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LangGraph Integration

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

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Prerequisites

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

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Basic Setup

First, install the required dependencies:

pip install marinabox langgraph langchain-anthropic

Set up your Anthropic API key:

import os
os.environ['ANTHROPIC_API_KEY'] = "your-anthropic-api-key"

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Creating the Workflow

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

from marinabox import mb_start_browser, mb_stop_browser, mb_use_browser_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_browser_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_browser")

def call_model(state: Annotated[dict, InjectedState()]):
    input_message = input("Enter your message: ")
    if input_message != "stop_browser":
        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_browser", mb_start_browser)
workflow.add_node("agent", call_model)
workflow.add_node("tool_node", tool_node)
workflow.add_node("stop_browser", mb_stop_browser)
workflow.add_node("should_continue", should_continue)

# Add edges
workflow.add_edge(START, "start_browser")
workflow.add_edge("start_browser", "agent")
workflow.add_edge("tool_node", "agent")
workflow.add_edge("agent", "should_continue")
workflow.add_edge("stop_browser", END)

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

MarinaBox provides three key LangGraph components:

  • mb_start_browser: A LangGraph node that initializes and starts up an isolated browser session
  • mb_stop_browser: A LangGraph node that safely closes the browser session
  • mb_use_browser_tool: A LangGraph tool that enables agents to interact with the browser using natural language commands

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How It Works

  1. Start Browser Node: The workflow begins with the mb_start_browser node, which creates and initializes an isolated browser session
  2. Browser Control Tool: The agent uses the mb_use_browser_tool to send natural language commands to control the browser
  3. Stop Browser Node: When finished, the mb_stop_browser node ensures proper cleanup and closure of the session

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Monitoring Sessions

You can monitor the browser session in real-time using the VNC port provided by MarinaBox. For embedding the live view in your application, see our Embedding Guide.

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Example Usage

Here’s a sample interaction with the agent:

Enter your message: Please search for "LangGraph documentation" on Google
# Agent will:
# 1. Navigate to Google
# 2. Search for LangGraph documentation
# 3. Display the results

Enter your message: stop_browser
# This will cleanly close the browser session

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