Spring AI ChatClient API Tutorial

3 min readAug 10, 2024

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.

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:

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-openai-spring-boot-starter</artifactId>
    <version>1.0.0</version>
</dependency>

Step 3: 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.

Check out how I can access the ChatGPT API.

For application.properties:

openai.api.key=your_openai_api_key

For application.yml:

openai:
  api:
    key: your_openai_api_key

Step 4: 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;

@Configuration
public class OpenAiConfig {

    @Bean
    public OpenAiClient openAiClient() {
        return new OpenAiClient();
    }

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

Step 5: 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;

@Service
public class ChatService {

    @Autowired
    private ChatClient chatClient;

    public String chat(String userInput) {
        ChatRequest request = new ChatRequest();
        request.setMessage(userInput);
        ChatResponse response = chatClient.sendMessage(request);
        return response.getReply();
    }
}

Step 6: 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;

@RestController
public class ChatController {

    @Autowired
    private ChatService chatService;

    @GetMapping("/chat")
    public String chat(@RequestParam String userInput) {
        return chatService.chat(userInput);
    }
}

Step 7: Create an HTML File

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

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

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

    <script>
        function sendMessage() {
            const userInput = document.getElementById('userInput').value;
            fetch(`/chat?userInput=${encodeURIComponent(userInput)}`)
                .then(response => response.text())
                .then(data => {
                    document.getElementById('response').innerText = data;
                });
        }
    </script>
</body>
</html>

Step 8: Run the Application

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

Step 9: 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.

Conclusion

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.