opensandbox-group/OpenSandbox

OpenSandbox

Secure, Fast, and Extensible Sandbox runtime for AI agents.

41/100Agents
Stars11,230
Forks911
LanguagePython
LicenseApache-2.0

Usage guide

OpenSandbox is an open-source project around ai-agent, ai-infra, kubernetes with 11,230 GitHub stars. This guide focuses on when to use it, how to install it, how to run the first example, and what to verify before adopting it.

Repository license: Apache-2.0Commercial use permitted, review additional terms

Key features

  • Implemented mainly in Python, useful for judging integration effort in a similar stack.
  • GitHub detected the Apache-2.0 repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.
  • The project has a homepage, so cross-check docs, examples, and release information beyond GitHub.

Best for

  • Evaluating OpenSandbox for Python AI workflows.
  • Comparing a GitHub project with 11,230 stars and current repository activity.

Pros

  • OpenSandbox has visible GitHub traction with 11,230 stars. Topics: ai, ai-agent, ai-infra.
  • The project provides an external homepage for deeper evaluation.

Cons

  • Production fit still depends on documentation depth, issue activity, and release cadence.
  • License review should confirm the Apache-2.0 terms fit your use case.

Production readiness

OpenSandbox should be validated with its README, release history, open issues, and integration requirements before production use.

License risk

Apache-2.0 is reported by GitHub; review the repository license before redistribution or commercial use.

OpenSandbox architecture preview

OpenSandbox's main path starts at the entry surface, runs through Coding agent runtime, combines LLM / model client, Runtime context, External tool adapters, and returns Assistant response / action result.

Entry

Web / product entry

Users start from a web UI, hosted product surface, or browser-based workflow.

https://open-sandbox.ai

Runtime

Coding agent runtime

The runtime reads developer intent, inspects repository context, plans edits, and returns code-oriented actions.

coding workflow

Runtime dependencies

Model

LLM / model client

The project connects its core runtime to local models or hosted AI APIs when model inference is required.

model signal

Context

Runtime context

Runtime state, user input, repository files, or configuration provide context for each task.

context signal

Tools

External tool adapters

Tool adapters let the runtime act outside the model through External tool adapters.

tool signal

Output

Assistant response / action result

The final result is a response, action, or task completion returned through the active channel.

assistant output

Featured video

XavkiEn

YouTube

Alibaba launches OpenSandbox #opensource #ai #computerscience

1,299 views · 2026-03-03

Install tutorial

Before you install

  • Python runtime and an isolated virtual environment
  • A clean working directory for the first test run
1
Step 1

Check the runtime environment

OpenSandbox depends on a Python-style environment. Use venv, conda, or a container to keep dependencies isolated.

2
Step 2

Get the project files

Start from the official repository or package so the first run matches the documented behavior.

terminal
$ git clone https://github.com/opensandbox-group/OpenSandbox.git
3
Step 3

Install or build dependencies

Run the next setup command detected from the project documentation.

terminal
$ uv pip install opensandbox-code-interpreter

Troubleshooting

  • If installation fails, first confirm the command is being run from the README-specified directory.
  • If dependencies conflict, retry in a fresh virtual environment, container, or working directory.
  • If output looks wrong, return to the smallest documented OpenSandbox example before adding complex data.
  • For keys, model files, or external services, verify environment variables, local paths, and permissions one by one.
  • Before production use, review recent updates, open issues, license terms, and safety boundaries.
What is OpenSandbox?

OpenSandbox is an open-source ai agents project. Secure, Fast, and Extensible Sandbox runtime for AI agents.

How do I install OpenSandbox?

Start with the official README. The first detected setup step is: git clone https://github.com/opensandbox-group/OpenSandbox.git.

Is OpenSandbox beginner-friendly?

If you already know the Python ecosystem, start with the smallest example. Otherwise test it in an isolated environment first.

Can OpenSandbox be used commercially?

GitHub detected the Apache-2.0 repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.

Does OpenSandbox need a GPU?

GPU requirements depend on the workload, model, and dataset size. Start with the smallest README example before scaling up.

How should I decide whether to adopt OpenSandbox?

Evaluate setup cost, maintenance activity, issue health, license terms, and fit with your real workflow.

Star trend

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