Alpha Notice: These docs cover the v1-alpha release. Content is incomplete and subject to change.For the latest stable version, see the current LangGraph Python or LangGraph JavaScript docs.
This guide shows you how to run a LangGraph application locally.

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Prerequisites

Before you begin, ensure you have the following:

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1. Install the LangGraph CLI

npx @langchain/langgraph-cli

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2. Create a LangGraph app 🌱

Create a new app from the new-langgraph-project-js template. This template demonstrates a single-node application you can extend with your own logic. 
npm create langgraph

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3. Install dependencies

In the root of your new LangGraph app, install the dependencies in edit mode so your local changes are used by the server: 
cd path/to/your/app
npm install

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4. Create a .env file

You will find a .env.example in the root of your new LangGraph app. Create a .env file in the root of your new LangGraph app and copy the contents of the .env.example file into it, filling in the necessary API keys: 
LANGSMITH_API_KEY=lsv2...

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5. Launch LangGraph Server 🚀

Start the LangGraph API server locally: 
npx @langchain/langgraph-cli dev
Sample output: 
>    Ready!
>
>    - API: [http://localhost:2024](http://localhost:2024/)
>
>    - Docs: http://localhost:2024/docs
>
>    - LangGraph Studio Web UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024
The langgraph dev command starts LangGraph Server in an in-memory mode. This mode is suitable for development and testing purposes. For production use, deploy LangGraph Server with access to a persistent storage backend. For more information, see Deployment options.

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6. Test your application in LangGraph Studio

LangGraph Studio is a specialized UI that you can connect to LangGraph API server to visualize, interact with, and debug your application locally. Test your graph in LangGraph Studio by visiting the URL provided in the output of the langgraph dev command: 
>    - LangGraph Studio Web UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024
For a LangGraph Server running on a custom host/port, update the baseURL parameter.

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7. Test the API

  1. Install the LangGraph JS SDK:
npm install @langchain/langgraph-sdk
  1. Send a message to the assistant (threadless run):
const { Client } = await import("@langchain/langgraph-sdk");

// only set the apiUrl if you changed the default port when calling langgraph dev
const client = new Client({ apiUrl: "http://localhost:2024"});

const streamResponse = client.runs.stream(
    null, // Threadless run
    "agent", // Assistant ID
    {
        input: {
            "messages": [
                { "role": "user", "content": "What is LangGraph?"}
            ]
        },
        streamMode: "messages-tuple",
    }
);

for await (const chunk of streamResponse) {
    console.log(`Receiving new event of type: ${chunk.event}...`);
    console.log(JSON.stringify(chunk.data));
    console.log("\n\n");
}

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Next steps

Now that you have a LangGraph app running locally, take your journey further by exploring deployment and advanced features: