package com.pharmacopoeia.service; import org.springframework.dao.DataAccessException; import org.springframework.data.redis.core.StringRedisTemplate; import org.springframework.jdbc.core.JdbcTemplate; import org.springframework.stereotype.Service; import java.nio.charset.StandardCharsets; import java.security.MessageDigest; import java.time.Duration; import java.util.*; import java.util.stream.Collectors; @Service public class RetrieverService { private final JdbcTemplate jdbc; private final LLMService llmService; private final StringRedisTemplate redis; private final boolean redisAvailable; // Embedding 缓存 key 前缀 + TTL(7 天,续期 3 次后不再续) private static final String EMBED_CACHE_PREFIX = "aiyaodian:embed:"; private static final String EMBED_RENEW_PREFIX = "aiyaodian:embed:renew:"; private static final Duration EMBED_CACHE_TTL = Duration.ofDays(7); private static final Duration EMBED_MAX_TTL = Duration.ofDays(30); private static final int MAX_RENEWALS = 3; private static final List NEGATION_PATTERNS = List.of( "不是", "没有", "并非", "算不上", "怎么会是", "不可能", "不会", "没得", "没", "无", "不属", "不属于", "不是什么", "这不是" ); public RetrieverService(JdbcTemplate jdbc, LLMService llmService, StringRedisTemplate redis) { this.jdbc = jdbc; this.llmService = llmService; this.redis = redis; // 探测 Redis 是否可用,不可用时降级为每次调用远程 API this.redisAvailable = pingRedis(); } /** 启动时探测 Redis,失败则降级为无缓存模式,避免阻塞主流程 */ private boolean pingRedis() { try { return "PONG".equals(redis.getConnectionFactory().getConnection().ping()); } catch (Exception e) { return false; } } /** 计算 query 的 SHA-256 作为缓存 key */ private String cacheKey(String text) { try { MessageDigest md = MessageDigest.getInstance("SHA-256"); byte[] hash = md.digest(text.getBytes(StandardCharsets.UTF_8)); StringBuilder sb = new StringBuilder(2 * hash.length); for (byte b : hash) sb.append(String.format("%02x", b)); return EMBED_CACHE_PREFIX + sb; } catch (Exception e) { return EMBED_CACHE_PREFIX + text.hashCode(); } } /** 将 List 序列化为逗号分隔字符串,便于存入 Redis */ private String encodeVec(List vec) { StringBuilder sb = new StringBuilder(vec.size() * 8); for (int i = 0; i < vec.size(); i++) { if (i > 0) sb.append(','); sb.append(vec.get(i)); } return sb.toString(); } /** 反序列化 */ private List decodeVec(String s) { if (s == null || s.isEmpty()) return List.of(); String[] parts = s.split(","); List vec = new ArrayList<>(parts.length); for (String p : parts) vec.add(Float.parseFloat(p)); return vec; } /** 带缓存的 Embedding 查询:相同 query 命中缓存则跳过远程 API 调用 */ private List embedWithCache(String query) { if (!redisAvailable) return llmService.embed(query); String key = cacheKey(query); try { String cached = redis.opsForValue().get(key); if (cached != null) { // 滑动续期:最多续 3 次,总时长不超 30 天 var renewKey = EMBED_RENEW_PREFIX + key.substring(EMBED_CACHE_PREFIX.length()); try { var ops = redis.opsForValue(); var cntVal = ops.get(renewKey); int renewals = cntVal != null ? Integer.parseInt(cntVal) : 0; if (renewals < MAX_RENEWALS) { redis.expire(key, EMBED_CACHE_TTL); ops.set(renewKey, String.valueOf(renewals + 1), EMBED_MAX_TTL); } } catch (Exception ignored) {} return decodeVec(cached); } } catch (DataAccessException ignored) { // Redis 异常时降级到远程调用 } List vec = llmService.embed(query); try { redis.opsForValue().set(key, encodeVec(vec), EMBED_CACHE_TTL); } catch (DataAccessException ignored) { // 缓存写入失败不影响主流程 } return vec; } /** 检测 query 中关键词之前是否存在否定词,避免误匹配 */ private boolean hasNegation(String text, String keyword) { int idx = text.indexOf(keyword); if (idx < 0) return false; String prefix = text.substring(0, idx); for (String neg : NEGATION_PATTERNS) { if (prefix.endsWith(neg) || prefix.contains(neg)) return true; } return false; } /** 已知药物过敏检测:用户明确询问对某药物的过敏处理方法 */ private static final List KNOWN_ALLERGY_DRUGS = List.of( "青霉素", "头孢", "磺胺", "阿莫西林", "布洛芬", "阿司匹林", "链霉素", "庆大霉素", "四环素", "红霉素", "氯霉素", "万古霉素", "喹诺酮", "普鲁卡因", "利多卡因", "碘", "破伤风" ); private static final java.util.regex.Pattern[] KNOWN_ALLERGY_REGEX = { java.util.regex.Pattern.compile("对.{1,6}过敏"), // 对青霉素过敏 java.util.regex.Pattern.compile(".{1,6}药过敏"), // 头孢药过敏 java.util.regex.Pattern.compile("药物过敏"), // 药物过敏 java.util.regex.Pattern.compile(".+过敏(处理|怎么办|急救|替代|注意|救治|抢救|应急)"), }; private boolean isKnownDrugAllergy(String query) { // 必须包含"过敏" if (!query.contains("过敏")) return false; // 精确匹配已知过敏药物清单 for (String drug : KNOWN_ALLERGY_DRUGS) { if (query.contains(drug)) return true; } // 正则模式匹配(对XX过敏 / XX药过敏 / 药物过敏 / 过敏处理/急救等) for (var pattern : KNOWN_ALLERGY_REGEX) { if (pattern.matcher(query).find()) return true; } return false; } public String classifyIntent(String query) { String q = query.trim(); // 0. 已知药物过敏检测(最高优先级,必须在 "过敏" 通用匹配之前) // 如 "青霉素过敏处理" "头孢过敏怎么办" → 用药安全咨询,非症状求药 if (isKnownDrugAllergy(q)) { return "usage_guide"; } // 1. 用药安全/用法用量(优先级最高,避免"过敏"与症状类冲突) if (anyMatch(q, "怎么吃", "吃多少", "怎么用", "怎么服用", "孕妇", "儿童用量", "副作用多大", "伤肝", "伤肾", "安全吗", "副作用", "不良反应", "禁忌", "过敏", "能不能", "可以吗", "用法", "用量", "剂量", "用药指导", "一天几次", "一次多少", "饭前", "饭后", "空腹", "能不能一起吃", "相互作用", "过量", "停用", "停药", "忌口", "饮酒", "肝功能", "肾功能")) { return "usage_guide"; } // 2. 考试辅导(高优先级,关键词明确) if (anyMatch(q, "执业药师", "考点", "历年真题", "考试大纲", "高频考点", "药物化学", "药剂学", "药理学", "药分", "药物分析")) { return "exam_tutor"; } // 3. 法规条款(关键词明确) if (anyMatch(q, "凡例", "通则规定", "制剂通则", "一般规定", "通则")) { return "regulation"; } // 4. 症状用药建议(安全类关键词已在上方处理,"过敏"不会落到这里) if (anyMatch(q, "发烧", "咳嗽", "感冒", "腹泻", "头疼", "头痛", "嗓子疼", "吃了什么药", "吃什么药", "该吃", "推荐用药", "推荐下用药", "体温", "多少度", "退烧", "止痛", "止泻", "鼻塞", "流鼻涕", "头晕", "乏力", "呕吐", "腹痛", "咽痛", "打喷嚏")) { return "symptom_advice"; } // 5. 兜底:药品查询 return "drug_query"; } /** 检索:仅 2025 年版药典,AI 兜底补充 */ public List> search(String query, String intent, int topK) { List vec = embedWithCache(query); if (vec.isEmpty()) return List.of(); String vecStr = vec.stream() .map(String::valueOf) .collect(Collectors.joining(",", "[", "]")); String drugName = extractDrugName(query); return searchWithVersion(vecStr, drugName, "2025年版", topK); } /** 响应式检索:供 SSE 端点使用,避免 reactor 线程中 block() */ public reactor.core.publisher.Mono>> searchReactive(String query, String intent, int topK) { return llmService.embedReactive(query) .map(vec -> { if (vec.isEmpty()) return List.>of(); String vecStr = vec.stream() .map(String::valueOf) .collect(Collectors.joining(",", "[", "]")); String drugName = extractDrugName(query); return searchWithVersion(vecStr, drugName, "2025年版", topK); }); } /** 带版本过滤的向量检索。version 为 null 时不限制版本。 */ private List> searchWithVersion( String vecStr, String drugName, String version, int topK) { String versionFilter = (version != null) ? " AND d.source_version = '" + version + "' " : " "; String sql; Object[] params; if (!drugName.isEmpty()) { // 精确匹配 sql = """ SELECT c.content, c.source, c.drug_id, c.section, d.name, d.category, d.source_version, d.source_volume, 1 - (c.vec <=> ?::vector) AS similarity FROM drug_chunks c JOIN drugs d ON d.drug_id = c.drug_id WHERE c.vec IS NOT NULL AND d.name = ?""" + versionFilter + """ ORDER BY c.vec <=> ?::vector LIMIT ? """; params = new Object[]{vecStr, drugName, vecStr, topK}; List> results = jdbc.queryForList(sql, params); if (!results.isEmpty()) return results; // 前缀匹配兜底 sql = """ SELECT c.content, c.source, c.drug_id, c.section, d.name, d.category, d.source_version, d.source_volume, 1 - (c.vec <=> ?::vector) AS similarity FROM drug_chunks c JOIN drugs d ON d.drug_id = c.drug_id WHERE c.vec IS NOT NULL AND d.name LIKE ?""" + versionFilter + """ ORDER BY c.vec <=> ?::vector LIMIT ? """; params = new Object[]{vecStr, drugName + "%", vecStr, topK}; } else { sql = """ SELECT c.content, c.source, c.drug_id, c.section, d.name, d.category, d.source_version, d.source_volume, 1 - (c.vec <=> ?::vector) AS similarity FROM drug_chunks c JOIN drugs d ON d.drug_id = c.drug_id WHERE c.vec IS NOT NULL""" + versionFilter + """ ORDER BY c.vec <=> ?::vector LIMIT ? """; params = new Object[]{vecStr, vecStr, topK}; } return jdbc.queryForList(sql, params); } // 剂型后缀(长后缀优先,避免"缓释胶囊"被错误截断为"缓释") private static final List FORMULATION_SUFFIXES = List.of( "缓释胶囊", "缓释片", "肠溶胶囊", "肠溶片", "分散片", "咀嚼片", "口服混悬液", "口服液", "混悬液", "滴眼液", "注射液", "缓释", "肠溶", "胶囊", "颗粒", "糖浆", "软膏", "栓剂", "片", "剂", "栓" ); /** 从 query 中提取已知药品名:查 drugs 表,支持剂型后缀剥离和模糊匹配 */ private String extractDrugName(String query) { String cleaned = query.trim(); // 第一步:去掉尾部常见修饰词 String[] querySuffixes = { "的用法与用量", "的用法用量", "用法与用量", "用法用量", "的用量", "的用法", "的副作用", "不良反应", "的禁忌", "禁忌", "的注意事项", "注意事项", "是什么", "说明书", "怎么用", "怎么吃", "的用量", "用量", "的剂量", "剂量" }; for (String s : querySuffixes) { if (cleaned.endsWith(s)) { cleaned = cleaned.substring(0, cleaned.length() - s.length()).trim(); break; } } // 去掉问句前缀 cleaned = cleaned.replaceAll("^(什么是|怎么|如何|告诉我|请问|查询|搜索|查一下)", "").trim(); if (cleaned.length() < 2) return ""; // 第二步:精确匹配原始 query(含剂型名如"布洛芬缓释胶囊") String exact = tryExactMatch(cleaned); if (!exact.isEmpty()) return exact; // 第三步:逐步剥剂型后缀再试("布洛芬缓释胶囊"→"布洛芬") for (String suffix : FORMULATION_SUFFIXES) { if (cleaned.endsWith(suffix)) { String base = cleaned.substring(0, cleaned.length() - suffix.length()).trim(); if (base.length() >= 2) { String match = tryExactMatch(base); if (!match.isEmpty()) return match; } } } // 第四步:ILIKE 模糊匹配兜底 return tryFuzzyMatch(cleaned); } private String tryExactMatch(String name) { try { List matches = jdbc.queryForList( "SELECT name FROM drugs WHERE name = ? AND is_active = TRUE LIMIT 1", String.class, name); if (!matches.isEmpty()) return matches.get(0); } catch (Exception ignored) {} return ""; } private String tryFuzzyMatch(String name) { try { List matches = jdbc.queryForList( "SELECT name FROM drugs WHERE name ILIKE ? AND is_active = TRUE ORDER BY name LIMIT 1", String.class, "%" + name + "%"); if (!matches.isEmpty()) return matches.get(0); } catch (Exception ignored) {} return ""; } private boolean anyMatch(String text, String... keywords) { for (String kw : keywords) { int idx = text.indexOf(kw); if (idx >= 0 && !hasNegation(text, kw)) { return true; } } return false; } }