package com.njuzr.eaibackend.service.impl;

import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.njuzr.eaibackend.mapper.StudentAssignmentMapper;
import com.njuzr.eaibackend.po.TextAnalysis;
import com.njuzr.eaibackend.service.TextAnalysisService;
import edu.stanford.nlp.simple.Document;
import edu.stanford.nlp.simple.Sentence;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.mongodb.core.MongoTemplate;
import org.springframework.data.mongodb.core.query.Criteria;
import org.springframework.data.mongodb.core.query.Query;
import org.springframework.http.HttpEntity;
import org.springframework.http.HttpHeaders;
import org.springframework.http.HttpStatus;
import org.springframework.http.MediaType;
import org.springframework.http.ResponseEntity;
import org.springframework.scheduling.annotation.Async;
import org.springframework.stereotype.Service;
import org.springframework.util.LinkedMultiValueMap;
import org.springframework.util.MultiValueMap;
import org.springframework.web.client.RestTemplate;

import java.util.ArrayList;
import java.util.List;

/**
 * 文本分析服务实现类
 * 提供异步文本分析功能，包括分句、分词和词汇级别分析
 * 
 * @author AI Assistant
 * @date 2025-01-27
 */
@Slf4j
@Service
public class TextAnalysisServiceImpl implements TextAnalysisService {

    private final StudentAssignmentMapper studentAssignmentMapper;
    private final MongoTemplate mongoTemplate;
    private final ObjectMapper objectMapper;
    private final RestTemplate restTemplate;

    // 外部API配置
    private static final String WORD_LEVEL_API_URL = "https://laurenceanthony.net/software/wordfamilyfinder/get_result.php";
    private static final String DATABASE = "basewords_130.db";
    private static final String CORPUS = "bnc_freq";
    private static final int MAX_RETRY_COUNT = 5;
    private static final long RETRY_DELAY_MS = 500;

    @Autowired
    public TextAnalysisServiceImpl(StudentAssignmentMapper studentAssignmentMapper,
            MongoTemplate mongoTemplate) {
        this.studentAssignmentMapper = studentAssignmentMapper;
        this.mongoTemplate = mongoTemplate;
        this.objectMapper = new ObjectMapper();
        this.restTemplate = new RestTemplate();
    }

    /**
     * 异步分析并保存文本内容
     * 该方法会在后台异步执行，不会阻塞主流程
     * 
     * @param studentId    学生ID
     * @param assignmentId 作业ID
     */
    @Async("textAnalysisTaskExecutor")
    @Override
    public void analyzeAndSaveTextContentAsync(Long studentId, Long assignmentId) {
        log.info("开始异步分析文本内容 - studentId: {}, assignmentId: {}", studentId, assignmentId);

        try {
            // 1. 获取最新的text_content
            String textContent = studentAssignmentMapper.getTextContent(studentId, assignmentId);
            if (textContent == null || textContent.trim().isEmpty()) {
                log.warn("文本内容为空，跳过分析 - studentId: {}, assignmentId: {}", studentId, assignmentId);
                return;
            }

            log.info("获取到文本内容，长度: {} - studentId: {}, assignmentId: {}",
                    textContent.length(), studentId, assignmentId);

            // 2. 使用Stanford CoreNLP进行分句和分词
            Document doc = new Document(textContent);
            List<Sentence> allSentences = new ArrayList<>(doc.sentences()); // 一次性加载所有句子到内存

            // 后续操作都使用allSentences集合，避免频繁调用doc.sentences()方法
            List<String> sentences = allSentences.stream()
                    .map(Sentence::text)
                    .toList();

            log.info("分句完成，共{}个句子 - studentId: {}, assignmentId: {}",
                    sentences.size(), studentId, assignmentId);

            // 3. 分词并获取词汇级别
            List<TextAnalysis.WordLevel> wordLevels = new ArrayList<>();
            for (Sentence sentence : allSentences) {
                for (String word : sentence.words()) {
                    TextAnalysis.WordLevel wordLevel = new TextAnalysis.WordLevel();
                    wordLevel.setWord(word);

                    // 判断是否为标点符号
                    if (isPunctuation(word)) {
                        wordLevel.setBasewordLevel(0);
                    } else {
                        // 获取词汇级别（带重试机制）
                        Integer level = fetchBasewordLevelWithRetry(word);
                        wordLevel.setBasewordLevel(level);
                    }

                    wordLevels.add(wordLevel);
                }
            }

            log.info("分词完成，共{}个词汇 - studentId: {}, assignmentId: {}",
                    wordLevels.size(), studentId, assignmentId);

            // 4. 组装TextAnalysis对象
            TextAnalysis analysis = new TextAnalysis();
            analysis.setStudentId(studentId);
            analysis.setAssignmentId(assignmentId);
            analysis.setTextContent(textContent);
            analysis.setSentences(sentences);
            analysis.setWordLevels(wordLevels);

            // 查找是否已有数据，若有则复用_id,实现数据的更新;若没有，则新插入
            Query query = new Query();
            query.addCriteria(Criteria.where("studentId").is(studentId).and("assignmentId").is(assignmentId));
            TextAnalysis old = mongoTemplate.findOne(query, TextAnalysis.class, "textAnalyses");
            if (old != null) {
                analysis.setId(old.getId());
            }

            // 5. 保存到MongoDB
            mongoTemplate.save(analysis, "textAnalyses");

            log.info("文本分析完成并保存到MongoDB - studentId: {}, assignmentId: {}",
                    studentId, assignmentId);

        } catch (Exception e) {
            log.error("文本分析失败 - studentId: {}, assignmentId: {}, error: {}",
                    studentId, assignmentId, e.getMessage(), e);
        }
    }

    /**
     * 判断字符串是否为标点符号
     * 
     * @param word 待判断的字符串
     * @return 是否为标点符号
     */
    private boolean isPunctuation(String word) {
        return word.matches("\\p{Punct}");
    }

    /**
     * 带重试机制的词汇级别获取
     * 
     * @param word 待查询的词汇
     * @return 词汇级别，如果查询失败返回0
     */
    private Integer fetchBasewordLevelWithRetry(String word) {
        for (int retry = 0; retry < MAX_RETRY_COUNT; retry++) {
            try {
                Integer level = fetchBasewordLevel(word);
                if (level != null) {
                    return level;
                }
            } catch (Exception e) {
                log.warn("获取词汇级别失败，第{}次重试 - word: {}, error: {}",
                        retry + 1, word, e.getMessage());
            }

            // 重试前等待
            if (retry < MAX_RETRY_COUNT - 1) {
                try {
                    Thread.sleep(RETRY_DELAY_MS);
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                    break;
                }
            }
        }

        log.warn("获取词汇级别失败，已达到最大重试次数 - word: {}", word);
        return 0;
    }

    /**
     * 调用外部API获取词汇级别
     * 
     * @param word 待查询的词汇
     * @return 词汇级别，如果查询失败返回null
     */
    private Integer fetchBasewordLevel(String word) {
        try {
            // 设置请求头
            HttpHeaders headers = new HttpHeaders();
            headers.setContentType(MediaType.APPLICATION_FORM_URLENCODED);

            // 设置请求参数
            MultiValueMap<String, String> params = new LinkedMultiValueMap<>();
            params.add("search", word);
            params.add("database", DATABASE);
            params.add("corpus", CORPUS);

            HttpEntity<MultiValueMap<String, String>> request = new HttpEntity<>(params, headers);

            // 发送POST请求
            ResponseEntity<String> response = restTemplate.postForEntity(
                    WORD_LEVEL_API_URL, request, String.class);

            if (response.getStatusCode() == HttpStatus.OK && response.getBody() != null) {
                // 解析JSON响应
                JsonNode jsonNode = objectMapper.readTree(response.getBody());

                // 检查响应格式：[[VALUE, level, ...]]
                if (jsonNode.isArray() && jsonNode.size() > 0) {
                    JsonNode firstElement = jsonNode.get(0);
                    if (firstElement.isArray() && firstElement.size() > 1) {
                        JsonNode levelNode = firstElement.get(1);
                        try {
                            return levelNode.asInt(); // 直接返回整数
                        } catch (NumberFormatException e) {
                            log.warn("level不是有效数字: {}", levelNode);
                            return 0;
                        }
                    }
                }
            }

            log.warn("API响应格式异常 - word: {}, response: {}", word, response.getBody());
            return 0;

        } catch (Exception e) {
            log.error("调用词汇级别API失败 - word: {}, error: {}", word, e.getMessage());
            return 0;
        }
    }
}