diff --git a/client-api/src/main/java/org/jiayunet/service/UserProfileService.java b/client-api/src/main/java/org/jiayunet/service/UserProfileService.java
index f06144d..4b94258 100644
--- a/client-api/src/main/java/org/jiayunet/service/UserProfileService.java
+++ b/client-api/src/main/java/org/jiayunet/service/UserProfileService.java
@@ -45,7 +45,7 @@ public class UserProfileService {
private UserProfileCompetitionMapper competitionMapper;
@Autowired
- private org.jiayunet.service.UserSkillTagMatchService userSkillTagMatchService;
+ private org.jiayunet.service.UserProfileAnalyzeService userProfileAnalyzeService;
// ==================== 主表 ====================
@@ -78,7 +78,7 @@ public class UserProfileService {
profile.setUpdateTime(now);
userProfileMapper.insert(profile);
}
- userSkillTagMatchService.matchUserSkillTags(userId);
+ userProfileAnalyzeService.analyzeUserProfile(userId);
}
// ==================== 教育经历 ====================
@@ -114,7 +114,7 @@ public class UserProfileService {
item.setUpdateTime(now);
});
educationMapper.batchInsert(list);
- userSkillTagMatchService.matchUserSkillTags(userId);
+ userProfileAnalyzeService.analyzeUserProfile(userId);
}
// ==================== 工作经历 ====================
@@ -151,7 +151,7 @@ public class UserProfileService {
item.setUpdateTime(now);
});
workMapper.batchInsert(list);
- userSkillTagMatchService.matchUserSkillTags(userId);
+ userProfileAnalyzeService.analyzeUserProfile(userId);
}
// ==================== 实习经历 ====================
@@ -188,7 +188,7 @@ public class UserProfileService {
item.setUpdateTime(now);
});
internshipMapper.batchInsert(list);
- userSkillTagMatchService.matchUserSkillTags(userId);
+ userProfileAnalyzeService.analyzeUserProfile(userId);
}
// ==================== 项目经历 ====================
@@ -225,7 +225,7 @@ public class UserProfileService {
item.setUpdateTime(now);
});
projectMapper.batchInsert(list);
- userSkillTagMatchService.matchUserSkillTags(userId);
+ userProfileAnalyzeService.analyzeUserProfile(userId);
}
// ==================== 竞赛经历 ====================
@@ -262,7 +262,7 @@ public class UserProfileService {
item.setUpdateTime(now);
});
competitionMapper.batchInsert(list);
- userSkillTagMatchService.matchUserSkillTags(userId);
+ userProfileAnalyzeService.analyzeUserProfile(userId);
}
// ==================== 内部方法 ====================
diff --git a/manager/src/main/java/org/jiayunet/service/UserProfileAnalyzeService.java b/manager/src/main/java/org/jiayunet/service/UserProfileAnalyzeService.java
new file mode 100644
index 0000000..2c2b333
--- /dev/null
+++ b/manager/src/main/java/org/jiayunet/service/UserProfileAnalyzeService.java
@@ -0,0 +1,341 @@
+package org.jiayunet.service;
+
+import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
+import com.baomidou.mybatisplus.core.toolkit.IdWorker;
+import com.fasterxml.jackson.databind.JsonNode;
+import lombok.extern.slf4j.Slf4j;
+import org.jiayunet.ai.AiChatAbility;
+import org.jiayunet.mapper.*;
+import org.jiayunet.pojo.po.*;
+import org.jiayunet.pojo.vo.UserHonorsVo;
+import org.jiayunet.tool.HttpTool;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.scheduling.annotation.Async;
+import org.springframework.stereotype.Service;
+
+import java.time.Instant;
+import java.util.*;
+import java.util.stream.Collectors;
+
+/**
+ * 用户简历分析服务
+ * 主要功能：用户保存简历后异步分析，提取学校等级、经历质量、专业、技能等维度数据
+ * 依赖：AiChatAbility（AI调用）、DictCacheService（专业分类缓存）
+ * 使用表：bg_user_profile（主表，读取/更新）、bg_user_profile_*（5张子表，读取）、
+ * bg_skill_tag（技能入库）、bg_user_profile_skill_tag_relation（关联表）
+ *
+ * @author zk
+ */
+@Slf4j
+@Service
+public class UserProfileAnalyzeService {
+
+ @Autowired
+ private AiChatAbility aiChatAbility;
+
+ @Autowired
+ private DictCacheService dictCacheService;
+
+ @Autowired
+ private UserProfileMapper userProfileMapper;
+
+ @Autowired
+ private UserProfileEducationMapper educationMapper;
+
+ @Autowired
+ private UserProfileWorkMapper workMapper;
+
+ @Autowired
+ private UserProfileInternshipMapper internshipMapper;
+
+ @Autowired
+ private UserProfileProjectMapper projectMapper;
+
+ @Autowired
+ private UserProfileCompetitionMapper competitionMapper;
+
+ @Autowired
+ private SkillTagMapper skillTagMapper;
+
+ @Autowired
+ private UserProfileSkillTagRelationMapper relationMapper;
+
+ /**
+ * 异步分析用户简历
+ * 1. 查询用户完整简历 2. 第一次AI综合分析 3. 第二次AI专业归一化 4. 第三次AI技能提取
+ */
+ @Async("userProfileAsyncExecutor")
+ public void analyzeUserProfile(Long userId) {
+ try {
+ log.info("开始分析用户简历, userId={}", userId);
+
+ // 1. 查询用户完整简历
+ UserProfile profile = userProfileMapper.selectOne(new LambdaQueryWrapper().eq(UserProfile::getUserId, userId));
+ if (profile == null) {
+ log.info("用户主表为空，清空技能标签, userId={}", userId);
+ clearSkillRelations(userId);
+ return;
+ }
+
+ List educationList = educationMapper.selectList(new LambdaQueryWrapper().eq(UserProfileEducation::getUserId, userId));
+ List workList = workMapper.selectList(new LambdaQueryWrapper().eq(UserProfileWork::getUserId, userId));
+ List internshipList = internshipMapper.selectList(new LambdaQueryWrapper().eq(UserProfileInternship::getUserId, userId));
+ List projectList = projectMapper.selectList(new LambdaQueryWrapper().eq(UserProfileProject::getUserId, userId));
+ List competitionList = competitionMapper.selectList(new LambdaQueryWrapper().eq(UserProfileCompetition::getUserId, userId));
+
+ // 2. 数据有效性检查
+ if (educationList.isEmpty() && workList.isEmpty() && internshipList.isEmpty() && projectList.isEmpty() && competitionList.isEmpty()) {
+ log.info("用户所有子表为空，清空技能标签, userId={}", userId);
+ clearSkillRelations(userId);
+ return;
+ }
+
+ String profileJson = buildProfileJson(profile, educationList, workList, internshipList, projectList, competitionList);
+
+ // 3. 第一次AI：简历综合分析（失败不影响后续）
+ try {
+ analyzeProfileDimensions(profile.getId(), profileJson);
+ } catch (Exception e) {
+ log.warn("简历综合分析失败, userId={}", userId, e);
+ }
+
+ // 4. 第二次AI：专业归一化（失败不影响后续）
+ try {
+ analyzeMajor(profile.getId(), profileJson);
+ } catch (Exception e) {
+ log.warn("专业归一化失败, userId={}", userId, e);
+ }
+
+ // 5. 第三次AI：技能提取
+ try {
+ extractSkillTags(userId, profileJson);
+ } catch (Exception e) {
+ log.warn("技能提取失败, userId={}", userId, e);
+ }
+
+ log.info("用户简历分析完成, userId={}", userId);
+
+ } catch (Exception e) {
+ log.error("用户简历分析异常, userId={}", userId, e);
+ }
+ }
+
+ /**
+ * 第一次AI：简历综合分析
+ * 一次性识别学校等级、公司背书、经历时长、职责深度、量化产出、荣誉
+ */
+ private void analyzeProfileDimensions(Long profileId, String profileJson) {
+ String systemPrompt = """
+ 你是一个简历分析助手。根据用户简历，分析以下维度并返回JSON。
+ 返回JSON格式：
+ {
+ "schoolRank": 1-4的数字(1=C9/985/QS前50 2=211/双一流/QS前200 3=普通一本/QS前500 4=其他，无教育经历则null),
+ "companyPrestige": 1-4的数字(1=名企(世界500强/互联网大厂/知名国企/独角兽) 2=普通实习 3=仅校内活动 4=无经历，取最高档),
+ "experienceDuration": 1-3的数字(1=实习≥3月 2=1-3月 3=≤1月，取最长的一段，无实习则null),
+ "roleDepth": 1-3的数字(1=主导/创新(主导、核心负责、从0到1、架构设计) 2=执行/应用(负责、开发、实现、维护) 3=辅助/学习(协助、参与、了解)，取最高档),
+ "outputQuality": 1-3的数字(1=有量化结果(含数字比率如提升20%) 2=有具体产出(明确产出物但无数字) 3=纯描述，取最高档),
+ "honors": {"national":["具体奖项名"],"provincial":["具体奖项名"],"school":["具体奖项/证书名"],"paper":["具体论文名"]}
+ }
+ 规则：
+ 1. 每个维度独立判断，某维度信息不足则设为null
+ 2. 多段经历取最高档（最优表现）
+ 3. honors中只填简历中明确提到的，没有则空数组
+ 4. 只返回JSON，不要其他内容
+ """;
+
+ String userMessage = "【用户简历】\n" + profileJson;
+ String aiResponse = aiChatAbility.chat(systemPrompt, userMessage);
+ String json = cleanAiResponse(aiResponse);
+
+ try {
+ JsonNode root = HttpTool.objectMapper.readTree(json);
+
+ UserProfile update = new UserProfile();
+ update.setId(profileId);
+ update.setSchoolRank(root.path("schoolRank").isNull() ? null : root.path("schoolRank").asInt());
+ update.setCompanyPrestige(root.path("companyPrestige").isNull() ? null : root.path("companyPrestige").asInt());
+ update.setExperienceDuration(root.path("experienceDuration").isNull() ? null : root.path("experienceDuration").asInt());
+ update.setRoleDepth(root.path("roleDepth").isNull() ? null : root.path("roleDepth").asInt());
+ update.setOutputQuality(root.path("outputQuality").isNull() ? null : root.path("outputQuality").asInt());
+
+ // 解析 honors
+ JsonNode honorsNode = root.path("honors");
+ if (!honorsNode.isMissingNode() && !honorsNode.isNull()) {
+ UserHonorsVo honors = HttpTool.objectMapper.treeToValue(honorsNode, UserHonorsVo.class);
+ update.setHonors(honors);
+ }
+
+ update.setUpdateTime(Instant.now());
+ userProfileMapper.updateById(update);
+ } catch (Exception e) {
+ log.warn("简历综合分析AI返回解析失败: {}", json, e);
+ }
+ }
+
+ /**
+ * 第二次AI：专业归一化
+ * 传入教育经历和三级专业分类列表，AI返回用户专业ID数组 → 更新 bg_user_profile.major_ids
+ */
+ private void analyzeMajor(Long profileId, String profileJson) {
+ String systemPrompt = """
+ 你是一个专业归一化助手。根据用户的教育经历，从专业分类列表中匹配用户的专业。
+ 返回JSON格式：
+ {
+ "majorIds": [专业ID数组，从专业列表中选择最匹配的，可多个（如本科+硕士不同专业），无法判断则空数组]
+ }
+ 规则：
+ 1. 只能从给定专业列表中选择ID
+ 2. 每段教育经历匹配一个最相关的专业
+ 3. 无教育经历或专业信息不足时返回空数组
+ 4. 只返回JSON，不要其他内容
+ """;
+
+ String userMessage = "【用户简历】\n" + profileJson + "\n\n【专业分类列表】\n" + dictCacheService.getMajorCategoryText();
+
+ String aiResponse = aiChatAbility.chat(systemPrompt, userMessage);
+ String json = cleanAiResponse(aiResponse);
+
+ try {
+ JsonNode root = HttpTool.objectMapper.readTree(json);
+ List majorIds = new ArrayList<>();
+ JsonNode idsNode = root.path("majorIds");
+ if (idsNode.isArray()) {
+ for (JsonNode node : idsNode) {
+ long id = node.asLong(0);
+ if (id > 0 && !majorIds.contains(id)) {
+ majorIds.add(id);
+ }
+ }
+ }
+
+ UserProfile update = new UserProfile();
+ update.setId(profileId);
+ update.setMajorIds(majorIds.isEmpty() ? null : majorIds);
+ update.setUpdateTime(Instant.now());
+ userProfileMapper.updateById(update);
+ } catch (Exception e) {
+ log.warn("专业归一化AI返回解析失败: {}", json, e);
+ }
+ }
+
+ /**
+ * 第三次AI：技能提取
+ * 自由提取用户技能，prompt与岗位侧保持一致，INSERT IGNORE入bg_skill_tag → 写关联表
+ */
+ private void extractSkillTags(Long userId, String profileJson) {
+ String systemPrompt = """
+ 你是一个技能提取助手。根据用户简历，提取该用户具备的核心专业能力和工具技能。
+ 返回JSON数组格式，如：["java", "spring boot", "mysql", "redis"]
+ 规则：
+ 1. 统一使用小写字母
+ 2. 尽量简短，使用业界通用缩写（如 js 而非 javascript，k8s 而非 kubernetes）
+ 3. 提取范围包括：技术栈、专业领域知识、行业工具、专业资质能力等
+ 4. 不提取纯软技能（如沟通能力、团队协作、学习能力、积极主动）
+ 5. 如果简历中完全没有专业能力体现，返回空数组 []
+ 6. 最多15个，按熟练度排序
+ 7. 只返回JSON数组，不要其他内容
+ 示例1（技术岗）：
+ 输入：3年Java开发经验，熟悉Spring Boot、MySQL、Redis
+ 输出：["java", "spring boot", "mysql", "redis"]
+ 示例2（财务岗）：
+ 输入：负责费用管理与审核，月度经营利润分析，会计学专业
+ 输出：["财务管理", "会计核算", "经营分析", "费用审核"]
+ 示例3（科研岗）：
+ 输入：开展生物合成相关研究，发酵工程方向博士
+ 输出：["生物合成", "发酵工程"]
+ 示例4（无专业能力）：
+ 输入：具备较强的沟通能力和创新意识，积极主动
+ 输出：[]
+ """;
+
+ String userMessage = "【用户简历】\n" + profileJson;
+ String aiResponse = aiChatAbility.chat(systemPrompt, userMessage);
+ String json = cleanAiResponse(aiResponse);
+
+ try {
+ JsonNode arrayNode = HttpTool.objectMapper.readTree(json);
+ if (!arrayNode.isArray() || arrayNode.isEmpty()) {
+ clearSkillRelations(userId);
+ return;
+ }
+
+ List skillTagIds = new ArrayList<>();
+ for (JsonNode node : arrayNode) {
+ String skillName = node.asText("").trim().toLowerCase();
+ if (skillName.isBlank() || skillName.length() > 50) {
+ continue;
+ }
+ Long tagId = findOrCreateSkillTag(skillName);
+ if (tagId != null && !skillTagIds.contains(tagId)) {
+ skillTagIds.add(tagId);
+ }
+ }
+
+ replaceSkillRelations(userId, skillTagIds);
+ } catch (Exception e) {
+ log.warn("技能提取AI返回解析失败: {}", json, e);
+ }
+ }
+
+ /**
+ * 查找或创建技能标签（依靠数据库唯一索引保证并发安全）
+ */
+ private Long findOrCreateSkillTag(String name) {
+ skillTagMapper.insertIgnore(IdWorker.getId(), name, Instant.now());
+ SkillTag tag = skillTagMapper.selectOne(new LambdaQueryWrapper().eq(SkillTag::getName, name).last("LIMIT 1"));
+ return tag != null ? tag.getId() : null;
+ }
+
+ /** 构建用户简历JSON */
+ private String buildProfileJson(UserProfile profile, List educationList,
+ List workList, List internshipList,
+ List projectList, List competitionList) {
+ Map data = new HashMap<>();
+ data.put("name", profile.getName());
+ data.put("skills", profile.getSkills());
+ data.put("certificates", profile.getCertificates());
+ data.put("education", educationList);
+ data.put("work", workList);
+ data.put("internship", internshipList);
+ data.put("project", projectList);
+ data.put("competition", competitionList);
+ try {
+ return HttpTool.objectMapper.writeValueAsString(data);
+ } catch (Exception e) {
+ log.error("用户资料序列化失败", e);
+ return "{}";
+ }
+ }
+
+ /** 清空用户技能标签关联 */
+ private void clearSkillRelations(Long userId) {
+ relationMapper.delete(new LambdaQueryWrapper().eq(UserProfileSkillTagRelation::getUserId, userId));
+ }
+
+ /** 全量替换用户技能标签关联 */
+ private void replaceSkillRelations(Long userId, List skillTagIds) {
+ relationMapper.delete(new LambdaQueryWrapper().eq(UserProfileSkillTagRelation::getUserId, userId));
+ if (skillTagIds.isEmpty()) {
+ return;
+ }
+ Instant now = Instant.now();
+ List relations = skillTagIds.stream().map(tagId -> {
+ UserProfileSkillTagRelation relation = new UserProfileSkillTagRelation();
+ relation.setUserId(userId);
+ relation.setSkillTagId(tagId);
+ relation.setCreateTime(now);
+ return relation;
+ }).collect(Collectors.toList());
+ relationMapper.batchInsert(relations);
+ }
+
+ /** 清理AI返回的markdown代码块和控制字符 */
+ private String cleanAiResponse(String response) {
+ String json = response.trim();
+ if (json.startsWith("```")) {
+ json = json.replaceAll("^```\\w*\\n?", "").replaceAll("\\n?```$", "").trim();
+ }
+ json = json.replaceAll("[\\x00-\\x08\\x0B\\x0C\\x0E-\\x1F]", "");
+ return json;
+ }
+}
diff --git a/manager/src/main/java/org/jiayunet/service/UserSkillTagMatchService.java b/manager/src/main/java/org/jiayunet/service/UserSkillTagMatchService.java
deleted file mode 100644
index e251874..0000000
--- a/manager/src/main/java/org/jiayunet/service/UserSkillTagMatchService.java
+++ /dev/null
@@ -1,324 +0,0 @@
-package org.jiayunet.service;
-
-import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
-import com.fasterxml.jackson.databind.JsonNode;
-import lombok.extern.slf4j.Slf4j;
-import org.jiayunet.ai.AiChatAbility;
-import org.jiayunet.mapper.*;
-import org.jiayunet.pojo.po.*;
-import org.jiayunet.tool.HttpTool;
-import org.springframework.beans.factory.annotation.Autowired;
-import org.springframework.scheduling.annotation.Async;
-import org.springframework.stereotype.Service;
-
-import java.time.Instant;
-import java.util.*;
-import java.util.stream.Collectors;
-
-/**
- * 用户技能标签匹配服务
- * 主要功能：根据用户个人资料，AI识别匹配的技能标签
- * 依赖：AiChatAbility（AI调用）
- * 使用表：bg_user_profile（主表）、bg_user_profile_*（5张子表）、
- * bg_job_category（岗位分类）、bg_skill_tag（技能标签）、
- * bg_user_profile_skill_tag_relation（关联表）
- *
- * @author zk
- */
-@Slf4j
-@Service
-public class UserSkillTagMatchService {
-
- @Autowired
- private AiChatAbility aiChatAbility;
-
- @Autowired
- private UserProfileMapper userProfileMapper;
-
- @Autowired
- private UserProfileEducationMapper educationMapper;
-
- @Autowired
- private UserProfileWorkMapper workMapper;
-
- @Autowired
- private UserProfileInternshipMapper internshipMapper;
-
- @Autowired
- private UserProfileProjectMapper projectMapper;
-
- @Autowired
- private UserProfileCompetitionMapper competitionMapper;
-
- @Autowired
- private JobCategoryMapper jobCategoryMapper;
-
- @Autowired
- private SkillTagMapper skillTagMapper;
-
- @Autowired
- private UserProfileSkillTagRelationMapper relationMapper;
-
- /**
- * 异步匹配用户技能标签
- * 1. 查询用户完整个人资料 2. 第一次AI调用识别二级分类 3. 查询三级分类
- * 4. 查询候选技能标签 5. 第二次AI调用匹配技能标签 6. 全量替换关联表
- */
- @Async("userProfileAsyncExecutor")
- public void matchUserSkillTags(Long userId) {
- try {
- log.info("开始匹配用户技能标签, userId={}", userId);
-
- // 1. 查询用户完整个人资料
- UserProfile profile = userProfileMapper.selectOne(new LambdaQueryWrapper().eq(UserProfile::getUserId, userId));
- if (profile == null) {
- log.info("用户主表为空，清空技能标签, userId={}", userId);
- clearRelations(userId);
- return;
- }
-
- List educationList = educationMapper.selectList(new LambdaQueryWrapper().eq(UserProfileEducation::getUserId, userId));
- List workList = workMapper.selectList(new LambdaQueryWrapper().eq(UserProfileWork::getUserId, userId));
- List internshipList = internshipMapper.selectList(new LambdaQueryWrapper().eq(UserProfileInternship::getUserId, userId));
- List projectList = projectMapper.selectList(new LambdaQueryWrapper().eq(UserProfileProject::getUserId, userId));
- List competitionList = competitionMapper.selectList(new LambdaQueryWrapper().eq(UserProfileCompetition::getUserId, userId));
-
- // 2. 数据有效性检查
- if (educationList.isEmpty() && workList.isEmpty() && internshipList.isEmpty() && projectList.isEmpty() && competitionList.isEmpty()) {
- log.info("用户所有子表为空，清空技能标签, userId={}", userId);
- clearRelations(userId);
- return;
- }
-
- // 3. 第一次 AI 调用（识别二级分类）
- List categoryIds = identifyCategories(profile, educationList, workList, internshipList, projectList, competitionList);
- if (categoryIds.isEmpty()) {
- log.info("AI未识别出岗位分类，清空技能标签, userId={}", userId);
- clearRelations(userId);
- return;
- }
-
- // 4. 查询三级分类（技能标签挂在三级分类下）
- List level3Categories = jobCategoryMapper.selectList(new LambdaQueryWrapper().eq(JobCategory::getLevel, 3).in(JobCategory::getParentId, categoryIds));
- if (level3Categories.isEmpty()) {
- log.info("二级分类下无三级分类，清空技能标签, userId={}", userId);
- clearRelations(userId);
- return;
- }
-
- // 5. 查询候选技能标签（使用三级分类ID）
- List level3CategoryIds = level3Categories.stream().map(JobCategory::getId).collect(Collectors.toList());
- List candidateTags = skillTagMapper.selectList(new LambdaQueryWrapper().in(SkillTag::getCategoryId, level3CategoryIds));
- if (candidateTags.isEmpty()) {
- log.info("候选技能标签为空，清空技能标签, userId={}", userId);
- clearRelations(userId);
- return;
- }
-
- // 6. 第二次 AI 调用（匹配技能标签）
- List matchedTagIds = matchSkillTags(profile, educationList, workList, internshipList, projectList, competitionList, candidateTags);
-
- // 7. 全量替换关联表
- replaceRelations(userId, matchedTagIds);
-
- log.info("用户技能标签匹配完成, userId={}, 匹配{}个标签", userId, matchedTagIds.size());
-
- } catch (Exception e) {
- log.error("用户技能标签匹配异常, userId={}", userId, e);
- }
- }
-
- /**
- * 第一次 AI 调用：识别用户所属的二级岗位分类
- */
- private List identifyCategories(UserProfile profile, List educationList,
- List workList, List internshipList,
- List projectList, List competitionList) {
- // 构建用户资料 JSON
- Map profileData = new HashMap<>();
- profileData.put("name", profile.getName());
- profileData.put("workYears", profile.getWorkYears());
- profileData.put("education", educationList);
- profileData.put("work", workList);
- profileData.put("internship", internshipList);
- profileData.put("project", projectList);
- profileData.put("competition", competitionList);
-
- String profileJson;
- try {
- profileJson = HttpTool.objectMapper.writeValueAsString(profileData);
- } catch (Exception e) {
- log.error("用户资料序列化失败", e);
- return List.of();
- }
-
- // 查询所有二级分类
- List allCategories = jobCategoryMapper.selectList(new LambdaQueryWrapper().eq(JobCategory::getLevel, 2));
-
- // 构建分类列表文本（带一级分类名称）
- Map parentNameMap = new HashMap<>();
- List parentCategories = jobCategoryMapper.selectList(new LambdaQueryWrapper().eq(JobCategory::getLevel, 1));
- for (JobCategory parent : parentCategories) {
- parentNameMap.put(parent.getId(), parent.getName());
- }
-
- StringBuilder categoryText = new StringBuilder();
- for (JobCategory category : allCategories) {
- String parentName = parentNameMap.getOrDefault(category.getParentId(), "未知");
- categoryText.append(String.format("ID: %d, 名称: %s > %s\n", category.getId(), parentName, category.getName()));
- }
-
- // 构建 Prompt
- String systemPrompt = """
- 任务：根据用户个人资料，选择最匹配的二级岗位分类。
-
- 规则：
- 1. 选择 1-10 个最匹配的二级分类（优先核心岗位，按匹配度排序）
- 2. 信息不足无法判断时返回空数组 []
- 3. 只返回纯数字数组 JSON，不要任何其他文字
-
- 返回格式示例：
- - 有分类：[23, 45, 67]
- - 无法判断：[]
- """;
-
- String userMessage = "【用户个人资料】\n" + profileJson + "\n\n【二级岗位分类列表（格式：一级分类 > 二级分类）】\n" + categoryText;
-
- try {
- String aiResponse = aiChatAbility.chat(systemPrompt, userMessage);
- return parseIdArray(aiResponse, allCategories.stream().map(JobCategory::getId).collect(Collectors.toSet()));
- } catch (Exception e) {
- log.error("AI识别岗位分类失败", e);
- return List.of();
- }
- }
-
- /**
- * 第二次 AI 调用：从候选标签中匹配用户技能标签
- */
- private List matchSkillTags(UserProfile profile, List educationList,
- List workList, List internshipList,
- List projectList, List competitionList,
- List candidateTags) {
- // 构建用户资料 JSON
- Map profileData = new HashMap<>();
- profileData.put("name", profile.getName());
- profileData.put("workYears", profile.getWorkYears());
- profileData.put("education", educationList);
- profileData.put("work", workList);
- profileData.put("internship", internshipList);
- profileData.put("project", projectList);
- profileData.put("competition", competitionList);
-
- String profileJson;
- try {
- profileJson = HttpTool.objectMapper.writeValueAsString(profileData);
- } catch (Exception e) {
- log.error("用户资料序列化失败", e);
- return List.of();
- }
-
- // 构建候选标签文本（按分类分组）
- Map categoryNameMap = new HashMap<>();
- Set categoryIds = candidateTags.stream().map(SkillTag::getCategoryId).collect(Collectors.toSet());
- List categories = jobCategoryMapper.selectList(new LambdaQueryWrapper().in(JobCategory::getId, categoryIds));
- for (JobCategory category : categories) {
- categoryNameMap.put(category.getId(), category.getName());
- }
-
- StringBuilder tagText = new StringBuilder();
- Map> groupedTags = candidateTags.stream().collect(Collectors.groupingBy(SkillTag::getCategoryId));
- for (Map.Entry> entry : groupedTags.entrySet()) {
- String categoryName = categoryNameMap.getOrDefault(entry.getKey(), "未知");
- tagText.append("【").append(categoryName).append("】\n");
- for (SkillTag tag : entry.getValue()) {
- tagText.append(String.format("ID: %d, 名称: %s\n", tag.getId(), tag.getName()));
- }
- tagText.append("\n");
- }
-
- // 构建 Prompt
- String systemPrompt = """
- 任务：根据用户个人资料，从候选技能标签中选出匹配的标签。
-
- 规则：
- 1. 只选择用户明确具备或可推断的技能
- 2. 无法匹配返回空数组 []
- 3. 只返回纯数字数组 JSON，不要任何其他文字
-
- 返回格式示例：
- - 有匹配：[12, 34, 56]
- - 无匹配：[]
- """;
-
- String userMessage = "【用户个人资料】\n" + profileJson + "\n\n【候选技能标签（按分类分组）】\n" + tagText;
-
- try {
- String aiResponse = aiChatAbility.chat(systemPrompt, userMessage);
- return parseIdArray(aiResponse, candidateTags.stream().map(SkillTag::getId).collect(Collectors.toSet()));
- } catch (Exception e) {
- log.error("AI匹配技能标签失败", e);
- return List.of();
- }
- }
-
- /**
- * 解析 AI 返回的 ID 数组
- */
- private List parseIdArray(String aiResponse, Set validIds) {
- String json = aiResponse.trim();
- if (json.startsWith("```")) {
- json = json.replaceAll("^```\\w*\\n?", "").replaceAll("\\n?```$", "").trim();
- }
-
- try {
- JsonNode arrayNode = HttpTool.objectMapper.readTree(json);
- List result = new ArrayList<>();
- if (arrayNode.isArray()) {
- for (JsonNode node : arrayNode) {
- long id = node.asLong(0);
- if (id > 0 && validIds.contains(id) && !result.contains(id)) {
- result.add(id);
- }
- }
- }
- return result;
- } catch (Exception e) {
- log.warn("AI返回解析失败: {}", json, e);
- return List.of();
- }
- }
-
- /**
- * 清空用户技能标签关联
- */
- public void clearRelations(Long userId) {
- relationMapper.delete(new LambdaQueryWrapper().eq(UserProfileSkillTagRelation::getUserId, userId));
- }
-
- /**
- * 全量替换用户技能标签关联
- */
-
- public void replaceRelations(Long userId, List skillTagIds) {
- // 先删除
- relationMapper.delete(new LambdaQueryWrapper().eq(UserProfileSkillTagRelation::getUserId, userId));
-
- // 结果为空则只删除
- if (skillTagIds.isEmpty()) {
- return;
- }
-
- // 批量插入
- Instant now = Instant.now();
- List relations = skillTagIds.stream().map(tagId -> {
- UserProfileSkillTagRelation relation = new UserProfileSkillTagRelation();
- relation.setUserId(userId);
- relation.setSkillTagId(tagId);
- relation.setCreateTime(now);
- return relation;
- }).collect(Collectors.toList());
-
- relationMapper.batchInsert(relations);
- }
-}