Deep Agents + OpenSandbox Example

Run a Deep Agent whose file and shell tools execute inside an OpenSandbox sandbox. The langchain-sandbox-opensandbox backend adapts the OpenSandbox Python SDK to the Deep Agents BaseSandbox interface, so every ls / read_file / write_file / glob / grep / command the agent performs is sandboxed.

The backend passes the full langchain-tests SandboxIntegrationTests conformance suite (86/86) against a live server.

Start OpenSandbox server [local]

Start a local OpenSandbox server, logs will be visible in the terminal:

uv pip install opensandbox-server
opensandbox-server init-config ~/.sandbox.toml --example docker
opensandbox-server

Run the example

# Install Deep Agents + the OpenSandbox backend
uv pip install deepagents langchain-sandbox-opensandbox

# Run the example (requires SANDBOX_DOMAIN / ANTHROPIC_API_KEY)
uv run python examples/deep-agents/main.py

The agent writes a Python script into the sandbox, runs it, and reports the output — all file and shell operations happen inside the sandbox rather than on the host. The sandbox is destroyed on exit (terminated and local resources closed).

Environment Variables

Variable	Default	Description
SANDBOX_DOMAIN	localhost:8080	Sandbox service address (host and optional port)
SANDBOX_PROTOCOL	http	Protocol used to reach the server (http or https)
SANDBOX_API_KEY	(optional for local)	API key if your server requires authentication
ANTHROPIC_API_KEY	(required)	Anthropic API key for the default Deep Agents model

References

• Deep Agents - Agent framework
• langchain-sandbox-opensandbox - OpenSandbox backend for Deep Agents
• Source code on GitHub