Runtimeuse

runtimeuse

[](https://twitter.com/getlark)

Run AI agents inside sandboxes and communicate with them over WebSocket.

Package	Language	Role	Install
`runtimeuse`	TypeScript	Agent runtime (runs inside the sandbox)	npm install runtimeuse
`runtimeuse-client`	Python	Client (connects from outside the sandbox)	pip install runtimeuse-client

Quick Start

1. Start the runtime (inside a sandbox)

export OPENAI_API_KEY=your_openai_api_key
npx -y runtimeuse@latest

This starts a WebSocket server on port 8080 using the default OpenAI handler. For fuller Claude-based sandbox examples, see [`examples/`](./examples).

2. Connect from Python

import asyncio
from runtimeuse_client import (
    QueryOptions,
    RuntimeEnvironmentDownloadableInterface,
    RuntimeUseClient,
    TextResult,
)

WORKDIR = "/runtimeuse"

async def main():
    client = RuntimeUseClient(ws_url="ws://localhost:8080")

    result = await client.query(
        prompt="Summarize the contents of the codex repository.",
        options=QueryOptions(
            system_prompt="You are a helpful assistant.",
            model="gpt-5.4",
            pre_agent_downloadables=[
                RuntimeEnvironmentDownloadableInterface(
                    download_url="https://github.com/openai/codex/archive/refs/heads/main.zip",
                    working_dir=WORKDIR,
                )
            ],
        ),
    )

    assert isinstance(result.data, TextResult)
    print(result.data.text)

asyncio.run(main())

See the