Spring AI ChatClient API Tutorial

This tutorial will guide you through building a Spring Boot application that serves as a chat client using the ChatClient abstraction provided by Spring AI. This abstraction allows you to interact with different types of large language models (LLMs) like GPT-4 without coupling with the actual LLM model.

The ChatClient offers a fluent API for communicating with an AI Model. It supports both a synchronous and reactive programming model. Read more about ChatClient API here.

1. Setting Up the Project

Step 1: Create a New Spring Boot Project

You can create a new Spring Boot project using Spring Initializr or your preferred IDE. Ensure you include the necessary dependencies for Spring Web.

Using Spring Initializr:

  • Go to start.spring.io
  • Select:
    • Project: Maven Project
    • Language: Java
    • Spring Boot: 3.0.0 (or latest)
    • Dependencies: Spring Web
  • Generate the project and unzip it.

Step 2: Add spring-ai-openai-spring-boot-starter Dependency

In your project's pom.xml, add the following dependency:


2. Configuring the Spring Boot Starter

Step 1: Add API Key to Configuration

Create a application.properties or application.yml file in your src/main/resources directory and add your OpenAI API key.

For application.properties:


For application.yml:

    key: your_openai_api_key

Step 2: Create a Configuration Class

Create a new configuration class to set up the OpenAI client and the ChatClient abstraction.

package com.example.demo.config;

import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.ai.openai.OpenAiChatClient;
import org.springframework.ai.openai.OpenAiClient;

public class OpenAiConfig {

    public OpenAiClient openAiClient() {
        return new OpenAiClient();

    public ChatClient chatClient(OpenAiClient openAiClient) {
        return new OpenAiChatClient(openAiClient);

3. Implementing the Chat Client

Step 1: Create a Chat Service

Create a service class that will handle interactions with the ChatClient abstraction.

package com.example.demo.service;

import org.springframework.ai.openai.ChatClient;
import org.springframework.ai.openai.model.ChatRequest;
import org.springframework.ai.openai.model.ChatResponse;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;

public class ChatService {

    private ChatClient chatClient;

    public String chat(String userInput) {
        ChatRequest request = new ChatRequest();

        ChatResponse response = chatClient.sendMessage(request);
        return response.getReply();

Step 2: Create a Chat Controller

Create a controller to expose an endpoint for the chat functionality.

package com.example.demo.controller;

import com.example.demo.service.ChatService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;

public class ChatController {

    private ChatService chatService;

    public String chat(@RequestParam String userInput) {
        return chatService.chat(userInput);

4. Creating a Simple Frontend

For demonstration purposes, we will create a simple HTML page that allows users to interact with the chat client.

Step 1: Create an HTML File

Create an index.html file in the src/main/resources/static directory.

<!DOCTYPE html>
<html lang="en">
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>AI Chat Client</title>
    <h1>AI Chat Client</h1>
        <textarea id="userInput" rows="4" cols="50" placeholder="Type your message here..."></textarea><br>
        <button onclick="sendMessage()">Send</button>
    <div id="response"></div>

        function sendMessage() {
            const userInput = document.getElementById('userInput').value;
                .then(response => response.text())
                .then(data => {
                    document.getElementById('response').innerText = data;

5. Testing the Integration

Step 1: Run the Application

Run your Spring Boot application. Ensure the application starts without errors.

Step 2: Access the Chat Client

Open your browser and navigate to http://localhost:8080. You should see the simple chat client interface. Type a message and click "Send" to interact with the AI chatbot.


In this tutorial, you learned how to set up a Spring Boot application that serves as a chat client using OpenAI's API through the ChatClient abstraction. You created a service to handle interactions with the AI model, a controller to expose the chat endpoint, and a simple frontend for user interaction. This setup provides a foundation for building more complex and feature-rich AI chat applications. Explore further customization and enhancements to create a robust chat client.