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Last Updated: 3/7/2026

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LangGraph APIs

Production

LangSmith Deployment

This guide shows you how to deploy your agent to LangSmith 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.

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

​ Prerequisites

Before you begin, ensure you have the following:

​ 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. Then, push your code to the repository.

​ 2. Deploy to LangSmith

1

Navigate to LangSmith Deployment

Log in to LangSmith . In the left sidebar, select Deployments.

2

Create new deployment

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

3

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.

4

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.

​ 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:

  • Python
  • Rest API
  1. Install LangGraph SDK:

Copy

pip install langgraph-sdk pip  install langgraph-sdk
  1. Send a message to the agent:

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from langgraph_sdk import get_sync_client # or get_client for async 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") client = get_sync_client(url ="your-deployment-url", api_key ="your-langsmith-api-key") for chunk in client.runs.stream(for  chunk in client.runs.stream( None, # Threadless run  None, # Threadless run "agent", # Name of agent. Defined in langgraph.json.  "agent", # Name of agent. Defined in langgraph.json. input={ input ={ "messages": [{ "messages": [{ "role": "human",  "role": "human", "content": "What is LangGraph?",  "content": "What is LangGraph?", }], }], }, }, stream_mode="updates",  stream_mode = "updates",):): print(f"Receiving new event of type: {chunk.event}...")  print(f"Receiving new event of type: {chunk.event}...") print(chunk.data)  print(chunk.data) print("\n\n")  print(" \n\n ")

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

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