Start, stop, and delete computers

A Celesto computer is a workspace you can create for a task, stop when you are done for now, start again later, and delete when the work is finished. Use the lifecycle when you want to control how long a workspace stays around. Lifecycle means the stages a computer moves through, from creation to cleanup.

Create, stop, start, and delete

Create a computer when you need a clean workspace. Stop it to pause work and keep the files inside it. Start it when you want to continue. Delete it when you no longer need the workspace.

from celesto import Celesto


client = Celesto()
computer = client.computers.create(template_id="coding-agent")
computer_id = computer["id"]

print(computer["name"])

client.computers.stop(computer_id)
client.computers.start(computer_id)
client.computers.delete(computer_id)

The same computer can stop, start again, and then be removed when the workspace is no longer needed.

Run work after a stop

The CLI can start a stopped computer automatically when you run a command or open a terminal. This lets you stop a computer between work sessions and continue from the same workspace later.

CLI

celesto computer run einstein "uname -a"
celesto computer ssh einstein

Commands that need a running computer can start the stopped computer before they run.

Read the computer status

Celesto computer responses include a status field. Status means the current stage of the computer, such as running, stopped, or deleted.

Status	Meaning
`creating`	Celesto is preparing the computer.
`running`	The computer can run commands and accept terminal connections.
`stopping`	Celesto is stopping the computer.
`stopped`	The workspace is saved and can be started again.
`starting`	Celesto is starting a stopped computer.
`restoring`	Celesto is restoring a saved workspace.
`restorable`	Saved workspace state is available to restore.
`deleting`	Celesto is deleting the computer and its resources.
`deleted`	The computer has been deleted.
`error`	The computer needs attention before it can be used.

Resume agent work later

For OpenAI SandboxAgent workflows, you can save session state and resume it later. Session state means the saved details Celesto uses to reconnect the same agent to the same sandbox workspace.

Use delete_on_close=False when you plan to resume an OpenAI sandbox session. Follow the complete example in the OpenAI agent sandbox guide.

Choose the right session pattern

Use these patterns to decide how long a computer should stay available.

Pattern	Use it when you want to
Create, run, delete	Start fresh for one task and clean up right away.
Create, stop, start	Keep files and installed packages between sessions.
Existing computer ID	Let a job or agent continue in a known workspace.
Saved OpenAI session state	Resume an agent session with the same sandbox identity.

​Create, stop, start, and delete

​Run work after a stop

​Read the computer status

​Resume agent work later

​Choose the right session pattern

Create, stop, start, and delete

Run work after a stop

Read the computer status

Resume agent work later

Choose the right session pattern