langchain-superserve adapts a Superserve sandbox to the Deep Agents sandbox protocol. Because Deep Agents compiles to a LangGraph graph, the same backend works across LangChain, LangGraph, and Deep Agents — agent shell commands and file operations run inside an isolated Firecracker microVM instead of on your machine.
Setup
langchain-anthropic ships as a base dependency of Deep Agents, so the Anthropic model used below is already installed. See API keys to create a Superserve API key.
Deep Agents SDK
Launch a sandbox from a python-equipped template, wrap it inSuperserveSandbox, and pass it as the backend to create_deep_agent(...) — the agent’s shell and file operations then run inside the sandbox:
SuperserveSandbox synthesizes ls/read/edit/glob with in-sandbox python3, so launch from a python-equipped image — superserve/python-3.11, superserve/python-ml, or superserve/code-interpreter. execute, grep, and file upload/download work on any image, including the minimal superserve/base.Deep Agents Code
Installinglangchain-superserve also registers a superserve sandbox provider for Deep Agents Code (dcode), the terminal coding agent built on the Deep Agents SDK:
superserve/python-3.11 template; override it with the SUPERSERVE_TEMPLATE environment variable.
Superserve extras
Beyond the standard Deep Agents backend, Superserve sandboxes supportpause()/resume() for idle cost savings and proxy-brokered secret binding (Sandbox.create(secrets=...)) so real credentials never enter the sandbox. Manage these through the Superserve SDK on the sandbox you pass to SuperserveSandbox.
Resources
langchain-superserve on GitHub
Browse the source, tests, and release notes.
langchain-superserve on PyPI
Install the package and check released versions.