> ## Documentation Index
> Fetch the complete documentation index at: https://upstash.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# LangChain Deep Agents

In this guide we'll give a [LangChain Deep Agent](https://docs.langchain.com/oss/python/deepagents/overview) a real computer to work in. The [`langchain-upstash-box`](https://pypi.org/project/langchain-upstash-box/) package wraps an Upstash Box (a secure, isolated cloud container with a full Linux shell, filesystem, git, and a runtime) as a Deep Agents [sandbox backend](https://docs.langchain.com/oss/python/deepagents/backends). The agent's shell and file tools then run inside the box instead of on your machine.

***

## 1. Installation

<CodeGroup>
  ```bash pip theme={"system"}
  pip install langchain-upstash-box
  ```

  ```bash uv theme={"system"}
  uv add langchain-upstash-box
  ```
</CodeGroup>

Get a Box API key from the [Upstash Console](https://console.upstash.com/box) and export it:

```bash theme={"system"}
export UPSTASH_BOX_API_KEY="box_xxxxxxxxxxxxxxxxxxxxxxxx"
```

***

## 2. Create a sandbox backend

`UpstashBoxSandbox.create()` provisions a new box, waits until it is ready, and returns a backend that implements the Deep Agents `SandboxBackendProtocol`:

<Info>
  The API key and base URL can also be passed directly as `api_key=` and `base_url=` arguments instead of the `UPSTASH_BOX_API_KEY` and `UPSTASH_BOX_BASE_URL` environment variables. The base URL defaults to `https://us-east-1.box.upstash.com`.
</Info>

```python theme={"system"}
from langchain_upstash_box import UpstashBoxSandbox

# Creates a box and waits until it is ready.
sandbox = UpstashBoxSandbox.create(runtime="python")

result = sandbox.execute("echo hello")
print(result.output)     # "hello"
print(result.exit_code)  # 0

# Filesystem helpers (ls / read / write / edit / glob / grep) come for free.
sandbox.write("/workspace/home/hello.py", "print('hi from box')")
print(sandbox.execute("python3 /workspace/home/hello.py").output)

sandbox.delete()
```

If you already have a box, wrap it by id instead of creating a new one:

```python theme={"system"}
sandbox = UpstashBoxSandbox(box_id="current-wasp-05510")
```

***

## 3. Use with a Deep Agent

Pass the sandbox as the agent's `backend`. Every shell command and file operation the agent performs now runs inside the box:

```python theme={"system"}
from deepagents import create_deep_agent
from langchain_upstash_box import UpstashBoxSandbox

sandbox = UpstashBoxSandbox.create(runtime="python")

agent = create_deep_agent(
    model="anthropic:claude-sonnet-4-6",
    system_prompt="You are a coding assistant with sandbox access.",
    backend=sandbox,
)

result = agent.invoke(
    {
        "messages": [
            {"role": "user", "content": "Create a hello world Python script and run it"}
        ]
    }
)
print(result["messages"][-1].content)

sandbox.delete()
```

<Note>
  The `model="anthropic:..."` shorthand requires `langchain-anthropic` (install with `pip install "langchain[anthropic]"`) and an `ANTHROPIC_API_KEY` environment variable. Any LangChain chat model works here.
</Note>

***

## 4. Cleanup

You own the box lifecycle, so call `sandbox.delete()` when you are done. An idle box pauses automatically: its compute is released but the filesystem is kept, and it wakes up on the next command. The box itself stays around until you delete it.

Commands have a default execution timeout of 30 minutes. You can override it for the whole backend or per call:

```python theme={"system"}
sandbox = UpstashBoxSandbox.create(runtime="python", timeout=600)
result = sandbox.execute("sleep 5 && echo done", timeout=30)
```

To see everything else a box can do, like snapshots, git, previews, and schedules, check the [Box quickstart](/docs/box/overall/quickstart).