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How to run agent-written code in an isolated sandbox with SPACE

Create a sandbox, run a command in it, and collect its output over the HTTP API.

Who it is forA developer building an AI agent that generates and runs code, and needs each run kept apart from the host and other users.

The problemRunning model-written code directly on your application server risks side effects, leaked files, and shared state between runs.

The outcomeEach run executes in its own Firecracker microVM sandbox, and your application receives the command output and exit result, then deletes the sandbox.

What you need first

  • A host that meets the prerequisites in docs/installation.md
  • Docker-compatible local setup for a Kind cluster, as described in docs/installation.md
  • Bash for installation and cluster diagnostics
  • Git and Python 3.11+ and mdBook 0.4.52 only if you build the docs locally

Steps

  1. Follow [Installation and configuration](docs/installation.md) to deploy SPACE in a local Kind cluster and authenticate.
  2. Follow [Your first sandbox](docs/first-sandbox.md) to create a sandbox from a template and wait for readiness.
  3. Create a command session, attach to it to start the process, and read the output and exit result.
  4. Delete the sandbox when the run finishes.

Prompt for your agent

Using the repo perplexityai/SPACE, follow docs/first-sandbox.md against a local deployment at <SPACE API URL> to run <command> in a new sandbox. Report the command output and exit result. Verify that the sandbox is deleted after the run.

Caveat. The README describes a Kubernetes-based local setup, so you need a working Kind cluster before the first sandbox can run.

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