Deployment

To deploy your LangGraph agent, create and configure a LangGraph app. This setup supports both local development and production deployments.

Features:

• 🖥️ Local server for development
• 🧩 Studio Web UI for visual debugging
• ☁️ Cloud and 🔧 self-hosted deployment options
• 📊 LangSmith integration for tracing and observability

:::info[Requirements]

• ✅ You must have a LangSmith account. You can sign up for free and get started with the free tier.

Create a LangGraph app

npm install -g create-langgraph
create-langgraph path/to/your/app

Follow the prompts and select New LangGraph Project. This will create an empty LangGraph project. You can modify it by replacing the code in src/agent/graph.ts with your agent code. For example:

import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { initChatModel } from "langchain/chat_models/universal";
import { tool } from "@langchain/core/tools";
import { z } from "zod";

const getWeather = tool(
  async (input: { city: string }) => {
    return `It's always sunny in ${input.city}!`;
  },
  {
    name: "getWeather",
    schema: z.object({
      city: z.string().describe("The city to get the weather for"),
    }),
    description: "Get weather for a given city.",
  }
);

const llm = await initChatModel("anthropic:claude-3-7-sonnet-latest");
// make sure to export the graph that will be used in the LangGraph API server
// highlight-next-line
export const graph = createReactAgent({
  llm,
  tools: [getWeather],
  prompt: "You are a helpful assistant"
})

Install dependencies

In the root of your new LangGraph app, install the dependencies:

yarn
# install these to use initChatModel with Anthropic
yarn add langchain
yarn add @langchain/anthropic

Create an .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...
ANTHROPIC_API_KEY=sk-

Launch LangGraph server locally

npx @langchain/langgraph-cli dev

This will start up the LangGraph API server locally. If this runs successfully, you should see something like:

Welcome to LangGraph.js!

• 🚀 API: http://localhost:2024

• 🎨 Studio UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024

LangGraph Studio Web UI

LangGraph Studio Web is a specialized UI that you can connect to LangGraph API server to enable visualization, interaction, and debugging of your application locally. Test your graph in the LangGraph Studio Web UI by visiting the URL provided in the output of the npx @langchain/langgraph-cli dev command.

• LangGraph Studio Web UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024

Deployment

Once your LangGraph app is running locally, you can deploy it using LangSmith Deployment or self-hosted options. Refer to the deployment options guide for detailed instructions on all supported deployment models.