package com.ard.agent.service;

import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.chat.prompt.PromptTemplate;
import org.springframework.ai.document.Document;
import org.springframework.ai.vectorstore.SearchRequest;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.stereotype.Service;
import reactor.core.publisher.Flux;

import java.util.List;
import java.util.stream.Collectors;

@Slf4j
@Service
public class RagChatService {
    @Resource
    private ChatClient chatClient;
    @Resource
    private VectorStore vectorStore;

    /**
     * RAG问答流式方法（推荐使用）
     */
    public Flux<String> chatStream(String question) {
        log.info("收到RAG流式请求，question={}", question);

        // 1. 向量检索：召回Top3相关文档（同步执行）
        List<org.springframework.ai.document.Document> similarDocs = vectorStore.similaritySearch(
                SearchRequest.builder()
                        .query(question)
                        .topK(3)
                        .build()
        );

        // 2. 拼接上下文
        String context = similarDocs.stream()
                .map(doc -> "【参考内容】：" + doc.getText())
                .collect(Collectors.joining("\n\n"));

        log.info("检索到{}条相关文档，开始流式生成回答", similarDocs.size());

        // 3. 构建Prompt模板
        String promptText = """
                你是专业知识库助手，基于以下参考内容回答用户问题，禁止编造，答案必须准确：
                {context}
                用户问题：{question}
                """;
        PromptTemplate promptTemplate = new PromptTemplate(promptText);
        promptTemplate.add("context", context);
        promptTemplate.add("question", question);
        Prompt prompt = promptTemplate.create();

        // 4. 流式调用大模型
        return chatClient.prompt(prompt)
                .stream()
                .content()
                .doOnNext(chunk -> log.debug("输出数据块: {}", chunk))
                .doOnComplete(() -> log.info("流式输出完成"))
                .doOnError(error -> log.error("流式输出出错: {}", error.getMessage()));
    }

}