHub integration
#code quality improvement
#Developer Tools
#CI/CD automation
#Docker support
#trajectory inspector
#linting tools
#testing automation
#repository management
#customizable coding solutions
#bug fixing automation
#code review tools
#AI-driven development
#Software maintenance
#DevOps efficiency
#Language model integration
#development frameworks
...
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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.
Workflow Automation
Web Tools
Search Technology
Software Testing
#AI code assistant
#automated debugging
#GitHub integration
#code quality improvement
#Developer Tools
#CI/CD automation
#Docker support
#trajectory inspector
#linting tools
#testing automation
#repository management
#customizable coding solutions
#bug fixing automation
#code review tools
#AI-driven development
#Software maintenance
#DevOps efficiency
#Language model integration
#development frameworks
...
Featured
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
- mac
- windows
- linux
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
43.2k
Avg Visit Duration
00:00:34
Page Per Visit
1.80
Bounce Rate
39.12%
Aug 2025 - Oct 2025 All Traffic
Geography
Top 5 Regions
United States
23.01%
India
10.47%
Thailand
8.43%
Singapore
6.94%
Vietnam
6.78%
Aug 2025 - Oct 2025 Worldwide Desktop Only
Traffic Sources
Direct
42.65%
Search
31.00%
Referrals
18.99%
Social
6.28%
Paid Referrals
0.93%
Mail
0.10%
Aug 2025 - Oct 2025 Desktop Only
Top Keywords
| Keyword | Traffic | Cost Per Click |
|---|---|---|
| swe agent | 2.5k | $ 4.82 |
| sweagent installation | 200 | $ -- |
| swe-agent | 2.1k | $ -- |
| sweagent running swebench | 200 | $ -- |
| sweagent | 620 | $ -- |
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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