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The Celesto SDK lets you create a safe computer for your code or agent, run work inside it, and clean it up when you are done. You can use Celesto from Python, TypeScript, JavaScript, or the celesto command line tool. Use this section when you want to:
  • Run generated code in an isolated computer.
  • Give an AI agent a workspace with files, shell commands, and optional public ports.
  • Keep long-running agent work in a durable cloud workspace.
  • Connect end-user data sources through Gatekeeper from TypeScript apps.

Quickstart

Install the SDK, create your first computer, run a command, and delete it.

Authentication

Save your API key for the CLI or pass it to the SDK from your environment.

Sandboxed computers

Create computers, use templates, run commands, manage ports, and control lifecycle.

CLI reference

Use celesto auth and celesto computer commands from your terminal.

Deployments

See the current status of managed deployment APIs.

Pi coding agent

Keep Pi local while its coding tools run on an isolated Celesto cloud computer.

OpenAI Agents

Give an OpenAI SandboxAgent a hosted Celesto computer or local SmolVM.

Gatekeeper

Connect your users to providers like Google Drive from TypeScript apps.

Errors

Handle authentication, validation, rate limit, server, and network errors.

Feature guides

These guides cover the parts of Celesto computers that matter most when you move from a quickstart to real agent workflows.

Publish ports

Expose a server, preview app, notebook, or webhook receiver running inside a computer.

Computer sessions

Create, stop, start, resume, and delete computers for temporary or long-lived work.

Computer resources

Choose CPU, memory, disk size, and templates for heavier agent workloads.

Persistent state

Keep files, installed packages, and agent workspace state between sessions.

Choose your SDK

Pages with SDK examples use Mintlify’s View component. Pick Python or TypeScript from the selector at the top of the page, and the examples and table of contents update for that language.
Use the Python SDK when you are building agents, automation scripts, or backend services in Python. Python examples use snake_case parameters such as template_id and disk_size_mb.
Start with the Python quickstart, then read Sandboxed computers when you need templates, command execution, ports, or lifecycle control.

How the SDK fits together

1

Authenticate

Create an API key in Celesto, then save it once with the CLI or set CELESTO_API_KEY for SDK code.
Your SDK client and CLI commands can call the Celesto API.
2

Create a computer

Start with the default scratch computer, or use the coding-agent template when your agent needs common coding tools.
You have an isolated Linux computer with an ID and a status.
3

Run work

Execute shell commands, inspect output, publish a supported port, or connect a terminal.
Your code or agent runs inside the sandbox instead of on your host machine.
4

Clean up

Delete temporary computers when you are done, or stop long-lived computers when you want to keep their files for later.
Last modified on July 10, 2026