《实战AI大模型》DeepSeek API实战-第03节：基于SpringAI实现智能问答系统

@SpringBootApplication
public class QaApplication {

    public static void main(String[] args) {
        SpringApplication.run(QaApplication.class, args);
    }

    @Bean
    public ChatClient chatClient(OpenAiChatModel model){
        return ChatClient
                .builder(model)
                .build();
    }

    @Bean
    public VectorStore vectorStore(EmbeddingModel embeddingModel) {
        VectorStore vectorStore = SimpleVectorStore.builder(embeddingModel).build();

        // 构建测试数据
        List<Document> documents =
                List.of(new Document("Hello Spring AI"),
                        new Document("Hello Spring Boot"));
        // 添加到向量数据库
        vectorStore.add(documents);

        return vectorStore;
    }
}

@Data
public class QuestionRequest {
    private String question;
    private String sessionId;
}

@Service
public class QaService {

    private final ChatClient chatClient;
    private final PromptTemplate promptTemplate;

    @Autowired
    public QaService(ChatClient chatClient) {
        this.chatClient = chatClient;
        // 创建一个提示模板，指导AI如何回答问题
        this.promptTemplate = new PromptTemplate("""
            你是一个智能问答助手，请简洁、准确地回答用户的问题。
            如果你不知道答案，请直接说不知道，不要编造信息。
            
            用户问题: {question}
            
            回答:
            """);
    }

    public String getAnswer(String question) {
        // 准备模板参数
        Map<String, Object> parameters = new HashMap<>();
        parameters.put("question", question);

        // 创建提示
        Prompt prompt = promptTemplate.create(parameters);

        // 调用AI获取回答
        return chatClient.prompt(prompt).call().content();
    }
}

@Service
public class ConversationService {

    private final ChatClient chatClient;

    private final Map<String, List<Message>> conversations = new ConcurrentHashMap<>();

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

    public String chat(String sessionId, String userMessage) {
        // 获取或创建会话历史
        List<Message> messages = conversations.computeIfAbsent(sessionId, k -> new ArrayList<>());

        // 添加用户消息
        messages.add(new UserMessage(userMessage));

        // 创建带有历史上下文的提示
        Prompt prompt = new Prompt(messages);

        // 调用AI
        String response = chatClient.prompt(prompt).call().content();

        // 保存AI回复
        messages.add(new AssistantMessage(response));

        // 管理会话长度，避免超出Token限制
        if (messages.size() > 10) {
            messages = messages.subList(messages.size() - 10, messages.size());
            conversations.put(sessionId, messages);
        }

        return response;
    }

    public void clearConversation(String sessionId) {
        conversations.remove(sessionId);
    }
}