case-data-api/src/main/java/com/example/caseData/service/BasicSensitiveWordService.java

package com.example.caseData.service;

import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
import com.example.caseData.dao.BasicSensitiveWordDao;
import com.example.caseData.model.BasicSensitiveWordModel;
import com.example.caseData.model.CaseClinicalArticleModel;
import com.fasterxml.jackson.databind.ObjectMapper;
import jakarta.annotation.Resource;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.stereotype.Service;
import com.fasterxml.jackson.core.type.TypeReference;

import java.time.Duration;
import java.util.*;
import java.util.concurrent.TimeUnit;
import java.util.stream.Collectors;

@Service
public class BasicSensitiveWordService {
    private static final String REDIS_SENSITIVE_WORD_KEY = "sensitive:word:list";
    private static final long REDIS_EXPIRE_MINUTES = 30;

    @Resource
    private RedisTemplate<String, String> redisTemplate;

    @Resource
    private BasicSensitiveWordDao basicSensitiveWordDao; // 假设你有这个 DAO

    private final ObjectMapper objectMapper = new ObjectMapper();

    // 主过滤方法
    public FilterResult filter(String comment) {
        List<String> wordList = loadSensitiveWords();
        if (wordList == null || wordList.isEmpty()) {
            return new FilterResult(comment, 0);
        }

        TrieNode root = buildTrie(wordList);
        return doFilter(comment, root);
    }

    // 加载敏感词（可替换为数据库查询）
    private List<String> loadSensitiveWords() {
        List<String> wordList = new ArrayList<>();

        // 尝试从 Redis 获取
        String wordJson = redisTemplate.opsForValue().get(REDIS_SENSITIVE_WORD_KEY);
        if (wordJson != null && !wordJson.isEmpty()) {
            try {
                // 反序列化 JSON 字符串为 List<String>
                wordList = objectMapper.readValue(wordJson, new TypeReference<List<String>>() {});
            } catch (Exception e) {
                return wordList;
            }
        }else{
            // Redis 无数据，则查询 DB
            LambdaQueryWrapper<BasicSensitiveWordModel> queryWrapper = new LambdaQueryWrapper<>();
            List<BasicSensitiveWordModel> basicSensitiveWords = basicSensitiveWordDao.selectList(queryWrapper); // 你自己的 DAO 方法
            if (basicSensitiveWords != null && !basicSensitiveWords.isEmpty()) {
                wordList = basicSensitiveWords.stream()
                        .map(BasicSensitiveWordModel::getWord)
                        .filter(Objects::nonNull)
                        .collect(Collectors.toList());

                try {
                    String wordListJson = objectMapper.writeValueAsString(wordList);
                    redisTemplate.opsForValue().set(REDIS_SENSITIVE_WORD_KEY, wordListJson, Duration.ofMinutes(REDIS_EXPIRE_MINUTES));
                } catch (Exception e) {
                    return wordList;
                }
            }
        }

        return wordList;
    }

    // 构建字典树
    private TrieNode buildTrie(List<String> words) {
        TrieNode root = new TrieNode();
        for (String word : words) {
            TrieNode node = root;
            for (char ch : word.toCharArray()) {
                node.children.putIfAbsent(ch, new TrieNode());
                node = node.children.get(ch);
            }
            node.isEnd = true;
        }
        return root;
    }

    // 实际过滤逻辑
    private FilterResult doFilter(String comment, TrieNode root) {
        char[] chars = comment.toCharArray();
        int isSensitive = 0;

        for (int i = 0; i < chars.length; i++) {
            TrieNode node = root;
            int j = i;
            while (j < chars.length && node.children.containsKey(chars[j])) {
                node = node.children.get(chars[j]);
                if (node.isEnd) {
                    for (int k = i; k <= j; k++) {
                        chars[k] = '*';
                    }
                    isSensitive = 1;
                    break;
                }
                j++;
            }
        }

        return new FilterResult(new String(chars), isSensitive);
    }

    // Trie 节点内部类
    private static class TrieNode {
        boolean isEnd = false;
        Map<Character, TrieNode> children = new HashMap<>();
    }

    // 返回结果封装
    public static class FilterResult {
        public final String comment;
        public final int hasSensitive;

        public FilterResult(String comment, int hasSensitive) {
            this.comment = comment;
            this.hasSensitive = hasSensitive;
        }
    }
}