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

# LangSmith Deployment

This guide shows you how to deploy your agent to **[LangSmith Cloud](/langsmith/deploy-to-cloud)**, a fully managed hosting platform designed for agent workloads. With Cloud deployment, you can deploy directly from your GitHub repository—LangSmith handles the infrastructure, scaling, and operational concerns.

Traditional hosting platforms are built for stateless, short-lived web applications. LangSmith Cloud is **purpose-built for stateful, long-running agents** that require persistent state and background execution.

<Tip>
  LangSmith offers multiple deployment options beyond Cloud, including deploying with a [control plane (hybrid/self-hosted)](/langsmith/deploy-with-control-plane) or as [standalone servers](/langsmith/deploy-standalone-server). For more information, refer to the [Deployment overview](/langsmith/deployment).
</Tip>

## Prerequisites

Before you begin, ensure you have the following:

* A [GitHub account](https://github.com/)
* A [LangSmith account](https://smith.langchain.com?utm_source=docs\&utm_medium=cta\&utm_campaign=langsmith-signup\&utm_content=oss-langgraph-deploy) (free to sign up)

## Deploy your agent

### 1. Create a repository on GitHub

Your application's code must reside in a GitHub repository to be deployed on LangSmith. Both public and private repositories are supported. For this quickstart, first make sure your app is LangGraph-compatible by following the [local server setup guide](/oss/javascript/langgraph/studio#set-up-local-agent-server). Then, push your code to the repository.

### 2. Deploy to LangSmith

<Steps>
  <Step title="Navigate to LangSmith Deployment">
    Log in to [LangSmith](https://smith.langchain.com?utm_source=docs\&utm_medium=cta\&utm_campaign=langsmith-signup\&utm_content=oss-langgraph-deploy). In the left sidebar, select **Deployments**.
  </Step>

  <Step title="Create new deployment">
    Click the **+ New Deployment** button. A pane will open where you can fill in the required fields.
  </Step>

  <Step title="Link repository">
    If you are a first time user or adding a private repository that has not been previously connected, click the **Add new account** button and follow the instructions to connect your GitHub account.
  </Step>

  <Step title="Deploy repository">
    Select your application's repository. Click **Submit** to deploy. This may take about 15 minutes to complete. You can check the status in the **Deployment details** view.
  </Step>
</Steps>

### 3. Test your application in Studio

Once your application is deployed:

1. Select the deployment you just created to view more details.
2. Click the **Studio** button in the top right corner. Studio will open to display your graph.

### 4. Get the API URL for your deployment

1. In the **Deployment details** view in LangGraph, click the **API URL** to copy it to your clipboard.
2. Click the `URL` to copy it to the clipboard.

### 5. Test the API

You can now test the API:

<Tabs>
  <Tab title="TypeScript">
    1. Install LangGraph SDK:

    ```shell theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
    npm install @langchain/langgraph-sdk
    ```

    2. Send a message to the agent:

    ```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
    import { Client } from "@langchain/langgraph-sdk";

    const client = new Client({ apiUrl: "your-deployment-url", apiKey: "your-langsmith-api-key" });

    const streamResponse = client.runs.stream(
      null,    // Threadless run
      "agent", // Name of agent. Defined in langgraph.json.
      {
        input: {
          "messages": [
            { "role": "user", "content": "What is LangGraph?"}
          ]
        },
        streamMode: "messages",
      }
    );

    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");
    }
    ```
  </Tab>

  <Tab title="Rest API">
    ```bash theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
    curl -s --request POST \
        --url <DEPLOYMENT_URL>/runs/stream \
        --header 'Content-Type: application/json' \
        --header "X-Api-Key: <LANGSMITH API KEY> \
        --data "{
            \"assistant_id\": \"agent\", `# Name of agent. Defined in langgraph.json.`
            \"input\": {
                \"messages\": [
                    {
                        \"role\": \"human\",
                        \"content\": \"What is LangGraph?\"
                    }
                ]
            },
            \"stream_mode\": \"updates\"
        }"
    ```
  </Tab>
</Tabs>

***

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