Azure OpenAI 聊天

@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();

这是一张水果篮的图片，设计简单。篮子由金属制成，带有弯曲的金属丝边缘，
形成一个开放的结构，使水果可以从各个角度看到。篮子里有两个
黄色的香蕉放在一个红色苹果上面。香蕉有点过熟，这可以从
香蕉皮上的棕色斑点看出。篮子在顶部有一个金属环，可能是用来
提篮子的把手。篮子放在一个平面上，背景是中性的，可以清晰地
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=YOUR_API_KEY
spring.ai.azure.openai.endpoint=YOUR_ENDPOINT
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。"));