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Documentation Index

Fetch the complete documentation index at: https://docs.celesto.ai/llms.txt

Use this file to discover all available pages before exploring further.

By the end of this guide you’ll have an isolated Linux sandbox running on your machine, ready to execute commands safely.
1

Install SmolVM

curl -sSL https://celesto.ai/install.sh | bash
This installs everything you need and configures your machine. See Installation for manual install and requirements.
2

Run your first sandbox

Create quickstart.py:
quickstart.py
from smolvm import SmolVM

vm = SmolVM()
result = vm.run("echo 'Hello from the sandbox!'")
print(result.stdout.strip())
vm.stop()
Run it:
python quickstart.py
You should see:
Hello from the sandbox!
The first run takes 30-60 seconds to download the operating system images.

Prefer the command line?

You can do the same thing without writing any Python:
smolvm create --name my-sandbox
smolvm ssh my-sandbox       # opens a shell inside the sandbox — type `exit` to leave
smolvm stop my-sandbox

Customize resources

Configure memory and disk for heavier workloads (defaults: 512 MiB memory, 512 MiB disk):
from smolvm import SmolVM

vm = SmolVM(memory=2048, disk_size=4096)
result = vm.run("free -m")
print(result.stdout)
vm.stop()

Next steps

AI agent integration

Plug SmolVM into PydanticAI, OpenAI Agents, LangChain, and more

Port forwarding

Expose services running inside a sandbox to your host machine

Custom images

Build specialized images with your own tools pre-installed

API reference

Explore the complete SmolVM API
Join the Slack community to get help and share your use cases.
Last modified on May 28, 2026