test(aihr): align pilot completion metric

backend/ruoyi-modules/ruoyi-aihr/src/main/java/org/dromara/aihr/service/AihrPracticeSeedService.java

@@ -535,9 +535,9 @@ public class AihrPracticeSeedService {
         ensureAssignmentTable();
         ensureCalibrationTable();
         int trainingCount = count("SELECT COUNT(*) FROM aihr_practice_session WHERE tenant_id = ? AND mode = 'mobile'", TENANT_ID);
-        int pendingAssignments = count("SELECT COUNT(*) FROM aihr_practice_assignment WHERE tenant_id = ? AND status = '待训练'", TENANT_ID);
-        int assignmentTotal = trainingCount + pendingAssignments;
-        boolean completionReady = assignmentTotal > 0 && trainingCount * 100 >= assignmentTotal * 80;
+        int completedPeople = countCompletedPilotPeople();
+        int pilotPeople = countPilotPeople();
+        boolean completionReady = pilotPeople > 0 && completedPeople * 100 >= pilotPeople * 80;
         int reviewed = count("SELECT COUNT(*) FROM aihr_practice_session WHERE tenant_id = ? AND mode = 'mobile' AND status = '已复盘'", TENANT_ID);
         CalibrationStats calibrationStats = calibrationStats();
         AihrSopSeedService.SopReviewStats sopStats = sopSeedService.sopReviewStats();
@@ -554,7 +554,9 @@ public class AihrPracticeSeedService {
         StringBuilder csv = new StringBuilder();
         appendCsvRow(csv, "metric", "value");
         appendCsvRow(csv, "training_count", trainingCount);
-        appendCsvRow(csv, "completion_rate", percent(trainingCount, assignmentTotal));
+        appendCsvRow(csv, "completion_people_count", completedPeople);
+        appendCsvRow(csv, "completion_people_total", pilotPeople);
+        appendCsvRow(csv, "completion_rate", percent(completedPeople, pilotPeople));
         appendCsvRow(csv, "completion_rate_target", "80.0%");
         appendCsvRow(csv, "completion_rate_ready", completionReady);
         appendCsvRow(csv, "average_score", String.format(java.util.Locale.ROOT, "%.1f", averageScore == null ? 0 : averageScore));
@@ -597,6 +599,34 @@ public class AihrPracticeSeedService {
         return csv.toString();
     }
 
+    private int countCompletedPilotPeople() {
+        return count("""
+            SELECT COUNT(*)
+            FROM (
+                SELECT DISTINCT ext_party_id
+                FROM aihr_practice_session
+                WHERE tenant_id = ? AND mode = 'mobile'
+            ) completed_people
+            """, TENANT_ID);
+    }
+
+    private int countPilotPeople() {
+        return count("""
+            SELECT COUNT(*)
+            FROM (
+                SELECT ext_party_id
+                FROM aihr_practice_session
+                WHERE tenant_id = ? AND mode = 'mobile'
+                UNION
+                SELECT ext_party_id
+                FROM aihr_practice_assignment
+                WHERE tenant_id = ?
+                  AND status = '待训练'
+                  AND (source <> 'daily' OR DATE(create_time) = CURRENT_DATE())
+            ) pilot_people
+            """, TENANT_ID, TENANT_ID);
+    }
+
     public ReviewDetailResponse reviewDetail(Long id) {
         ensurePracticeTable();
         if (id == null) {

docs/DEMO_ACCEPTANCE.md

@@ -32,7 +32,7 @@
 | 4 | 管理端 `/train/practice` | 选择训练记录 → 人工校准评分 → 导出试点 CSV | 导出包含训练次数、完训率、平均分、预警数、主管复盘率、AI/人工分档一致率、SOP 可用率 |
 | 5 | 模型成本闸门 | 设置 `AIHR_AI_RUNTIME_ENABLED=false` 后重启后端 → 调 `/api/aihr/model/chat` | 返回 `cost-guard-fallback`，chat/asr/tts 走现有文本兜底，不影响训练闭环 |
 
-试点正式验收前，用 `AIHR_PILOT_STRICT=true ./scripts/demo-check.sh` 检查 M5 样本闸门；完训率、校准样本、AI/人工分档一致率和 SOP 可用率未达标时应失败，不用静态演示 marker 代替真实试点数据。
+试点正式验收前，用 `AIHR_PILOT_STRICT=true ./scripts/demo-check.sh` 检查 M5 样本闸门；人员完训率、校准样本、AI/人工分档一致率和 SOP 可用率未达标时应失败，不用静态演示 marker 代替真实试点数据。
 
 ## 录屏兜底
 

scripts/demo-check.sh

@@ -57,11 +57,22 @@ check_pilot_samples() {
     return
   fi
 
-  local scenario_count training_count pending_assignments assignment_total calibration_stats calibration_count calibration_matched sop_total sop_usable sop_pending
+  local scenario_count completed_people pilot_people calibration_stats calibration_count calibration_matched sop_total sop_usable sop_pending
   scenario_count="$(pilot_sql_scalar "SELECT COUNT(*) FROM aihr_practice_scenario WHERE tenant_id = '000000' AND position = '生活顾问' AND enabled = 1")"
-  training_count="$(pilot_sql_scalar "SELECT COUNT(*) FROM aihr_practice_session WHERE tenant_id = '000000' AND mode = 'mobile'")"
-  pending_assignments="$(pilot_sql_scalar "SELECT COUNT(*) FROM aihr_practice_assignment WHERE tenant_id = '000000' AND status = '待训练'")"
-  assignment_total=$(( training_count + pending_assignments ))
+  completed_people="$(pilot_sql_scalar "SELECT COUNT(*) FROM (SELECT DISTINCT ext_party_id FROM aihr_practice_session WHERE tenant_id = '000000' AND mode = 'mobile') completed_people")"
+  pilot_people="$(pilot_sql_scalar "
+    SELECT COUNT(*)
+    FROM (
+      SELECT ext_party_id
+      FROM aihr_practice_session
+      WHERE tenant_id = '000000' AND mode = 'mobile'
+      UNION
+      SELECT ext_party_id
+      FROM aihr_practice_assignment
+      WHERE tenant_id = '000000'
+        AND status = '待训练'
+        AND (source <> 'daily' OR DATE(create_time) = CURRENT_DATE())
+    ) pilot_people")"
   calibration_stats="$(pilot_sql_scalar "
     SELECT COUNT(*) AS total,
            COALESCE(SUM(CASE
@@ -80,12 +91,12 @@ check_pilot_samples() {
   sop_total="$(pilot_sql_scalar "SELECT COUNT(*) FROM aihr_sop_answer_review WHERE tenant_id = '000000' AND status = '已评审'")"
   sop_usable="$(pilot_sql_scalar "SELECT COALESCE(SUM(CASE WHEN usable = 1 THEN 1 ELSE 0 END), 0) FROM aihr_sop_answer_review WHERE tenant_id = '000000' AND status = '已评审'")"
   sop_pending="$(pilot_sql_scalar "SELECT COUNT(*) FROM aihr_sop_answer_review WHERE tenant_id = '000000' AND status <> '已评审'")"
-  echo "OK: pilot gates scenarios=${scenario_count}/12 completion=${training_count}/${assignment_total} calibration=${calibration_count}/20 consistency=${calibration_matched}/${calibration_count} sop_usable=${sop_usable}/${sop_total} sop_pending=${sop_pending}"
+  echo "OK: pilot gates scenarios=${scenario_count}/12 completion=${completed_people}/${pilot_people} calibration=${calibration_count}/20 consistency=${calibration_matched}/${calibration_count} sop_usable=${sop_usable}/${sop_total} sop_pending=${sop_pending}"
 
   [[ "${AIHR_PILOT_STRICT:-false}" != "true" ]] || {
     (( scenario_count >= 12 )) || fail "pilot enabled scenarios ${scenario_count}/12"
-    (( assignment_total > 0 )) || fail "pilot completion samples missing"
-    (( training_count * 100 >= assignment_total * 80 )) || fail "pilot completion rate below 80% (${training_count}/${assignment_total})"
+    (( pilot_people > 0 )) || fail "pilot completion samples missing"
+    (( completed_people * 100 >= pilot_people * 80 )) || fail "pilot completion rate below 80% (${completed_people}/${pilot_people})"
     (( calibration_count >= 20 )) || fail "pilot calibration samples ${calibration_count}/20"
     (( calibration_matched * 100 >= calibration_count * 70 )) || fail "pilot AI/human band consistency below 70%"
     (( sop_total > 0 )) || fail "pilot SOP review samples missing"