Deployment of ChatKit Agent

Deployment with ChatKit

Make sure the necessary accounts and tools are available before you begin creating your ChatKit interface:

1.Node.js (at least version 20)

To execute the ChatKit starting application, this is necessary.

Verify the version:

node --version

Get it from nodejs.org if you haven't already.

2.npm (comes with Node.js)

Verify the version:

npm --version

3. Code Editor (VS Code is advised)

For optimal results, download from the official site.

4. OpenAI Account To install an agent, you must have access to the API.

Register at openai platform

5. Agent in Agent Builder

You must have an agent before you can use ChatKit.

Make it at platform.openai.com/agent-builder.

Requirements that are optional (Only required for the GitHub + Vercel approach)

Installing Git

Account on GitHub

Make one at github.com.

Now after this, you can start building.

What You Discover Here

At the end of this article, you exactly know what Chatkit is and when to use it.

How AgentKit and ChatKit are different

The operation of the deployment architecture

How to get the Workflow ID and deploy your agents

How to set up and duplicate the ChatKit beginning template

How to use ChatKit Studio to create unique user interface layouts

How to link your designs to the code itself

How to put the finished interface into production

How to set up domain allowlists for security

How to provide pilot testers access to your prototype

Everything you discover will enable you to create a professional chat interface that is ready for production.

ChatKit Overview

ChatKit: What is it?

Your website, dashboard, customer portal, mobile application, or internal tools may all incorporate ChatKit, a stunningly designed, pre-made chat interface.

Consider ChatKit as a high-end chat widget that is driven only by your OpenAI agent rather than human operators, akin to the support chat boxes found on contemporary websites.

Message bubbles are included with ChatKit.

Streamed answers

Support for uploading files

UI with a theme (light/dark mode)

Responsiveness on mobile

History of conversations

The capacity for custom branding

These features save days or even weeks of development time because they all function right out of the box.

A Basic Comparative Analysis

Let's say you wish to start a café:

Every single chair, table, and dish might be constructed by you.

Alternatively, you may purchase well-made, functional furniture and concentrate on providing customer service.

That prefabricated "furniture" is ChatKit.

All you have to do is link it to your AI agent and alter its appearance.

Why Make Use of ChatKit?

ChatKit provides an amazing blend of quality, speed, and personalisation.

Quick Development

Instead of coding everything by hand, set up a whole chat system in a matter of minutes.

Expert Design

The interface appears sleek, contemporary, and production-ready.

Completely Adaptable

Align the colours, typefaces, logos, and styles of your brand.

Rich in Features

Includes structured outputs, markdown answers, file uploads, typing indicators, and more.

Compatible with All Devices

automatically adjusts to computers, tablets, and mobile devices.

Expandable

OpenAI uses Agent Builder + Responses API to control backend scalability.

AgentKit vs ChatKit: A Clear Distinction

Because they cooperate, many people confuse these two, yet they have distinct functions.

AgentKit

The whole toolset for creating AI bots is called AgentKit. It consists of:

Builder Agent

Integrations and tools

API Responses

AgentKit is the entire ecosystem.

ChatKit

ChatKit is merely the layer of the chat interface that you use to interact with your agent.

ChatKit is AgentKit's user interface.

Real-World Illustration

The kitchen where the food is prepared is called Agent Builder.

The dining area where everything is designed is called ChatKit Studio.

The server delivering meals to customers using the ChatKit app

Comprehending Deployment Architecture

There are three primary components to the ChatKit ecosystem.

Where your agent resides is called Agent Builder.

The visual interface is designed in ChatKit Studio.

The code that links the UI and agent is called the ChatKit Starter App.

There are numerous advantages to this separation.

Without changing the coding, designers can enhance the user interface.

Features can be incorporated by developers without compromising design.

OpenAI manages API scaling and response streaming.

It is very simple to deploy to platforms like Vercel.

Getting the Workflow ID and Deploying Your Agent

Your agent needs to be deployed before you can connect ChatKit.

Procedure:

Builder for Open Agents

Select "Deploy."

A Workflow ID is created by OpenAI.

Use environment variables to store this value in a safe location.

Through the Responses API, this ID links ChatKit → Your agent.

Cloning and Setting Up the ChatKit Starter Program

On GitHub, OpenAI offers a fully functional beginner project.

1. Git clone https://github.com/openai/chatkit-starter-app
2. Open the ZIP extract in Visual Studio Code after downloading it.

Important Files:

Add your Workflow ID to env.local.

/src/app/page.tsx → primary ChatKit connection

/public → resources, including logos

After setup: npm install, npm run dev

The ChatKit user interface will now operate locally.

Using ChatKit Studio to Design Your Chat Interface

With ChatKit Studio, you can: Modify colour schemes

Modify the styles of message bubbles

Include conversation starters.

Make different layouts.

Add brand components

Preview the mobile and desktop versions

After you're pleased, export your JSON configuration and add it to your ChatKit application.

Production Deployment (Vercel Suggested)

Either of these can be used for deployment:

Method 1: Vercel Dashboard → GitHub → One-click deployment

Method 2: Use the Vercel CLI to upload the project directly.

In the Vercel environment settings, add your Workflow ID.

For security, create a domain allowlist within the OpenAI platform.

Last Action: Distribute to Pilot Testers

After deployment:

Give testers the URL.

Gather comments

Modify the user interface or agent behaviour

Enhance your conversation starters

Release the completed version.