前期准备：引入依赖

<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>org.springframework.ai</groupId>
      <artifactId>spring-ai-bom</artifactId>
      <version>0.8.1-SNAPSHOT</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>

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

1. ChatClient 对话

import org.springframework.ai.chat.ChatClient;
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 ChatClient chatClient;

    @GetMapping("/chat")
    public String generate(@RequestParam String message) {
        return chatClient.call(message);
    }

}

2. ImageClient 生成图片

@Autowired
private ImageClient imageClient;

@GetMapping("/image")
public String image(@RequestParam String message) {
    ImagePrompt imagePrompt = new ImagePrompt(message);
    ImageResponse imageResponse = imageClient.call(imagePrompt);
    return imageResponse.getResult().getOutput().getUrl();
}

3. OpenAiAudioTranscriptionClient 语音转文字

@Value("classpath:/jfk.flac")
private Resource audioFile;

@Autowired
private OpenAiAudioTranscriptionClient audioTranscriptionClient;


@GetMapping("/audio")
public String audio() {
    AudioTranscriptionPrompt transcriptionRequest = new AudioTranscriptionPrompt(audioFile);
    AudioTranscriptionResponse response = audioTranscriptionClient.call(transcriptionRequest);
    return response.getResult().getOutput();
}

传统语音识别 和 AI（深度学习）语音识别的区别

传统方法：
- 流程
- - 先把声音拆开 → 分析成一个个音节（就像拼音或音标）
  - 查字典 → 根据规则把音节组合成单词
  - 套模板 → 用预先写好的语言规则拼成一句话
- 缺点：
- - 口音一重就懵了（比如四川话说“是”听成“死”）
  - 背景吵就听不清
  - 必须提前喂给它很多针对性语料（方言就得专门训练）
AI 方法：
- 流程
- - 直接听完整句话（不拆音节）
  - 用大脑里的神经网络在海量真实录音中学过的经验来猜你说的内容
- 优点：
- - 不怕口音、方言（它见过太多了）
  - 背景有音乐、街道噪声也能识别
  - 一次训练就能识别多种语言
  - 还能自动加标点、断句，读起来更像人写的

4. EmbeddingClient 文本进行向量化

@Autowired
private EmbeddingClient embeddingClient;

@GetMapping("/embedding")
public List<Double> embedding(@RequestParam String message) {
    return embeddingClient.embed(message);
}

5. Function 工具

定义工具

import io.swagger.v3.oas.annotations.media.Schema;
import org.springframework.context.annotation.Description;
import org.springframework.stereotype.Component;

import java.time.LocalDateTime;
import java.util.function.Function;


@Component
@Description("获取指定地点的当前时间")
public class DateService implements Function<DateService.Request, DateService.Response> {

    public record Request(@Schema(description = "地点") String address) { }

    public record Response(String date) { }

    @Override
    public Response apply(Request request) {
        System.out.println(request.address);
        return new Response(String.format("%s的当前时间是%s", request.address, LocalDateTime.now()));
    }
}

调用方式一

@GetMapping("/function")
public String function(@RequestParam String message) {
    Prompt prompt = new Prompt(message, OpenAiChatOptions.builder().withFunction("dateService").build());
    Generation generation = chatClient.call(prompt).getResult();
    return (generation != null) ? generation.getOutput().getContent() : "";
}

调用方式二

@GetMapping("/functionCallback")
public String functionCallback(@RequestParam String message) {
    Prompt prompt = new Prompt(message, OpenAiChatOptions.builder().withFunctionCallbacks(
        List.of(FunctionCallbackWrapper.builder(new DateService())
                .withName("dateService")
                .withDescription("获取指定地点的当前时间").build())
    ).build());
    Generation generation = chatClient.call(prompt).getResult();
    return (generation != null) ? generation.getOutput().getContent() : "";
}

设置系统提示词后调用

@GetMapping("/functionCallback")
public String functionCallback(@RequestParam String message) {

    SystemMessage systemMessage = new SystemMessage("请用中文回答我");
    UserMessage userMessage = new UserMessage(message);

    Prompt prompt = new Prompt(List.of(systemMessage, userMessage), OpenAiChatOptions.builder().withFunctionCallbacks(
        List.of(FunctionCallbackWrapper.builder(new DateService())
                .withName("dateService")
                .withDescription("获取指定地点的当前时间").build())
    ).build());
    Generation generation = chatClient.call(prompt).getResult();
    return (generation != null) ? generation.getOutput().getContent() : "";
}