Azure OpenAI 聊天

spring.ai.azure.openai.chat.options.deployment-name=<我的部署名称>

@Configuration
public class AzureOpenAiConfig {

    @Bean
    public AzureOpenAIClientBuilderCustomizer responseTimeoutCustomizer() {
        return openAiClientBuilder -> {
            HttpClientOptions clientOptions = new HttpClientOptions()
                    .setResponseTimeout(Duration.ofMinutes(5));
            openAiClientBuilder.httpClient(HttpClient.createDefault(clientOptions));
        };
    }

}

ChatResponse response = chatModel.call(
    new Prompt(
        "生成 5 个著名海盗的名字。",
        AzureOpenAiChatOptions.builder()
            .deploymentName("gpt-4o")
            .temperature(0.4)
        .build()
    ));

URL url = new URL("https://docs.spring.io/spring-ai/reference/_images/multimodal.test.png");
String response = ChatClient.create(chatModel).prompt()
        .options(AzureOpenAiChatOptions.builder().deploymentName("gpt-4o").build())
        .user(u -> u.text("解释一下你在这张图片上看到了什么？").media(MimeTypeUtils.IMAGE_PNG, this.url))
        .call()
        .content();

这是一张水果盘的图片，设计简单。碗由金属制成，带有弯曲的金属丝边缘，
形成开放式结构，可以从各个角度看到水果。碗里，两根香蕉放在一个看起来像是红苹果的水果上面。
香蕉有点过熟，表皮上有褐色的斑点。碗的顶部有一个金属环，可能是用来提携的。
碗放在一个平坦的表面上，背景颜色中性，可以清楚地看到里面的水果。

Resource resource = new ClassPathResource("multimodality/multimodal.test.png");

String response = ChatClient.create(chatModel).prompt()
    .options(AzureOpenAiChatOptions.builder()
    .deploymentName("gpt-4o").build())
    .user(u -> u.text("解释一下你在这张图片上看到了什么？")
    .media(MimeTypeUtils.IMAGE_PNG, this.resource))
    .call()
    .content();

spring.ai.azure.openai.api-key=你的API密钥
spring.ai.azure.openai.endpoint=你的终结点
spring.ai.azure.openai.chat.options.deployment-name=gpt-4o
spring.ai.azure.openai.chat.options.temperature=0.7

@RestController
public class ChatController {

    private final AzureOpenAiChatModel chatModel;

    @Autowired
    public ChatController(AzureOpenAiChatModel chatModel) {
        this.chatModel = chatModel;
    }

    @GetMapping("/ai/generate")
    public Map generate(@RequestParam(value = "message", defaultValue = "给我讲个笑话") String message) {
        return Map.of("generation", this.chatModel.call(message));
    }

    @GetMapping("/ai/generateStream")
    public Flux<ChatResponse> generateStream(@RequestParam(value = "message", defaultValue = "给我讲个笑话") String message) {
        Prompt prompt = new Prompt(new UserMessage(message));
        return this.chatModel.stream(prompt);
    }
}

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-azure-openai</artifactId>
</dependency>

dependencies {
    implementation 'org.springframework.ai:spring-ai-azure-openai'
}

var openAIClientBuilder = new OpenAIClientBuilder()
  .credential(new AzureKeyCredential(System.getenv("AZURE_OPENAI_API_KEY")))
  .endpoint(System.getenv("AZURE_OPENAI_ENDPOINT"));

var openAIChatOptions = AzureOpenAiChatOptions.builder()
  .deploymentName("gpt-4o")
  .temperature(0.4)
  .maxTokens(200)
  .build();

var chatModel = AzureOpenAiChatModel.builder()
                .openAIClientBuilder(openAIClientBuilder)
                .defaultOptions(openAIChatOptions)
                .build();

ChatResponse response = chatModel.call(
  new Prompt("生成 5 个著名海盗的名字。"));

// 或使用流式响应
Flux<ChatResponse> streamingResponses = chatModel.stream(
  new Prompt("生成 5 个著名海盗的名字。"));