Quickstart

Prerequisites#

Before you begin, you'll need the following:

An OpenAI API key
Node.js 20+
Your favorite package manager
(Optional) A LangSmith API key - only required if using an existing LangGraph agent

Getting started#

Create a free account#

Sign up for a free developer account on our Enterprise Intelligence Platform to get a license key. You'll use it later to enable persistent threads, observability, and the inspector.

Choose your starting point#

You can either start fresh with our starter template or integrate CopilotKit into your existing LangGraph agent.

Start from scratch

Get started quickly with our ready-to-go starter application.

Use an existing agent

I already have a LangGraph agent and want to add CopilotKit.

Run our CLI#

npx copilotkit@latest create

The CLI walks you through:

Project name
Enterprise Intelligence Platform — persistent threads, observability, and the inspector. Choose Yes to scaffold a project pre-wired for the platform (the CLI walks you through sign-up, or you can create an account first), or No for a standard LangGraph setup.
Framework — pick LangGraph (Python) or LangGraph (JavaScript).

Install dependencies#

npm install

Configure your environment#

Create a .env file in your agent directory and add your OpenAI API key:

.env

OPENAI_API_KEY=your_openai_api_key

What about other models?

The starter template is configured to use OpenAI's GPT-4o by default, but you can modify it to use any language model supported by LangGraph.

Start the development server#

npm run dev

pnpm dev

yarn dev

bun dev

This will start both the UI and agent servers concurrently.

🎉 Start chatting!#

Your AI agent is now ready to use! Try asking it some questions:

Can you tell me a joke?

Can you help me understand AI?

What do you think about React?

Troubleshooting

If you're having connection issues, try using 0.0.0.0 or 127.0.0.1 instead of localhost
Make sure your agent folder contains a langgraph.json file
In the langgraph.json file, reference the path to a .env file
Check that your OpenAI API key is correctly set in the .env file
If using an existing agent, ensure your LangSmith API key is also configured
Make sure you're in the same folder as your langgraph.json file when running the langgraph dev command
"graph is nullish" error (JavaScript starters): This means the LangGraph CLI couldn't load your graph. Ensure the export name in your langgraph.json matches your code (e.g., "starterAgent": "./src/agent.ts:graph" requires export const graph = ... in agent.ts). Also verify all dependencies are installed with npm install in your agent directory.
Make sure the runtime endpoint path matches the runtimeUrl in your CopilotKit provider

Deploying to AWS?#

If you're planning to deploy your LangGraph agent to AWS Bedrock AgentCore, see the AgentCore deploy guide.

What's next?#

Now that you have your basic agent setup, explore these advanced features:

Implement Human in the Loop

Allow your users and agents to collaborate together on tasks.

Utilize Shared State

Learn how to synchronize your agent's state with your UI's state, and vice versa.

Add some generative UI

Render your agent's progress and output in the UI.

Setup frontend actions

Give your agent the ability to call frontend tools, directly updating your application.