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

# LangGraph Computer Use

> Create AI agents that can use computers with LangGraph and MarinaBox

# LangGraph Integration

MarinaBox can be integrated with LangGraph to create AI agents that can interact with isolated desktop environments. This guide shows you how to set up MarinaBox as a Computer Tool for LangGraph agents.

## Prerequisites

* MarinaBox installed and configured
* Python 3.8+
* Anthropic API key for Claude

## Basic Setup

First, install the required dependencies:

```bash theme={null}
pip install marinabox langgraph langchain-anthropic
```

Set up your Anthropic API key:

```python theme={null}
import os
os.environ['ANTHROPIC_API_KEY'] = "your-anthropic-api-key"
```

## Creating the Workflow

Here's a complete example showing how to create a LangGraph workflow with MarinaBox:

```python theme={null}
from marinabox import mb_start_computer, mb_stop_computer, mb_use_computer_tool
from langchain_core.messages import AIMessage, HumanMessage
from langchain_core.tools import tool
from langgraph.prebuilt import ToolNode
from langgraph.graph import StateGraph, START, END
from langchain_anthropic import ChatAnthropic
from typing import Annotated, Literal
from langgraph.types import Command

# Set up tools and model
tools = [mb_use_computer_tool]
tool_node = ToolNode(tools=tools)
model_with_tools = ChatAnthropic(
    model="claude-3-5-sonnet-20241022", 
    temperature=0
).bind_tools(tools)

# Define workflow logic
def should_continue(state: Annotated[dict, InjectedState()]):
    messages = state["messages"]
    if len(messages) > 0:
        last_message = messages[-1]
        if last_message.tool_calls:
            return Command(goto="tool_node")
    return Command(goto="stop_computer")

def call_model(state: Annotated[dict, InjectedState()]):
    input_message = input("Enter your message: ")
    if input_message != "stop_computer":
        messages = [HumanMessage(content=input_message)]
        response = model_with_tools.invoke(messages)
        return {
            "messages": [response], 
            "session_id": state.get("session_id")
        }
    return {
        "messages": [], 
        "session_id": state.get("session_id")
    }

# Create workflow
workflow = StateGraph(dict)

# Add nodes
workflow.add_node("start_computer", mb_start_computer)
workflow.add_node("agent", call_model)
workflow.add_node("tool_node", tool_node)
workflow.add_node("stop_computer", mb_stop_computer)
workflow.add_node("should_continue", should_continue)

# Add edges
workflow.add_edge(START, "start_computer")
workflow.add_edge("start_computer", "agent")
workflow.add_edge("tool_node", "agent")
workflow.add_edge("agent", "should_continue")
workflow.add_edge("stop_computer", END)

# Compile and run
app = workflow.compile()
app.invoke({"messages": ""})
```

MarinaBox provides three key LangGraph components:

* `mb_start_computer`: A LangGraph node that initializes and starts up an isolated desktop environment
* `mb_stop_computer`: A LangGraph node that safely shuts down the desktop session
* `mb_use_computer_tool`: A LangGraph tool that enables agents to interact with the desktop using natural language commands

## How It Works

1. **Start Computer Node**: The workflow begins with the `mb_start_computer` node, which creates and initializes an isolated desktop environment
2. **Computer Control Tool**: The agent uses the `mb_use_computer_tool` to send natural language commands to control the desktop
3. **Stop Computer Node**: When finished, the `mb_stop_computer` node ensures proper cleanup and shutdown of the session

## Monitoring Sessions

You can monitor the desktop session in your browser using the VNC port provided by MarinaBox. For embedding the live view in your application, see our [Embedding Guide](/guides/embedding-iframe).

## Example Usage

Here's a sample interaction with the agent:

```bash theme={null}
Enter your message: Please open Google Chrome and search for "LangGraph documentation"
# Agent will use the computer to:
# 1. Open Chrome
# 2. Navigate to Google
# 3. Search for LangGraph documentation

Enter your message: stop_computer
# This will cleanly shut down the session
```

***

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