feat(alerts): 新增客户集中度预警规则 customer_concentration + 预测偏差规则启用/联动每日预警生成

- alert_rules: 新增 rule_type=customer_concentration（单一/前N客户收入占比超阈值触发，黄=超阈值/红=阈值x倍数）
  数据源 zxt_masterbill 客户(往来单位)收入聚合，unit_id<=0 占位剔除；无客户数据可回退 KPI 口径
  复用现有 KPIAlert 生成链路：check-all 内联分支 + 专用端点 POST /run-customer-concentration
- alert_generator(每日9:00): 新增规则引擎步骤，复用上述检查函数跑 forecast_deviation/customer_concentration
- AlertList.vue: 规则类型筛选/编辑项 + 参数表单 + 客户集中度检查按钮
- 测试: tests/test_customer_concentration_rule.py 17 条（规则注册/聚合/双数据源/黄红灯/去重/check-all）
- 验证脚本: scripts/verify_forecast_deviation_rules_e2e.py / verify_customer_concentration_rule_e2e.py

backend/scripts/alert_generator.py

@@ -190,6 +190,41 @@ def run_alert_check(db_session, period: str = None) -> int:
     return new_count
 
 
+def run_rule_engine_checks(db_session) -> dict:
+    """预警规则引擎（rule_type 驱动）— 预测偏差 + 客户集中度（P2 2026-09-10）
+
+    复用 alert_rules 的检查端点实现（FastAPI 路由函数=带 Depends 默认值的普通函数，
+    显式传参即可复用，零逻辑复制），按存在规则的账套逐个执行。
+    任何单点失败只记录日志，不影响静态阈值主流程。
+    """
+    from app.api.alert_rules import (
+        AlertRule, run_forecast_deviation_check, run_customer_concentration_check,
+    )
+
+    stats = {"forecast_deviation": 0, "customer_concentration": 0}
+    try:
+        rows = db_session.query(AlertRule.entity_id).filter(
+            AlertRule.enabled == 1,
+            AlertRule.rule_type.in_(("forecast_deviation", "customer_concentration")),
+        ).distinct().all()
+    except Exception as e:
+        logger.error(f"规则引擎检查跳过（规则查询失败）: {e}")
+        return stats
+
+    for (eid,) in rows:
+        for key, fn in (("forecast_deviation", run_forecast_deviation_check),
+                        ("customer_concentration", run_customer_concentration_check)):
+            try:
+                r = fn(db=db_session, entity_id=eid)
+                n = int(r.get("generated", 0) or 0)
+                stats[key] += n
+                if n:
+                    logger.info(f"  规则预警 entity={eid} {key}: {n}条")
+            except Exception as e:
+                logger.error(f"规则检查失败 entity={eid} {key}: {e}")
+    return stats
+
+
 def generate_and_push(db_session) -> dict:
     """生成预警并推送，返回统计"""
     period = datetime.now().strftime("%Y-%m")
@@ -202,6 +237,9 @@ def generate_and_push(db_session) -> dict:
     new_count = run_alert_check(db_session, period)
     logger.info(f"预警检查完成: 新增 {new_count} 条")
 
+    # 1b. 规则引擎检查（预测偏差 / 客户集中度，P2 2026-09-10）
+    rule_stats = run_rule_engine_checks(db_session)
+
     # 2. 推送
     pushed = 0
     if new_count > 0:
@@ -212,7 +250,8 @@ def generate_and_push(db_session) -> dict:
         except Exception as e:
             logger.error(f"推送失败: {e}")
 
-    return {"period": period, "new_alerts": new_count, "pushed": pushed, "cleaned_green": cleaned}
+    return {"period": period, "new_alerts": new_count, "pushed": pushed,
+            "cleaned_green": cleaned, "rule_engine": rule_stats}
 
 
 if __name__ == "__main__":
@@ -224,6 +263,7 @@ if __name__ == "__main__":
     db = get_session_local()()
     try:
         result = generate_and_push(db)
-        print(f"预警检查: {result['new_alerts']}条新预警 / {result['pushed']}条已推送")
+        print(f"预警检查: {result['new_alerts']}条新预警 / {result['pushed']}条已推送"
+              f" / 规则引擎{result['rule_engine']}")
     finally:
         db.close()