RunloopSandbox integration

Integrate with the RunloopSandbox sandbox backend using LangChain Python.

Runloop provides disposable devboxes for running code in isolated environments. See the Runloop docs for signup, authentication, and platform details.

Installation

pip

pip install langchain-runloop

Create a sandbox backend

In Python, you create the devbox using the provider SDK, then wrap it with the deepagents backend.

from runloop_api_client import RunloopSDK

from langchain_runloop import RunloopSandbox

api_key = "..."
client = RunloopSDK(bearer_token=api_key)

devbox = client.devbox.create()
backend = RunloopSandbox(devbox=devbox)

try:
    result = backend.execute("echo hello")
    print(result.output)
finally:
    devbox.shutdown()

Use with Deep Agents

from runloop_api_client import RunloopSDK
from langchain_anthropic import ChatAnthropic

from deepagents import create_deep_agent
from langchain_runloop import RunloopSandbox

api_key = "..."
client = RunloopSDK(bearer_token=api_key)

devbox = client.devbox.create()
backend = RunloopSandbox(devbox=devbox)

agent = create_deep_agent(
    model=ChatAnthropic(model="claude-sonnet-4-20250514"),
    system_prompt="You are a coding assistant with sandbox access.",
    backend=backend,
)

try:
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "Create a small Python project and run tests"}]}
    )
finally:
    devbox.shutdown()

Cleanup

Always shut down devboxes when you are done to avoid ongoing resource usage.

See also: Sandboxes.

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