Deployment

When you are ready to deploy your LangGraph agent to production, choose a hosting model that fits your stack. LangSmith Cloud provides fully managed infrastructure for stateful, long-running agents with persistent state and background execution.

LangSmith offers multiple deployment options beyond Cloud, including hybrid, standalone servers, and self-hosted with control plane. For more information, see the LangSmith Deployment overview.

LangSmith Cloud

This section walks through deploying your agent to LangSmith Cloud from a GitHub repository. LangSmith handles infrastructure, scaling, and operational concerns.

Prerequisites

Before you begin, ensure you have the following:

A GitHub account (opens in a new tab)
A LangSmith account (opens in a new tab) (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 (opens in a new tab). Then, push your code to the repository.

2. Deploy to LangSmith

Log in to [LangSmith](https://smith.langchain.com). In the left sidebar, select **Deployments**.


Click the **+ New Deployment** button. A pane will open where you can fill in the required fields.


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.


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.

3. Test your application in Studio

Once your application is deployed:

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

4. Get the API URL for your deployment

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

5. Test the API

You can now test the API:

Python

Install LangGraph SDK:

pip install langgraph-sdk

Send a message to the agent:

from langgraph_sdk import get_sync_client # or get_client for async
 
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 agent. 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")

Rest API

curl -s --request POST \
    --url /runs/stream \
    --header 'Content-Type: application/json' \
    --header "X-Api-Key:  \
    --data "{
        \"assistant_id\": \"agent\", `# Name of agent. Defined in langgraph.json.`
        \"input\": {
            \"messages\": [
                {
                    \"role\": \"human\",
                    \"content\": \"What is LangGraph?\"
                }
            ]
        },
        \"stream_mode\": \"updates\"
    }"

Choosing between Graph and Functional APIs Event streaming