<dependency>
    <groupId>com.alibaba.cloud.ai</groupId>
    <artifactId>spring-ai-starter-model-aliyun-dashscope</artifactId>
</dependency>

dependencies {
    implementation 'com.alibaba.cloud.ai:spring-ai-starter-model-aliyun-dashscope'
}

spring:
  ai:
    alibaba:
      dashscope:
        api-key: ${DASHSCOPE_API_KEY}
        chat:
          options:
            model: qwen-turbo
            temperature: 0.7
            max-tokens: 2000

spring.ai.alibaba.dashscope.api-key=${DASHSCOPE_API_KEY}
spring.ai.alibaba.dashscope.chat.options.model=qwen-turbo
spring.ai.alibaba.dashscope.chat.options.temperature=0.7
spring.ai.alibaba.dashscope.chat.options.max-tokens=2000

@Service
public class ChatService {
    private final ChatClient chatClient;

    public ChatService(ChatClient chatClient) {
        this.chatClient = chatClient;
    }

    public String chat(String message) {
        return chatClient.call(message);
    }

    public String chatWithPrompt(String userMessage) {
        Prompt prompt = new Prompt(new UserMessage(userMessage));
        ChatResponse response = chatClient.call(prompt);
        return response.getResult().getOutput().getContent();
    }
}

@Service
public class ChatService {
    private final StreamingChatClient streamingChatClient;

    public ChatService(StreamingChatClient streamingChatClient) {
        this.streamingChatClient = streamingChatClient;
    }

    public Flux<String> streamChat(String message) {
        return streamingChatClient.stream(message)
            .map(response -> response.getResult().getOutput().getContent());
    }
}

spring:
  ai:
    alibaba:
      dashscope:
        chat:
          options:
            model: qwen-max  # 使用最强模型
            temperature: 0.7
            max-tokens: 2000

@Service
public class PromptService {
    private final PromptTemplate promptTemplate;

    public PromptService() {
        this.promptTemplate = new PromptTemplate(
            "请用{style}风格回答以下问题：{question}"
        );
    }

    public String generatePrompt(String style, String question) {
        Map<String, Object> variables = Map.of(
            "style", style,
            "question", question
        );
        return promptTemplate.render(variables);
    }
}

@Service
public class ChatService {
    private final ChatClient chatClient;
    private final PromptTemplate promptTemplate;

    public ChatService(ChatClient chatClient) {
        this.chatClient = chatClient;
        this.promptTemplate = new PromptTemplate(
            "请用{style}风格回答以下问题：{question}"
        );
    }

    public String chatWithStyle(String style, String question) {
        Prompt prompt = promptTemplate.create(Map.of(
            "style", style,
            "question", question
        ));
        ChatResponse response = chatClient.call(prompt);
        return response.getResult().getOutput().getContent();
    }
}

spring:
  ai:
    alibaba:
      dashscope:
        embedding:
          options:
            model: text-embedding-V1

@Service
public class EmbeddingService {
    private final EmbeddingClient embeddingClient;

    public EmbeddingService(EmbeddingClient embeddingClient) {
        this.embeddingClient = embeddingClient;
    }

    public List<Double> embed(String text) {
        EmbeddingResponse response = embeddingClient.embedForResponse(
            List.of(text)
        );
        return response.getResult().getOutput();
    }

    public List<List<Double>> embedBatch(List<String> texts) {
        EmbeddingResponse response = embeddingClient.embedForResponse(texts);
        return response.getResult().getOutput();
    }
}

@Service
public class ConversationService {
    private final ChatClient chatClient;
    private final List<Message> conversationHistory = new ArrayList<>();

    public ConversationService(ChatClient chatClient) {
        this.chatClient = chatClient;
    }

    public String chat(String userMessage) {
        conversationHistory.add(new UserMessage(userMessage));

        Prompt prompt = new Prompt(conversationHistory);
        ChatResponse response = chatClient.call(prompt);
        String assistantMessage = response.getResult().getOutput().getContent();

        conversationHistory.add(new AssistantMessage(assistantMessage));
        return assistantMessage;
    }

    public void clearHistory() {
        conversationHistory.clear();
    }
}

@Service
public class ChatService {
    private final ChatClient chatClient;

    public String chat(String message) {
        try {
            return chatClient.call(message);
        } catch (Exception e) {
            // 处理错误
            log.error("Chat error", e);
            return "抱歉，处理请求时出现错误";
        }
    }
}

<!-- Spring AI Alibaba DashScope -->
<dependency>
    <groupId>com.alibaba.cloud.ai</groupId>
    <artifactId>spring-ai-starter-model-aliyun-dashscope</artifactId>
</dependency>

<!-- Spring Boot Web (可选，用于 REST API) -->
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-web</artifactId>
</dependency>

spring:
  ai:
    alibaba:
      dashscope:
        api-key: ${DASHSCOPE_API_KEY}
        chat:
          options:
            model: qwen-turbo
            temperature: 0.7
            max-tokens: 2000
            top-p: 0.9
        embedding:
          options:
            model: text-embedding-V1