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📚Complete Guide

SWE-agent Tutorial: Get Started in 5 Minutes [2026]

Master SWE-agent with our step-by-step tutorial, detailed feature walkthrough, and expert tips.

Get Started with SWE-agent →Full Review ↗
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Getting Started with SWE-agent

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Install SWE

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agent via pip: run 'pip install sweagent' in a Python

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9+ environment with Docker installed and running Configure your LLM API key by setting the appropriate environment variable (e.g., OPENAI_API_KEY or ANTHROPIC_API_KEY) or add it to the YAML config file Run your first issue fix: execute 'sweagent run

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agent.model.name=gpt

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env.repo.github_url=https://github.com/OWNER/REPO

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problem_statement.github_url=https://github.com/OWNER/REPO/issues/NUMBER' Review the generated patch in the output directory and apply it to your repository with git apply Explore mini

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agent at https://github.com/SWE

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agent for a simplified 100

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line alternative

💡 Quick Start: Follow these 9 steps in order to get up and running with SWE-agent quickly.

🔍 SWE-agent Features Deep Dive

Explore the key features that make SWE-agent powerful for coding agents workflows.

Agent-Computer Interface (ACI)

What it does:

Use case:

Model-agnostic LLM backend

What it does:

Use case:

SWE-ReX sandboxed runtime

What it does:

Use case:

EnIGMA cybersecurity mode

What it does:

Use case:

Batch processing and trajectories

What it does:

Use case:

Python API and extensibility

What it does:

Use case:

❓ Frequently Asked Questions

What is SWE-agent and who built it?

SWE-agent is an open-source autonomous coding agent created by researchers at Princeton University and Stanford University. It was introduced in a NeurIPS 2024 paper and takes a GitHub issue as input, then uses an LLM to navigate the repository, edit files, and run tests to propose a fix. The same system, configured as EnIGMA, can also tackle offensive cybersecurity challenges.

Which language models can I use with SWE-agent?

SWE-agent is model-agnostic. It officially supports GPT-4o and other OpenAI models, Anthropic's Claude family (including Sonnet and Opus), DeepSeek, and any OpenAI-compatible endpoint — which means you can point it at local models served via Ollama, vLLM, or LM Studio. Model selection is handled in the agent config file.

Is SWE-agent free to use?

Yes. The SWE-agent codebase is fully open-source under the MIT license and free to self-host. The only costs are the LLM API fees you incur when using commercial models like GPT-4o or Claude; running it with a local model is free apart from compute.

How is SWE-agent different from tools like Devin or Cursor?

Devin is a closed, hosted autonomous agent with a managed UI and subscription pricing; Cursor is an interactive IDE with AI assistance. SWE-agent is an open-source, self-hostable agent framework focused on autonomously resolving issues end-to-end. It is research-grade software — you bring your own model and infrastructure, and you get full transparency into the agent's prompts, tools, and trajectories.

Can SWE-agent run safely on my codebase?

SWE-agent executes all commands inside Docker containers via its SWE-ReX runtime, which isolates file and network access from the host. For additional safety on private repos, you can use ephemeral sandboxes on Modal or AWS, and you should always review generated patches before merging — especially for long autonomous runs.

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Ready to Get Started?

Now that you know how to use SWE-agent, it's time to put this knowledge into practice.

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Try It Out

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Start Using SWE-agent Today

Follow our tutorial and master this powerful coding agents tool in minutes.

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Tutorial updated March 2026