smolvm 0.0.2

Secure runtime for AI agents, and tools -- free and open-source from Celesto AI 🧡

SmolVM

Secure runtime for AI agents and tools

Docs • Examples • GitHub

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SmolVM is a lightning-fast, secure microVM runtime designed for high-density isolation. It provides AI agents and tools with a safe, hardware-virtualized environment to execute untrusted code without risking the host system.

✨ Features

• 🔒 Secure Isolation: Hardware-level virtualization (utilizing Firecracker) for strong sandbox boundaries.
• ⚡ Blazing Fast: MicroVMs boot in sub-second time with minimal overhead.
• 🐍 Python Native: Clean, high-level SDK for managing VM lifecycles and command execution.
• 🌐 Automatic Networking: Built-in NAT, port forwarding, and SSH tunneling.
• 🛠️ Custom Images: Build specialized Debian-based rootfs images with your own tools.
• 🧹 Auto-Cleanup: Integrated resource management to keep your host system clean.

🤔 Why SmolVM?

AI agents often need to execute arbitrary code (Python, JS, shell scripts) generated by LLMs. Running this code directly on your host or in standard containers can be risky.

• MicroVM-based Security: Unlike containers that share the host kernel, SmolVM uses KVM-backed microVMs. This provides a significantly smaller attack surface and stronger hardware-level isolation.
• Agent-First Design: SmolVM abstracts away the complexity of microVM networking, storage, and TAP devices into a simple, pythonic API.

🚀 Quickstart

1. Prerequisites

• Linux + Firecracker backend: KVM support (Ubuntu/Debian/Fedora).
• macOS + QEMU backend: Homebrew and QEMU (qemu-system-*).

2. Installation

# Install the Python package
pip install smolvm

Linux (Firecracker):

sudo ./scripts/system-setup.sh --configure-runtime

macOS (QEMU):

./scripts/system-setup-macos.sh
# Optional explicit backend override:
# export SMOLVM_BACKEND=qemu

3. Basic Usage

Initialize a VM with no arguments for an auto-configured, SSH-ready environment:

from smolvm import VM

# Auto-configures keys, image, and network automatically
with VM() as vm:
    result = vm.run("echo 'Hello from the sandbox!'")
    print(result.output)

Customize auto-config memory and disk size:

from smolvm import VM

with VM(mem_size_mib=2048, disk_size_mib=4096) as vm:
    print(vm.run("free -m").output)

4. Reconnect to an existing VM

You can also reconnect to a running VM by its ID:

from smolvm import VM

# Reconnect to an existing VM
vm = VM.from_id("vm-abcdef12")
print(f"Status: {vm.status}")

5. Port Forwarding

Expose a guest application to your local machine securely. expose_local prefers host-local iptables forwarding and automatically falls back to an SSH tunnel when needed.

from smolvm import VM

with VM() as vm:
    # Example: App in VM listening on port 8080, expose to host port 18080
    host_port = vm.expose_local(guest_port=8080, host_port=18080)
    print(f"App available at http://localhost:{host_port}")

6. Environment Variables

Inject environment variables into a running VM. Variables are persisted in /etc/profile.d/smolvm_env.sh and apply to new SSH/login shell sessions.

from smolvm import VM

with VM() as vm:
    vm.set_env_vars({"API_KEY": "sk-...", "DEBUG": "1"})
    print(vm.list_env_vars())
    print(vm.run("echo $API_KEY").output)

CLI:

smolvm env set <vm_id> API_KEY=sk-... DEBUG=1
smolvm env list <vm_id> --show-values
smolvm env unset <vm_id> DEBUG

📄 License

Apache 2.0 License - see LICENSE for details.

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Built with 🧡 by Celesto AI