Deploy your app to Cloud ↗

    pip install langgraph-sdk
    ```

2. Send a message to the assistant (threadless run):

```python
    from langgraph_sdk import get_client

    client = get_client(url="your-deployment-url", api_key="your-langsmith-api-key")

    async for chunk in client.runs.stream(
        None,  # Threadless run
        "agent", # Name of assistant. Defined in langgraph.json.
        input={
            "messages": [{
                "role": "human",
                "content": "What is LangGraph?",
            }],
        },
        stream_mode="updates",
    ):
        print(f"Receiving new event of type: {chunk.event}...")
        print(chunk.data)
        print("\n\n")
    ```
  <span class="tab-end"></span>

  <span class="tab-start" data-tab-title="Python SDK (Sync)"></span>
1. Install the LangGraph Python SDK:

```shell
    pip install langgraph-sdk
    ```

2. Send a message to the assistant (threadless run):

```python
    from langgraph_sdk import get_sync_client

    client = get_sync_client(url="your-deployment-url", api_key="your-langsmith-api-key")

    for chunk in client.runs.stream(
        None,  # Threadless run
        "agent", # Name of assistant. Defined in langgraph.json.
        input={
            "messages": [{
                "role": "human",
                "content": "What is LangGraph?",
            }],
        },
        stream_mode="updates",
    ):
        print(f"Receiving new event of type: {chunk.event}...")
        print(chunk.data)
        print("\n\n")
    ```
  <span class="tab-end"></span>

  <span class="tab-start" data-tab-title="JavaScript SDK"></span>
1. Install the LangGraph JS SDK

```shell
    npm install @langchain/langgraph-sdk
    ```

2. Send a message to the assistant (threadless run):

```js
    const { Client } = await import("@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", // Assistant ID
        {
            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");
    }
    ```
  <span class="tab-end"></span>

  <span class="tab-start" data-tab-title="Rest API"></span>
```bash
    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\",
            \"input\": {
                \"messages\": [
                    {
                        \"role\": \"human\",
                        \"content\": \"What is LangGraph?\"
                    }
                ]
            },
            \"stream_mode\": \"updates\"
        }"
    ```
  <span class="tab-end"></span>
<span class="tab-group-end"></span>

## Next steps

You've successfully deployed your application to LangSmith Cloud. Here are some next steps:

* **Explore Studio**: Use [Studio](/langsmith/studio) to visualize and debug your graph interactively.
* **Monitor your app**: Set up [observability](/langsmith/observability) with traces, dashboards, and alerts.
* **Learn more about Cloud**: See the [complete Cloud setup guide](/langsmith/deploy-to-cloud) for all configuration options.

***


  <span class="callout-start" data-callout-type="note"></span>
[Edit this page on GitHub](https://github.com/langchain-ai/docs/edit/main/src/langsmith/deployment-quickstart.mdx) or [file an issue](https://github.com/langchain-ai/docs/issues/new/choose).
  <span class="callout-end"></span>

  <span class="callout-start" data-callout-type="note"></span>
[Connect these docs](/use-these-docs) to Claude, VSCode, and more via MCP for real-time answers.
  <span class="callout-end"></span>