优化接口响应速度

client-api/src/main/java/org/jiayunet/service/JobService.java

@@ -2,6 +2,7 @@ package org.jiayunet.service;
 
 import org.jiayunet.ai.AiChatAbility;
 import org.jiayunet.ai.AiResponseCleanTool;
+import org.springframework.util.StopWatch;
 import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
 import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
 import lombok.extern.slf4j.Slf4j;
@@ -591,13 +592,17 @@ public class JobService {
      * <p>1. 查求职意向构造筛选条件（无意向则不设条件） 2. 排除已推荐的+已投递的 3. 取前35条候选 4. AI精筛返回8-10个</p>
      */
     public JobAgentRecommendDto recommendJobs(JobAgentRecommendParam param, Long userId) {
+        StopWatch sw = new StopWatch("recommendJobs");
+
         // 1. 查求职意向
+        sw.start("查求职意向");
         UserJobIntention intention = userJobIntentionMapper.selectOne(new LambdaQueryWrapper<UserJobIntention>().eq(UserJobIntention::getUserId, userId));
+        sw.stop();
 
         // 2. 构造查询参数
         JobQueryParam queryParam = new JobQueryParam();
         queryParam.setPageNum(1);
-        queryParam.setPageSize(35);
+        queryParam.setPageSize(60);
         if (intention != null) {
             queryParam.setCategoryIds(intention.getCategoryIds());
             queryParam.setRegionCodes(intention.getRegionCodes());
@@ -610,12 +615,16 @@ public class JobService {
         if (param.getExcludeJobIds() != null) {
             excludeIds.addAll(param.getExcludeJobIds());
         }
+        sw.start("查投递记录");
         List<UserJobApplication> applications = userJobApplicationMapper.selectList(new LambdaQueryWrapper<UserJobApplication>().eq(UserJobApplication::getUserId, userId));
+        sw.stop();
         applications.forEach(a -> excludeIds.add(a.getJobId()));
         queryParam.setExcludeJobIds(excludeIds);
 
         // 4. 查询候选岗位（完整列表数据）
+        sw.start("查候选岗位");
         PageResult<JobDto> candidates = listJobs(queryParam, userId);
+        sw.stop();
         if (candidates.getList().isEmpty()) {
             JobAgentRecommendDto dto = new JobAgentRecommendDto();
             dto.setSummary("暂无合适的岗位推荐");
@@ -624,18 +633,28 @@ public class JobService {
         }
 
         // 5. 批量查岗位详情（title + description + requirement）
+        sw.start("查岗位详情");
         List<Long> candidateJobIds = candidates.getList().stream().map(JobDto::getId).collect(Collectors.toList());
         List<Job> jobDetails = jobMapper.selectList(new LambdaQueryWrapper<Job>().in(Job::getId, candidateJobIds).select(Job::getId, Job::getTitle, Job::getDescription, Job::getRequirement));
         Map<Long, Job> jobDetailMap = jobDetails.stream().collect(Collectors.toMap(Job::getId, j -> j));
+        sw.stop();
 
-        // 6. 构造候选岗位映射（供AI返回后过滤使用）
-        Map<Long, JobDto> candidateMap = candidates.getList().stream().collect(Collectors.toMap(JobDto::getId, d -> d));
+        // 6. 构造别名映射（短序号 → 真实ID）和候选岗位映射
+        Map<Integer, Long> aliasToRealId = new HashMap<>();
+        Map<Long, JobDto> candidateMap = new HashMap<>();
+        int seq = 1;
+        for (JobDto dto : candidates.getList()) {
+            aliasToRealId.put(seq, dto.getId());
+            candidateMap.put(dto.getId(), dto);
+            seq++;
+        }
 
-        // 7. 构造AI输入
+        // 7. 构造AI输入（用短序号替代19位雪花ID，减少token消耗）
         StringBuilder jobInfo = new StringBuilder();
+        seq = 1;
         for (JobDto dto : candidates.getList()) {
             Job detail = jobDetailMap.get(dto.getId());
-            jobInfo.append("ID:").append(dto.getId())
+            jobInfo.append("ID:").append(seq++)
                     .append("\n标题:").append(dto.getTitle())
                     .append("\n公司:").append(dto.getCompanyName())
                     .append("\n岗位职责:").append(detail != null ? detail.getDescription() : "")
@@ -646,25 +665,29 @@ public class JobService {
         String preferenceInfo = param.getPreference() != null ? param.getPreference() : "无特殊偏好";
 
         String systemPrompt = "你是一个求职推荐助手。根据用户的偏好，从候选岗位中选出8-10个最合适的岗位。" +
-                "返回JSON格式：{\"summary\":\"推荐说明（20字以内）\",\"jobIds\":[岗位ID列表]}。" +
+                "返回JSON格式：{\"summary\":\"推荐说明（14字以内）\",\"jobIds\":[岗位ID列表]}。" +
                 "只返回JSON，不要其他内容。";
         String userMessage = "【用户偏好】\n" + preferenceInfo + "\n\n【候选岗位】\n" + jobInfo;
 
         // 8. 调用AI
+        sw.start("AI调用");
         String aiResponse = aiChatAbility.chat("job-recommend", systemPrompt, userMessage);
         String json = AiResponseCleanTool.clean(aiResponse);
+        sw.stop();
 
-        // 9. 解析AI返回，过滤出选中的岗位
+        log.info("recommendJobs耗时统计:\n{}", sw.prettyPrint());
+
+        // 9. 解析AI返回，别名映射回真实ID，过滤出选中的岗位
         try {
             JsonNode root = HttpTool.objectMapper.readTree(json);
             String summary = root.path("summary").asText("为你精选了合适的岗位");
-            List<Long> selectedIds = new ArrayList<>();
-            root.path("jobIds").forEach(node -> selectedIds.add(node.asLong()));
+            List<Long> selectedRealIds = new ArrayList<>();
+            root.path("jobIds").forEach(node -> {
+                Long realId = aliasToRealId.get(node.asInt());
+                if (realId != null) selectedRealIds.add(realId);
+            });
 
-            List<JobDto> selectedJobs = selectedIds.stream()
-                    .map(candidateMap::get)
-                    .filter(Objects::nonNull)
-                    .collect(Collectors.toList());
+            List<JobDto> selectedJobs = selectedRealIds.stream().map(candidateMap::get).filter(Objects::nonNull).collect(Collectors.toList());
 
             JobAgentRecommendDto result = new JobAgentRecommendDto();
             result.setSummary(summary);

client-api/src/main/resources/application-local.yml

@@ -91,7 +91,7 @@ app:
       job-recommend:
         base-url: ${AI_BASE_URL:https://ark.cn-beijing.volces.com/api/v3}
         api-key: ${AI_API_KEY:fd065993-bee2-4f31-8bf2-56d5d3012c02}
-        model: ${AI_MODEL:doubao-1-5-pro-32k-250115}
+        model: ${AI_MODEL:doubao-1-5-lite-32k-250115}
 
 
   # 岗位清洗配置