feat: 2026-04-15~05-02 累积变更基线 — AI 重构 + Runtime Context + DWS 修复

涵盖（每条对应已存的审计记录）：
- AI 模块拆分：apps/backend/app/ai/apps -> prompts/（8 个 APP + app2a 派生）
  audit: 2026-04-20__ai-module-complete.md
- admin-web AI 管理套件：AIDashboard / AIOperations / AIRunLogs / AITriggers / TriggerManager
  audit: 2026-04-21__admin-web-ai-management-suite.md
- App2 财务洞察 prompt v3 -> v5.1 + 小程序 AI 接入（chat / board-finance）
  audit: 2026-04-22__app2_prompt_v5_1_and_miniprogram_ai_insight.md
- App2 prewarm 全过滤器 + AI 触发器 cron reschedule
  audit: 2026-04-21__app2-finance-prewarm-all-filters.md
  migration: 20260420_ai_trigger_jobs_and_app2_prewarm.sql / 20260421_app2_prewarm_cron_reschedule.sql
- AppType 联合类型对齐 + adminAiAppTypes.test.ts
  audit: 2026-04-30__admin_web_ai_app_type_alignment.md
- DashScope tokens_used 提取修复
  audit: 2026-04-30__backend_dashscope_tokens_used_extraction.md
- App3 线索完整详情 prompt
  audit: 2026-05-01__backend_app3_full_detail_prompt.md
- Runtime Context 沙箱（5-1~5-2 主线）：
  - 后端 schema/service + admin_runtime_context / xcx_runtime_clock 两个 router
  - admin-web RuntimeContext.tsx + miniprogram runtime-clock.ts
  - migration: 20260501__runtime_context_sandbox.sql
  - tools/db/verify_admin_web_sandbox.py + verify_sandbox_end_to_end.py
  - database/changes: 7 份 sandbox_* 验证报告
- 飞球 DWS 修复：finance_area_daily 区域汇总 + task_engine 调整
  + RLS 视图业务日上界（migration 20260502 + scripts/ops/gen_rls_business_date_migration.py）

合规：
- .gitignore 启用 tmp/ 排除
- 不入仓：apps/etl/connectors/feiqiu/.env（API_TOKEN secret，本地修改保留）

待验证清单：
- docs/audit/changes/2026-05-04__cumulative_baseline_pending_verification.md
  每个主题的功能完整性 / 上线验证几乎都未收口，按优先级 P0~P3 逐一处理

apps/admin-web/src/App.tsx

@@ -25,6 +25,7 @@ import {
   TeamOutlined,
   BugOutlined,
   ApartmentOutlined,
+  RobotOutlined,
 } from "@ant-design/icons";
 import type { MenuProps } from "antd";
 import { useAuthStore } from "./store/authStore";
@@ -36,6 +37,10 @@ import EnvConfig from "./pages/EnvConfig";
 import DBViewer from "./pages/DBViewer";
 import TenantAdmins from "./pages/TenantAdmins";
 import AIRunLogs from "./pages/AIRunLogs";
+import AIDashboard from "./pages/AIDashboard";
+import AIOperations from "./pages/AIOperations";
+import AITriggerJobs from "./pages/AITriggerJobs";
+import AIPrewarm from "./pages/AIPrewarm";
 import DevTrace from "./pages/DevTrace";
 import TriggerJobs from "./pages/TriggerJobs";
 import TransferLog from "./pages/TransferLog";
@@ -44,6 +49,7 @@ import TaskEngineConfig from "./pages/TaskEngineConfig";
 import Dashboard from "./pages/Dashboard";
 import ETLTasks from "./pages/ETLTasks";
 import TriggerManager from "./pages/TriggerManager";
+import RuntimeContextPage from "./pages/RuntimeContext";
 
 const { Sider, Content, Footer } = Layout;
 const { Text } = Typography;
@@ -65,11 +71,22 @@ export const NAV_ITEMS: MenuProps["items"] = [
     ],
   },
   { key: "/triggers", icon: <ClockCircleOutlined />, label: "触发器管理" },
+  {
+    key: "ai-group", icon: <RobotOutlined />, label: "AI 管理",
+    children: [
+      { key: "/ai/dashboard", label: "总览" },
+      { key: "/ai/operations", label: "手动操作" },
+      { key: "/ai/prewarm", label: "预热进度" },
+      { key: "/triggers?tab=ai", label: "触发器设置" },
+      { key: "/ai/trigger-jobs", label: "调度历史" },
+    ],
+  },
   { key: "/tenant-admins", icon: <TeamOutlined />, label: "租户管理员" },
   {
     key: "settings-group", icon: <SettingOutlined />, label: "系统设置",
     children: [
       { key: "/settings/env-config", label: "环境配置" },
+      { key: "/settings/runtime-context", label: "业务运行上下文 / 沙箱" },
       { key: "/triggers?tab=biz", label: "触发器配置" },
     ],
   },
@@ -90,12 +107,14 @@ export const NAV_ITEMS: MenuProps["items"] = [
 /** 根据当前路径计算 selectedKeys */
 export function getSelectedKeys(pathname: string, search: string): string[] {
   const fullPath = pathname + search;
-  // 精确匹配含查询参数的菜单项（如 /triggers?tab=biz）
+  // 精确匹配含查询参数的菜单项（如 /triggers?tab=biz / ?tab=ai）
   if (fullPath === "/triggers?tab=biz") return ["/triggers?tab=biz"];
+  if (fullPath === "/triggers?tab=ai") return ["/triggers?tab=ai"];
   // 子路由匹配
   if (pathname.startsWith("/task-engine/")) return [pathname];
   if (pathname.startsWith("/settings/")) return [pathname];
   if (pathname.startsWith("/logs/")) return [pathname];
+  if (pathname.startsWith("/ai/")) return [pathname];
   // 一级路由直接匹配
   return [pathname];
 }
@@ -106,6 +125,9 @@ export function getDefaultOpenKeys(pathname: string): string[] {
   if (pathname.startsWith("/task-engine/")) keys.push("task-engine-group");
   if (pathname.startsWith("/settings/")) keys.push("settings-group");
   if (pathname.startsWith("/logs/")) keys.push("logs-group");
+  if (pathname.startsWith("/ai/")) keys.push("ai-group");
+  // 从 AI 菜单跳过来的"触发器设置"（/triggers?tab=ai）也展开 ai-group
+  // 注：此函数参数只接收 pathname，无法判断 tab，交由路由侧 searchParams 处理默认展开
   // 触发器配置跳转入口也需要展开系统设置
   if (pathname === "/triggers") keys.push("settings-group");
   return keys;
@@ -225,6 +247,13 @@ const AppLayout: React.FC = () => {
 
             {/* 系统设置 */}
             <Route path="/settings/env-config" element={<EnvConfig />} />
+            <Route path="/settings/runtime-context" element={<RuntimeContextPage />} />
+
+            {/* AI 管理 */}
+            <Route path="/ai/dashboard" element={<AIDashboard />} />
+            <Route path="/ai/operations" element={<AIOperations />} />
+            <Route path="/ai/prewarm" element={<AIPrewarm />} />
+            <Route path="/ai/trigger-jobs" element={<AITriggerJobs />} />
 
             {/* 日志调试 */}
             <Route path="/logs/dev-trace" element={<DevTrace />} />

apps/admin-web/src/__tests__/adminAiAppTypes.test.ts

@@ -0,0 +1,43 @@
+/**
+ * 回归测试：admin-web 手动执行 App 类型必须与后端 /api/admin/ai/run/{app_type} 对齐。
+ *
+ * 缓存类型仍使用 `*_analysis` / `*_consolidated`，但手动执行和 run log
+ * 应使用 dispatcher 支持的 app_type，避免前端发出后端 400 的路径。
+ */
+
+import { describe, expect, it } from "vitest";
+import { RUN_APP_TYPES } from "../api/adminAI";
+import { CACHE_TYPE_OPTIONS, RUN_APP_TYPE_OPTIONS } from "../pages/AIOperations";
+import { RUN_LOG_APP_TYPE_OPTIONS } from "../pages/AIRunLogs";
+
+describe("admin AI app_type 对齐", () => {
+  it("手动执行类型使用后端支持的 app_type，而不是缓存类型", () => {
+    const apiTypes = [...RUN_APP_TYPES];
+    const runOptionValues = RUN_APP_TYPE_OPTIONS.map((item) => item.value);
+
+    for (const appType of ["app6_note", "app7_customer", "app8_consolidation"]) {
+      expect(apiTypes).toContain(appType);
+      expect(runOptionValues).toContain(appType);
+    }
+
+    for (const cacheType of ["app6_note_analysis", "app7_customer_analysis", "app8_clue_consolidated"]) {
+      expect(runOptionValues).not.toContain(cacheType);
+    }
+  });
+
+  it("缓存失效继续使用 cache_type，避免破坏已有缓存管理", () => {
+    const cacheOptionValues = CACHE_TYPE_OPTIONS.map((item) => item.value);
+
+    expect(cacheOptionValues).toContain("app6_note_analysis");
+    expect(cacheOptionValues).toContain("app7_customer_analysis");
+    expect(cacheOptionValues).toContain("app8_clue_consolidated");
+  });
+
+  it("调用记录筛选包含真实写入 ai_run_logs 的 app_type", () => {
+    const runLogOptionValues = RUN_LOG_APP_TYPE_OPTIONS.map((item) => item.value);
+
+    expect(runLogOptionValues).toContain("app6_note");
+    expect(runLogOptionValues).toContain("app7_customer");
+    expect(runLogOptionValues).toContain("app8_consolidate");
+  });
+});

apps/admin-web/src/api/adminAI.ts

@@ -9,29 +9,30 @@ import { apiClient } from "./client";
 
 // ---- 公共类型 ----
 
+export const RUN_APP_TYPES = [
+  "app2_finance",
+  "app2a_finance_area",
+  "app3_clue",
+  "app4_analysis",
+  "app5_tactics",
+  "app6_note",
+  "app7_customer",
+  "app8_consolidation",
+] as const;
+
 /**
- * AI APP 类型联合（与后端 `CacheTypeEnum` / `_SUPPORTED_APP_TYPES` 同步）。
+ * 按需执行 App 类型联合（与后端 `/api/admin/ai/run/{app_type}` 同步）。
  *
- * - app1_chat          · 小程序聊天（无缓存）
  * - app2_finance       · 全域财务洞察（area = 'all'，8 组合）
  * - app2a_finance_area · 区域财务洞察（area != 'all'，64 组合，2026-04-23 新增）
  * - app3_clue          · 客户线索分析
  * - app4_analysis      · 助教关系分析
  * - app5_tactics       · 话术参考
- * - app6_note_analysis · 备注分析
- * - app7_customer_analysis · 客户综合分析
- * - app8_clue_consolidated · 线索整合
+ * - app6_note          · 备注分析
+ * - app7_customer      · 客户综合分析
+ * - app8_consolidation · 线索整合
  */
-export type AppType =
-  | "app1_chat"
-  | "app2_finance"
-  | "app2a_finance_area"
-  | "app3_clue"
-  | "app4_analysis"
-  | "app5_tactics"
-  | "app6_note_analysis"
-  | "app7_customer_analysis"
-  | "app8_clue_consolidated";
+export type AppType = (typeof RUN_APP_TYPES)[number];
 
 // ---- 类型定义 ----
 

apps/admin-web/src/api/runtimeContext.ts

@@ -0,0 +1,78 @@
+/**
+ * 业务运行上下文 / 沙箱配置 API。
+ */
+
+import { apiClient } from "./client";
+
+export type RuntimeMode = "live" | "sandbox";
+export type AIMode = "live";
+export type RuntimeStepStatus = "success" | "skipped" | "warning" | "failed";
+
+export interface RuntimeContext {
+  site_id: number;
+  mode: RuntimeMode;
+  business_day_start_hour: number;
+  business_date: string;
+  business_now: string;
+  sandbox_date: string | null;
+  sandbox_instance_id: string | null;
+  ai_mode: AIMode;
+  status: string;
+  is_sandbox: boolean;
+}
+
+export interface RuntimeSiteItem {
+  site_id: number;
+  site_name: string | null;
+  site_code: string | null;
+  is_active: boolean;
+  mode: RuntimeMode | null;
+  sandbox_date: string | null;
+  sandbox_instance_id: string | null;
+  ai_mode: AIMode | null;
+  status: string | null;
+  updated_at: string | null;
+}
+
+export interface RuntimeSwitchRequest {
+  site_id: number;
+  mode: RuntimeMode;
+  sandbox_date?: string | null;
+  reset_sandbox?: boolean;
+  reason?: string | null;
+}
+
+export interface RuntimeTransitionStep {
+  key: string;
+  title: string;
+  status: RuntimeStepStatus;
+  detail: string;
+  count: number;
+}
+
+export interface RuntimeSwitchResponse {
+  context: RuntimeContext;
+  steps: RuntimeTransitionStep[];
+}
+
+export async function fetchRuntimeSites(): Promise<RuntimeSiteItem[]> {
+  const { data } = await apiClient.get<RuntimeSiteItem[]>("/admin/runtime-context/sites");
+  return data;
+}
+
+export async function fetchRuntimeContext(siteId: number): Promise<RuntimeContext> {
+  const { data } = await apiClient.get<RuntimeContext>("/admin/runtime-context", {
+    params: { site_id: siteId },
+  });
+  return data;
+}
+
+export async function switchRuntimeContext(
+  payload: RuntimeSwitchRequest,
+): Promise<RuntimeSwitchResponse> {
+  const { data } = await apiClient.patch<RuntimeSwitchResponse>(
+    "/admin/runtime-context",
+    payload,
+  );
+  return data;
+}

apps/admin-web/src/pages/AIDashboard.tsx

@@ -8,12 +8,27 @@
  * - 第四行：告警列表
  */
 
-import React, { useEffect, useState, useCallback } from "react";
+import React, { useEffect, useRef, useState, useCallback } from "react";
 import {
   Card, Row, Col, Statistic, Table, Tag, Badge, Progress,
-  Select, Button, message, Typography, Space,
+  Select, Button, message, Typography, Space, DatePicker,
 } from "antd";
-import { ReloadOutlined } from "@ant-design/icons";
+import { ReloadOutlined, WifiOutlined } from "@ant-design/icons";
+import type { Dayjs } from "dayjs";
+
+const { RangePicker } = DatePicker;
+
+const RANGE_OPTIONS = [
+  { label: "今日", value: 1 },
+  { label: "近 3 天", value: 3 },
+  { label: "近 7 天", value: 7 },
+  { label: "近 10 天", value: 10 },
+  { label: "指定日期", value: 0 },     // 0 = 启用 RangePicker
+];
+
+const RANGE_LABEL: Record<number, string> = {
+  1: "今日", 3: "近 3 天", 7: "近 7 天", 10: "近 10 天",
+};
 import type { ColumnsType } from "antd/es/table";
 import {
   getDashboard,
@@ -85,51 +100,119 @@ const AIDashboard: React.FC = () => {
   const [data, setData] = useState<DashboardResponse | null>(null);
   const [loading, setLoading] = useState(false);
   const [siteId, setSiteId] = useState<number | undefined>(undefined);
+  const [rangeDays, setRangeDays] = useState<number>(1);   // 0=自定义日期 / 1/3/7/10
+  const [customRange, setCustomRange] = useState<[Dayjs, Dayjs] | null>(null);
+  const [wsStatus, setWsStatus] = useState<"connecting" | "connected" | "disconnected">("disconnected");
+  const [realtimeAlerts, setRealtimeAlerts] = useState<AlertItem[]>([]);
+  const wsRef = useRef<WebSocket | null>(null);
 
   const load = useCallback(async () => {
     setLoading(true);
     try {
-      const res = await getDashboard(siteId);
+      const query: { site_id?: number; range_days?: number; date_from?: string; date_to?: string } = {};
+      if (siteId != null) query.site_id = siteId;
+      if (rangeDays === 0 && customRange) {
+        query.date_from = customRange[0].format("YYYY-MM-DD");
+        query.date_to = customRange[1].format("YYYY-MM-DD");
+      } else if (rangeDays > 0) {
+        query.range_days = rangeDays;
+      }
+      const res = await getDashboard(query);
       setData(res);
     } catch {
       message.error("加载 Dashboard 失败");
     } finally {
       setLoading(false);
     }
-  }, [siteId]);
+  }, [siteId, rangeDays, customRange]);
 
   useEffect(() => { load(); }, [load]);
 
+  const statLabel = rangeDays === 0
+    ? (customRange ? `${customRange[0].format("MM-DD")} ~ ${customRange[1].format("MM-DD")}` : "指定日期")
+    : (RANGE_LABEL[rangeDays] || "今日");
+
+  // WebSocket 实时告警订阅
+  useEffect(() => {
+    const wsKey = siteId ?? -1;
+    const proto = window.location.protocol === "https:" ? "wss" : "ws";
+    const url = `${proto}://${window.location.host}/ws/ai-alerts/${wsKey}`;
+    setWsStatus("connecting");
+
+    const ws = new WebSocket(url);
+    wsRef.current = ws;
+
+    ws.onopen = () => setWsStatus("connected");
+    ws.onclose = () => setWsStatus("disconnected");
+    ws.onerror = () => setWsStatus("disconnected");
+    ws.onmessage = (evt) => {
+      try {
+        const msg = JSON.parse(evt.data as string) as {
+          type: string;
+          payload: AlertItem;
+        };
+        if (msg.type === "alert_created" && msg.payload) {
+          setRealtimeAlerts((prev) => [msg.payload, ...prev].slice(0, 20));
+          message.warning(`[实时] ${msg.payload.app_type} ${msg.payload.status}`);
+        }
+      } catch {
+        // 忽略非 JSON 消息
+      }
+    };
+
+    return () => {
+      ws.close();
+      wsRef.current = null;
+      setWsStatus("disconnected");
+    };
+  }, [siteId]);
+
   return (
     <div>
       {/* 顶部：门店筛选 + 刷新 */}
       <Row justify="space-between" align="middle" style={{ marginBottom: 16 }}>
-        <Space>
+        <Space wrap>
           <Title level={4} style={{ margin: 0 }}>AI 运行总览</Title>
           <Select
-            allowClear placeholder="门店筛选" style={{ width: 200 }}
+            allowClear placeholder="门店筛选" style={{ width: 180 }}
             value={siteId} onChange={(v) => setSiteId(v)}
             options={[{ label: "默认门店", value: 2790685415443269 }]}
           />
+          <Select
+            value={rangeDays} onChange={setRangeDays} style={{ width: 140 }}
+            options={RANGE_OPTIONS}
+          />
+          {rangeDays === 0 && (
+            <RangePicker
+              value={customRange}
+              onChange={(v) => setCustomRange(v as [Dayjs, Dayjs] | null)}
+            />
+          )}
+        </Space>
+        <Space>
+          <Badge
+            status={wsStatus === "connected" ? "success" : wsStatus === "connecting" ? "processing" : "default"}
+            text={<span style={{ fontSize: 12, color: "#888" }}><WifiOutlined /> 实时 {wsStatus === "connected" ? "已连接" : wsStatus === "connecting" ? "连接中" : "断开"}</span>}
+          />
+          <Button icon={<ReloadOutlined />} onClick={load} loading={loading}>刷新</Button>
         </Space>
-        <Button icon={<ReloadOutlined />} onClick={load} loading={loading}>刷新</Button>
       </Row>
 
       {/* 第一行：4 个统计卡片 */}
       <Row gutter={16} style={{ marginBottom: 16 }}>
         <Col span={6}>
-          <Card><Statistic title="今日调用次数" value={data?.today_calls ?? 0} /></Card>
+          <Card><Statistic title={`${statLabel}调用次数`} value={data?.today_calls ?? 0} /></Card>
         </Col>
         <Col span={6}>
           <Card>
             <Statistic
-              title="今日成功率" suffix="%"
+              title={`${statLabel}成功率`} suffix="%"
               value={data ? (data.today_success_rate * 100).toFixed(1) : "0.0"}
             />
           </Card>
         </Col>
         <Col span={6}>
-          <Card><Statistic title="今日 Token 消耗" value={data?.today_tokens ?? 0} /></Card>
+          <Card><Statistic title={`${statLabel} Token 消耗`} value={data?.today_tokens ?? 0} /></Card>
         </Col>
         <Col span={6}>
           <Card>
@@ -201,11 +284,22 @@ const AIDashboard: React.FC = () => {
         </Col>
       </Row>
 
-      {/* 第四行：告警列表 */}
-      <Card title="告警列表" size="small">
+      {/* 第四行：告警列表（实时 + 历史合并） */}
+      <Card
+        title="告警列表"
+        size="small"
+        extra={realtimeAlerts.length > 0 && (
+          <Tag color="orange">{realtimeAlerts.length} 条实时</Tag>
+        )}
+      >
         <Table<AlertItem>
           columns={alertColumns}
-          dataSource={data?.recent_alerts ?? []}
+          dataSource={[
+            ...realtimeAlerts,
+            ...(data?.recent_alerts ?? []).filter(
+              (a) => !realtimeAlerts.some((r) => r.id === a.id)
+            ),
+          ]}
           rowKey="id" size="small" pagination={{ pageSize: 10 }}
           loading={loading}
         />

apps/admin-web/src/pages/AIOperations.tsx

@@ -31,7 +31,7 @@ const EVENT_TYPE_OPTIONS = [
 const { TextArea } = Input;
 const { Title } = Typography;
 
-const APP_TYPE_OPTIONS = [
+export const CACHE_TYPE_OPTIONS = [
   { label: "App3 维客线索", value: "app3_clue" },
   { label: "App4 关系分析", value: "app4_analysis" },
   { label: "App5 话术参考", value: "app5_tactics" },
@@ -40,6 +40,15 @@ const APP_TYPE_OPTIONS = [
   { label: "App8 线索整理", value: "app8_clue_consolidated" },
 ];
 
+export const RUN_APP_TYPE_OPTIONS: { label: string; value: AppType }[] = [
+  { label: "App3 维客线索", value: "app3_clue" },
+  { label: "App4 关系分析", value: "app4_analysis" },
+  { label: "App5 话术参考", value: "app5_tactics" },
+  { label: "App6 备注分析", value: "app6_note" },
+  { label: "App7 客户分析", value: "app7_customer" },
+  { label: "App8 线索整理", value: "app8_consolidation" },
+];
+
 const ALERT_STATUS_COLOR: Record<string, string> = {
   failed: "red", timeout: "orange", circuit_open: "volcano",
 };
@@ -160,7 +169,7 @@ const AIOperations: React.FC = () => {
   };
 
   // ---- Card 3: 批量执行 ----
-  const [batchAppTypes, setBatchAppTypes] = useState<string[]>([]);
+  const [batchAppTypes, setBatchAppTypes] = useState<AppType[]>([]);
   const [batchMemberIds, setBatchMemberIds] = useState<string>("");
   const [batchSiteId, setBatchSiteId] = useState<number>(2790685415443269);
   const [batchLoading, setBatchLoading] = useState(false);
@@ -294,7 +303,7 @@ const AIOperations: React.FC = () => {
               <Select
                 allowClear placeholder="App 类型（可选）" style={{ width: "100%" }}
                 value={cacheAppType} onChange={setCacheAppType}
-                options={APP_TYPE_OPTIONS}
+                options={CACHE_TYPE_OPTIONS}
               />
               <Input
                 placeholder="会员 ID（可选）" value={cacheMemberId}
@@ -321,7 +330,7 @@ const AIOperations: React.FC = () => {
             <Select
               allowClear placeholder="App 类型" style={{ width: "100%" }}
               value={runAppType} onChange={setRunAppType}
-              options={APP_TYPE_OPTIONS}
+              options={RUN_APP_TYPE_OPTIONS}
             />
           </Col>
           <Col span={6}>
@@ -403,9 +412,9 @@ const AIOperations: React.FC = () => {
           <Col span={8}>
             <div style={{ marginBottom: 8, fontWeight: 500 }}>选择 App</div>
             <Checkbox.Group
-              options={APP_TYPE_OPTIONS}
+              options={RUN_APP_TYPE_OPTIONS}
               value={batchAppTypes}
-              onChange={(v) => setBatchAppTypes(v as string[])}
+              onChange={(v) => setBatchAppTypes(v as AppType[])}
               style={{ display: "flex", flexDirection: "column", gap: 4 }}
             />
           </Col>

apps/admin-web/src/pages/AIRunLogs.tsx

@@ -85,11 +85,7 @@ const AIRunLogs: React.FC = () => {
     }
   };
 
-  const APP_TYPE_OPTIONS = [
-    "app1_chat", "app2_finance", "app3_clue", "app4_analysis",
-    "app5_tactics", "app6_note_analysis", "app7_customer_analysis",
-    "app8_clue_consolidated",
-  ].map((v) => ({ label: v, value: v }));
+  const APP_TYPE_OPTIONS = RUN_LOG_APP_TYPE_OPTIONS;
 
   const columns: ColumnsType<RunLogItem> = [
     { title: "ID", dataIndex: "id", key: "id", width: 70 },
@@ -227,3 +223,9 @@ const AIRunLogs: React.FC = () => {
 };
 
 export default AIRunLogs;
+
+export const RUN_LOG_APP_TYPE_OPTIONS = [
+  "app1_chat", "app2_finance", "app2a_finance_area", "app3_clue",
+  "app4_analysis", "app5_tactics", "app6_note", "app7_customer",
+  "app8_consolidate", "app8_consolidation",
+].map((v) => ({ label: v, value: v }));

apps/admin-web/src/pages/AITriggers.tsx

@@ -0,0 +1,243 @@
+/**
+ * AI 触发器设置页面。
+ *
+ * 管理 biz.trigger_jobs 表中 job_type='ai_*' 的所有触发器，支持：
+ * - 启用/禁用
+ * - 修改 cron 表达式（仅 cron 类型）
+ * - 修改描述
+ * - 查看事件名、最近运行、下次运行、最后错误
+ */
+
+import React, { useCallback, useEffect, useState } from "react";
+import {
+  Card, Table, Tag, Button, Space, Modal, Input, Switch,
+  message, Typography, Tooltip, Descriptions,
+} from "antd";
+import { ReloadOutlined, EditOutlined } from "@ant-design/icons";
+import type { ColumnsType } from "antd/es/table";
+import {
+  listTriggers, updateTrigger,
+  type TriggerItem,
+} from "../api/adminAI";
+
+const { Title, Paragraph } = Typography;
+
+const STATUS_COLOR: Record<string, string> = {
+  enabled: "success",
+  disabled: "default",
+};
+
+const CONDITION_COLOR: Record<string, string> = {
+  event: "processing",
+  cron: "warning",
+  interval: "cyan",
+};
+
+function fmtTime(raw: string | null): string {
+  if (!raw) return "—";
+  const d = new Date(raw);
+  return Number.isNaN(d.getTime()) ? raw : d.toLocaleString("zh-CN");
+}
+
+function cronExpr(item: TriggerItem): string {
+  const cfg = item.trigger_config || {};
+  return String(cfg.cron_expression || cfg.event_name || "—");
+}
+
+const AITriggers: React.FC = () => {
+  const [items, setItems] = useState<TriggerItem[]>([]);
+  const [loading, setLoading] = useState(false);
+  const [editing, setEditing] = useState<TriggerItem | null>(null);
+  const [editCron, setEditCron] = useState("");
+  const [editDesc, setEditDesc] = useState("");
+  const [saving, setSaving] = useState(false);
+
+  const load = useCallback(async () => {
+    setLoading(true);
+    try {
+      const res = await listTriggers();
+      setItems(res);
+    } catch {
+      message.error("加载触发器列表失败");
+    } finally {
+      setLoading(false);
+    }
+  }, []);
+
+  useEffect(() => { load(); }, [load]);
+
+  const handleToggle = async (item: TriggerItem, next: boolean) => {
+    try {
+      await updateTrigger(item.id, { status: next ? "enabled" : "disabled" });
+      message.success(next ? "已启用" : "已禁用");
+      load();
+    } catch {
+      message.error("状态切换失败");
+    }
+  };
+
+  const openEdit = (item: TriggerItem) => {
+    setEditing(item);
+    setEditCron(String(item.trigger_config?.cron_expression || ""));
+    setEditDesc(item.description || "");
+  };
+
+  const handleSave = async () => {
+    if (!editing) return;
+    setSaving(true);
+    try {
+      const body: { cron_expression?: string; description?: string } = {};
+      if (editing.trigger_condition === "cron" && editCron !== editing.trigger_config?.cron_expression) {
+        body.cron_expression = editCron;
+      }
+      if (editDesc !== (editing.description || "")) {
+        body.description = editDesc;
+      }
+      if (Object.keys(body).length === 0) {
+        message.info("无变更");
+        setEditing(null);
+        return;
+      }
+      await updateTrigger(editing.id, body);
+      message.success("已保存");
+      setEditing(null);
+      load();
+    } catch (err) {
+      const msg = (err as { response?: { data?: { detail?: string } } })?.response?.data?.detail;
+      message.error(`保存失败${msg ? `：${msg}` : ""}`);
+    } finally {
+      setSaving(false);
+    }
+  };
+
+  const columns: ColumnsType<TriggerItem> = [
+    { title: "ID", dataIndex: "id", key: "id", width: 60 },
+    {
+      title: "触发器名", dataIndex: "job_name", key: "job_name", width: 200,
+      render: (v: string, r) => (
+        <div>
+          <div style={{ fontWeight: 500 }}>{v}</div>
+          {r.description && (
+            <div style={{ fontSize: 12, color: "#888", marginTop: 2 }}>{r.description}</div>
+          )}
+        </div>
+      ),
+    },
+    {
+      title: "类型", dataIndex: "trigger_condition", key: "trigger_condition", width: 80,
+      render: (v: string) => <Tag color={CONDITION_COLOR[v] ?? "default"}>{v}</Tag>,
+    },
+    {
+      title: "表达式 / 事件", key: "expr", width: 240,
+      render: (_: unknown, r) => (
+        <code style={{ fontSize: 12 }}>{cronExpr(r)}</code>
+      ),
+    },
+    {
+      title: "状态", dataIndex: "status", key: "status", width: 100,
+      render: (v: string, r) => (
+        <Space>
+          <Switch
+            size="small"
+            checked={v === "enabled"}
+            onChange={(c) => handleToggle(r, c)}
+          />
+          <Tag color={STATUS_COLOR[v] ?? "default"}>{v}</Tag>
+        </Space>
+      ),
+    },
+    { title: "最近运行", dataIndex: "last_run_at", key: "last_run_at", width: 160, render: fmtTime },
+    { title: "下次运行", dataIndex: "next_run_at", key: "next_run_at", width: 160, render: fmtTime },
+    {
+      title: "最后错误", dataIndex: "last_error", key: "last_error", ellipsis: true,
+      render: (v: string | null) => v ? (
+        <Tooltip title={v}><span style={{ color: "#d46b08" }}>{v.slice(0, 40)}…</span></Tooltip>
+      ) : "—",
+    },
+    {
+      title: "操作", key: "action", width: 100, fixed: "right",
+      render: (_: unknown, r) => (
+        <Button size="small" icon={<EditOutlined />} onClick={() => openEdit(r)}>编辑</Button>
+      ),
+    },
+  ];
+
+  return (
+    <div>
+      <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center", marginBottom: 16 }}>
+        <div>
+          <Title level={4} style={{ margin: 0 }}>AI 触发器设置</Title>
+          <Paragraph type="secondary" style={{ margin: 0, fontSize: 13 }}>
+            管理 <code>biz.trigger_jobs</code> 中 AI 相关触发器，支持启停与 cron 修改。修改立即生效。
+          </Paragraph>
+        </div>
+        <Button icon={<ReloadOutlined />} onClick={load} loading={loading}>刷新</Button>
+      </div>
+
+      <Card size="small">
+        <Table<TriggerItem>
+          columns={columns}
+          dataSource={items}
+          rowKey="id"
+          loading={loading}
+          pagination={false}
+          size="small"
+          scroll={{ x: 1200 }}
+        />
+      </Card>
+
+      <Modal
+        title={editing ? `编辑触发器 #${editing.id}` : ""}
+        open={!!editing}
+        onCancel={() => setEditing(null)}
+        onOk={handleSave}
+        confirmLoading={saving}
+        okText="保存" cancelText="取消"
+        width={600}
+      >
+        {editing && (
+          <>
+            <Descriptions size="small" column={1} bordered style={{ marginBottom: 16 }}>
+              <Descriptions.Item label="触发器名">{editing.job_name}</Descriptions.Item>
+              <Descriptions.Item label="类型">
+                <Tag color={CONDITION_COLOR[editing.trigger_condition] ?? "default"}>
+                  {editing.trigger_condition}
+                </Tag>
+              </Descriptions.Item>
+              {editing.trigger_condition === "event" && (
+                <Descriptions.Item label="事件名">
+                  <code>{String(editing.trigger_config?.event_name || "—")}</code>
+                </Descriptions.Item>
+              )}
+            </Descriptions>
+
+            {editing.trigger_condition === "cron" && (
+              <div style={{ marginBottom: 16 }}>
+                <div style={{ marginBottom: 4, fontWeight: 500 }}>Cron 表达式</div>
+                <Input
+                  value={editCron}
+                  onChange={(e) => setEditCron(e.target.value)}
+                  placeholder="标准 5 段 cron，例如 0 10 * * *"
+                />
+                <Paragraph type="secondary" style={{ fontSize: 12, margin: "4px 0 0 0" }}>
+                  格式：<code>分 时 日 月 周</code>。示例：<code>0 10 * * *</code>（每日 10:00）、<code>*/30 * * * *</code>（每 30 分钟）。
+                </Paragraph>
+              </div>
+            )}
+
+            <div>
+              <div style={{ marginBottom: 4, fontWeight: 500 }}>描述</div>
+              <Input.TextArea
+                value={editDesc}
+                onChange={(e) => setEditDesc(e.target.value)}
+                rows={3}
+              />
+            </div>
+          </>
+        )}
+      </Modal>
+    </div>
+  );
+};
+
+export default AITriggers;

apps/admin-web/src/pages/RuntimeContext.tsx

@@ -0,0 +1,335 @@
+/**
+ * 业务运行上下文 / 沙箱设置页面。
+ *
+ * 仅限超级管理员：列出门店当前模式，支持切换到 sandbox 指定历史日期或切回 live。
+ * 切换会按 site_id 暂停或恢复 biz.trigger_jobs，确保多门店隔离。
+ */
+
+import React, { useEffect, useMemo, useState, useCallback } from "react";
+import {
+  Alert, Button, Card, DatePicker, Form, Input, Modal, Popconfirm, Space,
+  Switch, Table, Tag, Tooltip, Typography, message,
+} from "antd";
+import { ReloadOutlined, SwapOutlined } from "@ant-design/icons";
+import type { ColumnsType } from "antd/es/table";
+import dayjs, { type Dayjs } from "dayjs";
+import {
+  fetchRuntimeSites, switchRuntimeContext,
+  type RuntimeSiteItem, type RuntimeMode, type RuntimeTransitionStep,
+} from "../api/runtimeContext";
+import { useAuthStore } from "../store/authStore";
+
+const { Title, Text } = Typography;
+
+interface SwitchFormValues {
+  mode: RuntimeMode;
+  sandbox_date: Dayjs | null;
+  reset_sandbox: boolean;
+  reason: string;
+}
+
+const stepStatusColor: Record<RuntimeTransitionStep["status"], string> = {
+  success: "green",
+  skipped: "default",
+  warning: "orange",
+  failed: "red",
+};
+
+const RuntimeContextPage: React.FC = () => {
+  const user = useAuthStore((s) => s.user);
+  const isSuperAdmin = user?.roles?.includes("super_admin") ?? false;
+
+  const [sites, setSites] = useState<RuntimeSiteItem[]>([]);
+  const [loading, setLoading] = useState(false);
+  const [switchTarget, setSwitchTarget] = useState<RuntimeSiteItem | null>(null);
+  const [submitting, setSubmitting] = useState(false);
+  const [stepsModal, setStepsModal] = useState<{ siteName: string; steps: RuntimeTransitionStep[] } | null>(null);
+  const [form] = Form.useForm<SwitchFormValues>();
+
+  const load = useCallback(async () => {
+    setLoading(true);
+    try {
+      const data = await fetchRuntimeSites();
+      setSites(data);
+    } catch {
+      message.error("加载门店运行上下文失败");
+    } finally {
+      setLoading(false);
+    }
+  }, []);
+
+  useEffect(() => {
+    if (isSuperAdmin) {
+      load();
+    }
+  }, [isSuperAdmin, load]);
+
+  const openSwitch = (record: RuntimeSiteItem, mode: RuntimeMode) => {
+    setSwitchTarget(record);
+    form.resetFields();
+    form.setFieldsValue({
+      mode,
+      sandbox_date: record.sandbox_date ? dayjs(record.sandbox_date) : null,
+      reset_sandbox: true,
+      reason: "",
+    });
+  };
+
+  const handleSubmit = async () => {
+    if (!switchTarget) return;
+    let values: SwitchFormValues;
+    try {
+      values = await form.validateFields();
+    } catch {
+      return;
+    }
+    setSubmitting(true);
+    try {
+      const resp = await switchRuntimeContext({
+        site_id: switchTarget.site_id,
+        mode: values.mode,
+        sandbox_date: values.mode === "sandbox" ? values.sandbox_date?.format("YYYY-MM-DD") : null,
+        reset_sandbox: values.mode === "sandbox" ? values.reset_sandbox : true,
+        reason: values.reason || null,
+      });
+      message.success(values.mode === "sandbox" ? "已切换为沙箱模式" : "已切回 live 模式");
+      setStepsModal({
+        siteName: switchTarget.site_name || `#${switchTarget.site_id}`,
+        steps: resp.steps,
+      });
+      setSwitchTarget(null);
+      form.resetFields();
+      load();
+    } catch (err: unknown) {
+      const msg = (err as { response?: { data?: { detail?: string } } })?.response?.data?.detail;
+      message.error(msg || "切换失败");
+    } finally {
+      setSubmitting(false);
+    }
+  };
+
+  const columns: ColumnsType<RuntimeSiteItem> = useMemo(
+    () => [
+      {
+        title: "门店",
+        key: "site",
+        width: 200,
+        render: (_: unknown, r) => (
+          <Space direction="vertical" size={0}>
+            <Text strong>{r.site_name || `#${r.site_id}`}</Text>
+            <Text type="secondary" style={{ fontSize: 12 }}>
+              {r.site_code ? `${r.site_code} · ` : ""}site_id={r.site_id}
+            </Text>
+          </Space>
+        ),
+      },
+      {
+        title: "运行模式",
+        key: "mode",
+        width: 140,
+        render: (_: unknown, r) => {
+          const mode = (r.mode ?? "live") as RuntimeMode;
+          return mode === "sandbox" ? (
+            <Tag color="purple">沙箱模式</Tag>
+          ) : (
+            <Tag color="blue">正式 live</Tag>
+          );
+        },
+      },
+      {
+        title: "业务日期",
+        key: "business_date",
+        width: 160,
+        render: (_: unknown, r) =>
+          r.mode === "sandbox" && r.sandbox_date ? (
+            <Tooltip title="沙箱模拟的业务日期">
+              <Tag color="purple">{r.sandbox_date}</Tag>
+            </Tooltip>
+          ) : (
+            <Text type="secondary">真实日期</Text>
+          ),
+      },
+      {
+        title: "沙箱实例",
+        dataIndex: "sandbox_instance_id",
+        key: "sandbox_instance_id",
+        width: 240,
+        render: (v: string | null) => (v ? <Text code>{v}</Text> : "—"),
+      },
+      {
+        title: "AI 模式",
+        dataIndex: "ai_mode",
+        key: "ai_mode",
+        width: 100,
+        render: (v: string | null) => v ?? "live",
+      },
+      {
+        title: "更新时间",
+        dataIndex: "updated_at",
+        key: "updated_at",
+        width: 170,
+        render: (v: string | null) => (v ? dayjs(v).format("YYYY-MM-DD HH:mm") : "—"),
+      },
+      {
+        title: "操作",
+        key: "action",
+        fixed: "right",
+        width: 220,
+        render: (_: unknown, r) => {
+          const mode = (r.mode ?? "live") as RuntimeMode;
+          if (mode === "sandbox") {
+            return (
+              <Space>
+                <Button size="small" icon={<SwapOutlined />} onClick={() => openSwitch(r, "sandbox")}>
+                  调整沙箱
+                </Button>
+                <Popconfirm
+                  title="确认切回 live 模式？"
+                  description="将恢复该门店触发器并清理沙箱状态。"
+                  okText="切回 live"
+                  cancelText="取消"
+                  onConfirm={() => openSwitch(r, "live")}
+                >
+                  <Button size="small" danger>
+                    切回 live
+                  </Button>
+                </Popconfirm>
+              </Space>
+            );
+          }
+          return (
+            <Button size="small" type="primary" icon={<SwapOutlined />} onClick={() => openSwitch(r, "sandbox")}>
+              进入沙箱
+            </Button>
+          );
+        },
+      },
+    ],
+    [form],
+  );
+
+  if (!isSuperAdmin) {
+    return (
+      <Alert
+        type="warning"
+        showIcon
+        message="无权限"
+        description="业务运行上下文/沙箱设置仅对超级管理员开放。"
+      />
+    );
+  }
+
+  const target = switchTarget;
+  const targetMode = Form.useWatch("mode", form) ?? "live";
+
+  return (
+    <Card
+      title={<Title level={4} style={{ margin: 0 }}>业务运行上下文 / 沙箱</Title>}
+      extra={
+        <Button icon={<ReloadOutlined />} onClick={load} loading={loading}>
+          刷新
+        </Button>
+      }
+    >
+      <Alert
+        type="info"
+        showIcon
+        style={{ marginBottom: 16 }}
+        message="按门店隔离的业务时钟"
+        description={
+          <Space direction="vertical" size={2}>
+            <Text>live 模式：使用真实系统日期，正常生产逻辑。</Text>
+            <Text>
+              sandbox 模式：业务上假设是 sandbox_date，按 sandbox_instance_id 隔离写入；
+              切换会终止当前 ETL、取消未完成 AI 触发记录，但不会暂停全局 biz.trigger_jobs（多门店共用）。
+            </Text>
+            <Text type="secondary">
+              真实预算、AI tokens 计费、运行日志写入时间、调度元数据仍按真实系统时间，不受沙箱影响。
+            </Text>
+            <Text type="warning">
+              本次改造目标是让看板 / 任务 / 会员 / AI 等数据读取也按 sandbox_date 截断，
+              进度详见 <Text code>docs/database/changes/2026-05-02__sandbox_no_future_data_plan.md</Text>。
+            </Text>
+          </Space>
+        }
+      />
+      <Table
+        rowKey="site_id"
+        loading={loading}
+        dataSource={sites}
+        columns={columns}
+        size="middle"
+        pagination={false}
+        scroll={{ x: 1100 }}
+      />
+      <Modal
+        open={!!target}
+        title={target ? `切换运行上下文 — ${target.site_name || `#${target.site_id}`}` : ""}
+        onCancel={() => {
+          if (!submitting) {
+            setSwitchTarget(null);
+            form.resetFields();
+          }
+        }}
+        onOk={handleSubmit}
+        okText="确认切换"
+        cancelText="取消"
+        confirmLoading={submitting}
+        destroyOnClose
+        width={640}
+      >
+        <Form
+          layout="vertical"
+          form={form}
+          initialValues={{ mode: "sandbox", reset_sandbox: true, reason: "" }}
+        >
+          <Form.Item label="目标模式" name="mode" rules={[{ required: true }]}>
+            <Input disabled />
+          </Form.Item>
+          {targetMode === "sandbox" && (
+            <>
+              <Form.Item
+                label="沙箱业务日期"
+                name="sandbox_date"
+                rules={[{ required: true, message: "沙箱模式需要选择历史业务日期" }]}
+              >
+                <DatePicker
+                  style={{ width: "100%" }}
+                  disabledDate={(d) => d && d.isAfter(dayjs(), "day")}
+                />
+              </Form.Item>
+              <Form.Item label="重置沙箱实例" name="reset_sandbox" valuePropName="checked">
+                <Switch checkedChildren="新实例" unCheckedChildren="沿用原实例" />
+              </Form.Item>
+            </>
+          )}
+          <Form.Item label="操作原因（可选）" name="reason">
+            <Input.TextArea rows={2} maxLength={500} showCount placeholder="例如：演示按 2026-03-15 重放任务分发" />
+          </Form.Item>
+        </Form>
+      </Modal>
+      <Modal
+        open={!!stepsModal}
+        title={stepsModal ? `切换执行结果 — ${stepsModal.siteName}` : ""}
+        onCancel={() => setStepsModal(null)}
+        onOk={() => setStepsModal(null)}
+        okText="知道了"
+        cancelButtonProps={{ style: { display: "none" } }}
+        width={640}
+        destroyOnClose
+      >
+        <Space direction="vertical" size={8} style={{ width: "100%" }}>
+          {(stepsModal?.steps ?? []).map((s) => (
+            <div key={s.key}>
+              <Tag color={stepStatusColor[s.status]}>{s.title}</Tag>
+              {s.count ? <Text type="secondary">影响 {s.count} 条</Text> : null}
+              <Text style={{ marginLeft: 8 }}>{s.detail}</Text>
+            </div>
+          ))}
+        </Space>
+      </Modal>
+    </Card>
+  );
+};
+
+export default RuntimeContextPage;

apps/admin-web/src/pages/TriggerManager.tsx

@@ -6,7 +6,7 @@
  * - destroyInactiveTabPane={false} 保持 Tab 状态不丢失
  * - "全部"Tab 调用 fetchUnifiedTriggers()，展示统一字段表格
  * - "业务"Tab 复用 TriggerJobs 组件 + 编辑 Modal
- * - "AI"Tab 复用 AIOperations + AITriggerJobs 组件
+ * - "AI"Tab 复用 AITriggers（触发器设置）+ AIOperations + AITriggerJobs 组件
  * - "ETL"Tab 展示 scheduled_tasks 数据
  *
  * CHANGE 2026-07-15 | Task 10.1：创建 TriggerManager 页面
@@ -37,6 +37,7 @@ import { fetchSchedules } from '../api/schedules';
 import type { ScheduledTask } from '../types';
 import AIOperations from './AIOperations';
 import AITriggerJobs from './AITriggerJobs';
+import AITriggers from './AITriggers';
 
 const { Title } = Typography;
 
@@ -319,6 +320,7 @@ const BizTriggersTab: React.FC = () => {
 
 const AITriggersTab: React.FC = () => (
   <Space direction="vertical" style={{ width: '100%' }} size="large">
+    <AITriggers />
     <AIOperations />
     <AITriggerJobs />
   </Space>

apps/backend/app/ai/apps/__init__.py

@@ -1 +0,0 @@
-# AI 应用子模块：app1_chat ~ app8_consolidation

apps/backend/app/ai/apps/app1_chat.py

@@ -1,274 +0,0 @@
-"""应用 1：通用对话（SSE 流式）。
-
-每次进入 chat 页面新建 ai_conversations 记录（不复用），
-首条消息注入页面上下文，流式返回 AI 回复。
-
-app_id = "app1_chat"
-"""
-
-from __future__ import annotations
-
-import json
-import logging
-from typing import AsyncGenerator
-
-from app.ai.dashscope_client import DashScopeClient
-from app.ai.cache_service import AICacheService
-from app.ai.conversation_service import ConversationService
-from app.ai.data_fetchers import build_page_text
-from app.ai.schemas import SSEEvent
-
-logger = logging.getLogger(__name__)
-
-APP_ID = "app1_chat"
-
-# system prompt 总字符数上限
-_MAX_SYSTEM_PROMPT_LEN = 4000
-
-
-async def chat_stream(
-    *,
-    message: str,
-    user_id: int | str,
-    nickname: str,
-    role: str,
-    site_id: int,
-    source_page: str | None = None,
-    page_context: dict | None = None,
-    screen_content: str | None = None,
-    client: DashScopeClient,
-    conv_svc: ConversationService,
-) -> AsyncGenerator[SSEEvent, None]:
-    """流式对话入口，返回 SSEEvent 异步生成器。
-
-    流程：
-    1. 创建 conversation 记录
-    2. 写入 user message
-    3. 构建 system prompt（注入页面上下文）
-    4. 调用 bailian.chat_stream 流式获取回复
-    5. 逐 chunk yield SSEEvent(type="chunk")
-    6. 完成后写入 assistant message，yield SSEEvent(type="done")
-    7. 异常时 yield SSEEvent(type="error")
-    """
-    conversation_id: int | None = None
-
-    try:
-        # 1. 每次新建 conversation（不复用）
-        source_ctx = _build_source_context(
-            source_page=source_page,
-            page_context=page_context,
-            screen_content=screen_content,
-        )
-        conversation_id = conv_svc.create_conversation(
-            user_id=user_id,
-            nickname=nickname,
-            app_id=APP_ID,
-            site_id=site_id,
-            source_page=source_page,
-            source_context=source_ctx,
-        )
-        logger.info(
-            "App1 新建对话: conversation_id=%s user_id=%s site_id=%s",
-            conversation_id, user_id, site_id,
-        )
-
-        # 2. 立即写入 user message
-        conv_svc.add_message(
-            conversation_id=conversation_id,
-            role="user",
-            content=message,
-        )
-
-        # 3. 构建消息列表（system prompt + user message）
-        messages = await _build_messages(
-            message=message,
-            user_id=user_id,
-            nickname=nickname,
-            role=role,
-            site_id=site_id,
-            source_page=source_page,
-            page_context=page_context,
-            screen_content=screen_content,
-        )
-
-        # 4-5. 流式调用百炼，逐 chunk yield
-        full_reply_parts: list[str] = []
-        async for chunk in bailian.chat_stream(messages):
-            full_reply_parts.append(chunk)
-            yield SSEEvent(type="chunk", content=chunk)
-
-        # 6. 流式完成，拼接完整回复并写入 assistant message
-        full_reply = "".join(full_reply_parts)
-        # 百炼流式模式不返回 tokens_used，按字符数估算（粗略）
-        estimated_tokens = len(full_reply)
-        conv_svc.add_message(
-            conversation_id=conversation_id,
-            role="assistant",
-            content=full_reply,
-            tokens_used=estimated_tokens,
-        )
-
-        yield SSEEvent(
-            type="done",
-            conversation_id=conversation_id,
-            tokens_used=estimated_tokens,
-        )
-
-    except Exception as e:
-        logger.error(
-            "App1 对话异常: conversation_id=%s error=%s",
-            conversation_id, e,
-            exc_info=True,
-        )
-        yield SSEEvent(type="error", message=str(e))
-
-
-async def _build_messages(
-    *,
-    message: str,
-    user_id: int | str,
-    nickname: str,
-    role: str,
-    site_id: int,
-    source_page: str | None,
-    page_context: dict | None,
-    screen_content: str | None,
-) -> list[dict]:
-    """构建发送给百炼的消息列表。
-
-    首条 system 消息注入页面上下文和用户信息。
-    """
-    system_content = await _build_system_prompt(
-        user_id=user_id,
-        nickname=nickname,
-        role=role,
-        site_id=site_id,
-        source_page=source_page,
-        page_context=page_context,
-        screen_content=screen_content,
-    )
-
-    content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    # system prompt 总字符数控制
-    if len(content_str) > _MAX_SYSTEM_PROMPT_LEN:
-        # 截断 page_context 中的 data_text
-        pc = system_content.get("page_context", {})
-        dt = pc.get("data_text", "")
-        if dt and len(dt) > 500:
-            pc["data_text"] = dt[:500] + "…（已截断）"
-            content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-
-    return [
-        {"role": "system", "content": content_str},
-        {"role": "user", "content": message},
-    ]
-
-
-async def _build_system_prompt(
-    *,
-    user_id: int | str,
-    nickname: str,
-    role: str,
-    site_id: int,
-    source_page: str | None,
-    page_context: dict | None,
-    screen_content: str | None,
-) -> dict:
-    """构建 system prompt JSON。
-
-    通过 biz_params.user_prompt_params 传入用户信息，
-    注入页面上下文供 AI 理解当前场景。
-    """
-    prompt: dict = {
-        "task": (
-            "你是台球门店的 AI 助手，根据用户的问题和当前页面上下文提供帮助。"
-            "当 page_context 中包含 memberNickname、contextId 或 data_text 时，"
-            "你必须直接使用这些信息回答问题，不要再向用户索要已有的信息。"
-            "例如用户在客户详情页提问时，直接基于该客户的数据回答，无需要求提供会员 ID。"
-        ),
-        "biz_params": {
-            "user_prompt_params": {
-                "User_ID": str(user_id),
-                "Role": role,
-                "Nickname": nickname,
-            },
-        },
-    }
-
-    # 注入页面上下文（首条消息）
-    page_ctx = await _build_page_context(
-        source_page=source_page,
-        page_context=page_context,
-        screen_content=screen_content,
-        site_id=site_id,
-    )
-    if page_ctx:
-        prompt["page_context"] = page_ctx
-
-    return prompt
-
-
-async def _build_page_context(
-    *,
-    source_page: str | None,
-    page_context: dict | None,
-    screen_content: str | None,
-    site_id: int,
-) -> dict:
-    """构建页面上下文信息。
-
-    根据 source_page（contextType）调用 build_page_text 获取结构化文本，
-    看板类页面从 page_context 提取筛选参数传入 filters。
-    contextType 为空或未识别时返回空 dict（跳过注入）。
-    """
-    ctx: dict = {}
-
-    if source_page:
-        ctx["source_page"] = source_page
-
-        # 从 page_context 提取 contextId 和筛选参数
-        context_id = None
-        filters: dict = {}
-        if page_context:
-            context_id = page_context.get("contextId")
-            # 看板类页面筛选参数透传
-            for key in ("timeDimension", "areaFilter", "dimension", "typeFilter", "projectFilter"):
-                if key in page_context:
-                    filters[key] = page_context[key]
-
-        # 调用 data_fetcher 获取页面数据文本
-        try:
-            data_text = await build_page_text(
-                source_page=source_page,
-                context_id=context_id,
-                site_id=site_id,
-                filters=filters if filters else None,
-            )
-            if data_text:
-                ctx["data_text"] = data_text
-        except Exception:
-            logger.warning("页面上下文文本化失败: source_page=%s", source_page, exc_info=True)
-
-    if page_context:
-        ctx["page_context"] = page_context
-    if screen_content:
-        ctx["screen_content"] = screen_content
-
-    return ctx
-
-
-def _build_source_context(
-    *,
-    source_page: str | None,
-    page_context: dict | None,
-    screen_content: str | None,
-) -> dict | None:
-    """构建存入 ai_conversations.source_context 的 JSON。"""
-    ctx: dict = {}
-    if source_page:
-        ctx["source_page"] = source_page
-    if page_context:
-        ctx["page_context"] = page_context
-    if screen_content:
-        ctx["screen_content"] = screen_content
-    return ctx if ctx else None

apps/backend/app/ai/apps/app2_finance.py

@@ -1,210 +0,0 @@
-"""应用 2：财务洞察。
-
-8 个时间维度独立调用，每次调用结果写入 ai_cache，
-同时创建 ai_conversations + ai_messages 记录。
-
-营业日分界点：每日 08:00（BUSINESS_DAY_START_HOUR 环境变量，默认 8）。
-
-app_id = "app2_finance"
-"""
-
-from __future__ import annotations
-
-import json
-import logging
-import os
-from datetime import date, datetime, timedelta
-
-from app.ai.dashscope_client import DashScopeClient
-from app.ai.cache_service import AICacheService
-from app.ai.conversation_service import ConversationService
-from app.ai.prompts.app2_finance_prompt import build_prompt
-from app.ai.schemas import CacheTypeEnum
-
-logger = logging.getLogger(__name__)
-
-APP_ID = "app2_finance"
-
-# 8 个时间维度编码
-TIME_DIMENSIONS = (
-    "this_month",
-    "last_month",
-    "this_week",
-    "last_week",
-    "last_3_months",
-    "this_quarter",
-    "last_quarter",
-    "last_6_months",
-)
-
-
-def get_business_date() -> date:
-    """根据营业日分界点计算当前营业日。
-
-    分界点前（如 07:59）视为前一天营业日，
-    分界点及之后（如 08:00）视为当天营业日。
-    """
-    hour = int(os.environ.get("BUSINESS_DAY_START_HOUR", "8"))
-    now = datetime.now()
-    if now.hour < hour:
-        return (now - timedelta(days=1)).date()
-    return now.date()
-
-
-def compute_time_range(dimension: str, business_date: date) -> tuple[date, date]:
-    """计算时间维度对应的日期范围 [start, end]（闭区间）。
-
-    Args:
-        dimension: 时间维度编码
-        business_date: 当前营业日
-
-    Returns:
-        (start_date, end_date) 元组
-    """
-    y, m, d = business_date.year, business_date.month, business_date.day
-
-    if dimension == "this_month":
-        start = date(y, m, 1)
-        return start, business_date
-
-    if dimension == "last_month":
-        prev = _month_offset(y, m, -1)
-        start = date(prev[0], prev[1], 1)
-        end = date(y, m, 1) - timedelta(days=1)
-        return start, end
-
-    if dimension == "this_week":
-        # 周一起算
-        weekday = business_date.weekday()  # 0=周一
-        start = business_date - timedelta(days=weekday)
-        return start, business_date
-
-    if dimension == "last_week":
-        weekday = business_date.weekday()
-        this_monday = business_date - timedelta(days=weekday)
-        last_monday = this_monday - timedelta(days=7)
-        last_sunday = this_monday - timedelta(days=1)
-        return last_monday, last_sunday
-
-    if dimension == "last_3_months":
-        # 当前月 - 3 ~ 当前月 - 1
-        end_ym = _month_offset(y, m, -1)
-        start_ym = _month_offset(y, m, -3)
-        start = date(start_ym[0], start_ym[1], 1)
-        # end = 上月最后一天
-        end = date(y, m, 1) - timedelta(days=1)
-        return start, end
-
-    if dimension == "this_quarter":
-        q_start_month = ((m - 1) // 3) * 3 + 1
-        start = date(y, q_start_month, 1)
-        return start, business_date
-
-    if dimension == "last_quarter":
-        q_start_month = ((m - 1) // 3) * 3 + 1
-        # 上季度结束 = 本季度第一天 - 1
-        this_q_start = date(y, q_start_month, 1)
-        end = this_q_start - timedelta(days=1)
-        # 上季度开始
-        ly, lm = end.year, end.month
-        lq_start_month = ((lm - 1) // 3) * 3 + 1
-        start = date(ly, lq_start_month, 1)
-        return start, end
-
-    if dimension == "last_6_months":
-        # 当前月 - 6 ~ 当前月 - 1
-        end_ym = _month_offset(y, m, -1)
-        start_ym = _month_offset(y, m, -6)
-        start = date(start_ym[0], start_ym[1], 1)
-        end = date(y, m, 1) - timedelta(days=1)
-        return start, end
-
-    raise ValueError(f"未知时间维度: {dimension}")
-
-
-async def run(
-    context: dict,
-    client: DashScopeClient,
-    cache_svc: AICacheService,
-    conv_svc: ConversationService,
-) -> dict:
-    """执行 App2 财务洞察调用。
-
-    Args:
-        context: 包含 site_id, time_dimension, user_id(默认'system'), nickname(默认'')
-        bailian: 百炼客户端
-        cache_svc: 缓存服务
-        conv_svc: 对话服务
-
-    Returns:
-        百炼返回的结构化 JSON（insights 数组）
-    """
-    site_id = context["site_id"]
-    time_dimension = context["time_dimension"]
-    user_id = context.get("user_id", "system")
-    nickname = context.get("nickname", "")
-
-    # 构建 Prompt
-    prompt_context = {
-        "site_id": site_id,
-        "time_dimension": time_dimension,
-        "current_data": context.get("current_data", {}),
-        "previous_data": context.get("previous_data", {}),
-    }
-    messages = build_prompt(prompt_context)
-
-    # 创建对话记录
-    conversation_id = conv_svc.create_conversation(
-        user_id=user_id,
-        nickname=nickname,
-        app_id=APP_ID,
-        site_id=site_id,
-        source_context={"time_dimension": time_dimension},
-    )
-
-    # 写入 system prompt 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="system",
-        content=messages[0]["content"],
-    )
-    # 写入 user 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="user",
-        content=messages[1]["content"],
-    )
-
-    # 调用百炼 API
-    result, tokens_used = await bailian.chat_json(messages)
-
-    # 写入 assistant 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="assistant",
-        content=json.dumps(result, ensure_ascii=False),
-        tokens_used=tokens_used,
-    )
-
-    # 写入缓存
-    cache_svc.write_cache(
-        cache_type=CacheTypeEnum.APP2_FINANCE.value,
-        site_id=site_id,
-        target_id=time_dimension,
-        result_json=result,
-        triggered_by=f"user:{user_id}",
-    )
-
-    logger.info(
-        "App2 财务洞察完成: site_id=%s dimension=%s conversation_id=%s tokens=%d",
-        site_id, time_dimension, conversation_id, tokens_used,
-    )
-
-    return result
-
-
-def _month_offset(year: int, month: int, offset: int) -> tuple[int, int]:
-    """计算月份偏移，返回 (year, month)。"""
-    # 转为 0-based 计算
-    total = (year * 12 + (month - 1)) + offset
-    return total // 12, total % 12 + 1

apps/backend/app/ai/apps/app3_clue.py

@@ -1,263 +0,0 @@
-"""应用 3：客户数据维客线索分析（骨架）。
-
-客户新增消费时自动触发，通过 AI 分析客户数据提取维客线索。
-线索 category 限定 3 个枚举值：客户基础、消费习惯、玩法偏好。
-线索提供者统一标记为"系统"。
-
-使用 items_sum 口径（= table_charge_money + goods_money
-+ assistant_pd_money + assistant_cx_money + electricity_money），
-禁止使用 consume_money。
-
-app_id = "app3_clue"
-"""
-
-from __future__ import annotations
-
-import json
-import logging
-from datetime import datetime
-
-from app.ai.dashscope_client import DashScopeClient
-from app.ai.cache_service import AICacheService
-from app.ai.conversation_service import ConversationService
-from app.ai.data_fetchers import fetch_member_consumption_data
-from app.ai.schemas import CacheTypeEnum
-
-logger = logging.getLogger(__name__)
-
-APP_ID = "app3_clue"
-
-# system message content 上限
-_MAX_SYSTEM_CONTENT_LEN = 8000
-
-
-def _default_member_data() -> dict:
-    """数据获取失败时的默认空值。"""
-    return {
-        "member_nickname": "",
-        "consumption_records": [],
-        "member_cards": [],
-        "card_balance_total": 0,
-        "stored_value_balance_total": 0,
-        "expected_visit_date": None,
-        "days_since_last_visit": None,
-    }
-
-
-async def build_prompt(
-    context: dict,
-    cache_svc: AICacheService | None = None,
-) -> list[dict]:
-    """构建 Prompt 消息列表。
-
-    从 data_fetchers 获取真实消费数据，失败时降级为空值。
-
-    Args:
-        context: 包含 site_id, member_id, nickname 等
-        cache_svc: 缓存服务，用于获取 reference 历史数据
-
-    Returns:
-        消息列表 [{"role": "system", "content": ...}, {"role": "user", ...}]
-    """
-    site_id = context["site_id"]
-    member_id = context["member_id"]
-
-    # 获取消费数据（失败时降级）
-    data_fetch_failed = False
-    try:
-        member_data = await fetch_member_consumption_data(site_id, member_id)
-    except Exception:
-        logger.warning("App3 消费数据获取失败，使用默认空值: site_id=%s member_id=%s", site_id, member_id, exc_info=True)
-        member_data = _default_member_data()
-        data_fetch_failed = True
-
-    # 构建 reference：App6 线索 + 最近 2 套 App8 历史（附 generated_at）
-    reference = _build_reference(site_id, member_id, cache_svc)
-
-    member_nickname = member_data.get("member_nickname", "")
-    consumption_records = member_data.get("consumption_records", [])
-
-    # 空数据标注
-    if not consumption_records:
-        if data_fetch_failed:
-            consumption_records = "⚠ 消费数据获取失败，该客户暂无消费记录可供分析"
-        else:
-            consumption_records = "该客户暂无消费记录"
-
-    system_content = {
-        "task": "分析客户消费数据，提取维客线索。",
-        "app_id": APP_ID,
-        "rules": {
-            "category_enum": ["客户基础", "消费习惯", "玩法偏好"],
-            "providers": "系统",
-            "amount_caliber": "items_sum = table_charge_money + goods_money + assistant_pd_money + assistant_cx_money + electricity_money",
-            "禁止使用": "consume_money",
-        },
-        "output_format": {
-            "clues": [
-                {
-                    "category": "枚举值（客户基础/消费习惯/玩法偏好）",
-                    "summary": "一句话摘要",
-                    "detail": "详细说明",
-                    "emoji": "表情符号",
-                }
-            ]
-        },
-        "current_time": datetime.now().strftime("%Y-%m-%d %H:%M"),
-        "member_nickname": member_nickname,
-        "main_data": {
-            "consumption_records": consumption_records,
-            "member_cards": member_data.get("member_cards", []),
-            "card_balance_total": member_data.get("card_balance_total", 0),
-            "stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
-            "expected_visit_date": member_data.get("expected_visit_date"),
-            "days_since_last_visit": member_data.get("days_since_last_visit"),
-        },
-        "reference": reference,
-    }
-
-    # Token 预算控制：截断 consumption_records
-    content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    if len(content_str) > _MAX_SYSTEM_CONTENT_LEN:
-        records = system_content["main_data"].get("consumption_records")
-        if isinstance(records, list) and len(records) > 5:
-            system_content["main_data"]["consumption_records"] = records[:5]
-            system_content["main_data"]["_truncated"] = f"消费记录已截断，原始共 {len(records)} 条"
-        content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-
-    user_content = (
-        f"请分析会员 {member_id} 的消费数据，提取维客线索。"
-        "每条线索包含 category、summary、detail、emoji 四个字段。"
-        "category 必须是：客户基础、消费习惯、玩法偏好 之一。"
-    )
-
-    return [
-        {"role": "system", "content": content_str},
-        {"role": "user", "content": user_content},
-    ]
-
-
-def _build_reference(
-    site_id: int,
-    member_id: int,
-    cache_svc: AICacheService | None,
-) -> dict:
-    """构建 Prompt reference 字段。
-
-    包含：
-    - App6 备注分析线索（最新一条，如有）
-    - 最近 2 套 App8 维客线索整理历史（附 generated_at）
-
-    缓存不存在时返回空对象 {}。
-    """
-    if cache_svc is None:
-        return {}
-
-    reference: dict = {}
-    target_id = str(member_id)
-
-    # App6 备注分析线索
-    app6_latest = cache_svc.get_latest(
-        CacheTypeEnum.APP6_NOTE_ANALYSIS.value, site_id, target_id,
-    )
-    if app6_latest:
-        reference["app6_note_clues"] = {
-            "result_json": app6_latest.get("result_json"),
-            "generated_at": app6_latest.get("created_at"),
-        }
-
-    # 最近 2 套 App8 历史
-    app8_history = cache_svc.get_history(
-        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id, limit=2,
-    )
-    if app8_history:
-        reference["app8_history"] = [
-            {
-                "result_json": h.get("result_json"),
-                "generated_at": h.get("created_at"),
-            }
-            for h in app8_history
-        ]
-
-    return reference
-
-
-async def run(
-    context: dict,
-    client: DashScopeClient,
-    cache_svc: AICacheService,
-    conv_svc: ConversationService,
-) -> dict:
-    """执行 App3 客户数据维客线索分析。
-
-    流程：
-    1. build_prompt 构建 Prompt
-    2. bailian.chat_json 调用百炼
-    3. 写入 conversation + messages
-    4. 写入 ai_cache
-    5. 返回结果
-
-    Args:
-        context: site_id, member_id, user_id(默认'system'), nickname(默认'')
-        bailian: 百炼客户端
-        cache_svc: 缓存服务
-        conv_svc: 对话服务
-
-    Returns:
-        百炼返回的结构化 JSON（clues 数组）
-    """
-    site_id = context["site_id"]
-    member_id = context["member_id"]
-    user_id = context.get("user_id", "system")
-    nickname = context.get("nickname", "")
-
-    # 1. 构建 Prompt
-    messages = await build_prompt(context, cache_svc)
-
-    # 2. 创建对话记录
-    conversation_id = conv_svc.create_conversation(
-        user_id=user_id,
-        nickname=nickname,
-        app_id=APP_ID,
-        site_id=site_id,
-        source_context={"member_id": member_id},
-    )
-
-    # 写入 system + user 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="system",
-        content=messages[0]["content"],
-    )
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="user",
-        content=messages[1]["content"],
-    )
-
-    # 3. 调用百炼 API
-    result, tokens_used = await bailian.chat_json(messages)
-
-    # 4. 写入 assistant 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="assistant",
-        content=json.dumps(result, ensure_ascii=False),
-        tokens_used=tokens_used,
-    )
-
-    # 5. 写入缓存
-    cache_svc.write_cache(
-        cache_type=CacheTypeEnum.APP3_CLUE.value,
-        site_id=site_id,
-        target_id=str(member_id),
-        result_json=result,
-        triggered_by=f"user:{user_id}",
-    )
-
-    logger.info(
-        "App3 线索分析完成: site_id=%s member_id=%s conversation_id=%s tokens=%d",
-        site_id, member_id, conversation_id, tokens_used,
-    )
-
-    return result

apps/backend/app/ai/apps/app4_analysis.py

@@ -1,300 +0,0 @@
-"""应用 4：关系分析/任务建议（骨架）。
-
-助教参与新结算或被分配召回任务时自动触发，
-生成关系分析和任务建议。
-
-Prompt reference 包含 App8 最新 + 最近 2 套历史（附 generated_at）。
-缓存不存在时 reference 传空对象，标注"暂无历史线索"。
-
-app_id = "app4_analysis"
-"""
-
-from __future__ import annotations
-
-import asyncio
-import json
-import logging
-from datetime import datetime
-
-from app.ai.dashscope_client import DashScopeClient
-from app.ai.cache_service import AICacheService
-from app.ai.conversation_service import ConversationService
-from app.ai.data_fetchers import (
-    fetch_assistant_info,
-    fetch_member_consumption_data,
-    fetch_member_notes,
-    fetch_service_history,
-)
-from app.ai.schemas import CacheTypeEnum
-
-logger = logging.getLogger(__name__)
-
-APP_ID = "app4_analysis"
-
-# system message content 上限
-_MAX_SYSTEM_CONTENT_LEN = 8000
-
-
-def _default_member_data() -> dict:
-    """数据获取失败时的默认空值。"""
-    return {
-        "member_nickname": "",
-        "consumption_records": [],
-        "member_cards": [],
-        "card_balance_total": 0,
-        "stored_value_balance_total": 0,
-        "expected_visit_date": None,
-        "days_since_last_visit": None,
-    }
-
-
-async def build_prompt(
-    context: dict,
-    cache_svc: AICacheService | None = None,
-) -> list[dict]:
-    """构建 Prompt 消息列表。
-
-    并发获取助教信息、服务历史、客户消费数据、备注，部分失败不阻断。
-
-    Args:
-        context: 包含 site_id, assistant_id, member_id
-        cache_svc: 缓存服务，用于获取 reference 历史数据
-
-    Returns:
-        消息列表
-    """
-    site_id = context["site_id"]
-    assistant_id = context["assistant_id"]
-    member_id = context["member_id"]
-
-    # 并发获取 4 类数据，部分失败不阻断
-    results = await asyncio.gather(
-        fetch_assistant_info(site_id, assistant_id),
-        fetch_service_history(site_id, assistant_id, member_id),
-        fetch_member_consumption_data(site_id, member_id),
-        fetch_member_notes(site_id, member_id),
-        return_exceptions=True,
-    )
-
-    # 降级处理
-    fetch_errors: list[str] = []
-
-    if isinstance(results[0], Exception):
-        logger.warning("App4 助教信息获取失败: %s", results[0])
-        assistant_info = {}
-        fetch_errors.append("助教信息获取失败")
-    else:
-        assistant_info = results[0]
-
-    if isinstance(results[1], Exception):
-        logger.warning("App4 服务历史获取失败: %s", results[1])
-        service_history: list = []
-        fetch_errors.append("服务历史获取失败")
-    else:
-        service_history = results[1]
-
-    if isinstance(results[2], Exception):
-        logger.warning("App4 消费数据获取失败: %s", results[2])
-        member_data = _default_member_data()
-        fetch_errors.append("消费数据获取失败")
-    else:
-        member_data = results[2]
-
-    if isinstance(results[3], Exception):
-        logger.warning("App4 备注获取失败: %s", results[3])
-        notes: list = []
-        fetch_errors.append("备注获取失败")
-    else:
-        notes = results[3]
-
-    # 构建 reference：App8 最新 + 最近 2 套历史
-    reference = _build_reference(site_id, member_id, cache_svc)
-
-    system_content: dict = {
-        "task": "分析助教与客户的关系，生成任务建议。",
-        "app_id": APP_ID,
-        "output_format": {
-            "task_description": "任务描述文本",
-            "action_suggestions": ["建议1", "建议2"],
-            "one_line_summary": "一句话总结",
-        },
-        "current_time": datetime.now().strftime("%Y-%m-%d %H:%M"),
-        "assistant_info": assistant_info if assistant_info else "⚠ 助教信息获取失败",
-        "service_history": service_history if service_history else "暂无服务记录",
-        "task_assignment_basis": {
-            "consumption_records": member_data.get("consumption_records", []) or "该客户暂无消费记录",
-            "member_cards": member_data.get("member_cards", []),
-            "card_balance_total": member_data.get("card_balance_total", 0),
-            "stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
-            "expected_visit_date": member_data.get("expected_visit_date"),
-            "days_since_last_visit": member_data.get("days_since_last_visit"),
-        },
-        "customer_data": {
-            "system_data": {
-                "member_nickname": member_data.get("member_nickname", ""),
-            },
-            "notes": notes if notes else "暂无备注",
-        },
-        "reference": reference,
-    }
-
-    if fetch_errors:
-        system_content["_data_warnings"] = fetch_errors
-
-    # Token 预算控制
-    content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    if len(content_str) > _MAX_SYSTEM_CONTENT_LEN:
-        # 优先截断 service_history
-        sh = system_content.get("service_history")
-        if isinstance(sh, list) and len(sh) > 5:
-            system_content["service_history"] = sh[:5]
-            system_content["_truncated_service_history"] = f"服务记录已截断，原始共 {len(sh)} 条"
-        content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    if len(content_str) > _MAX_SYSTEM_CONTENT_LEN:
-        records = system_content["task_assignment_basis"].get("consumption_records")
-        if isinstance(records, list) and len(records) > 5:
-            system_content["task_assignment_basis"]["consumption_records"] = records[:5]
-            system_content["task_assignment_basis"]["_truncated"] = f"消费记录已截断，原始共 {len(records)} 条"
-        content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    if len(content_str) > _MAX_SYSTEM_CONTENT_LEN:
-        n = system_content["customer_data"].get("notes")
-        if isinstance(n, list) and len(n) > 10:
-            system_content["customer_data"]["notes"] = n[:10]
-            system_content["customer_data"]["_truncated_notes"] = f"备注已截断，原始共 {len(n)} 条"
-        content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-
-    # 缓存不存在时在 user prompt 中标注
-    no_history_hint = ""
-    if not reference:
-        no_history_hint = "（暂无历史线索，请基于现有信息分析）"
-
-    user_content = (
-        f"请分析助教 {assistant_id} 与会员 {member_id} 的关系，"
-        f"生成任务建议。{no_history_hint}"
-        "返回 task_description、action_suggestions、one_line_summary 三个字段。"
-    )
-
-    return [
-        {"role": "system", "content": content_str},
-        {"role": "user", "content": user_content},
-    ]
-
-
-def _build_reference(
-    site_id: int,
-    member_id: int,
-    cache_svc: AICacheService | None,
-) -> dict:
-    """构建 Prompt reference 字段。
-
-    包含：
-    - App8 最新维客线索（如有）
-    - 最近 2 套 App8 历史（附 generated_at）
-
-    缓存不存在时返回空对象 {}。
-    """
-    if cache_svc is None:
-        return {}
-
-    reference: dict = {}
-    target_id = str(member_id)
-
-    # App8 最新
-    app8_latest = cache_svc.get_latest(
-        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id,
-    )
-    if app8_latest:
-        reference["app8_latest"] = {
-            "result_json": app8_latest.get("result_json"),
-            "generated_at": app8_latest.get("created_at"),
-        }
-
-    # 最近 2 套 App8 历史
-    app8_history = cache_svc.get_history(
-        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id, limit=2,
-    )
-    if app8_history:
-        reference["app8_history"] = [
-            {
-                "result_json": h.get("result_json"),
-                "generated_at": h.get("created_at"),
-            }
-            for h in app8_history
-        ]
-
-    return reference
-
-
-async def run(
-    context: dict,
-    client: DashScopeClient,
-    cache_svc: AICacheService,
-    conv_svc: ConversationService,
-) -> dict:
-    """执行 App4 关系分析。
-
-    Args:
-        context: site_id, assistant_id, member_id
-        bailian: 百炼客户端
-        cache_svc: 缓存服务
-        conv_svc: 对话服务
-
-    Returns:
-        百炼返回的结构化 JSON（task_description, action_suggestions, one_line_summary）
-    """
-    site_id = context["site_id"]
-    assistant_id = context["assistant_id"]
-    member_id = context["member_id"]
-    user_id = context.get("user_id", "system")
-    nickname = context.get("nickname", "")
-
-    # 1. 构建 Prompt
-    messages = await build_prompt(context, cache_svc)
-
-    # 2. 创建对话记录
-    conversation_id = conv_svc.create_conversation(
-        user_id=user_id,
-        nickname=nickname,
-        app_id=APP_ID,
-        site_id=site_id,
-        source_context={"assistant_id": assistant_id, "member_id": member_id},
-    )
-
-    # 写入 system + user 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="system",
-        content=messages[0]["content"],
-    )
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="user",
-        content=messages[1]["content"],
-    )
-
-    # 3. 调用百炼 API
-    result, tokens_used = await bailian.chat_json(messages)
-
-    # 4. 写入 assistant 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="assistant",
-        content=json.dumps(result, ensure_ascii=False),
-        tokens_used=tokens_used,
-    )
-
-    # 5. 写入缓存（target_id = {assistant_id}_{member_id}）
-    cache_svc.write_cache(
-        cache_type=CacheTypeEnum.APP4_ANALYSIS.value,
-        site_id=site_id,
-        target_id=f"{assistant_id}_{member_id}",
-        result_json=result,
-        triggered_by=f"user:{user_id}",
-    )
-
-    logger.info(
-        "App4 关系分析完成: site_id=%s assistant=%s member=%s conversation_id=%s tokens=%d",
-        site_id, assistant_id, member_id, conversation_id, tokens_used,
-    )
-
-    return result

apps/backend/app/ai/apps/app5_tactics.py

@@ -1,288 +0,0 @@
-"""应用 5：话术参考（骨架）。
-
-App4 完成后自动联动触发，接收 App4 完整返回结果
-作为 Prompt 中的 task_suggestion 字段。
-
-Prompt reference 包含最近 2 套 App8 历史（附 generated_at）。
-
-app_id = "app5_tactics"
-"""
-
-from __future__ import annotations
-
-import asyncio
-import json
-import logging
-from datetime import datetime
-
-from app.ai.dashscope_client import DashScopeClient
-from app.ai.cache_service import AICacheService
-from app.ai.conversation_service import ConversationService
-from app.ai.data_fetchers import (
-    fetch_assistant_info,
-    fetch_member_consumption_data,
-    fetch_member_notes,
-    fetch_service_history,
-)
-from app.ai.schemas import CacheTypeEnum
-
-logger = logging.getLogger(__name__)
-
-APP_ID = "app5_tactics"
-
-# system message content 上限
-_MAX_SYSTEM_CONTENT_LEN = 8000
-
-
-def _default_member_data() -> dict:
-    """数据获取失败时的默认空值。"""
-    return {
-        "member_nickname": "",
-        "consumption_records": [],
-        "member_cards": [],
-        "card_balance_total": 0,
-        "stored_value_balance_total": 0,
-        "expected_visit_date": None,
-        "days_since_last_visit": None,
-    }
-
-
-async def build_prompt(
-    context: dict,
-    cache_svc: AICacheService | None = None,
-) -> list[dict]:
-    """构建 Prompt 消息列表。
-
-    复用 App4 的数据获取逻辑（并发获取助教信息、服务历史、消费数据、备注），
-    额外从 context["app4_result"] 获取 task_suggestion。
-
-    Args:
-        context: 包含 site_id, assistant_id, member_id, app4_result(dict)
-        cache_svc: 缓存服务，用于获取 reference 历史数据
-
-    Returns:
-        消息列表
-    """
-    site_id = context["site_id"]
-    assistant_id = context["assistant_id"]
-    member_id = context["member_id"]
-    # App4 结果作为 task_suggestion，缺失时设为空对象
-    task_suggestion = context.get("app4_result") or {}
-
-    # 并发获取 4 类数据，部分失败不阻断
-    results = await asyncio.gather(
-        fetch_assistant_info(site_id, assistant_id),
-        fetch_service_history(site_id, assistant_id, member_id),
-        fetch_member_consumption_data(site_id, member_id),
-        fetch_member_notes(site_id, member_id),
-        return_exceptions=True,
-    )
-
-    # 降级处理
-    fetch_errors: list[str] = []
-
-    if isinstance(results[0], Exception):
-        logger.warning("App5 助教信息获取失败: %s", results[0])
-        assistant_info = {}
-        fetch_errors.append("助教信息获取失败")
-    else:
-        assistant_info = results[0]
-
-    if isinstance(results[1], Exception):
-        logger.warning("App5 服务历史获取失败: %s", results[1])
-        service_history: list = []
-        fetch_errors.append("服务历史获取失败")
-    else:
-        service_history = results[1]
-
-    if isinstance(results[2], Exception):
-        logger.warning("App5 消费数据获取失败: %s", results[2])
-        member_data = _default_member_data()
-        fetch_errors.append("消费数据获取失败")
-    else:
-        member_data = results[2]
-
-    if isinstance(results[3], Exception):
-        logger.warning("App5 备注获取失败: %s", results[3])
-        notes: list = []
-        fetch_errors.append("备注获取失败")
-    else:
-        notes = results[3]
-
-    # 构建 reference：最近 2 套 App8 历史
-    reference = _build_reference(site_id, member_id, cache_svc)
-
-    system_content: dict = {
-        "task": (
-            "基于关系分析和任务建议，生成沟通话术参考。"
-            "输出必须严格遵循 output_format 中定义的 JSON 结构，"
-            "每条话术必须包含 scenario（场景描述）和 script（话术内容）两个字段，"
-            "禁止使用 content 或其他字段名替代。"
-        ),
-        "app_id": APP_ID,
-        "task_suggestion": task_suggestion,
-        "output_format": {
-            "tactics": [
-                {"scenario": "场景描述", "script": "话术内容"}
-            ]
-        },
-        "current_time": datetime.now().strftime("%Y-%m-%d %H:%M"),
-        "assistant_info": assistant_info if assistant_info else "⚠ 助教信息获取失败",
-        "service_history": service_history if service_history else "暂无服务记录",
-        "task_assignment_basis": {
-            "consumption_records": member_data.get("consumption_records", []) or "该客户暂无消费记录",
-            "member_cards": member_data.get("member_cards", []),
-            "card_balance_total": member_data.get("card_balance_total", 0),
-            "stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
-            "expected_visit_date": member_data.get("expected_visit_date"),
-            "days_since_last_visit": member_data.get("days_since_last_visit"),
-        },
-        "customer_data": {
-            "system_data": {
-                "member_nickname": member_data.get("member_nickname", ""),
-            },
-            "notes": notes if notes else "暂无备注",
-        },
-        "reference": reference,
-    }
-
-    if fetch_errors:
-        system_content["_data_warnings"] = fetch_errors
-
-    # Token 预算控制
-    content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    if len(content_str) > _MAX_SYSTEM_CONTENT_LEN:
-        sh = system_content.get("service_history")
-        if isinstance(sh, list) and len(sh) > 5:
-            system_content["service_history"] = sh[:5]
-            system_content["_truncated_service_history"] = f"服务记录已截断，原始共 {len(sh)} 条"
-        content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    if len(content_str) > _MAX_SYSTEM_CONTENT_LEN:
-        records = system_content["task_assignment_basis"].get("consumption_records")
-        if isinstance(records, list) and len(records) > 5:
-            system_content["task_assignment_basis"]["consumption_records"] = records[:5]
-            system_content["task_assignment_basis"]["_truncated"] = f"消费记录已截断，原始共 {len(records)} 条"
-        content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    if len(content_str) > _MAX_SYSTEM_CONTENT_LEN:
-        n = system_content["customer_data"].get("notes")
-        if isinstance(n, list) and len(n) > 10:
-            system_content["customer_data"]["notes"] = n[:10]
-            system_content["customer_data"]["_truncated_notes"] = f"备注已截断，原始共 {len(n)} 条"
-        content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-
-    user_content = (
-        f"请为助教 {assistant_id} 生成与会员 {member_id} 沟通的话术参考。"
-        "返回 tactics 数组，每条包含 scenario 和 script 字段。"
-    )
-
-    return [
-        {"role": "system", "content": content_str},
-        {"role": "user", "content": user_content},
-    ]
-
-
-def _build_reference(
-    site_id: int,
-    member_id: int,
-    cache_svc: AICacheService | None,
-) -> dict:
-    """构建 Prompt reference 字段。
-
-    包含最近 2 套 App8 历史（附 generated_at）。
-    缓存不存在时返回空对象 {}。
-    """
-    if cache_svc is None:
-        return {}
-
-    reference: dict = {}
-    target_id = str(member_id)
-
-    # 最近 2 套 App8 历史
-    app8_history = cache_svc.get_history(
-        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id, limit=2,
-    )
-    if app8_history:
-        reference["app8_history"] = [
-            {
-                "result_json": h.get("result_json"),
-                "generated_at": h.get("created_at"),
-            }
-            for h in app8_history
-        ]
-
-    return reference
-
-
-async def run(
-    context: dict,
-    client: DashScopeClient,
-    cache_svc: AICacheService,
-    conv_svc: ConversationService,
-) -> dict:
-    """执行 App5 话术参考。
-
-    Args:
-        context: site_id, assistant_id, member_id, app4_result(dict)
-        bailian: 百炼客户端
-        cache_svc: 缓存服务
-        conv_svc: 对话服务
-
-    Returns:
-        百炼返回的结构化 JSON（tactics 数组）
-    """
-    site_id = context["site_id"]
-    assistant_id = context["assistant_id"]
-    member_id = context["member_id"]
-    user_id = context.get("user_id", "system")
-    nickname = context.get("nickname", "")
-
-    # 1. 构建 Prompt
-    messages = await build_prompt(context, cache_svc)
-
-    # 2. 创建对话记录
-    conversation_id = conv_svc.create_conversation(
-        user_id=user_id,
-        nickname=nickname,
-        app_id=APP_ID,
-        site_id=site_id,
-        source_context={"assistant_id": assistant_id, "member_id": member_id},
-    )
-
-    # 写入 system + user 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="system",
-        content=messages[0]["content"],
-    )
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="user",
-        content=messages[1]["content"],
-    )
-
-    # 3. 调用百炼 API
-    result, tokens_used = await bailian.chat_json(messages)
-
-    # 4. 写入 assistant 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="assistant",
-        content=json.dumps(result, ensure_ascii=False),
-        tokens_used=tokens_used,
-    )
-
-    # 5. 写入缓存（target_id = {assistant_id}_{member_id}）
-    cache_svc.write_cache(
-        cache_type=CacheTypeEnum.APP5_TACTICS.value,
-        site_id=site_id,
-        target_id=f"{assistant_id}_{member_id}",
-        result_json=result,
-        triggered_by=f"user:{user_id}",
-    )
-
-    logger.info(
-        "App5 话术参考完成: site_id=%s assistant=%s member=%s conversation_id=%s tokens=%d",
-        site_id, assistant_id, member_id, conversation_id, tokens_used,
-    )
-
-    return result

apps/backend/app/ai/apps/app6_note.py

@@ -1,289 +0,0 @@
-"""应用 6：备注分析（骨架）。
-
-助教提交备注后自动触发，通过 AI 分析备注内容，
-提取维客线索并评分。
-
-返回 score（1-10）+ clues 数组。
-评分规则：6 分为标准分，重复/低价值/时效性低酌情扣分，高价值信息酌情加分。
-线索 category 限定 6 个枚举值。
-线索提供者标记为当前备注提供人（context.noted_by_name）。
-
-app_id = "app6_note"
-"""
-
-from __future__ import annotations
-
-import asyncio
-import json
-import logging
-from datetime import datetime
-
-from app.ai.dashscope_client import DashScopeClient
-from app.ai.cache_service import AICacheService
-from app.ai.conversation_service import ConversationService
-from app.ai.data_fetchers import fetch_member_consumption_data, fetch_member_notes
-from app.ai.schemas import CacheTypeEnum
-
-logger = logging.getLogger(__name__)
-
-APP_ID = "app6_note"
-
-# system message content 上限
-_MAX_SYSTEM_CONTENT_LEN = 8000
-
-
-def _default_member_data() -> dict:
-    """数据获取失败时的默认空值。"""
-    return {
-        "member_nickname": "",
-        "consumption_records": [],
-        "member_cards": [],
-        "card_balance_total": 0,
-        "stored_value_balance_total": 0,
-        "expected_visit_date": None,
-        "days_since_last_visit": None,
-    }
-
-
-async def build_prompt(
-    context: dict,
-    cache_svc: AICacheService | None = None,
-) -> list[dict]:
-    """构建 Prompt 消息列表。
-
-    并发获取消费数据和备注，失败时降级为空值。
-
-    Args:
-        context: 包含 site_id, member_id, note_content, noted_by_name
-        cache_svc: 缓存服务，用于获取 reference 历史数据
-
-    Returns:
-        消息列表
-    """
-    site_id = context["site_id"]
-    member_id = context["member_id"]
-    note_content = context.get("note_content", "")
-    noted_by_name = context.get("noted_by_name", "")
-    noted_by_created_at = context.get("noted_by_created_at", "")
-
-    # 并发获取消费数据和备注
-    results = await asyncio.gather(
-        fetch_member_consumption_data(site_id, member_id),
-        fetch_member_notes(site_id, member_id),
-        return_exceptions=True,
-    )
-
-    fetch_errors: list[str] = []
-
-    if isinstance(results[0], Exception):
-        logger.warning("App6 消费数据获取失败: %s", results[0])
-        member_data = _default_member_data()
-        fetch_errors.append("消费数据获取失败")
-    else:
-        member_data = results[0]
-
-    if isinstance(results[1], Exception):
-        logger.warning("App6 备注获取失败: %s", results[1])
-        all_notes: list = []
-        fetch_errors.append("备注获取失败")
-    else:
-        all_notes = results[1]
-
-    # 构建 reference：App3 线索 + 最近 2 套 App8 历史
-    reference = _build_reference(site_id, member_id, cache_svc)
-
-    # 将消费数据和备注注入 reference
-    reference["member_nickname"] = member_data.get("member_nickname", "")
-    reference["consumption_data"] = {
-        "consumption_records": member_data.get("consumption_records", []) or "该客户暂无消费记录",
-        "member_cards": member_data.get("member_cards", []),
-        "card_balance_total": member_data.get("card_balance_total", 0),
-        "stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
-        "expected_visit_date": member_data.get("expected_visit_date"),
-        "days_since_last_visit": member_data.get("days_since_last_visit"),
-    }
-    reference["all_notes"] = all_notes if all_notes else []
-
-    system_content: dict = {
-        "task": "分析备注内容，提取维客线索并评分。",
-        "app_id": APP_ID,
-        "rules": {
-            "category_enum": [
-                "客户基础", "消费习惯", "玩法偏好",
-                "促销偏好", "社交关系", "重要反馈",
-            ],
-            "providers": noted_by_name,
-            "scoring": "6 分为标准分，重复/低价值/时效性低酌情扣分，高价值信息酌情加分",
-            "score_range": "1-10",
-        },
-        "output_format": {
-            "score": "1-10 整数",
-            "clues": [
-                {
-                    "category": "枚举值（6 选 1）",
-                    "summary": "一句话摘要",
-                    "detail": "详细说明",
-                    "emoji": "表情符号",
-                }
-            ],
-        },
-        "current_time": datetime.now().strftime("%Y-%m-%d %H:%M"),
-        "current_note": {
-            "content": note_content,
-            "recorded_by": noted_by_name,
-            "created_at": noted_by_created_at,
-        },
-        "reference": reference,
-    }
-
-    if fetch_errors:
-        system_content["_data_warnings"] = fetch_errors
-
-    # Token 预算控制
-    content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    if len(content_str) > _MAX_SYSTEM_CONTENT_LEN:
-        records = system_content["reference"].get("consumption_data", {}).get("consumption_records")
-        if isinstance(records, list) and len(records) > 5:
-            system_content["reference"]["consumption_data"]["consumption_records"] = records[:5]
-            system_content["reference"]["consumption_data"]["_truncated"] = f"消费记录已截断，原始共 {len(records)} 条"
-        content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    if len(content_str) > _MAX_SYSTEM_CONTENT_LEN:
-        n = system_content["reference"].get("all_notes")
-        if isinstance(n, list) and len(n) > 10:
-            system_content["reference"]["all_notes"] = n[:10]
-            system_content["reference"]["_truncated_notes"] = f"备注已截断，原始共 {len(n)} 条"
-        content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-
-    user_content = (
-        f"请分析以下备注内容，提取维客线索并评分。\n"
-        f"备注提供人：{noted_by_name}\n"
-        f"备注内容：{note_content}\n"
-        "返回 score（1-10 整数）和 clues 数组。"
-        "category 必须是：客户基础、消费习惯、玩法偏好、促销偏好、社交关系、重要反馈 之一。"
-    )
-
-    return [
-        {"role": "system", "content": content_str},
-        {"role": "user", "content": user_content},
-    ]
-
-
-def _build_reference(
-    site_id: int,
-    member_id: int,
-    cache_svc: AICacheService | None,
-) -> dict:
-    """构建 Prompt reference 字段。
-
-    包含：
-    - App3 客户数据线索（最新一条，如有）
-    - 最近 2 套 App8 维客线索整理历史（附 generated_at）
-
-    缓存不存在时返回空对象 {}。
-    """
-    if cache_svc is None:
-        return {}
-
-    reference: dict = {}
-    target_id = str(member_id)
-
-    # App3 客户数据线索
-    app3_latest = cache_svc.get_latest(
-        CacheTypeEnum.APP3_CLUE.value, site_id, target_id,
-    )
-    if app3_latest:
-        reference["app3_clues"] = {
-            "result_json": app3_latest.get("result_json"),
-            "generated_at": app3_latest.get("created_at"),
-        }
-
-    # 最近 2 套 App8 历史
-    app8_history = cache_svc.get_history(
-        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id, limit=2,
-    )
-    if app8_history:
-        reference["app8_history"] = [
-            {
-                "result_json": h.get("result_json"),
-                "generated_at": h.get("created_at"),
-            }
-            for h in app8_history
-        ]
-
-    return reference
-
-
-async def run(
-    context: dict,
-    client: DashScopeClient,
-    cache_svc: AICacheService,
-    conv_svc: ConversationService,
-) -> dict:
-    """执行 App6 备注分析。
-
-    Args:
-        context: site_id, member_id, note_content, noted_by_name
-        bailian: 百炼客户端
-        cache_svc: 缓存服务
-        conv_svc: 对话服务
-
-    Returns:
-        百炼返回的结构化 JSON（score + clues 数组）
-    """
-    site_id = context["site_id"]
-    member_id = context["member_id"]
-    user_id = context.get("user_id", "system")
-    nickname = context.get("nickname", "")
-
-    # 1. 构建 Prompt
-    messages = await build_prompt(context, cache_svc)
-
-    # 2. 创建对话记录
-    conversation_id = conv_svc.create_conversation(
-        user_id=user_id,
-        nickname=nickname,
-        app_id=APP_ID,
-        site_id=site_id,
-        source_context={"member_id": member_id},
-    )
-
-    # 写入 system + user 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="system",
-        content=messages[0]["content"],
-    )
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="user",
-        content=messages[1]["content"],
-    )
-
-    # 3. 调用百炼 API
-    result, tokens_used = await bailian.chat_json(messages)
-
-    # 4. 写入 assistant 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="assistant",
-        content=json.dumps(result, ensure_ascii=False),
-        tokens_used=tokens_used,
-    )
-
-    # 5. 写入缓存（score 存入 ai_cache.score）
-    score = result.get("score")
-    cache_svc.write_cache(
-        cache_type=CacheTypeEnum.APP6_NOTE_ANALYSIS.value,
-        site_id=site_id,
-        target_id=str(member_id),
-        result_json=result,
-        triggered_by=f"user:{user_id}",
-        score=score,
-    )
-
-    logger.info(
-        "App6 备注分析完成: site_id=%s member_id=%s score=%s conversation_id=%s tokens=%d",
-        site_id, member_id, score, conversation_id, tokens_used,
-    )
-
-    return result

apps/backend/app/ai/apps/app7_customer.py

@@ -1,282 +0,0 @@
-"""应用 7：客户分析（骨架）。
-
-消费事件链中 App8 完成后串行触发，生成客户全量分析与运营建议。
-
-使用 items_sum 口径（= table_charge_money + goods_money
-+ assistant_pd_money + assistant_cx_money + electricity_money），
-禁止使用 consume_money。
-
-对主观信息（来自备注）标注【来源：XXX，请甄别信息真实性】。
-
-app_id = "app7_customer"
-"""
-
-from __future__ import annotations
-
-import asyncio
-import json
-import logging
-from datetime import datetime
-
-from app.ai.dashscope_client import DashScopeClient
-from app.ai.cache_service import AICacheService
-from app.ai.conversation_service import ConversationService
-from app.ai.data_fetchers import fetch_member_consumption_data, fetch_member_notes
-from app.ai.schemas import CacheTypeEnum
-
-logger = logging.getLogger(__name__)
-
-APP_ID = "app7_customer"
-
-# system message content 上限
-_MAX_SYSTEM_CONTENT_LEN = 8000
-
-
-def _default_member_data() -> dict:
-    """数据获取失败时的默认空值。"""
-    return {
-        "member_nickname": "",
-        "consumption_records": [],
-        "member_cards": [],
-        "card_balance_total": 0,
-        "stored_value_balance_total": 0,
-        "expected_visit_date": None,
-        "days_since_last_visit": None,
-    }
-
-
-async def build_prompt(
-    context: dict,
-    cache_svc: AICacheService | None = None,
-) -> list[dict]:
-    """构建 Prompt 消息列表。
-
-    并发获取消费数据和备注，备注标注来源信息。
-
-    Args:
-        context: 包含 site_id, member_id
-        cache_svc: 缓存服务，用于获取 reference 历史数据
-
-    Returns:
-        消息列表
-    """
-    site_id = context["site_id"]
-    member_id = context["member_id"]
-
-    # 并发获取消费数据和备注
-    results = await asyncio.gather(
-        fetch_member_consumption_data(site_id, member_id),
-        fetch_member_notes(site_id, member_id),
-        return_exceptions=True,
-    )
-
-    fetch_errors: list[str] = []
-
-    if isinstance(results[0], Exception):
-        logger.warning("App7 消费数据获取失败: %s", results[0])
-        member_data = _default_member_data()
-        fetch_errors.append("消费数据获取失败")
-    else:
-        member_data = results[0]
-
-    if isinstance(results[1], Exception):
-        logger.warning("App7 备注获取失败: %s", results[1])
-        notes_raw: list = []
-        fetch_errors.append("备注获取失败")
-    else:
-        notes_raw = results[1]
-
-    # 备注标注来源信息
-    if notes_raw:
-        subjective_notes = []
-        for note in notes_raw:
-            recorded_by = note.get("recorded_by", "未知")
-            annotated = dict(note)
-            annotated["content"] = f"{note.get('content', '')}【来源：{recorded_by}，请甄别信息真实性】"
-            subjective_notes.append(annotated)
-    else:
-        subjective_notes = "该客户暂无主观备注信息"
-
-    member_nickname = member_data.get("member_nickname", "")
-
-    # 构建 reference：最新 + 最近 2 套 App8 历史
-    reference = _build_reference(site_id, member_id, cache_svc)
-
-    system_content: dict = {
-        "task": "综合分析客户数据，生成运营策略建议。",
-        "app_id": APP_ID,
-        "rules": {
-            "amount_caliber": "items_sum = table_charge_money + goods_money + assistant_pd_money + assistant_cx_money + electricity_money",
-            "禁止使用": "consume_money",
-            "subjective_info_label": "对主观信息（来自备注）标注【来源：XXX，请甄别信息真实性】",
-        },
-        "output_format": {
-            "strategies": [
-                {"title": "策略标题", "content": "策略内容"}
-            ],
-            "summary": "一句话总结",
-        },
-        "current_time": datetime.now().strftime("%Y-%m-%d %H:%M"),
-        "member_id": member_id,
-        "member_nickname": member_nickname,
-        "objective_data": {
-            "consumption_records": member_data.get("consumption_records", []) or "该客户暂无消费记录",
-            "member_cards": member_data.get("member_cards", []),
-            "card_balance_total": member_data.get("card_balance_total", 0),
-            "stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
-            "expected_visit_date": member_data.get("expected_visit_date"),
-            "days_since_last_visit": member_data.get("days_since_last_visit"),
-        },
-        "subjective_data": {
-            "notes": subjective_notes,
-        },
-        "reference": reference,
-    }
-
-    if fetch_errors:
-        system_content["_data_warnings"] = fetch_errors
-
-    # Token 预算控制
-    content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    if len(content_str) > _MAX_SYSTEM_CONTENT_LEN:
-        records = system_content["objective_data"].get("consumption_records")
-        if isinstance(records, list) and len(records) > 5:
-            system_content["objective_data"]["consumption_records"] = records[:5]
-            system_content["objective_data"]["_truncated"] = f"消费记录已截断，原始共 {len(records)} 条"
-        content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-    if len(content_str) > _MAX_SYSTEM_CONTENT_LEN:
-        n = system_content["subjective_data"].get("notes")
-        if isinstance(n, list) and len(n) > 10:
-            system_content["subjective_data"]["notes"] = n[:10]
-            system_content["subjective_data"]["_truncated_notes"] = f"备注已截断，原始共 {len(n)} 条"
-        content_str = json.dumps(system_content, ensure_ascii=False, default=str)
-
-    user_content = (
-        f"请综合分析会员 {member_id} 的客户数据，生成运营策略建议。"
-        "返回 strategies 数组（每条含 title 和 content）和 summary 字段。"
-        "对来自备注的主观信息，请标注【来源：XXX，请甄别信息真实性】。"
-    )
-
-    return [
-        {"role": "system", "content": content_str},
-        {"role": "user", "content": user_content},
-    ]
-
-
-def _build_reference(
-    site_id: int,
-    member_id: int,
-    cache_svc: AICacheService | None,
-) -> dict:
-    """构建 Prompt reference 字段。
-
-    包含：
-    - App8 最新维客线索（如有）
-    - 最近 2 套 App8 历史（附 generated_at）
-
-    缓存不存在时返回空对象 {}。
-    """
-    if cache_svc is None:
-        return {}
-
-    reference: dict = {}
-    target_id = str(member_id)
-
-    # App8 最新
-    app8_latest = cache_svc.get_latest(
-        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id,
-    )
-    if app8_latest:
-        reference["app8_latest"] = {
-            "result_json": app8_latest.get("result_json"),
-            "generated_at": app8_latest.get("created_at"),
-        }
-
-    # 最近 2 套 App8 历史
-    app8_history = cache_svc.get_history(
-        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id, limit=2,
-    )
-    if app8_history:
-        reference["app8_history"] = [
-            {
-                "result_json": h.get("result_json"),
-                "generated_at": h.get("created_at"),
-            }
-            for h in app8_history
-        ]
-
-    return reference
-
-
-async def run(
-    context: dict,
-    client: DashScopeClient,
-    cache_svc: AICacheService,
-    conv_svc: ConversationService,
-) -> dict:
-    """执行 App7 客户分析。
-
-    Args:
-        context: site_id, member_id
-        bailian: 百炼客户端
-        cache_svc: 缓存服务
-        conv_svc: 对话服务
-
-    Returns:
-        百炼返回的结构化 JSON（strategies 数组 + summary）
-    """
-    site_id = context["site_id"]
-    member_id = context["member_id"]
-    user_id = context.get("user_id", "system")
-    nickname = context.get("nickname", "")
-
-    # 1. 构建 Prompt
-    messages = await build_prompt(context, cache_svc)
-
-    # 2. 创建对话记录
-    conversation_id = conv_svc.create_conversation(
-        user_id=user_id,
-        nickname=nickname,
-        app_id=APP_ID,
-        site_id=site_id,
-        source_context={"member_id": member_id},
-    )
-
-    # 写入 system + user 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="system",
-        content=messages[0]["content"],
-    )
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="user",
-        content=messages[1]["content"],
-    )
-
-    # 3. 调用百炼 API
-    result, tokens_used = await bailian.chat_json(messages)
-
-    # 4. 写入 assistant 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="assistant",
-        content=json.dumps(result, ensure_ascii=False),
-        tokens_used=tokens_used,
-    )
-
-    # 5. 写入缓存
-    cache_svc.write_cache(
-        cache_type=CacheTypeEnum.APP7_CUSTOMER_ANALYSIS.value,
-        site_id=site_id,
-        target_id=str(member_id),
-        result_json=result,
-        triggered_by=f"user:{user_id}",
-    )
-
-    logger.info(
-        "App7 客户分析完成: site_id=%s member_id=%s conversation_id=%s tokens=%d",
-        site_id, member_id, conversation_id, tokens_used,
-    )
-
-    return result

apps/backend/app/ai/apps/app8_consolidation.py

@@ -1,211 +0,0 @@
-"""应用 8：维客线索整理。
-
-接收 App3（消费分析）和 App6（备注分析）的线索，
-通过百炼 AI 整合去重，然后全量替换写入 member_retention_clue 表。
-
-app_id = "app8_consolidation"
-"""
-
-from __future__ import annotations
-
-import json
-import logging
-
-from app.ai.dashscope_client import DashScopeClient
-from app.ai.cache_service import AICacheService
-from app.ai.conversation_service import ConversationService
-from app.ai.prompts.app8_consolidation_prompt import build_prompt
-from app.ai.schemas import CacheTypeEnum
-from app.database import get_connection
-
-logger = logging.getLogger(__name__)
-
-APP_ID = "app8_consolidation"
-
-
-class ClueWriter:
-    """维客线索全量替换写入器。
-
-    DELETE source IN ('ai_consumption', 'ai_note') → INSERT 新线索（事务）。
-    人工线索（source='manual'）不受影响。
-    """
-
-    def replace_ai_clues(
-        self,
-        member_id: int,
-        site_id: int,
-        clues: list[dict],
-    ) -> int:
-        """全量替换该客户的 AI 来源线索，返回写入数量。
-
-        在单个事务中执行 DELETE + INSERT，失败时回滚保留原有线索。
-
-        字段映射：
-        - category → category
-        - emoji + " " + summary → summary（如 "📅 偏好周末下午时段消费"）
-        - detail → detail
-        - providers → recorded_by_name
-        - source: 根据 providers 判断（见 _determine_source）
-        - recorded_by_assistant_id: NULL（系统触发）
-        """
-        conn = get_connection()
-        try:
-            with conn.cursor() as cur:
-                # 1. 删除该客户所有 AI 来源线索
-                cur.execute(
-                    """
-                    DELETE FROM member_retention_clue
-                    WHERE member_id = %s AND site_id = %s
-                      AND source IN ('ai_consumption', 'ai_note')
-                    """,
-                    (member_id, site_id),
-                )
-
-                # 2. 插入新线索
-                for clue in clues:
-                    emoji = clue.get("emoji", "")
-                    raw_summary = clue.get("summary", "")
-                    summary = f"{emoji} {raw_summary}" if emoji else raw_summary
-                    source = _determine_source(clue.get("providers", ""))
-
-                    cur.execute(
-                        """
-                        INSERT INTO member_retention_clue
-                            (member_id, site_id, category, summary, detail,
-                             source, recorded_by_name, recorded_by_assistant_id)
-                        VALUES (%s, %s, %s, %s, %s, %s, %s, NULL)
-                        """,
-                        (
-                            member_id,
-                            site_id,
-                            clue.get("category", ""),
-                            summary,
-                            clue.get("detail", ""),
-                            source,
-                            clue.get("providers", ""),
-                        ),
-                    )
-
-                conn.commit()
-                return len(clues)
-        except Exception:
-            conn.rollback()
-            raise
-        finally:
-            conn.close()
-
-
-def _determine_source(providers: str) -> str:
-    """根据 providers 判断 source 值。
-
-    - 纯 App3（providers 仅含"系统"）→ ai_consumption
-    - 纯 App6（providers 不含"系统"）→ ai_note
-    - 混合来源 → ai_consumption
-    """
-    if not providers:
-        return "ai_consumption"
-    provider_list = [p.strip() for p in providers.split(",")]
-    has_system = "系统" in provider_list
-    has_human = any(p != "系统" for p in provider_list if p)
-    if has_system and not has_human:
-        # 纯 App3（系统自动分析）
-        return "ai_consumption"
-    elif has_human and not has_system:
-        # 纯 App6（人工备注分析）
-        return "ai_note"
-    else:
-        # 混合来源
-        return "ai_consumption"
-
-
-async def run(
-    context: dict,
-    client: DashScopeClient,
-    cache_svc: AICacheService,
-    conv_svc: ConversationService,
-) -> dict:
-    """执行 App8 维客线索整理。
-
-    流程：
-    1. build_prompt 构建 Prompt
-    2. bailian.chat_json 调用百炼
-    3. 写入 conversation + messages
-    4. 写入 ai_cache
-    5. ClueWriter 全量替换 member_retention_clue
-    6. 返回结果
-
-    Args:
-        context: site_id, member_id, app3_clues, app6_clues,
-                 app3_generated_at, app6_generated_at
-        bailian: 百炼客户端
-        cache_svc: 缓存服务
-        conv_svc: 对话服务
-
-    Returns:
-        百炼返回的结构化 JSON（clues 数组）
-    """
-    site_id = context["site_id"]
-    member_id = context["member_id"]
-    user_id = context.get("user_id", "system")
-    nickname = context.get("nickname", "")
-
-    # 1. 构建 Prompt
-    messages = build_prompt(context)
-
-    # 2. 创建对话记录
-    conversation_id = conv_svc.create_conversation(
-        user_id=user_id,
-        nickname=nickname,
-        app_id=APP_ID,
-        site_id=site_id,
-        source_context={"member_id": member_id},
-    )
-
-    # 写入 system + user 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="system",
-        content=messages[0]["content"],
-    )
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="user",
-        content=messages[1]["content"],
-    )
-
-    # 3. 调用百炼 API
-    result, tokens_used = await bailian.chat_json(messages)
-
-    # 4. 写入 assistant 消息
-    conv_svc.add_message(
-        conversation_id=conversation_id,
-        role="assistant",
-        content=json.dumps(result, ensure_ascii=False),
-        tokens_used=tokens_used,
-    )
-
-    # 5. 写入缓存
-    cache_svc.write_cache(
-        cache_type=CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value,
-        site_id=site_id,
-        target_id=str(member_id),
-        result_json=result,
-        triggered_by=f"user:{user_id}",
-    )
-
-    # 6. 全量替换 member_retention_clue
-    clues = result.get("clues", [])
-    if clues:
-        writer = ClueWriter()
-        written = writer.replace_ai_clues(member_id, site_id, clues)
-        logger.info(
-            "App8 线索写入完成: site_id=%s member_id=%s written=%d",
-            site_id, member_id, written,
-        )
-
-    logger.info(
-        "App8 线索整理完成: site_id=%s member_id=%s conversation_id=%s tokens=%d",
-        site_id, member_id, conversation_id, tokens_used,
-    )
-
-    return result

apps/backend/app/ai/cache_service.py

@@ -18,6 +18,12 @@ import logging
 from datetime import datetime, timedelta, timezone
 
 from app.database import get_connection
+from app.services.runtime_context import (
+    LIVE_INSTANCE_ID,
+    MODE_LIVE,
+    MODE_SANDBOX,
+    get_runtime_context,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -39,6 +45,14 @@ CACHE_MAX_PER_APP = 20_000
 class AICacheService:
     """AI 缓存读写服务。"""
 
+    @staticmethod
+    def _runtime_scope(site_id: int, target_id: str, conn) -> tuple[str, str, str]:
+        """返回运行模式、实例 ID 和实际 cache target_id。"""
+        ctx = get_runtime_context(site_id, conn=conn)
+        if ctx.is_sandbox and ctx.sandbox_instance_id:
+            return MODE_SANDBOX, ctx.sandbox_instance_id, f"{ctx.sandbox_instance_id}:{target_id}"
+        return MODE_LIVE, LIVE_INSTANCE_ID, target_id
+
     def get_latest(
         self,
         cache_type: str,
@@ -52,6 +66,9 @@ class AICacheService:
         """
         conn = get_connection()
         try:
+            runtime_mode, sandbox_instance_id, scoped_target_id = self._runtime_scope(
+                site_id, target_id, conn
+            )
             with conn.cursor() as cur:
                 cur.execute(
                     """
@@ -60,12 +77,14 @@ class AICacheService:
                            created_at, expires_at, status
                     FROM biz.ai_cache
                     WHERE cache_type = %s AND site_id = %s AND target_id = %s
+                      AND COALESCE(runtime_mode, 'live') = %s
+                      AND COALESCE(sandbox_instance_id, 'live') = %s
                       AND (status = 'valid' OR status IS NULL)
                       AND (expires_at IS NULL OR expires_at > now())
                     ORDER BY created_at DESC
                     LIMIT 1
                     """,
-                    (cache_type, site_id, target_id),
+                    (cache_type, site_id, scoped_target_id, runtime_mode, sandbox_instance_id),
                 )
                 columns = [desc[0] for desc in cur.description]
                 row = cur.fetchone()
@@ -88,6 +107,9 @@ class AICacheService:
         """
         conn = get_connection()
         try:
+            runtime_mode, sandbox_instance_id, scoped_target_id = self._runtime_scope(
+                site_id, target_id, conn
+            )
             with conn.cursor() as cur:
                 cur.execute(
                     """
@@ -96,10 +118,12 @@ class AICacheService:
                            created_at, expires_at
                     FROM biz.ai_cache
                     WHERE cache_type = %s AND site_id = %s AND target_id = %s
+                      AND COALESCE(runtime_mode, 'live') = %s
+                      AND COALESCE(sandbox_instance_id, 'live') = %s
                     ORDER BY created_at DESC
                     LIMIT %s
                     """,
-                    (cache_type, site_id, target_id, limit),
+                    (cache_type, site_id, scoped_target_id, runtime_mode, sandbox_instance_id, limit),
                 )
                 columns = [desc[0] for desc in cur.description]
                 rows = cur.fetchall()
@@ -128,23 +152,29 @@ class AICacheService:
 
         conn = get_connection()
         try:
+            runtime_mode, sandbox_instance_id, scoped_target_id = self._runtime_scope(
+                site_id, target_id, conn
+            )
             with conn.cursor() as cur:
                 cur.execute(
                     """
                     INSERT INTO biz.ai_cache
                         (cache_type, site_id, target_id, result_json,
-                         triggered_by, score, expires_at, status)
-                    VALUES (%s, %s, %s, %s, %s, %s, %s, 'valid')
+                         triggered_by, score, expires_at, status,
+                         runtime_mode, sandbox_instance_id)
+                    VALUES (%s, %s, %s, %s, %s, %s, %s, 'valid', %s, %s)
                     RETURNING id
                     """,
                     (
                         cache_type,
                         site_id,
-                        target_id,
+                        scoped_target_id,
                         json.dumps(result_json, ensure_ascii=False),
                         triggered_by,
                         score,
                         expires_at,
+                        runtime_mode,
+                        sandbox_instance_id,
                     ),
                 )
                 row = cur.fetchone()
@@ -158,7 +188,7 @@ class AICacheService:
 
         # 写入成功后清理超限记录
         try:
-            deleted = self._cleanup_excess(cache_type, site_id, target_id)
+            deleted = self._cleanup_excess(cache_type, site_id, scoped_target_id)
             if deleted > 0:
                 logger.info(
                     "清理超限缓存: cache_type=%s site_id=%s target_id=%s 删除=%d",
@@ -183,15 +213,19 @@ class AICacheService:
         """写入 generating 状态占位记录，返回 id。完成后调用 finalize_cache 更新。"""
         conn = get_connection()
         try:
+            runtime_mode, sandbox_instance_id, scoped_target_id = self._runtime_scope(
+                site_id, target_id, conn
+            )
             with conn.cursor() as cur:
                 cur.execute(
                     """
                     INSERT INTO biz.ai_cache
-                        (cache_type, site_id, target_id, result_json, status, triggered_by)
-                    VALUES (%s, %s, %s, '{}', 'generating', %s)
+                        (cache_type, site_id, target_id, result_json, status, triggered_by,
+                         runtime_mode, sandbox_instance_id)
+                    VALUES (%s, %s, %s, '{}', 'generating', %s, %s, %s)
                     RETURNING id
                     """,
-                    (cache_type, site_id, target_id, triggered_by),
+                    (cache_type, site_id, scoped_target_id, triggered_by, runtime_mode, sandbox_instance_id),
                 )
                 row = cur.fetchone()
                 conn.commit()

apps/backend/app/ai/dashscope_client.py

@@ -28,6 +28,44 @@ from app.ai.exceptions import (
 logger = logging.getLogger(__name__)
 
 
+def _field_value(source: Any, key: str, default: Any = None) -> Any:
+    """兼容 dict、DashScope DictMixin 和普通对象取字段。"""
+    if isinstance(source, dict):
+        return source.get(key, default)
+    return getattr(source, key, default)
+
+
+def _safe_int(value: Any) -> int:
+    """把 token 字段安全转换为 int，异常值按 0 处理。"""
+    try:
+        return int(value or 0)
+    except (TypeError, ValueError):
+        return 0
+
+
+def _extract_tokens_used(usage: Any) -> int:
+    """从 DashScope usage 多种结构中提取 tokens_used。"""
+    if not usage:
+        return 0
+
+    models = _field_value(usage, "models")
+    if models:
+        total = 0
+        for model_usage in models:
+            total += _safe_int(_field_value(model_usage, "input_tokens"))
+            total += _safe_int(_field_value(model_usage, "output_tokens"))
+        return total
+
+    total_tokens = _field_value(usage, "total_tokens")
+    if total_tokens is not None:
+        return _safe_int(total_tokens)
+
+    return (
+        _safe_int(_field_value(usage, "input_tokens"))
+        + _safe_int(_field_value(usage, "output_tokens"))
+    )
+
+
 class DashScopeClient:
     """DashScope Application API 统一封装层。
 
@@ -54,22 +92,28 @@ class DashScopeClient:
         prompt: str,
         session_id: str | None = None,
         biz_params: dict | None = None,
-    ) -> AsyncGenerator[str, None]:
-        """App1 流式调用。
+    ) -> AsyncGenerator[tuple[str, str | None], None]:
+        """App1 流式调用，支持 multi-turn session_id 透传。
 
         在线程中消费同步迭代器，通过 asyncio.Queue 桥接到 async generator。
-        错误通过 queue 传递给调用方。
+        每个 yield 返回 (text_chunk, session_id_or_none) 元组：
+        - 首次调用（传入 session_id=None）时，百炼在流中会返回新 session_id，
+          应由调用方在流结束后回写 DB。
+        - 后续调用传入 DB 中的 session_id 后，百炼自动关联历史上下文，
+          返回的 session_id 通常一致。
 
         Args:
             app_id: 百炼应用 ID
             prompt: 用户输入
-            session_id: 百炼 session_id（多轮对话）
+            session_id: 百炼 session_id；首次对话传 None
             biz_params: 业务参数（如 user_prompt_params）
 
         Yields:
-            文本 chunk
+            (text_chunk, session_id_or_none) 元组。
+            text_chunk 为空字符串时（例如仅承载 session_id 的心跳 chunk），
+            调用方应忽略文本但保留 session_id。
         """
-        queue: asyncio.Queue[str | BaseException | None] = asyncio.Queue()
+        queue: asyncio.Queue[tuple[str, str | None] | BaseException | None] = asyncio.Queue()
         loop = asyncio.get_running_loop()
 
         def _consume_in_thread() -> None:
@@ -91,10 +135,17 @@ class DashScopeClient:
                 response = Application.call(**call_kwargs)
                 for chunk in response:
                     if chunk.status_code == 200:
-                        text = chunk.output.get("text", "")
-                        if text:
+                        output = chunk.output if hasattr(chunk, "output") else {}
+                        if isinstance(output, dict):
+                            text = output.get("text", "") or ""
+                            new_sid = output.get("session_id")
+                        else:
+                            text = getattr(output, "text", "") or ""
+                            new_sid = getattr(output, "session_id", None)
+                        # 文本或 session_id 任一非空都推入（心跳 chunk 也传出 session_id）
+                        if text or new_sid:
                             asyncio.run_coroutine_threadsafe(
-                                queue.put(text), loop
+                                queue.put((text, new_sid)), loop
                             )
                     else:
                         # 非 200 状态码，构造异常传递给调用方
@@ -180,16 +231,12 @@ class DashScopeClient:
                     raw_text = output.text or ""
 
             # 提取 tokens_used
+            # DashScope Application.call() 返回的 usage 实际结构（2026-04 验证）：
+            # ApplicationUsage(models=[ApplicationModelUsage(model_id, input_tokens, output_tokens)])
+            # 旧代码只处理 dict / total_tokens 两种分支，导致该嵌套结构下 tokens_used 恒为 0
             tokens_used = 0
             if hasattr(response, "usage") and response.usage:
-                usage = response.usage
-                if isinstance(usage, dict):
-                    # input_tokens + output_tokens
-                    tokens_used = usage.get("input_tokens", 0) + usage.get(
-                        "output_tokens", 0
-                    )
-                elif hasattr(usage, "total_tokens"):
-                    tokens_used = usage.total_tokens or 0
+                tokens_used = _extract_tokens_used(response.usage)
 
             # 提取 new_session_id
             new_session_id: str | None = None

apps/backend/app/ai/data_fetchers/assistant_data.py

@@ -58,10 +58,16 @@ def _fetch_assistant_info_sync(site_id: int, assistant_id: int) -> dict[str, Any
         conn = get_etl_readonly_connection(site_id)
         # RLS 隔离 + 语句超时（get_etl_readonly_connection 的 SET LOCAL 在 commit 后失效，
         # 需在查询事务中重新设置）
+        # CHANGE 2026-05-02 | 同时下发 app.current_business_date，供 RLS 视图业务日上界裁剪
+        from app.services.runtime_context import as_runtime_today_param as _rt_today
+        _ref_date = _rt_today(site_id)
         with conn.cursor() as cur:
             cur.execute(
                 "SET LOCAL app.current_site_id = %s", (str(site_id),)
             )
+            cur.execute(
+                "SET LOCAL app.current_business_date = %s", (_ref_date.isoformat(),)
+            )
             cur.execute(
                 "SET LOCAL statement_timeout = %s",
                 (f"{FDW_QUERY_TIMEOUT_SEC * 1000}",),
@@ -86,11 +92,12 @@ def _fetch_assistant_info_sync(site_id: int, assistant_id: int) -> dict[str, Any
             level = row[1] or ""
             hire_date = row[2]
 
-            # 计算工龄
+            # 计算工龄（CHANGE 2026-05-02 | 用 business_date 替代 today，沙箱按当时工龄）
+            from app.services.runtime_context import as_runtime_today_param
+            ref_date = as_runtime_today_param(site_id)
             tenure_months = 0
             if hire_date and isinstance(hire_date, date):
-                today = date.today()
-                tenure_months = (today.year - hire_date.year) * 12 + (today.month - hire_date.month)
+                tenure_months = (ref_date.year - hire_date.year) * 12 + (ref_date.month - hire_date.month)
 
             # 绩效数据
             # ⚠️ 列名映射: monthly_customers 不存在（用 0 占位），performance_tier→tier_name
@@ -184,10 +191,16 @@ def _fetch_service_history_sync(
         conn = get_etl_readonly_connection(site_id)
         # RLS 隔离 + 语句超时（get_etl_readonly_connection 的 SET LOCAL 在 commit 后失效，
         # 需在查询事务中重新设置）
+        # CHANGE 2026-05-02 | 同时下发 app.current_business_date，供 RLS 视图业务日上界裁剪
+        from app.services.runtime_context import as_runtime_today_param as _rt_today2
+        _ref_date_outer = _rt_today2(site_id)
         with conn.cursor() as cur:
             cur.execute(
                 "SET LOCAL app.current_site_id = %s", (str(site_id),)
             )
+            cur.execute(
+                "SET LOCAL app.current_business_date = %s", (_ref_date_outer.isoformat(),)
+            )
             cur.execute(
                 "SET LOCAL statement_timeout = %s",
                 (f"{FDW_QUERY_TIMEOUT_SEC * 1000}",),
@@ -197,6 +210,9 @@ def _fetch_service_history_sync(
             # is_trash=false→is_delete=0, service_date→create_time,
             # duration_minutes→real_use_seconds/60, items_sum→ledger_amount,
             # room_name→site_table_id, is_pd→(order_assistant_type=1)
+            # CHANGE 2026-05-02 | 用 business_date 替代 CURRENT_DATE，沙箱不读「未来」服务记录
+            from app.services.runtime_context import as_runtime_today_param
+            ref_date = as_runtime_today_param(site_id)
             cur.execute(
                 """
                 SELECT
@@ -209,10 +225,11 @@ def _fetch_service_history_sync(
                 WHERE site_assistant_id = %s
                   AND tenant_member_id = %s
                   AND is_delete = 0
-                  AND create_time >= (CURRENT_DATE - INTERVAL '%s months')
+                  AND create_time >= (%s::date - (INTERVAL '1 month' * %s))
+                  AND create_time <  (%s::date + INTERVAL '1 day')
                 ORDER BY create_time DESC
                 """,
-                (assistant_id, member_id, months),
+                (assistant_id, member_id, ref_date, months, ref_date),
             )
             columns = [desc[0] for desc in cur.description]
             rows = cur.fetchall()

apps/backend/app/ai/data_fetchers/member_data.py

@@ -63,16 +63,27 @@ def _fetch_member_consumption_data_sync(
     member_id: int,
     months: int,
 ) -> dict[str, Any]:
-    """同步实现：在单个 FDW 连接上串行执行多个查询。"""
+    """同步实现：在单个 FDW 连接上串行执行多个查询。
+
+    CHANGE 2026-05-02 | 所有窗口查询都按业务日上界裁剪，
+    sandbox 模式下不再读取 sandbox_date 之后的真实消费 / 到店。
+    """
+    from app.services.runtime_context import as_runtime_today_param
+
     conn = None
     try:
         conn = get_etl_readonly_connection(site_id)
+        ref_date = as_runtime_today_param(site_id)
         # RLS 隔离 + 语句超时（get_etl_readonly_connection 的 SET LOCAL 在 commit 后失效，
         # 需在查询事务中重新设置）
+        # CHANGE 2026-05-02 | 同时下发 app.current_business_date，供 RLS 视图业务日上界裁剪
         with conn.cursor() as cur:
             cur.execute(
                 "SET LOCAL app.current_site_id = %s", (str(site_id),)
             )
+            cur.execute(
+                "SET LOCAL app.current_business_date = %s", (ref_date.isoformat(),)
+            )
             cur.execute(
                 "SET LOCAL statement_timeout = %s",
                 (f"{FDW_QUERY_TIMEOUT_SEC * 1000}",),  # 毫秒
@@ -82,7 +93,7 @@ def _fetch_member_consumption_data_sync(
         nickname = _query_member_nickname(conn, member_id)
 
         # 2. 消费记录（台桌结账 + 商城订单）
-        records, total_count = _query_consumption_records(conn, member_id, months)
+        records, total_count = _query_consumption_records(conn, member_id, months, ref_date)
 
         # 3. 会员卡明细
         cards = _query_member_cards(conn, member_id)
@@ -91,7 +102,7 @@ def _fetch_member_consumption_data_sync(
         balance_info = _query_balance_summary(conn, member_id)
 
         # 5. 到店数据
-        visit_info = _query_visit_info(conn, member_id)
+        visit_info = _query_visit_info(conn, member_id, ref_date)
 
         result: dict[str, Any] = {
             "member_nickname": nickname,
@@ -145,7 +156,7 @@ def _query_member_nickname(conn: Any, member_id: int) -> str:
 
 
 def _query_consumption_records(
-    conn: Any, member_id: int, months: int
+    conn: Any, member_id: int, months: int, ref_date: date
 ) -> tuple[list[dict], int]:
     """从 app.v_dwd_settlement_head + app.v_dwd_table_fee_log 获取消费记录。
 
@@ -153,6 +164,7 @@ def _query_consumption_records(
     ⚠️ 费用拆分字段（table_charge_money, assistant_pd/cx_money）在 settlement_head 上。
     ⚠️ table_fee_log 提供台桌时长（real_table_use_seconds）和桌台ID（site_table_id）。
     ⚠️ 列名映射: settle_date→create_time, settle_id→order_settle_id, sale_amount→ledger_amount。
+    CHANGE 2026-05-02 | 用 ref_date（业务日）替代 CURRENT_DATE，沙箱不读「未来」消费。
     返回 (records, total_count)。
     """
     with conn.cursor() as cur:
@@ -163,9 +175,10 @@ def _query_consumption_records(
             FROM app.v_dwd_settlement_head sh
             WHERE sh.member_id = %s
               AND sh.settle_type IN (1, 3)
-              AND sh.create_time >= (CURRENT_DATE - INTERVAL '%s months')
+              AND sh.create_time >= (%s::date - (INTERVAL '1 month' * %s))
+              AND sh.create_time <  (%s::date + INTERVAL '1 day')
             """,
-            (member_id, months),
+            (member_id, ref_date, months, ref_date),
         )
         total_count = cur.fetchone()[0]
 
@@ -208,11 +221,12 @@ def _query_consumption_records(
             ) coaches ON true
             WHERE sh.member_id = %s
               AND sh.settle_type IN (1, 3)
-              AND sh.create_time >= (CURRENT_DATE - INTERVAL '%s months')
+              AND sh.create_time >= (%s::date - (INTERVAL '1 month' * %s))
+              AND sh.create_time <  (%s::date + INTERVAL '1 day')
             ORDER BY sh.create_time DESC
             LIMIT %s
             """,
-            (member_id, months, MAX_CONSUMPTION_RECORDS),
+            (member_id, ref_date, months, ref_date, MAX_CONSUMPTION_RECORDS),
         )
         columns = [desc[0] for desc in cur.description]
         rows = cur.fetchall()
@@ -294,9 +308,10 @@ def _query_balance_summary(conn: Any, member_id: int) -> dict:
     }
 
 
-def _query_visit_info(conn: Any, member_id: int) -> dict:
+def _query_visit_info(conn: Any, member_id: int, ref_date: date) -> dict:
     """从 app.v_dws_member_visit_detail 获取到店数据，推算预计到店日期。
     ⚠️ 列名映射: last_visit_date→MAX(visit_date), avg_visit_interval_days 需从明细计算。
+    CHANGE 2026-05-02 | 仅取 ref_date 及之前的到店明细，days_since 按 ref_date 计算。
     """
     with conn.cursor() as cur:
         # 获取最近到店日期和平均到店间隔
@@ -307,6 +322,7 @@ def _query_visit_info(conn: Any, member_id: int) -> dict:
                        LAG(visit_date) OVER (ORDER BY visit_date) AS prev_visit
                 FROM app.v_dws_member_visit_detail
                 WHERE member_id = %s
+                  AND visit_date <= %s
             )
             SELECT
                 MAX(visit_date) AS last_visit_date,
@@ -314,7 +330,7 @@ def _query_visit_info(conn: Any, member_id: int) -> dict:
             FROM visits
             WHERE prev_visit IS NOT NULL
             """,
-            (member_id,),
+            (member_id, ref_date),
         )
         row = cur.fetchone()
 
@@ -323,8 +339,7 @@ def _query_visit_info(conn: Any, member_id: int) -> dict:
 
     last_visit = row[0]
     avg_interval = row[1]
-    today = date.today()
-    days_since = (today - last_visit).days if isinstance(last_visit, date) else None
+    days_since = (ref_date - last_visit).days if isinstance(last_visit, date) else None
 
     expected = None
     if avg_interval and last_visit:

apps/backend/app/ai/data_fetchers/page_context.py

@@ -352,7 +352,9 @@ def _text_board_finance(
                 "SET LOCAL statement_timeout = %s",
                 (f"{FDW_QUERY_TIMEOUT_SEC * 1000}",),
             )
-            # 简化查询：获取汇总数据
+            # 简化查询：获取汇总数据（CHANGE 2026-05-02 | 用 business_date 替代 CURRENT_DATE）
+            from app.services.runtime_context import as_runtime_today_param
+            _ref_date = as_runtime_today_param(site_id)
             cur.execute(
                 """
                 SELECT
@@ -361,8 +363,10 @@ def _text_board_finance(
                     COALESCE(AVG(items_sum), 0) AS avg_revenue
                 FROM app.v_dwd_settlement_head
                 WHERE settle_type IN (1, 3)
-                  AND settle_date >= (CURRENT_DATE - INTERVAL '1 month')
+                  AND settle_date >= (%s::date - INTERVAL '1 month')
+                  AND settle_date <= %s::date
                 """,
+                (_ref_date, _ref_date),
             )
             row = cur.fetchone()
         etl_conn.commit()
@@ -399,7 +403,9 @@ def _text_board_customer(
                 "SET LOCAL statement_timeout = %s",
                 (f"{FDW_QUERY_TIMEOUT_SEC * 1000}",),
             )
-            # Top 10 客户
+            # Top 10 客户（CHANGE 2026-05-02 | 用 business_date 替代 CURRENT_DATE）
+            from app.services.runtime_context import as_runtime_today_param
+            _ref_date = as_runtime_today_param(site_id)
             cur.execute(
                 """
                 SELECT
@@ -410,11 +416,13 @@ def _text_board_customer(
                     ON dm.member_id = sh.member_id AND dm.scd2_is_current = 1
                 WHERE sh.settle_type IN (1, 3)
                   AND sh.member_id > 0
-                  AND sh.settle_date >= (CURRENT_DATE - INTERVAL '1 month')
+                  AND sh.settle_date >= (%s::date - INTERVAL '1 month')
+                  AND sh.settle_date <= %s::date
                 GROUP BY dm.nickname
                 ORDER BY total_consumption DESC
                 LIMIT 10
                 """,
+                (_ref_date, _ref_date),
             )
             rows = cur.fetchall()
         etl_conn.commit()
@@ -452,6 +460,9 @@ def _text_board_coach(
                 "SET LOCAL statement_timeout = %s",
                 (f"{FDW_QUERY_TIMEOUT_SEC * 1000}",),
             )
+            # CHANGE 2026-05-02 | 用 business_date 替代 CURRENT_DATE
+            from app.services.runtime_context import as_runtime_today_param
+            _ref_date = as_runtime_today_param(site_id)
             cur.execute(
                 """
                 SELECT
@@ -462,11 +473,13 @@ def _text_board_coach(
                 JOIN app.v_dim_assistant da
                     ON da.assistant_id = sl.site_assistant_id
                 WHERE sl.is_delete = 0
-                  AND sl.create_time >= (CURRENT_DATE - INTERVAL '1 month')
+                  AND sl.create_time >= (%s::date - INTERVAL '1 month')
+                  AND sl.create_time <  (%s::date + INTERVAL '1 day')
                 GROUP BY da.nickname
                 ORDER BY service_count DESC
                 LIMIT 10
                 """,
+                (_ref_date, _ref_date),
             )
             rows = cur.fetchall()
         etl_conn.commit()
@@ -590,6 +603,9 @@ def _text_customer_service_records(
                 "SET LOCAL statement_timeout = %s",
                 (f"{FDW_QUERY_TIMEOUT_SEC * 1000}",),
             )
+            # CHANGE 2026-05-02 | 仅取业务日及之前的服务记录，沙箱不读「未来」
+            from app.services.runtime_context import as_runtime_today_param
+            _ref_date = as_runtime_today_param(site_id)
             cur.execute(
                 """
                 SELECT
@@ -599,10 +615,11 @@ def _text_customer_service_records(
                     site_table_id
                 FROM app.v_dwd_assistant_service_log
                 WHERE tenant_member_id = %s AND is_delete = 0
+                  AND create_time < (%s::date + INTERVAL '1 day')
                 ORDER BY create_time DESC
                 LIMIT 10
                 """,
-                (member_id,),
+                (member_id, _ref_date),
             )
             rows = cur.fetchall()
         etl_conn.commit()

apps/backend/app/ai/dispatcher.py

@@ -207,6 +207,25 @@ class AIDispatcher:
 
         # 内存 trigger_job 计数器（DB 迁移完成后改为 INSERT RETURNING id）
         self._next_job_id = 1
+        self._running_tasks: dict[int, asyncio.Task] = {}
+        self._running_task_sites: dict[int, int] = {}
+
+    def _forget_running_task(self, job_id: int) -> None:
+        self._running_tasks.pop(job_id, None)
+        self._running_task_sites.pop(job_id, None)
+
+    def cancel_running(self, site_id: int) -> int:
+        """取消当前进程内指定门店未完成的 AI 调用链。"""
+        cancelled = 0
+        for job_id, task in list(self._running_tasks.items()):
+            if self._running_task_sites.get(job_id) != site_id:
+                continue
+            if task.done():
+                self._forget_running_task(job_id)
+                continue
+            task.cancel()
+            cancelled += 1
+        return cancelled
 
     # ── 统一事件入口 ─────────────────────────────────────
 
@@ -242,7 +261,10 @@ class AIDispatcher:
         self._dedup_set.add(dedup_key)
 
         # 后台异步执行调用链，不阻塞返回
-        asyncio.create_task(self._execute_chain(job_id, event))
+        task = asyncio.create_task(self._execute_chain(job_id, event))
+        self._running_tasks[job_id] = task
+        self._running_task_sites[job_id] = event.site_id
+        task.add_done_callback(lambda _task, _job_id=job_id: self._forget_running_task(_job_id))
         return job_id
 
     # ── 调用链分发 ───────────────────────────────────────
@@ -278,6 +300,10 @@ class AIDispatcher:
             await asyncio.wait_for(handler(event), timeout=chain_timeout)
             logger.info("调用链完成: job_id=%d event_type=%s", job_id, event.event_type)
             _update_trigger_job_status(job_id, "completed", set_finished=True)
+        except asyncio.CancelledError:
+            logger.warning("调用链已取消: job_id=%d event_type=%s", job_id, event.event_type)
+            _update_trigger_job_status(job_id, "cancelled", error_message="业务运行上下文切换取消", set_finished=True)
+            raise
         except asyncio.TimeoutError:
             logger.error("调用链超时: job_id=%d event_type=%s", job_id, event.event_type)
             _update_trigger_job_status(job_id, "failed", error_message="调用链超时", set_finished=True)

apps/backend/app/ai/event_bus.py

@@ -0,0 +1,123 @@
+"""AI 事件广播总线（in-process pub/sub）。
+
+支持按 site_id 订阅的异步事件分发，用于：
+- Phase 1.4：AI 缓存主动失效 / 更新通知 → admin-web、小程序刷新
+- Phase 3.1：AI 告警实时推送（告警发生 / 确认 / 忽略）
+
+设计要点：
+- 仿 TaskExecutor.subscribe/unsubscribe 模式（单进程共享）
+- 每个订阅者独立 asyncio.Queue，互不干扰
+- 订阅必须指定 site_id（全局订阅需显式 site_id=None）
+- publish 异步写入所有订阅者 queue；端点侧通过 get() 消费
+"""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+from dataclasses import dataclass, field
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class AIEvent:
+    """统一事件结构。
+
+    type 示例：
+    - cache_updated     — 新缓存写入
+    - cache_invalidated — 缓存主动失效
+    - alert_created     — 新告警（Phase 3.1）
+    - alert_updated     — 告警状态变更（Phase 3.1）
+    """
+
+    type: str
+    site_id: int | None
+    payload: dict[str, Any] = field(default_factory=dict)
+
+
+class EventBus:
+    """单进程事件广播总线。"""
+
+    def __init__(self) -> None:
+        # {site_id | None: [queue, ...]}  None 表示全局订阅（收所有 site 事件）
+        self._subscribers: dict[int | None, list[asyncio.Queue[AIEvent | None]]] = {}
+        self._lock = asyncio.Lock()
+
+    async def subscribe(self, site_id: int | None) -> asyncio.Queue[AIEvent | None]:
+        """订阅事件流，返回独立 asyncio.Queue。
+
+        site_id=None 表示订阅全部门店事件（admin-web 全局监控用）。
+        site_id=<int> 表示仅订阅该门店事件（小程序或单门店后台）。
+
+        unsubscribe 时需将返回的 queue 作为参数传入。
+        """
+        queue: asyncio.Queue[AIEvent | None] = asyncio.Queue()
+        async with self._lock:
+            self._subscribers.setdefault(site_id, []).append(queue)
+        return queue
+
+    async def unsubscribe(
+        self, site_id: int | None, queue: asyncio.Queue[AIEvent | None]
+    ) -> None:
+        """解除订阅，从订阅者列表移除 queue。"""
+        async with self._lock:
+            subs = self._subscribers.get(site_id, [])
+            try:
+                subs.remove(queue)
+            except ValueError:
+                pass
+            if not subs:
+                self._subscribers.pop(site_id, None)
+
+    def publish(self, event: AIEvent) -> int:
+        """同步 publish 事件，返回送达的订阅者数。
+
+        可从任意线程 / sync 上下文调用（如 dispatcher._write_cache）。
+        内部使用 run_coroutine_threadsafe 线程安全写入 queue。
+        """
+        targets = self._collect_targets(event.site_id)
+        sent = 0
+        for queue in targets:
+            try:
+                # 优先同步调用 put_nowait（最常见：同一 running loop）
+                queue.put_nowait(event)
+                sent += 1
+            except RuntimeError:
+                # 无 running loop 场景极少，跳过
+                logger.debug("publish 无 running loop：跳过 queue")
+        return sent
+
+    def _collect_targets(self, site_id: int | None) -> list[asyncio.Queue[AIEvent | None]]:
+        """收集要推送的订阅者列表：该 site_id 的订阅者 + 全局订阅者。"""
+        targets: list[asyncio.Queue[AIEvent | None]] = []
+        if site_id is not None:
+            targets.extend(self._subscribers.get(site_id, []))
+        targets.extend(self._subscribers.get(None, []))
+        return targets
+
+    async def close_all(self) -> None:
+        """结束时给所有订阅者发哨兵 None，通知连接关闭。"""
+        async with self._lock:
+            all_queues = [q for subs in self._subscribers.values() for q in subs]
+            self._subscribers.clear()
+        for q in all_queues:
+            try:
+                q.put_nowait(None)
+            except Exception:
+                pass
+
+
+# ── 单例 ──────────────────────────────────────────────────
+
+
+_bus: EventBus | None = None
+
+
+def get_event_bus() -> EventBus:
+    """获取全局 EventBus 单例。进程启动时按需创建。"""
+    global _bus
+    if _bus is None:
+        _bus = EventBus()
+    return _bus

apps/backend/app/ai/prompts/app2_finance_prompt.py

@@ -1,145 +1,873 @@
-"""应用 2 财务洞察 Prompt 模板。
+"""应用 2 财务洞察 Prompt 拼装。
 
-构建包含当期和上期收入结构的完整 Prompt，供百炼 API 生成财务洞察。
+cron 每日 10:00 预热触发，对所有筛选组合（时间 × 区域）生成洞察。
+- 数据源：board_service.get_finance_board(time, area, compare=1, site_id)
+- 筛选维度：8 个时间维度 × 9 个区域 = 72 组合
+- 输出字段：insights 数组（seq + title + body）
+- system prompt 在百炼控制台配置
 
-收入字段映射（严格遵守 items_sum 口径）：
-- table_fee = table_charge_money（台费）
-- assistant_pd = assistant_pd_money（陪打费）
-- assistant_cx = assistant_cx_money（超休费）
-- goods = goods_money（商品收入）
-- recharge = 充值 pay_amount settle_type=5（充值收入）
-
-禁止使用 consume_money，统一使用：
-items_sum = table_charge_money + goods_money + assistant_pd_money
-            + assistant_cx_money + electricity_money
+Prompt 中 board_data 字段名会自动翻译为中文（KEY_TRANSLATIONS），
+目的：减少 AI 理解英文变量的成本，生成的洞察正文可读性更强。
 """
 
 from __future__ import annotations
 
 import json
+import logging
+from datetime import datetime
+from typing import Any
 
+from app.services.board_service import get_finance_board, _calc_date_range, _calc_prev_range
 
-def build_prompt(context: dict) -> list[dict]:
-    """构建 App2 财务洞察 Prompt 消息列表。
+logger = logging.getLogger(__name__)
 
-    Args:
-        context: 包含以下字段：
-            - site_id: int，门店 ID
-            - time_dimension: str，时间维度编码
-            - current_data: dict，当期数据
-            - previous_data: dict，上期数据
+# App2 时间维度 → board_service 时间枚举
+DIMENSION_MAP: dict[str, str] = {
+    "this_month": "month",
+    "last_month": "lastMonth",
+    "this_week": "week",
+    "last_week": "lastWeek",
+    "this_quarter": "quarter",
+    "last_quarter": "lastQuarter",
+    "last_3_months": "last_3m",
+    "last_6_months": "last_6m",
+}
 
-    Returns:
-        messages 列表（system + user），供 BailianClient.chat_json 调用
-    """
-    site_id = context.get("site_id", 0)
-    time_dimension = context.get("time_dimension", "")
-    current_data = context.get("current_data", {})
-    previous_data = context.get("previous_data", {})
-
-    system_content = _build_system_content(
-        site_id=site_id,
-        time_dimension=time_dimension,
-        current_data=current_data,
-        previous_data=previous_data,
-    )
-
-    user_content = (
-        f"请根据以上数据，为门店 {site_id} 生成 {_dimension_label(time_dimension)} 的财务洞察分析。"
-        "以 JSON 格式返回，包含 insights 数组，每项含 seq（序号）、title（标题）、body（正文）。"
-    )
-
-    return [
-        {"role": "system", "content": json.dumps(system_content, ensure_ascii=False)},
-        {"role": "user", "content": user_content},
-    ]
-
-
-def _build_system_content(
-    *,
-    site_id: int,
-    time_dimension: str,
-    current_data: dict,
-    previous_data: dict,
-) -> dict:
-    """构建 system prompt JSON 结构。"""
-    return {
-        "task": (
-            "你是台球门店的财务分析 AI 助手。"
-            "根据提供的当期和上期经营数据，生成结构化的财务洞察。"
-            "分析维度包括：收入结构变化、各收入项占比、环比趋势、异常波动。"
-            "输出 JSON 格式：{\"insights\": [{\"seq\": 1, \"title\": \"...\", \"body\": \"...\"}]}"
-        ),
-        "data": {
-            "site_id": site_id,
-            "time_dimension": time_dimension,
-            "time_dimension_label": _dimension_label(time_dimension),
-            "current_period": _build_period_data(current_data),
-            "previous_period": _build_period_data(previous_data),
-        },
-        "reference": {
-            "field_mapping": {
-                "items_sum": (
-                    "table_charge_money + goods_money + assistant_pd_money"
-                    " + assistant_cx_money + electricity_money"
-                ),
-                "table_fee": "table_charge_money（台费收入）",
-                "assistant_pd": "assistant_pd_money（陪打费）",
-                "assistant_cx": "assistant_cx_money（超休费）",
-                "goods": "goods_money（商品收入）",
-                "recharge": "充值 pay_amount（settle_type=5，充值收入）",
-                "electricity": "electricity_money（电费，当前未启用，全为 0）",
-            },
-            "rules": [
-                "统一使用 items_sum 口径计算营收总额",
-                "助教费用必须拆分为 assistant_pd_money（陪打）和 assistant_cx_money（超休）",
-                "支付渠道恒等式：balance_amount = recharge_card_amount + gift_card_amount",
-                "金额单位：元（CNY），保留两位小数",
-            ],
-        },
-    }
-
-
-def _build_period_data(data: dict) -> dict:
-    """构建单期数据结构，确保字段名遵守 items_sum 口径。"""
-    return {
-        # 收入结构（items_sum 口径）
-        "table_charge_money": data.get("table_charge_money", 0),
-        "goods_money": data.get("goods_money", 0),
-        "assistant_pd_money": data.get("assistant_pd_money", 0),
-        "assistant_cx_money": data.get("assistant_cx_money", 0),
-        "electricity_money": data.get("electricity_money", 0),
-        # 充值收入
-        "recharge_income": data.get("recharge_income", 0),
-        # 储值资产
-        "balance_pay": data.get("balance_pay", 0),
-        "recharge_card_pay": data.get("recharge_card_pay", 0),
-        "gift_card_pay": data.get("gift_card_pay", 0),
-        # 费用汇总
-        "discount_amount": data.get("discount_amount", 0),
-        "adjust_amount": data.get("adjust_amount", 0),
-        # 平台结算
-        "platform_settlement_amount": data.get("platform_settlement_amount", 0),
-        "groupbuy_pay_amount": data.get("groupbuy_pay_amount", 0),
-        # 汇总
-        "order_count": data.get("order_count", 0),
-        "member_count": data.get("member_count", 0),
-    }
-
-
-# 时间维度编码 → 中文标签
-_DIMENSION_LABELS: dict[str, str] = {
+DIMENSION_LABELS: dict[str, str] = {
     "this_month": "本月",
     "last_month": "上月",
     "this_week": "本周",
     "last_week": "上周",
-    "last_3_months": "近三个月",
     "this_quarter": "本季度",
     "last_quarter": "上季度",
-    "last_6_months": "近六个月",
+    "last_3_months": "近三个月（不含本月）",
+    "last_6_months": "近六个月（不含本月）",
+}
+
+# 区域枚举与中文标签（与 miniprogram/board-finance.ts areaOptions 对齐）
+AREA_OPTIONS: tuple[str, ...] = (
+    "all", "hall", "hallA", "hallB", "hallC",
+    "vip", "snooker", "mahjong", "ktv",
+)
+
+AREA_LABELS: dict[str, str] = {
+    "all": "全部区域",
+    "hall": "大厅",
+    "hallA": "A区",
+    "hallB": "B区",
+    "hallC": "C区",
+    "vip": "台球包厢",
+    "snooker": "斯诺克",
+    "mahjong": "麻将房",
+    "ktv": "团建房",
+}
+
+# 业务字段 → 中文名。覆盖 board_service 返回的所有层级字段。
+# 只做键名翻译，不改变值与结构；未命中的键原样保留。
+KEY_TRANSLATIONS: dict[str, str] = {
+    # 顶层板块
+    "overview": "经营一览",
+    "recharge": "预收资产",
+    "revenue": "应计收入确认",
+    "cashflow": "现金流入",
+    "expense": "现金流出",
+    "coach_analysis": "助教分析",
+
+    # 经营一览
+    "occurrence": "发生额",
+    "discount": "总优惠",
+    "discount_rate": "优惠率",
+    "confirmed_revenue": "成交收入",
+    "cash_in": "现金流入",
+    "cash_out": "现金流出",
+    "cash_balance": "现金结余",
+    "balance_rate": "结余率",
+
+    # 预收资产
+    "actual_income": "储值卡充值实收",
+    "first_charge": "首充",
+    "renew_charge": "续费",
+    "consumed": "储值卡消耗",
+    "card_balance": "储值卡总余额",
+    "all_card_balance": "全类别卡余额合计",
+    "gift_rows": "赠送卡矩阵",
+    "liquor": "酒水卡",
+    "table_fee": "台费卡",
+    "voucher": "抵用券",
+
+    # 应计收入确认
+    "total_occurrence": "发生额合计",
+    "discount_total": "优惠合计",
+    "confirmed_total": "确认收入合计",
+    "structure_rows": "收入结构",
+    "price_items": "价目明细",
+    "discount_items": "优惠明细",
+    "channel_items": "渠道明细",
+    "booked": "入账金额",
+    "booked_compare": "入账环比",
+
+    # 现金流入/流出
+    "consume_items": "消费收款项",
+    "recharge_items": "充值收款项",
+    "operation_items": "运营支出",
+    "fixed_items": "固定支出",
+    "coach_items": "助教支出",
+    "platform_items": "平台支出",
+
+    # 助教分析
+    "basic": "基础助教",
+    "incentive": "激励助教",
+    "total_pay": "合计薪酬",
+    "total_share": "合计分成",
+    "avg_hourly": "平均时薪",
+    "level": "级别",
+    "pay": "薪酬",
+    "share": "分成",
+    "hourly": "时薪",
+    "rows": "明细",
+
+    # 通用元素
+    "label": "名称",
+    "amount": "金额",
+    "desc": "说明",
+    "total": "合计",
+    "value": "数值",
+    "compare": "环比",
+    "id": "编号",
+
+    # 环比后缀（小程序约定）
+    "occurrence_compare": "发生额环比",
+    "occurrence_down": "发生额是否下降",
+    "occurrence_flat": "发生额是否持平",
+    "discount_compare": "总优惠环比",
+    "discount_down": "总优惠是否下降",
+    "discount_flat": "总优惠是否持平",
+    "discount_rate_compare": "优惠率环比",
+    "discount_rate_down": "优惠率是否下降",
+    "discount_rate_flat": "优惠率是否持平",
+    "confirmed_revenue_compare": "成交收入环比",
+    "confirmed_revenue_down": "成交收入是否下降",
+    "confirmed_revenue_flat": "成交收入是否持平",
+    "cash_in_compare": "现金流入环比",
+    "cash_in_down": "现金流入是否下降",
+    "cash_in_flat": "现金流入是否持平",
+    "cash_out_compare": "现金流出环比",
+    "cash_out_down": "现金流出是否下降",
+    "cash_out_flat": "现金流出是否持平",
+    "cash_balance_compare": "现金结余环比",
+    "cash_balance_down": "现金结余是否下降",
+    "cash_balance_flat": "现金结余是否持平",
+    "balance_rate_compare": "结余率环比",
+    "balance_rate_down": "结余率是否下降",
+    "balance_rate_flat": "结余率是否持平",
+    "actual_income_compare": "储值卡充值实收环比",
+    "actual_income_down": "储值卡充值实收是否下降",
+    "first_charge_compare": "首充环比",
+    "first_charge_down": "首充是否下降",
+    "renew_charge_compare": "续费环比",
+    "renew_charge_down": "续费是否下降",
+    "consumed_compare": "储值卡消耗环比",
+    "consumed_down": "储值卡消耗是否下降",
+    "card_balance_compare": "储值卡总余额环比",
+    "card_balance_down": "储值卡总余额是否下降",
+    "all_card_balance_compare": "全类别卡余额合计环比",
+    "all_card_balance_down": "全类别卡余额合计是否下降",
+    "total_compare": "合计环比",
+    "total_down": "合计是否下降",
+    "total_flat": "合计是否持平",
+    "total_pay_compare": "合计薪酬环比",
+    "total_pay_down": "合计薪酬是否下降",
+    "total_share_compare": "合计分成环比",
+    "total_share_down": "合计分成是否下降",
+    "avg_hourly_compare": "平均时薪环比",
+    "avg_hourly_flat": "平均时薪是否持平",
+    "pay_compare": "薪酬环比",
+    "pay_down": "薪酬是否下降",
+    "share_compare": "分成环比",
+    "share_down": "分成是否下降",
+    "hourly_compare": "时薪环比",
+    "hourly_flat": "时薪是否持平",
+
+    # 赠送卡矩阵
+    "wine": "酒水",
+    "table": "台费",
+    "coupon": "抵用券",
+
+    # 元数据
+    "down": "是否下降",
+    "flat": "是否持平",
 }
 
 
-def _dimension_label(dimension: str) -> str:
-    """将时间维度编码转为中文标签。"""
-    return _DIMENSION_LABELS.get(dimension, dimension)
+# 裁剪时丢弃的"冗余"字段：_down / _flat 布尔元数据（*_compare 字符串已携带符号）
+_DROP_SUFFIX = ("_down", "_flat")
+
+# 行级明细字段：展示用，AI 洞察不需要
+_DROP_DETAIL_KEYS = {
+    "structure_rows", "price_items", "channel_items", "gift_rows",
+    "discount_items",   # 2026-04-22：升顶层"优惠构成"后，明细源从 revenue 里 drop 去重
+}
+
+
+def _is_drop_key(k: str) -> bool:
+    if not isinstance(k, str):
+        return False
+    if k in _DROP_DETAIL_KEYS:
+        return True
+    return k.endswith(_DROP_SUFFIX)
+
+
+def _slim(data: Any) -> Any:
+    """递归裁剪：drop 明细 + _down/_flat + None 值。"""
+    if isinstance(data, dict):
+        out = {}
+        for k, v in data.items():
+            if _is_drop_key(k):
+                continue
+            slim_v = _slim(v)
+            if slim_v is None:
+                continue
+            out[k] = slim_v
+        return out if out else None
+    if isinstance(data, list):
+        return [_slim(item) for item in data]
+    return data
+
+
+def _pct(numerator: float, denominator: float) -> float:
+    """百分比（小数），分母 0 返回 0。保留 4 位便于 AI 读取。"""
+    if not denominator:
+        return 0.0
+    return round(numerator / denominator, 4)
+
+
+# 日粒度异常检测参数
+_ANOMALY_MIN_DAYS = 7           # 少于 7 天样本不检测（噪声太大）
+_ANOMALY_DEVIATION = 0.4        # 偏离"同星期均值" > 40% 标记为异常（2026-04-22 改为同星期基线）
+_ANOMALY_MAX_ITEMS = 10         # 最多保留 10 条（按 |偏离度| 降序截断，防 prompt 膨胀）
+_ANOMALY_MIN_SAME_WEEKDAY = 2   # 同星期至少 2 天样本才可作基线；不足时回退到整体均值
+
+# 星期中文映射（0=Monday）
+_WEEKDAY_ZH = ("周一", "周二", "周三", "周四", "周五", "周六", "周日")
+
+# 行业基线常量（综合商业球房）
+# 2026-04-22：移除各类警戒线/健康区间（各球房定位/地段/业态差异大，不宜一刀切）。
+# 仅保留"周中客流规律"这类行业普适的时间分布特征。
+INDUSTRY_BASELINES: dict[str, Any] = {
+    "周中客流规律": "周五至周日旺季 / 周一最淡 / 周二至周四逐步回升",
+}
+
+
+def _fetch_daily_series(
+    site_id: int, start_date: str, end_date: str,
+) -> list[tuple] | None:
+    """查 [start, end] 日粒度财务流水，一次查完供多个分析函数复用。
+
+    返回字段顺序：(stat_date, gross, cash_in, order_count, member_order_count, confirmed)
+    过滤全 0 停业日；样本不足时返回 None。
+    """
+    from app.services.fdw_queries import _fdw_context
+    from app.database import get_connection
+
+    try:
+        conn = get_connection()
+    except Exception:
+        logger.debug("日粒度查询连接失败", exc_info=True)
+        return None
+
+    try:
+        with _fdw_context(conn, site_id) as cur:
+            cur.execute(
+                """
+                SELECT stat_date,
+                       COALESCE(gross_amount, 0)           AS gross,
+                       COALESCE(cash_inflow_total, 0)      AS cash_in,
+                       COALESCE(order_count, 0)            AS order_count,
+                       COALESCE(member_order_count, 0)     AS member_order_count,
+                       COALESCE(confirmed_income, 0)       AS confirmed
+                FROM app.v_dws_finance_daily_summary
+                WHERE stat_date >= %s::date
+                  AND stat_date <= %s::date
+                ORDER BY stat_date
+                """,
+                (start_date, end_date),
+            )
+            rows = cur.fetchall()
+    except Exception:
+        logger.debug("日粒度数据查询失败: site_id=%s", site_id, exc_info=True)
+        return None
+    finally:
+        try:
+            conn.close()
+        except Exception:
+            pass
+
+    active = [
+        (r[0], float(r[1]), float(r[2]), int(r[3] or 0), int(r[4] or 0), float(r[5] or 0))
+        for r in rows
+        if float(r[1] or 0) > 0 or float(r[2] or 0) > 0
+    ]
+    return active if active else None
+
+
+_WEEKDAY_MIN_DAYS = 14  # 月初场景：样本 < 14 天时，每个星期最多 1-2 天，"日均"接近单日值，不注入以免 AI 被误导
+
+
+def _aggregate_by_weekday(series: list[tuple] | None) -> dict | None:
+    """按星期聚合 7 段日均值（发生额/现金流入/订单数），供 AI 观察周中规律。
+
+    要求至少 14 天样本（保证每个星期至少有 2 天），否则返回 None；
+    防止月初场景下单日值被包装成"日均"迷惑 AI 做周规律判断。
+    """
+    if not series or len(series) < _WEEKDAY_MIN_DAYS:
+        return None
+    from collections import defaultdict
+    buckets: dict[int, list[tuple]] = defaultdict(list)
+    for row in series:
+        buckets[row[0].weekday()].append(row)
+    out: dict[str, dict] = {}
+    for wd in range(7):
+        rows = buckets.get(wd) or []
+        if not rows:
+            continue
+        n = len(rows)
+        out[_WEEKDAY_ZH[wd]] = {
+            "日均发生额": round(sum(r[1] for r in rows) / n, 2),
+            "日均现金流入": round(sum(r[2] for r in rows) / n, 2),
+            "日均订单数": round(sum(r[3] for r in rows) / n, 1),
+            "营业日数": n,
+        }
+    return out or None
+
+
+def _build_unit_economics(
+    series: list[tuple] | None,
+    prev_series: list[tuple] | None = None,
+) -> dict | None:
+    """单位经济派生：客单价 / 日均订单数 / 会员订单占比 / 散客订单占比。
+
+    口径：全期汇总后再算（避免日均 avg 失真）。
+    客单价取两口径：
+    - 按成交收入（去除优惠的真实收入单价） — 反映真实收入能力
+    - 按发生额（含优惠的账单均值） — 反映顾客端认知的单次消费量级
+    若 prev_series 可用，则附加 _环比 字段避免 AI 推测幻觉。
+    """
+    if not series:
+        return None
+    total_orders = sum(r[3] for r in series)
+    if total_orders <= 0:
+        return None
+    total_member_orders = sum(r[4] for r in series)
+    total_confirmed = sum(r[5] for r in series)
+    total_gross = sum(r[1] for r in series)
+    days = len(series)
+
+    price_confirmed = total_confirmed / total_orders
+    price_gross = total_gross / total_orders
+    member_share = total_member_orders / total_orders
+    daily_orders = total_orders / days
+
+    out: dict[str, Any] = {
+        "总订单数": total_orders,
+        "日均订单数": round(daily_orders, 1),
+        "客单价_按成交收入": round(price_confirmed, 2),
+        "客单价_按发生额": round(price_gross, 2),
+        "会员订单数": total_member_orders,
+        "会员订单占比": round(member_share, 4),
+        "散客订单数": total_orders - total_member_orders,
+        "散客订单占比": round((total_orders - total_member_orders) / total_orders, 4),
+    }
+
+    if prev_series:
+        prev_orders = sum(r[3] for r in prev_series)
+        if prev_orders > 0:
+            prev_days = len(prev_series)
+            prev_confirmed = sum(r[5] for r in prev_series)
+            prev_gross = sum(r[1] for r in prev_series)
+            prev_member = sum(r[4] for r in prev_series)
+            # 月初场景：上期样本 < 5 天时客单价环比噪声极大（单日波动主导），加标注供 AI 降权引用
+            low_sample = prev_days < 5
+
+            def _pct_change(cur: float, prev: float) -> str:
+                if prev <= 0:
+                    return "无上期数据"
+                value = f"{(cur - prev) / prev * 100:+.1f}%"
+                return f"{value}（上期仅 {prev_days} 天，样本不足仅供参考）" if low_sample else value
+
+            out["客单价_按成交收入_环比"] = _pct_change(price_confirmed, prev_confirmed / prev_orders)
+            out["客单价_按发生额_环比"] = _pct_change(price_gross, prev_gross / prev_orders)
+            out["日均订单数_环比"] = _pct_change(daily_orders, prev_orders / prev_days)
+            out["会员订单占比_环比"] = _pct_change(member_share, prev_member / prev_orders)
+    return out
+
+
+def _detect_anomaly_days(
+    site_id: int, start_date: str, end_date: str,
+    series: list[tuple] | None = None,
+) -> list[dict] | None:
+    """扫描日粒度财务数据，标记偏离同星期均值 > 40% 的异常日。
+
+    series 可由调用方传入复用，避免重复查 DB。
+    """
+    if series is None:
+        series = _fetch_daily_series(site_id, start_date, end_date)
+    if not series or len(series) < _ANOMALY_MIN_DAYS:
+        return None
+    active = series
+
+    # 2026-04-22 改进：按"同星期均值"做基线，比"期均"更贴近业态（周一淡/周末旺）
+    # 同星期样本 < _ANOMALY_MIN_SAME_WEEKDAY 天时回退到整体均值
+    from collections import defaultdict
+
+    def _scan(idx: int, label: str) -> list[dict]:
+        vals = [row[idx] for row in active]
+        global_mean = sum(vals) / len(vals)
+        if global_mean <= 0:
+            return []
+
+        # 按 weekday 分组统计均值
+        by_weekday: dict[int, list[float]] = defaultdict(list)
+        for d, *metrics in active:
+            by_weekday[d.weekday()].append(metrics[idx - 1])
+        weekday_mean: dict[int, float] = {
+            wd: (sum(xs) / len(xs)) for wd, xs in by_weekday.items()
+        }
+
+        flagged: list[dict] = []
+        for d, *metrics in active:
+            v = metrics[idx - 1]
+            wd = d.weekday()
+            same_count = len(by_weekday.get(wd, []))
+            # 基线选择：同星期样本 >= 2 用同星期均值，否则用整体均值
+            if same_count >= _ANOMALY_MIN_SAME_WEEKDAY and weekday_mean[wd] > 0:
+                base = weekday_mean[wd]
+                base_label = f"同{_WEEKDAY_ZH[wd]}均值"
+            else:
+                base = global_mean
+                base_label = "期均"
+
+            deviation = (v - base) / base
+            if abs(deviation) >= _ANOMALY_DEVIATION:
+                weekday_zh = _WEEKDAY_ZH[wd]
+                flagged.append({
+                    "日期": f"{d} {weekday_zh}",
+                    "指标": label,
+                    "当日": round(v, 2),
+                    "基线": round(base, 2),
+                    "基线类型": base_label,
+                    "偏离": f"{deviation * 100:+.1f}%",
+                    "_abs_dev": abs(deviation),
+                })
+        return flagged
+
+    candidates: list[dict] = _scan(1, "发生额") + _scan(2, "现金流入")
+    if not candidates:
+        return None
+    # 按绝对偏离排序，取 top N，去掉排序用辅助键
+    candidates.sort(key=lambda x: x["_abs_dev"], reverse=True)
+    out = []
+    for c in candidates[:_ANOMALY_MAX_ITEMS]:
+        c.pop("_abs_dev", None)
+        out.append(c)
+    return out
+
+
+def _fetch_card_balance_opening(site_id: int, start_date: str) -> float | None:
+    """取 start_date 前一日的储值卡总余额（作为本期期初余额）。
+
+    数据源：etl 库 app.v_dws_finance_recharge_summary（每日快照，total_card_balance 字段）。
+    若前一日无数据（门店刚开业 / 数据缺失），返回 None。
+    """
+    from app.services.fdw_queries import _fdw_context
+    from app.database import get_connection
+
+    try:
+        conn = get_connection()
+    except Exception:
+        logger.debug("期初余额查询连接失败", exc_info=True)
+        return None
+
+    try:
+        with _fdw_context(conn, site_id) as cur:
+            cur.execute(
+                """
+                SELECT total_card_balance
+                FROM app.v_dws_finance_recharge_summary
+                WHERE stat_date < %s::date
+                ORDER BY stat_date DESC
+                LIMIT 1
+                """,
+                (start_date,),
+            )
+            row = cur.fetchone()
+    except Exception:
+        logger.debug("期初余额查询失败: site_id=%s", site_id, exc_info=True)
+        return None
+    finally:
+        try:
+            conn.close()
+        except Exception:
+            pass
+
+    if not row or row[0] is None:
+        return None
+    return float(row[0])
+
+
+def _aggregate_expense(expense: dict | None) -> dict | None:
+    """从 expense 四类明细聚合出顶层金额，便于 AI 直接看四大块支出占比。"""
+    if not isinstance(expense, dict):
+        return None
+    def _sum(key: str) -> float:
+        items = expense.get(key) or []
+        if not isinstance(items, list):
+            return 0.0
+        return round(sum(float(x.get("amount", 0) or 0) for x in items if isinstance(x, dict)), 2)
+    total = float(expense.get("total", 0) or 0)
+    if total <= 0:
+        return None  # 全 0 数据对 AI 无意义，直接丢
+    return {
+        "合计": round(total, 2),
+        "合计环比": expense.get("total_compare") or "持平",
+        "运营支出": _sum("operation_items"),
+        "固定支出": _sum("fixed_items"),
+        "助教支出": _sum("coach_items"),
+        "平台支出": _sum("platform_items"),
+    }
+
+
+def _build_discount_kpi(revenue: dict | None, overview: dict | None) -> dict | None:
+    """把优惠拆成顶层 KPI + 派生指标（占比、贡献率）。
+
+    AI 数据挖掘视角：
+    - 按金额排序展示，top1 一眼看出来
+    - 每项带 amount / compare / share（占总优惠比）
+    - 整体带优惠率（discount / occurrence）便于判断利润侵蚀程度
+    """
+    if not isinstance(revenue, dict):
+        return None
+    items = revenue.get("discount_items") or []
+    if not isinstance(items, list) or not items:
+        return None
+
+    total = round(sum(float(x.get("amount", 0) or 0) for x in items if isinstance(x, dict)), 2)
+    breakdown = []
+    for it in items:
+        if not isinstance(it, dict):
+            continue
+        amt = float(it.get("amount", 0) or 0)
+        row: dict[str, Any] = {
+            "名称": it.get("label"),
+            "金额": round(amt, 2),
+            "占总优惠": _pct(amt, total),
+        }
+        if it.get("compare"):
+            row["环比"] = it["compare"]
+        breakdown.append(row)
+    # 按金额从大到小排序 → AI 阅读顺序 = 重要度顺序
+    breakdown.sort(key=lambda r: float(r.get("金额") or 0), reverse=True)
+
+    overview = overview or {}
+    occurrence = float(overview.get("occurrence", 0) or 0)
+
+    kpi: dict[str, Any] = {
+        "总优惠": total,
+        "优惠率": _pct(total, occurrence),   # 0.3796 表示 37.96%
+        "占比排序": breakdown,
+    }
+    if breakdown:
+        top = breakdown[0]
+        kpi["最大优惠来源"] = f"{top.get('名称')}（金额 {top.get('金额')} 元，占总优惠 {int(float(top.get('占总优惠', 0))*100)}%）"
+    return kpi
+
+
+def _build_cashflow_kpi(cashflow: dict | None) -> dict | None:
+    """消费收款拆三档（纸币/线上/团购）+ 充值到账，给 AI 直接看资金来源结构。"""
+    if not isinstance(cashflow, dict):
+        return None
+    consume = cashflow.get("consume_items") or []
+    recharge = cashflow.get("recharge_items") or []
+    total = float(cashflow.get("total", 0) or 0)
+    if total <= 0:
+        return None
+
+    consume_map = {}
+    for it in consume:
+        if not isinstance(it, dict):
+            continue
+        consume_map[it.get("label")] = {
+            "金额": round(float(it.get("amount", 0) or 0), 2),
+            "环比": it.get("compare") or "持平",
+        }
+
+    recharge_total = round(sum(float(x.get("amount", 0) or 0) for x in recharge if isinstance(x, dict)), 2)
+    consume_total = round(sum(float(v.get("金额", 0) or 0) for v in consume_map.values()), 2)
+
+    return {
+        "合计": round(total, 2),
+        "合计环比": cashflow.get("total_compare") or "持平",
+        "消费收款合计": consume_total,
+        "消费收款占比": _pct(consume_total, total),
+        "充值收款合计": recharge_total,
+        "充值收款占比": _pct(recharge_total, total),
+        "按渠道": consume_map,
+    }
+
+
+def _build_coach_kpi(coach: dict | None) -> dict | None:
+    """助教成本压缩：只保留两档的合计薪酬+合计分成+平均时薪+3 级别薪酬分布。"""
+    if not isinstance(coach, dict):
+        return None
+    def _slim_tier(t: dict | None) -> dict | None:
+        if not isinstance(t, dict):
+            return None
+        rows = t.get("rows") or []
+        # 只保留级别-薪酬-时薪 3 字段，作为分布快照
+        tier_dist = [
+            {"级别": r.get("level"), "薪酬": r.get("pay"), "时薪": r.get("hourly")}
+            for r in rows if isinstance(r, dict)
+        ]
+        total_pay = float(t.get("total_pay", 0) or 0)
+        if total_pay <= 0:
+            return None
+        return {
+            "合计薪酬": round(total_pay, 2),
+            "合计薪酬环比": t.get("total_pay_compare") or "持平",
+            "合计分成": round(float(t.get("total_share", 0) or 0), 2),
+            "平均时薪": round(float(t.get("avg_hourly", 0) or 0), 2),
+            "各级别分布": tier_dist,
+        }
+    basic = _slim_tier(coach.get("basic"))
+    incentive = _slim_tier(coach.get("incentive"))
+    if not basic and not incentive:
+        return None
+    out: dict[str, Any] = {}
+    if basic:
+        out["基础助教"] = basic
+    if incentive:
+        out["激励助教"] = incentive
+    # 派生：人力成本占收入比（需要收入传进来，这里只给基础值）
+    total_pay = (basic or {}).get("合计薪酬", 0) + (incentive or {}).get("合计薪酬", 0)
+    if total_pay > 0:
+        out["人力薪酬合计"] = round(total_pay, 2)
+    return out
+
+
+def _build_derived_ratios(overview: dict | None, cashflow_kpi: dict | None,
+                         coach_kpi: dict | None, discount_kpi: dict | None) -> dict:
+    """数据挖掘视角：派生关键比率，让 AI 不用自己算。
+
+    - 储值卡贡献率：充值到账 / 总现金流入
+    - 人力成本占收入比：助教薪酬合计 / 成交收入
+    - 优惠侵蚀率：总优惠 / 发生额
+    - 现金结余率：现金结余 / 现金流入
+    """
+    ov = overview or {}
+    confirmed = float(ov.get("confirmed_revenue", 0) or 0)
+    occurrence = float(ov.get("occurrence", 0) or 0)
+    cash_in = float(ov.get("cash_in", 0) or 0)
+    cash_balance = float(ov.get("cash_balance", 0) or 0)
+    total_pay = (coach_kpi or {}).get("人力薪酬合计", 0)
+    recharge_in = (cashflow_kpi or {}).get("充值收款合计", 0)
+    discount_total = (discount_kpi or {}).get("总优惠", 0)
+
+    out: dict[str, Any] = {}
+    if confirmed > 0 and total_pay:
+        out["人力成本占成交收入比"] = _pct(total_pay, confirmed)
+    if cash_in > 0 and recharge_in:
+        out["储值卡充值占现金流入比"] = _pct(recharge_in, cash_in)
+    if occurrence > 0 and discount_total:
+        out["优惠侵蚀率"] = _pct(discount_total, occurrence)
+    if cash_in > 0:
+        out["现金结余率"] = _pct(cash_balance, cash_in)
+    return out
+
+
+# 2026-04-22：异常检测由 AI 侧自行判断，后端只提供客观 KPI（不给规则结论）
+
+
+def _translate_keys(data: Any) -> Any:
+    """递归翻译 dict/list 中所有键为中文；值保持不变。
+
+    - dict: 键命中 KEY_TRANSLATIONS 则替换，未命中保留原键
+    - list: 逐项递归
+    - 其他类型（str/int/float/bool/None）原样返回
+    """
+    if isinstance(data, dict):
+        return {
+            KEY_TRANSLATIONS.get(k, k): _translate_keys(v)
+            for k, v in data.items()
+        }
+    if isinstance(data, list):
+        return [_translate_keys(item) for item in data]
+    return data
+
+
+async def build_prompt(
+    context: dict,
+    cache_svc: Any | None = None,  # 兼容统一签名，App2 不用
+) -> str:
+    """构建 App2 prompt 字符串。
+
+    Args:
+        context: site_id, time_dimension, area（可选，默认 all）
+
+    Returns:
+        JSON 序列化后的 prompt 字符串，所有 board 数据字段已翻译为中文。
+    """
+    site_id = context["site_id"]
+    time_dimension = context["time_dimension"]
+    area = context.get("area", "all")
+
+    board_time = DIMENSION_MAP.get(time_dimension)
+    if not board_time:
+        raise ValueError(f"App2 不支持的时间维度: {time_dimension}")
+
+    if area not in AREA_LABELS:
+        raise ValueError(f"App2 不支持的区域: {area}")
+
+    try:
+        board_data = await get_finance_board(
+            time=board_time, area=area, compare=1, site_id=site_id,
+        )
+    except Exception:
+        logger.warning(
+            "App2 财务看板查询失败: site_id=%s dimension=%s area=%s",
+            site_id, time_dimension, area, exc_info=True,
+        )
+        board_data = {}
+
+    # 2026-04-22 数据挖掘视角 prompt 结构化：
+    # - 优惠/现金流/助教/支出 四大领域分别派生 KPI（带占比/排序/派生指标）
+    # - 异常检测：规则法标注 AI 必看异常点
+    # - 派生比率：人力成本占比/优惠侵蚀率/储值卡贡献率 等不用 AI 再算
+    # - 原始财务数据经 _slim 裁剪后作为"原始指标"补充，避免 AI 失去追溯能力
+    overview = board_data.get("overview") if isinstance(board_data, dict) else None
+    revenue = board_data.get("revenue") if isinstance(board_data, dict) else None
+    cashflow = board_data.get("cashflow") if isinstance(board_data, dict) else None
+    expense = board_data.get("expense") if isinstance(board_data, dict) else None
+    coach = board_data.get("coach_analysis") if isinstance(board_data, dict) else None
+
+    discount_kpi = _build_discount_kpi(revenue, overview)
+    cashflow_kpi = _build_cashflow_kpi(cashflow)
+    expense_kpi = _aggregate_expense(expense)
+    coach_kpi = _build_coach_kpi(coach)
+    ratios = _build_derived_ratios(overview, cashflow_kpi, coach_kpi, discount_kpi)
+
+    # 原始数据：slim 后再翻译，供 AI 追溯细节
+    slim_data = _slim(board_data) or {}
+    raw_cn = _translate_keys(slim_data)
+
+    # 对比口径说明：当期/对比期均为"同天数对齐"，避免 AI 把环比误读为"当期部分 vs 上期整月"
+    compare_caliber: dict[str, Any] | None = None
+    try:
+        from app.services.runtime_context import get_runtime_context
+
+        runtime_ctx = get_runtime_context(site_id)
+        cur_start, cur_end = _calc_date_range(board_time, ref_date=runtime_ctx.business_date)
+        prev_start, prev_end = _calc_prev_range(board_time, cur_start, cur_end)
+        cur_days = (cur_end - cur_start).days + 1
+        prev_days = (prev_end - prev_start).days + 1
+        compare_caliber = {
+            "当期范围": f"{cur_start} ~ {cur_end}（{cur_days} 天）",
+            "对比期范围": f"{prev_start} ~ {prev_end}（{prev_days} 天）",
+            "对齐方式": "上期同天数对齐（非整月/整周对比）",
+            "说明": "所有 _环比 / _compare 字段均按上表口径计算；月中调用时对比期会自动截断到与当期相同天数",
+        }
+    except Exception:
+        logger.debug("对比口径字段生成失败（不影响主流程）", exc_info=True)
+
+    payload: dict[str, Any] = {
+        "当前时间": get_runtime_context(site_id).business_now.strftime("%Y-%m-%d %H:%M"),
+        "门店编号": site_id,
+        "时间维度": DIMENSION_LABELS.get(time_dimension, time_dimension),
+        "区域": AREA_LABELS.get(area, area),
+        # 0. 对比口径：让 AI 正确解读环比字段
+        **({"对比口径": compare_caliber} if compare_caliber else {}),
+        # 1. 核心 KPI：AI 洞察首要依据
+        "核心KPI": {
+            "发生额": float(overview.get("occurrence", 0)) if overview else 0,
+            "发生额环比": (overview or {}).get("occurrence_compare") or "持平",
+            "成交收入": float(overview.get("confirmed_revenue", 0)) if overview else 0,
+            "成交收入环比": (overview or {}).get("confirmed_revenue_compare") or "持平",
+            "现金流入": (overview or {}).get("cash_in"),
+            "现金流入环比": (overview or {}).get("cash_in_compare") or "持平",
+            "现金结余": (overview or {}).get("cash_balance"),
+            "现金结余环比": (overview or {}).get("cash_balance_compare") or "持平",
+        },
+        # 2. 派生比率：不用 AI 再算
+        "派生比率": ratios,
+    }
+    # 3. 优惠构成（带排序/占比/环比/最大来源提示）
+    if discount_kpi:
+        payload["优惠构成"] = discount_kpi
+    # 4. 现金流入来源分布
+    if cashflow_kpi:
+        payload["现金流入来源"] = cashflow_kpi
+    # 5. 支出概况（聚合到四大类，total=0 则不给 AI）
+    if expense_kpi:
+        payload["支出概况"] = expense_kpi
+    # 6. 助教成本画像
+    if coach_kpi:
+        payload["助教成本"] = coach_kpi
+    # 7. 储值卡余额变化：期初 + 期末 + 充值 + 消耗 + 其他调整（揭示"充值-消耗≠余额变化"的差异）
+    #    避免 AI 在只看当期充值/消耗时对"余额为何涨"的矛盾自圆其说
+    if area == "all" and isinstance(recharge := board_data.get("recharge"), dict):
+        try:
+            start_date_obj, _end = _calc_date_range(board_time)
+            opening = _fetch_card_balance_opening(site_id, str(start_date_obj))
+            closing = float(recharge.get("card_balance") or 0)
+            period_recharge = float(recharge.get("actual_income") or 0)
+            period_consume = float(recharge.get("consumed") or 0)
+            if opening is not None and (opening > 0 or closing > 0):
+                diff = closing - opening
+                other_adj = round(diff - (period_recharge - period_consume), 2)
+                payload["储值卡余额变化"] = {
+                    "期初余额": round(opening, 2),
+                    "期末余额": round(closing, 2),
+                    "余额变化": round(diff, 2),
+                    "本期充值": round(period_recharge, 2),
+                    "本期消耗": round(period_consume, 2),
+                    "其他调整": other_adj,  # 含过期/赠送/退款/手动调整，非 0 时 AI 需要关注
+                }
+        except Exception:
+            logger.debug("储值卡余额变化注入失败", exc_info=True)
+    # 8. 日粒度派生（仅 area=all，样本 ≥ 7 天）：一次 DB 查询，三段派生
+    #    - 单位经济：客单价/订单数/会员占比（含环比，避免 AI 对客单走势推测幻觉）
+    #    - 按星期聚合：供 E 板块做周中规律宏观洞察
+    #    - 日粒度异常：同星期均值基线下的极端偏离
+    if area == "all":
+        try:
+            start_date, end_date = _calc_date_range(board_time)
+            series = _fetch_daily_series(site_id, str(start_date), str(end_date))
+            # 上期序列（用于客单价环比）
+            prev_series: list[tuple] | None = None
+            try:
+                prev_start, prev_end = _calc_prev_range(board_time, start_date, end_date)
+                prev_series = _fetch_daily_series(site_id, str(prev_start), str(prev_end))
+            except Exception:
+                logger.debug("上期 series 查询失败，客单价环比字段将省略", exc_info=True)
+
+            if series:
+                unit_econ = _build_unit_economics(series, prev_series=prev_series)
+                if unit_econ:
+                    payload["单位经济"] = unit_econ
+                by_weekday = _aggregate_by_weekday(series)
+                if by_weekday:
+                    payload["按星期聚合"] = by_weekday
+                anomalies = _detect_anomaly_days(
+                    site_id, str(start_date), str(end_date), series=series,
+                )
+                if anomalies:
+                    payload["日粒度异常"] = anomalies
+        except Exception:
+            logger.debug("日粒度派生字段注入失败（不影响主流程）", exc_info=True)
+    # 9. 行业基线：AI 判断是否超警戒线的参照
+    payload["行业基线"] = INDUSTRY_BASELINES
+    # 10. 原始财务数据：供 AI 追溯（大部分 prompt 长度来自这里，已 slim）
+    payload["原始指标"] = raw_cn
+
+    if not board_data:
+        payload["数据缺失提示"] = "财务看板数据获取失败，请基于已有缓存或常识分析"
+
+    return json.dumps(payload, ensure_ascii=False, default=str)

apps/backend/app/ai/prompts/app2a_finance_area_prompt.py

@@ -396,7 +396,10 @@ async def build_prompt(
     # 对比口径（所有环比字段的前置依赖 · H1）
     compare_caliber: dict[str, Any] | None = None
     try:
-        cur_start, cur_end = _calc_date_range(board_time)
+        from app.services.runtime_context import get_runtime_context
+
+        runtime_ctx = get_runtime_context(site_id)
+        cur_start, cur_end = _calc_date_range(board_time, ref_date=runtime_ctx.business_date)
         prev_start, prev_end = _calc_prev_range(board_time, cur_start, cur_end)
         cur_days = (cur_end - cur_start).days + 1
         prev_days = (prev_end - prev_start).days + 1
@@ -419,7 +422,7 @@ async def build_prompt(
     }
 
     payload: dict[str, Any] = {
-        "当前时间": datetime.now().strftime("%Y-%m-%d %H:%M"),
+        "当前时间": get_runtime_context(site_id).business_now.strftime("%Y-%m-%d %H:%M"),
         "门店编号": site_id,
         "时间维度": DIMENSION_LABELS.get(time_dimension, time_dimension),
         "区域": AREA_LABELS.get(area, area),

apps/backend/app/ai/prompts/app3_clue_prompt.py

@@ -0,0 +1,131 @@
+"""应用 3 客户数据维客线索分析 Prompt 拼装。
+
+消费事件触发，从客户消费数据提取维客线索。
+- 数据源：fetch_member_consumption_data（DWS）
+- 金额口径：items_sum（禁止 consume_money）
+- 线索 category：客户基础 / 消费习惯 / 玩法偏好（3 选 1）
+- 线索 providers 统一为"系统"
+- system prompt 在百炼控制台配置，本模块只拼数据上下文 JSON
+
+返回：单个 prompt 字符串（直接传给 Application.call）。
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+from typing import Any
+
+from app.ai.cache_service import AICacheService
+from app.ai.data_fetchers import fetch_member_consumption_data
+from app.ai.schemas import CacheTypeEnum
+from app.services.runtime_context import as_runtime_business_now_str
+
+logger = logging.getLogger(__name__)
+
+# prompt 观测阈值：历史上 4000 字会触发裁剪；现保留完整消费明细，仅用于测试/审计参考
+_MAX_PROMPT_LEN = 4000
+
+
+async def build_prompt(
+    context: dict,
+    cache_svc: AICacheService | None = None,
+) -> str:
+    """构建 App3 prompt 字符串。
+
+    Args:
+        context: site_id, member_id
+        cache_svc: 缓存服务，用于读取 reference 历史数据
+
+    Returns:
+        JSON 序列化后的 prompt 字符串
+    """
+    site_id = context["site_id"]
+    member_id = context["member_id"]
+
+    # 数据获取（失败降级）
+    fetch_failed = False
+    try:
+        member_data = await fetch_member_consumption_data(site_id, member_id)
+    except Exception:
+        logger.warning(
+            "App3 消费数据获取失败: site_id=%s member_id=%s",
+            site_id, member_id, exc_info=True,
+        )
+        member_data = _default_member_data()
+        fetch_failed = True
+
+    consumption_records = member_data.get("consumption_records") or []
+    if not consumption_records:
+        consumption_records = (
+            "⚠ 消费数据获取失败，该客户暂无消费记录可供分析"
+            if fetch_failed else "该客户暂无消费记录"
+        )
+
+    payload: dict[str, Any] = {
+        "current_time": as_runtime_business_now_str(site_id, fmt="%Y-%m-%d %H:%M"),
+        "member_id": member_id,
+        "member_nickname": member_data.get("member_nickname", ""),
+        "main_data": {
+            "consumption_records": consumption_records,
+            "member_cards": member_data.get("member_cards", []),
+            "card_balance_total": member_data.get("card_balance_total", 0),
+            "stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
+            "expected_visit_date": member_data.get("expected_visit_date"),
+            "days_since_last_visit": member_data.get("days_since_last_visit"),
+        },
+        "reference": _build_reference(site_id, member_id, cache_svc),
+    }
+
+    # 完整明细策略：App3 需要尽量保留消费行为模式，不在本地裁剪消费记录。
+    # 真实 App3 完整 100 条明细调用已验证可在 180s 单步超时内返回。
+    text = json.dumps(payload, ensure_ascii=False, default=str)
+    return text
+
+
+def _default_member_data() -> dict:
+    return {
+        "member_nickname": "",
+        "consumption_records": [],
+        "member_cards": [],
+        "card_balance_total": 0,
+        "stored_value_balance_total": 0,
+        "expected_visit_date": None,
+        "days_since_last_visit": None,
+    }
+
+
+def _build_reference(
+    site_id: int,
+    member_id: int,
+    cache_svc: AICacheService | None,
+) -> dict:
+    """组装参考字段：App6 备注线索最新 + App8 历史最近 2 条。"""
+    if cache_svc is None:
+        return {}
+
+    ref: dict = {}
+    target_id = str(member_id)
+
+    app6_latest = cache_svc.get_latest(
+        CacheTypeEnum.APP6_NOTE_ANALYSIS.value, site_id, target_id,
+    )
+    if app6_latest:
+        ref["app6_note_clues"] = {
+            "result_json": app6_latest.get("result_json"),
+            "generated_at": app6_latest.get("created_at"),
+        }
+
+    app8_history = cache_svc.get_history(
+        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id, limit=2,
+    )
+    if app8_history:
+        ref["app8_history"] = [
+            {
+                "result_json": h.get("result_json"),
+                "generated_at": h.get("created_at"),
+            }
+            for h in app8_history
+        ]
+
+    return ref

apps/backend/app/ai/prompts/app4_analysis_prompt.py

@@ -0,0 +1,177 @@
+"""应用 4 关系分析 / 任务建议 Prompt 拼装。
+
+助教被分配召回任务或参与新结算时触发。
+- 数据源：fetch_assistant_info + fetch_service_history + fetch_member_consumption_data + fetch_member_notes
+- 输出字段：task_description / action_suggestions / one_line_summary
+- system prompt 在百炼控制台配置
+
+返回：单个 prompt 字符串。
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+from typing import Any
+
+from app.ai.cache_service import AICacheService
+from app.ai.data_fetchers import (
+    fetch_assistant_info,
+    fetch_member_consumption_data,
+    fetch_member_notes,
+    fetch_service_history,
+)
+from app.ai.schemas import CacheTypeEnum
+from app.services.runtime_context import as_runtime_business_now_str
+
+logger = logging.getLogger(__name__)
+
+_MAX_PROMPT_LEN = 8000
+
+
+async def build_prompt(
+    context: dict,
+    cache_svc: AICacheService | None = None,
+) -> str:
+    """构建 App4 prompt 字符串。
+
+    Args:
+        context: site_id, assistant_id, member_id
+        cache_svc: 缓存服务，用于读取 reference 历史数据
+
+    Returns:
+        JSON 序列化后的 prompt 字符串
+    """
+    site_id = context["site_id"]
+    assistant_id = context["assistant_id"]
+    member_id = context["member_id"]
+
+    results = await asyncio.gather(
+        fetch_assistant_info(site_id, assistant_id),
+        fetch_service_history(site_id, assistant_id, member_id),
+        fetch_member_consumption_data(site_id, member_id),
+        fetch_member_notes(site_id, member_id),
+        return_exceptions=True,
+    )
+
+    warnings: list[str] = []
+
+    assistant_info = results[0] if not isinstance(results[0], Exception) else {}
+    if isinstance(results[0], Exception):
+        warnings.append("助教信息获取失败")
+        logger.warning("App4 助教信息获取失败: %s", results[0])
+
+    service_history = results[1] if not isinstance(results[1], Exception) else []
+    if isinstance(results[1], Exception):
+        warnings.append("服务历史获取失败")
+        logger.warning("App4 服务历史获取失败: %s", results[1])
+
+    if isinstance(results[2], Exception):
+        member_data = _default_member_data()
+        warnings.append("消费数据获取失败")
+        logger.warning("App4 消费数据获取失败: %s", results[2])
+    else:
+        member_data = results[2]
+
+    notes = results[3] if not isinstance(results[3], Exception) else []
+    if isinstance(results[3], Exception):
+        warnings.append("备注获取失败")
+        logger.warning("App4 备注获取失败: %s", results[3])
+
+    payload: dict[str, Any] = {
+        "current_time": as_runtime_business_now_str(site_id, fmt="%Y-%m-%d %H:%M"),
+        "assistant_id": assistant_id,
+        "member_id": member_id,
+        "assistant_info": assistant_info or "⚠ 助教信息获取失败",
+        "service_history": service_history or "暂无服务记录",
+        "task_assignment_basis": {
+            "consumption_records": member_data.get("consumption_records", []) or "该客户暂无消费记录",
+            "member_cards": member_data.get("member_cards", []),
+            "card_balance_total": member_data.get("card_balance_total", 0),
+            "stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
+            "expected_visit_date": member_data.get("expected_visit_date"),
+            "days_since_last_visit": member_data.get("days_since_last_visit"),
+        },
+        "customer_data": {
+            "member_nickname": member_data.get("member_nickname", ""),
+            "notes": notes or "暂无备注",
+        },
+        "reference": _build_reference(site_id, member_id, cache_svc),
+    }
+
+    if warnings:
+        payload["_data_warnings"] = warnings
+
+    return _truncate_payload(payload)
+
+
+def _default_member_data() -> dict:
+    return {
+        "member_nickname": "",
+        "consumption_records": [],
+        "member_cards": [],
+        "card_balance_total": 0,
+        "stored_value_balance_total": 0,
+        "expected_visit_date": None,
+        "days_since_last_visit": None,
+    }
+
+
+def _build_reference(
+    site_id: int,
+    member_id: int,
+    cache_svc: AICacheService | None,
+) -> dict:
+    """组装 App8 最新 + 最近 2 条历史。"""
+    if cache_svc is None:
+        return {}
+
+    ref: dict = {}
+    target_id = str(member_id)
+
+    latest = cache_svc.get_latest(
+        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id,
+    )
+    if latest:
+        ref["app8_latest"] = {
+            "result_json": latest.get("result_json"),
+            "generated_at": latest.get("created_at"),
+        }
+
+    history = cache_svc.get_history(
+        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id, limit=2,
+    )
+    if history:
+        ref["app8_history"] = [
+            {"result_json": h.get("result_json"), "generated_at": h.get("created_at")}
+            for h in history
+        ]
+
+    return ref
+
+
+def _truncate_payload(payload: dict) -> str:
+    """按优先级截断 service_history → consumption_records → notes，控制 prompt 长度。"""
+    text = json.dumps(payload, ensure_ascii=False, default=str)
+    if len(text) <= _MAX_PROMPT_LEN:
+        return text
+
+    sh = payload.get("service_history")
+    if isinstance(sh, list) and len(sh) > 5:
+        payload["service_history"] = sh[:5]
+        payload["_truncated_service_history"] = f"服务记录已截断，原始 {len(sh)} 条"
+        text = json.dumps(payload, ensure_ascii=False, default=str)
+    if len(text) > _MAX_PROMPT_LEN:
+        records = payload["task_assignment_basis"].get("consumption_records")
+        if isinstance(records, list) and len(records) > 5:
+            payload["task_assignment_basis"]["consumption_records"] = records[:5]
+            payload["task_assignment_basis"]["_truncated"] = f"消费记录已截断，原始 {len(records)} 条"
+            text = json.dumps(payload, ensure_ascii=False, default=str)
+    if len(text) > _MAX_PROMPT_LEN:
+        n = payload["customer_data"].get("notes")
+        if isinstance(n, list) and len(n) > 10:
+            payload["customer_data"]["notes"] = n[:10]
+            payload["customer_data"]["_truncated_notes"] = f"备注已截断，原始 {len(n)} 条"
+            text = json.dumps(payload, ensure_ascii=False, default=str)
+    return text

apps/backend/app/ai/prompts/app5_tactics_prompt.py

@@ -0,0 +1,170 @@
+"""应用 5 话术参考 Prompt 拼装。
+
+App4 完成后串行触发，接收 App4 返回结果作为 task_suggestion。
+- 数据源：fetch_assistant_info + fetch_service_history + fetch_member_consumption_data + fetch_member_notes + context.app4_result
+- 输出字段：tactics 数组（每条含 scenario + script）
+- system prompt 在百炼控制台配置
+
+返回：单个 prompt 字符串。
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+from typing import Any
+
+from app.ai.cache_service import AICacheService
+from app.ai.data_fetchers import (
+    fetch_assistant_info,
+    fetch_member_consumption_data,
+    fetch_member_notes,
+    fetch_service_history,
+)
+from app.ai.schemas import CacheTypeEnum
+from app.services.runtime_context import as_runtime_business_now_str
+
+logger = logging.getLogger(__name__)
+
+_MAX_PROMPT_LEN = 8000
+
+
+async def build_prompt(
+    context: dict,
+    cache_svc: AICacheService | None = None,
+) -> str:
+    """构建 App5 prompt 字符串。
+
+    Args:
+        context: site_id, assistant_id, member_id, app4_result(dict|None)
+
+    Returns:
+        JSON 序列化后的 prompt 字符串
+    """
+    site_id = context["site_id"]
+    assistant_id = context["assistant_id"]
+    member_id = context["member_id"]
+    task_suggestion = context.get("app4_result") or {}
+
+    results = await asyncio.gather(
+        fetch_assistant_info(site_id, assistant_id),
+        fetch_service_history(site_id, assistant_id, member_id),
+        fetch_member_consumption_data(site_id, member_id),
+        fetch_member_notes(site_id, member_id),
+        return_exceptions=True,
+    )
+
+    warnings: list[str] = []
+
+    assistant_info = results[0] if not isinstance(results[0], Exception) else {}
+    if isinstance(results[0], Exception):
+        warnings.append("助教信息获取失败")
+        logger.warning("App5 助教信息获取失败: %s", results[0])
+
+    service_history = results[1] if not isinstance(results[1], Exception) else []
+    if isinstance(results[1], Exception):
+        warnings.append("服务历史获取失败")
+        logger.warning("App5 服务历史获取失败: %s", results[1])
+
+    if isinstance(results[2], Exception):
+        member_data = _default_member_data()
+        warnings.append("消费数据获取失败")
+        logger.warning("App5 消费数据获取失败: %s", results[2])
+    else:
+        member_data = results[2]
+
+    notes = results[3] if not isinstance(results[3], Exception) else []
+    if isinstance(results[3], Exception):
+        warnings.append("备注获取失败")
+        logger.warning("App5 备注获取失败: %s", results[3])
+
+    payload: dict[str, Any] = {
+        "current_time": as_runtime_business_now_str(site_id, fmt="%Y-%m-%d %H:%M"),
+        "assistant_id": assistant_id,
+        "member_id": member_id,
+        "task_suggestion": task_suggestion,
+        "assistant_info": assistant_info or "⚠ 助教信息获取失败",
+        "service_history": service_history or "暂无服务记录",
+        "task_assignment_basis": {
+            "consumption_records": member_data.get("consumption_records", []) or "该客户暂无消费记录",
+            "member_cards": member_data.get("member_cards", []),
+            "card_balance_total": member_data.get("card_balance_total", 0),
+            "stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
+            "expected_visit_date": member_data.get("expected_visit_date"),
+            "days_since_last_visit": member_data.get("days_since_last_visit"),
+        },
+        "customer_data": {
+            "member_nickname": member_data.get("member_nickname", ""),
+            "notes": notes or "暂无备注",
+        },
+        "reference": _build_reference(site_id, member_id, cache_svc),
+    }
+
+    if warnings:
+        payload["_data_warnings"] = warnings
+
+    return _truncate_payload(payload)
+
+
+def _default_member_data() -> dict:
+    return {
+        "member_nickname": "",
+        "consumption_records": [],
+        "member_cards": [],
+        "card_balance_total": 0,
+        "stored_value_balance_total": 0,
+        "expected_visit_date": None,
+        "days_since_last_visit": None,
+    }
+
+
+def _build_reference(
+    site_id: int,
+    member_id: int,
+    cache_svc: AICacheService | None,
+) -> dict:
+    """组装最近 2 条 App8 历史。"""
+    if cache_svc is None:
+        return {}
+
+    ref: dict = {}
+    history = cache_svc.get_history(
+        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value,
+        site_id,
+        str(member_id),
+        limit=2,
+    )
+    if history:
+        ref["app8_history"] = [
+            {"result_json": h.get("result_json"), "generated_at": h.get("created_at")}
+            for h in history
+        ]
+
+    return ref
+
+
+def _truncate_payload(payload: dict) -> str:
+    """按优先级截断 service_history → consumption_records → notes。"""
+    text = json.dumps(payload, ensure_ascii=False, default=str)
+    if len(text) <= _MAX_PROMPT_LEN:
+        return text
+
+    sh = payload.get("service_history")
+    if isinstance(sh, list) and len(sh) > 5:
+        payload["service_history"] = sh[:5]
+        payload["_truncated_service_history"] = f"服务记录已截断，原始 {len(sh)} 条"
+        text = json.dumps(payload, ensure_ascii=False, default=str)
+    if len(text) > _MAX_PROMPT_LEN:
+        records = payload["task_assignment_basis"].get("consumption_records")
+        if isinstance(records, list) and len(records) > 5:
+            payload["task_assignment_basis"]["consumption_records"] = records[:5]
+            payload["task_assignment_basis"]["_truncated"] = f"消费记录已截断，原始 {len(records)} 条"
+            text = json.dumps(payload, ensure_ascii=False, default=str)
+    if len(text) > _MAX_PROMPT_LEN:
+        n = payload["customer_data"].get("notes")
+        if isinstance(n, list) and len(n) > 10:
+            payload["customer_data"]["notes"] = n[:10]
+            payload["customer_data"]["_truncated_notes"] = f"备注已截断，原始 {len(n)} 条"
+            text = json.dumps(payload, ensure_ascii=False, default=str)
+    return text

apps/backend/app/ai/prompts/app6_note_prompt.py

@@ -0,0 +1,160 @@
+"""应用 6 备注分析 Prompt 拼装。
+
+助教提交备注后触发，AI 分析备注内容并评分（1-10）+ 提取维客线索。
+- 数据源：context.note_content + fetch_member_consumption_data + fetch_member_notes
+- 线索 category：6 选 1（含促销偏好/社交关系/重要反馈）
+- 线索 providers 标记当前备注提供人
+- system prompt 在百炼控制台配置
+
+返回：单个 prompt 字符串。
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+from typing import Any
+
+from app.ai.cache_service import AICacheService
+from app.ai.data_fetchers import fetch_member_consumption_data, fetch_member_notes
+from app.ai.schemas import CacheTypeEnum
+from app.services.runtime_context import as_runtime_business_now_str
+
+logger = logging.getLogger(__name__)
+
+_MAX_PROMPT_LEN = 8000
+
+
+async def build_prompt(
+    context: dict,
+    cache_svc: AICacheService | None = None,
+) -> str:
+    """构建 App6 prompt 字符串。
+
+    Args:
+        context: site_id, member_id, note_content, noted_by_name, noted_by_created_at
+
+    Returns:
+        JSON 序列化后的 prompt 字符串
+    """
+    site_id = context["site_id"]
+    member_id = context["member_id"]
+    note_content = context.get("note_content", "")
+    noted_by_name = context.get("noted_by_name", "")
+    noted_by_created_at = context.get("noted_by_created_at", "")
+
+    results = await asyncio.gather(
+        fetch_member_consumption_data(site_id, member_id),
+        fetch_member_notes(site_id, member_id),
+        return_exceptions=True,
+    )
+
+    warnings: list[str] = []
+
+    if isinstance(results[0], Exception):
+        member_data = _default_member_data()
+        warnings.append("消费数据获取失败")
+        logger.warning("App6 消费数据获取失败: %s", results[0])
+    else:
+        member_data = results[0]
+
+    all_notes = results[1] if not isinstance(results[1], Exception) else []
+    if isinstance(results[1], Exception):
+        warnings.append("备注获取失败")
+        logger.warning("App6 备注获取失败: %s", results[1])
+
+    reference = _build_reference(site_id, member_id, cache_svc)
+    reference["member_nickname"] = member_data.get("member_nickname", "")
+    reference["consumption_data"] = {
+        "consumption_records": member_data.get("consumption_records", []) or "该客户暂无消费记录",
+        "member_cards": member_data.get("member_cards", []),
+        "card_balance_total": member_data.get("card_balance_total", 0),
+        "stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
+        "expected_visit_date": member_data.get("expected_visit_date"),
+        "days_since_last_visit": member_data.get("days_since_last_visit"),
+    }
+    reference["all_notes"] = all_notes
+
+    payload: dict[str, Any] = {
+        "current_time": as_runtime_business_now_str(site_id, fmt="%Y-%m-%d %H:%M"),
+        "member_id": member_id,
+        "current_note": {
+            "content": note_content,
+            "recorded_by": noted_by_name,
+            "created_at": noted_by_created_at,
+        },
+        "providers_label": noted_by_name,
+        "reference": reference,
+    }
+
+    if warnings:
+        payload["_data_warnings"] = warnings
+
+    return _truncate_payload(payload)
+
+
+def _default_member_data() -> dict:
+    return {
+        "member_nickname": "",
+        "consumption_records": [],
+        "member_cards": [],
+        "card_balance_total": 0,
+        "stored_value_balance_total": 0,
+        "expected_visit_date": None,
+        "days_since_last_visit": None,
+    }
+
+
+def _build_reference(
+    site_id: int,
+    member_id: int,
+    cache_svc: AICacheService | None,
+) -> dict:
+    """组装 App3 客户线索最新 + App8 历史最近 2 条。"""
+    if cache_svc is None:
+        return {}
+
+    ref: dict = {}
+    target_id = str(member_id)
+
+    app3_latest = cache_svc.get_latest(
+        CacheTypeEnum.APP3_CLUE.value, site_id, target_id,
+    )
+    if app3_latest:
+        ref["app3_clues"] = {
+            "result_json": app3_latest.get("result_json"),
+            "generated_at": app3_latest.get("created_at"),
+        }
+
+    app8_history = cache_svc.get_history(
+        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id, limit=2,
+    )
+    if app8_history:
+        ref["app8_history"] = [
+            {"result_json": h.get("result_json"), "generated_at": h.get("created_at")}
+            for h in app8_history
+        ]
+
+    return ref
+
+
+def _truncate_payload(payload: dict) -> str:
+    """按优先级截断 consumption_records → all_notes。"""
+    text = json.dumps(payload, ensure_ascii=False, default=str)
+    if len(text) <= _MAX_PROMPT_LEN:
+        return text
+
+    cd = payload["reference"].get("consumption_data", {})
+    records = cd.get("consumption_records")
+    if isinstance(records, list) and len(records) > 5:
+        cd["consumption_records"] = records[:5]
+        cd["_truncated"] = f"消费记录已截断，原始 {len(records)} 条"
+        text = json.dumps(payload, ensure_ascii=False, default=str)
+    if len(text) > _MAX_PROMPT_LEN:
+        notes = payload["reference"].get("all_notes")
+        if isinstance(notes, list) and len(notes) > 10:
+            payload["reference"]["all_notes"] = notes[:10]
+            payload["reference"]["_truncated_notes"] = f"备注已截断，原始 {len(notes)} 条"
+            text = json.dumps(payload, ensure_ascii=False, default=str)
+    return text

apps/backend/app/ai/prompts/app7_customer_prompt.py

@@ -0,0 +1,165 @@
+"""应用 7 客户分析 Prompt 拼装。
+
+消费链 App8 完成后串行触发，生成客户全量分析与运营策略。
+- 数据源：fetch_member_consumption_data + fetch_member_notes
+- 备注内容标注【来源：XXX，请甄别信息真实性】
+- 输出字段：strategies 数组 + summary
+- system prompt 在百炼控制台配置
+
+返回：单个 prompt 字符串。
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+from typing import Any
+
+from app.ai.cache_service import AICacheService
+from app.ai.data_fetchers import fetch_member_consumption_data, fetch_member_notes
+from app.ai.schemas import CacheTypeEnum
+from app.services.runtime_context import as_runtime_business_now_str
+
+logger = logging.getLogger(__name__)
+
+_MAX_PROMPT_LEN = 5000
+
+
+async def build_prompt(
+    context: dict,
+    cache_svc: AICacheService | None = None,
+) -> str:
+    """构建 App7 prompt 字符串。
+
+    Args:
+        context: site_id, member_id
+
+    Returns:
+        JSON 序列化后的 prompt 字符串
+    """
+    site_id = context["site_id"]
+    member_id = context["member_id"]
+
+    results = await asyncio.gather(
+        fetch_member_consumption_data(site_id, member_id),
+        fetch_member_notes(site_id, member_id),
+        return_exceptions=True,
+    )
+
+    warnings: list[str] = []
+
+    if isinstance(results[0], Exception):
+        member_data = _default_member_data()
+        warnings.append("消费数据获取失败")
+        logger.warning("App7 消费数据获取失败: %s", results[0])
+    else:
+        member_data = results[0]
+
+    notes_raw = results[1] if not isinstance(results[1], Exception) else []
+    if isinstance(results[1], Exception):
+        warnings.append("备注获取失败")
+        logger.warning("App7 备注获取失败: %s", results[1])
+
+    # 主观信息标注来源
+    if notes_raw:
+        annotated = []
+        for note in notes_raw:
+            recorded_by = note.get("recorded_by", "未知")
+            n = dict(note)
+            n["content"] = (
+                f"{note.get('content', '')}"
+                f"【来源：{recorded_by}，请甄别信息真实性】"
+            )
+            annotated.append(n)
+        subjective_notes: Any = annotated
+    else:
+        subjective_notes = "该客户暂无主观备注信息"
+
+    payload: dict[str, Any] = {
+        "current_time": as_runtime_business_now_str(site_id, fmt="%Y-%m-%d %H:%M"),
+        "member_id": member_id,
+        "member_nickname": member_data.get("member_nickname", ""),
+        "objective_data": {
+            "consumption_records": member_data.get("consumption_records", []) or "该客户暂无消费记录",
+            "member_cards": member_data.get("member_cards", []),
+            "card_balance_total": member_data.get("card_balance_total", 0),
+            "stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
+            "expected_visit_date": member_data.get("expected_visit_date"),
+            "days_since_last_visit": member_data.get("days_since_last_visit"),
+        },
+        "subjective_data": {
+            "notes": subjective_notes,
+        },
+        "reference": _build_reference(site_id, member_id, cache_svc),
+    }
+
+    if warnings:
+        payload["_data_warnings"] = warnings
+
+    return _truncate_payload(payload)
+
+
+def _default_member_data() -> dict:
+    return {
+        "member_nickname": "",
+        "consumption_records": [],
+        "member_cards": [],
+        "card_balance_total": 0,
+        "stored_value_balance_total": 0,
+        "expected_visit_date": None,
+        "days_since_last_visit": None,
+    }
+
+
+def _build_reference(
+    site_id: int,
+    member_id: int,
+    cache_svc: AICacheService | None,
+) -> dict:
+    """组装 App8 最新 + 最近 2 条历史。"""
+    if cache_svc is None:
+        return {}
+
+    ref: dict = {}
+    target_id = str(member_id)
+
+    latest = cache_svc.get_latest(
+        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id,
+    )
+    if latest:
+        ref["app8_latest"] = {
+            "result_json": latest.get("result_json"),
+            "generated_at": latest.get("created_at"),
+        }
+
+    history = cache_svc.get_history(
+        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id, limit=2,
+    )
+    if history:
+        ref["app8_history"] = [
+            {"result_json": h.get("result_json"), "generated_at": h.get("created_at")}
+            for h in history
+        ]
+
+    return ref
+
+
+def _truncate_payload(payload: dict) -> str:
+    """按优先级截断 consumption_records → notes。"""
+    text = json.dumps(payload, ensure_ascii=False, default=str)
+    if len(text) <= _MAX_PROMPT_LEN:
+        return text
+
+    records = payload["objective_data"].get("consumption_records")
+    if isinstance(records, list) and len(records) > 5:
+        payload["objective_data"]["consumption_records"] = records[:5]
+        payload["objective_data"]["_truncated"] = f"消费记录已截断，原始 {len(records)} 条"
+        text = json.dumps(payload, ensure_ascii=False, default=str)
+    if len(text) > _MAX_PROMPT_LEN:
+        n = payload["subjective_data"].get("notes")
+        if isinstance(n, list) and len(n) > 10:
+            payload["subjective_data"]["notes"] = n[:10]
+            payload["subjective_data"]["_truncated_notes"] = f"备注已截断，原始 {len(n)} 条"
+            text = json.dumps(payload, ensure_ascii=False, default=str)
+    return text

apps/backend/app/ai/prompts/app8_consolidation_prompt.py

@@ -1,93 +1,52 @@
-"""应用 8：维客线索整理 Prompt 模板。
+"""应用 8 维客线索整理 Prompt 拼装。
 
 接收 App3（消费分析）和 App6（备注分析）的全部线索，
 整合去重后输出统一维客线索。
+- 数据源：context.app3_clues + context.app6_clues（dispatcher 已查好传入）
+- 分类标签 6 选 1（与 member_retention_clue CHECK 约束一致）
+- 合并规则：相似线索合并，providers 逗号分隔
+- system prompt 在百炼控制台配置
 
-分类标签限定 6 个枚举值（与 member_retention_clue CHECK 约束一致）：
-客户基础、消费习惯、玩法偏好、促销偏好、社交关系、重要反馈。
-
-合并规则：
-- 相似线索合并，providers 以逗号分隔
-- 其余线索原文返回
-- 最小改动原则
+返回：单个 prompt 字符串。
 """
 
 from __future__ import annotations
 
 import json
+from typing import Any
 
 
-def build_prompt(context: dict) -> list[dict]:
-    """构建 App8 维客线索整理 Prompt。
+async def build_prompt(
+    context: dict,
+    cache_svc: Any | None = None,  # 兼容统一签名，App8 不用
+) -> str:
+    """构建 App8 prompt 字符串。
 
     Args:
-        context: 包含以下字段：
-            - site_id: int
-            - member_id: int
-            - app3_clues: list[dict] — App3 产出的线索列表
-            - app6_clues: list[dict] — App6 产出的线索列表
-            - app3_generated_at: str | None — App3 线索生成时间
-            - app6_generated_at: str | None — App6 线索生成时间
+        context: site_id, member_id, app3_clues(list), app6_clues(list),
+                 app3_generated_at(str|None), app6_generated_at(str|None)
 
     Returns:
-        消息列表 [{"role": "system", ...}, {"role": "user", ...}]
+        JSON 序列化后的 prompt 字符串
     """
     member_id = context["member_id"]
-    app3_clues = context.get("app3_clues", [])
-    app6_clues = context.get("app6_clues", [])
-    app3_generated_at = context.get("app3_generated_at")
-    app6_generated_at = context.get("app6_generated_at")
+    app3_clues = context.get("app3_clues") or []
+    app6_clues = context.get("app6_clues") or []
 
-    system_content = {
-        "task": "整合去重来自消费分析和备注分析的维客线索，输出统一线索列表。",
-        "app_id": "app8_consolidation",
-        "rules": {
-            "category_enum": [
-                "客户基础", "消费习惯", "玩法偏好",
-                "促销偏好", "社交关系", "重要反馈",
-            ],
-            "merge_strategy": (
-                "相似线索合并为一条，providers 以逗号分隔（如 '系统,张三'）；"
-                "不相似的线索原文保留，不做修改。最小改动原则。"
-            ),
-            "output_format": {
-                "clues": [
-                    {
-                        "category": "枚举值（6 选 1）",
-                        "summary": "一句话摘要",
-                        "detail": "详细说明",
-                        "emoji": "表情符号",
-                        "providers": "提供者（逗号分隔）",
-                    }
-                ]
-            },
-        },
+    payload: dict[str, Any] = {
+        "member_id": member_id,
         "input": {
             "app3_clues": {
                 "source": "消费数据分析（App3）",
-                "generated_at": app3_generated_at,
+                "generated_at": context.get("app3_generated_at"),
                 "clues": app3_clues,
             },
             "app6_clues": {
                 "source": "备注分析（App6）",
-                "generated_at": app6_generated_at,
+                "generated_at": context.get("app6_generated_at"),
                 "clues": app6_clues,
             },
         },
     }
 
-    user_content = (
-        f"请整合会员 {member_id} 的维客线索。\n"
-        "输入包含两个来源的线索：App3（消费数据分析）和 App6（备注分析）。\n"
-        "规则：\n"
-        "1. 相似线索合并为一条，providers 字段以逗号分隔多个提供者\n"
-        "2. 不相似的线索原文保留\n"
-        "3. category 必须是：客户基础、消费习惯、玩法偏好、促销偏好、社交关系、重要反馈 之一\n"
-        "4. 每条线索包含 category、summary、detail、emoji、providers 五个字段\n"
-        "5. 最小改动原则，尽量保留原始表述"
-    )
-
-    return [
-        {"role": "system", "content": json.dumps(system_content, ensure_ascii=False)},
-        {"role": "user", "content": user_content},
-    ]
+    return json.dumps(payload, ensure_ascii=False, default=str)

apps/backend/app/ai/references.py

@@ -0,0 +1,137 @@
+"""AI references 工具模块。
+
+为 AI 输出（ai_cache.result_json / ai_messages.reference_card）
+注入数据来源引用元数据，便于前端渲染可点击引用卡片。
+
+- App2~8：通过 dispatcher._write_cache 统一注入到 result['_references']
+- App1：通过 xcx_chat 在 assistant 消息写入时调用 build_app1_reference 生成单卡片
+"""
+
+from __future__ import annotations
+
+from typing import Any
+
+
+def build_app_references(app_type: str, context: dict) -> list[dict]:
+    """为 App2~8 构建 references 列表，供前端消息卡片渲染。
+
+    引用结构：
+        {
+          "type": "member" | "task" | "assistant" | "finance",
+          "id": int | str,
+          "label": "卡片上的文字",
+          "link": "/pages/xxx/xxx?param=val"（小程序页面路径）,
+          "source_page": 小程序页面 contextType
+        }
+
+    Args:
+        app_type: 应用名称
+        context: 传给 build_prompt 的上下文（含 site_id / member_id 等）
+
+    Returns:
+        refs 数组。无有效上下文时返回空数组。
+    """
+    refs: list[dict] = []
+    site_id = context.get("site_id")
+    member_id = context.get("member_id")
+    assistant_id = context.get("assistant_id")
+    time_dimension = context.get("time_dimension")
+
+    if member_id is not None:
+        refs.append({
+            "type": "member",
+            "id": member_id,
+            "label": f"客户 #{member_id}",
+            "link": f"/pages/customer-detail/customer-detail?customerId={member_id}",
+            "source_page": "customer-detail",
+        })
+
+    if assistant_id is not None:
+        refs.append({
+            "type": "assistant",
+            "id": assistant_id,
+            "label": f"助教 #{assistant_id}",
+            "link": f"/pages/coach-detail/coach-detail?coachId={assistant_id}",
+            "source_page": "coach-detail",
+        })
+
+    if app_type == "app2_finance" and time_dimension:
+        refs.append({
+            "type": "finance",
+            "id": time_dimension,
+            "label": f"财务看板：{_label_for_dimension(time_dimension)}",
+            "link": f"/pages/board-finance/board-finance?timeDimension={time_dimension}",
+            "source_page": "board-finance",
+        })
+
+    # 保留 site_id 作为兜底上下文（不单独成卡，但用于前端场景判断）
+    if site_id is not None and refs:
+        for r in refs:
+            r.setdefault("site_id", site_id)
+
+    return refs
+
+
+def attach_references(app_type: str, result: dict | None, context: dict) -> dict | None:
+    """向 AI 输出 result 追加 _references 字段（非破坏性）。
+
+    - result 为 None 时原样返回（调用失败不注入）
+    - result 为 dict 时追加 _references 字段；如果 result 已含 _references，保留原值
+    """
+    if result is None or not isinstance(result, dict):
+        return result
+    if "_references" in result:
+        return result
+    refs = build_app_references(app_type, context)
+    if refs:
+        result["_references"] = refs
+    return result
+
+
+def build_app1_reference_card(source_page: str | None, context_id: int | str | None) -> dict | None:
+    """为 App1（chat）assistant 消息构建单个 reference_card。
+
+    兼容前端 chat.wxml 已有的 {type, title, summary, data, dataList} 渲染结构，
+    额外携带 link 字段供前端点击跳转详情页。
+
+    当用户在特定页面（customer-detail / coach-detail / task-detail）发起对话时，
+    自动附加对应跳转卡片。普通浮窗对话（source_page='general'）返回 None。
+
+    与 chat_service.build_reference_card 不同：本函数不查 DB，仅按 source_page 构造链接。
+    """
+    if not source_page or not context_id:
+        return None
+
+    mapping: dict[str, tuple[str, str, str]] = {
+        "customer-detail": ("customer", "客户", "customerId"),
+        "coach-detail": ("assistant", "助教", "coachId"),
+        "task-detail": ("task", "任务", "taskId"),
+    }
+    entry = mapping.get(source_page)
+    if entry is None:
+        return None
+    ref_type, label_prefix, param = entry
+
+    return {
+        "type": ref_type,
+        "title": f"{label_prefix} #{context_id}",
+        "summary": f"点击查看{label_prefix}详情",
+        "data": {},
+        "link": f"/pages/{source_page}/{source_page}?{param}={context_id}",
+        "source_page": source_page,
+    }
+
+
+def _label_for_dimension(dimension: str) -> str:
+    """8 个财务维度 → 中文标签。"""
+    mapping = {
+        "this_month": "本月",
+        "last_month": "上月",
+        "this_week": "本周",
+        "last_week": "上周",
+        "this_quarter": "本季度",
+        "last_quarter": "上季度",
+        "last_3_months": "近三个月",
+        "last_6_months": "近六个月",
+    }
+    return mapping.get(dimension, dimension)

apps/backend/app/ai/run_log_service.py

@@ -14,12 +14,17 @@ from typing import Callable
 
 import psycopg2.extensions
 
+from app.services.runtime_context import LIVE_INSTANCE_ID, MODE_LIVE, MODE_SANDBOX, get_runtime_context
+
 # prompt 最大存储长度
-_MAX_PROMPT_LENGTH = 2000
+# 2026-04-22：2000→8000。app2_finance 真实 prompt 约 4-8KB（72 组合财务看板 + 中文 key 膨胀），
+# 2000 字符截断会丢掉 optimization-critical 字段（如 discount_items 含团购折扣明细），
+# admin-web 调用详情页无法完整审阅 → 提高到 8000 覆盖绝大部分场景
+_MAX_PROMPT_LENGTH = 8000
 
 
 def _truncate_prompt(prompt: str | None) -> str | None:
-    """截断 prompt 为前 2000 字符。None 原样返回。"""
+    """截断 prompt 为 _MAX_PROMPT_LENGTH 字符上限。None 原样返回。"""
     if prompt is None:
         return None
     return prompt[:_MAX_PROMPT_LENGTH]
@@ -54,17 +59,21 @@ class AIRunLogService:
         truncated = _truncate_prompt(request_prompt)
         conn = self._get_conn()
         try:
+            ctx = get_runtime_context(site_id, conn=conn)
+            runtime_mode = MODE_SANDBOX if ctx.is_sandbox else MODE_LIVE
+            sandbox_instance_id = ctx.sandbox_instance_id if ctx.is_sandbox else LIVE_INSTANCE_ID
             with conn.cursor() as cur:
                 cur.execute(
                     """
                     INSERT INTO biz.ai_run_logs
                         (site_id, app_type, trigger_type, member_id,
-                         request_prompt, session_id, status)
-                    VALUES (%s, %s, %s, %s, %s, %s, 'pending')
+                         request_prompt, session_id, status,
+                         runtime_mode, sandbox_instance_id)
+                    VALUES (%s, %s, %s, %s, %s, %s, 'pending', %s, %s)
                     RETURNING id
                     """,
                     (site_id, app_type, trigger_type, member_id,
-                     truncated, session_id),
+                     truncated, session_id, runtime_mode, sandbox_instance_id),
                 )
                 row = cur.fetchone()
                 assert row is not None, "INSERT RETURNING 应返回 id"

apps/backend/app/main.py

@@ -36,11 +36,12 @@ from app import config
 # CHANGE 2026-03-23 | 新增 trigger_jobs 路由（定时任务管理页面 API）
 # CHANGE 2026-03-24 | P18 任务引擎运营看板：新增 admin_task_engine 路由
 # CHANGE 2026-03-29 | DWS_TASK_ENGINE：新增 internal_events 路由（按 job_name 执行任务）
-from app.routers import auth, execution, schedules, tasks, env_config, db_viewer, etl_status, xcx_test, wx_callback, member_retention_clue, ops_panel, xcx_auth, xcx_avatar, admin_applications, business_day, xcx_tasks, xcx_notes, xcx_chat, xcx_ai_cache, xcx_performance, xcx_customers, xcx_coaches, xcx_board, xcx_config, tenant_auth, tenant_users, tenant_excel, tenant_clues, tenant_site_admins, admin_tenant_admins, admin_registry, internal_ai, admin_ai, admin_dev_trace, trigger_jobs, admin_task_engine, admin_db_health, admin_triggers, internal_events
+from app.routers import auth, execution, schedules, tasks, env_config, db_viewer, etl_status, xcx_test, wx_callback, member_retention_clue, ops_panel, xcx_auth, xcx_avatar, admin_applications, business_day, xcx_tasks, xcx_notes, xcx_chat, xcx_ai_cache, xcx_performance, xcx_customers, xcx_coaches, xcx_board, xcx_config, xcx_runtime_clock, tenant_auth, tenant_users, tenant_excel, tenant_clues, tenant_site_admins, admin_tenant_admins, admin_registry, internal_ai, admin_ai, admin_dev_trace, trigger_jobs, admin_task_engine, admin_db_health, admin_triggers, internal_events, admin_runtime_context
 from app.services.scheduler import scheduler
 from app.services.task_queue import task_queue
 from app.services.task_executor import task_executor
 from app.ws.logs import ws_router
+from app.ws.ai_events import ws_router as ai_ws_router
 
 
 @asynccontextmanager
@@ -99,6 +100,33 @@ async def lifespan(app: FastAPI):
         import logging as _log
         _log.getLogger(__name__).warning("启动检查定时任务失败", exc_info=True)
 
+    # CHANGE 2026-04-22 | 启动时清理上次进程遗留的孤儿 run_logs（worker 被 kill/reload 导致 status 卡在 running）
+    try:
+        from app.database import get_connection as _get_conn_cleanup
+        _c = _get_conn_cleanup()
+        try:
+            with _c.cursor() as _cur:
+                _cur.execute(
+                    """
+                    UPDATE biz.ai_run_logs
+                    SET status = 'failed',
+                        error_message = COALESCE(error_message, '') || ' [orphaned_by_restart]',
+                        finished_at = COALESCE(finished_at, NOW())
+                    WHERE status = 'running'
+                      AND created_at < NOW() - INTERVAL '5 minutes'
+                    """
+                )
+                _cleaned = _cur.rowcount
+            _c.commit()
+            if _cleaned:
+                import logging as _log
+                _log.getLogger(__name__).info("启动清理 %d 条孤儿 run_logs（status=running > 5min）", _cleaned)
+        finally:
+            _c.close()
+    except Exception:
+        import logging as _log
+        _log.getLogger(__name__).warning("孤儿 run_logs 清理失败（忽略）", exc_info=True)
+
     # CHANGE 2026-03-10 | 注册 AI 事件处理器（消费/备注/任务分配 → AI 调用链）
     # CHANGE 2026-03-22 | P14 迁移：BailianClient → DashScopeClient + AIConfig + 防护层
     try:
@@ -127,6 +155,8 @@ async def lifespan(app: FastAPI):
             config=_ai_config,
         )
         register_ai_handlers(_dispatcher)
+        from app.routers import internal_ai as _internal_ai_router
+        _internal_ai_router.set_dispatcher(_dispatcher)
     except Exception:
         import logging as _log
         _log.getLogger(__name__).warning("AI 事件处理器注册失败，AI 功能不可用", exc_info=True)
@@ -178,6 +208,7 @@ app.include_router(env_config.router)
 app.include_router(db_viewer.router)
 app.include_router(etl_status.router)
 app.include_router(ws_router)
+app.include_router(ai_ws_router)
 app.include_router(xcx_test.router)
 app.include_router(wx_callback.router)
 app.include_router(member_retention_clue.router)
@@ -195,6 +226,7 @@ app.include_router(xcx_customers.router)
 app.include_router(xcx_coaches.router)
 app.include_router(xcx_board.router)
 app.include_router(xcx_config.router)
+app.include_router(xcx_runtime_clock.router)
 app.include_router(tenant_auth.router)
 app.include_router(tenant_users.router)
 app.include_router(tenant_excel.router)
@@ -210,6 +242,8 @@ app.include_router(trigger_jobs.router)
 app.include_router(admin_task_engine.router)
 app.include_router(admin_db_health.router)
 app.include_router(admin_triggers.router)
+app.include_router(admin_runtime_context.router)
+app.include_router(admin_runtime_context.config_router)
 
 
 @app.get("/health", tags=["系统"])

apps/backend/app/routers/admin_runtime_context.py

@@ -0,0 +1,309 @@
+# -*- coding: utf-8 -*-
+"""业务运行上下文管理 API。"""
+
+from __future__ import annotations
+
+import logging
+from datetime import date
+
+from fastapi import APIRouter, Depends, HTTPException, Query, status
+from psycopg2.extras import RealDictCursor
+
+from app.auth.dependencies import CurrentUser, get_current_user
+from app.database import get_connection
+from app.schemas.runtime_context import (
+    RuntimeContextResponse,
+    RuntimeSwitchRequest,
+    RuntimeSwitchResponse,
+    RuntimeTransitionStep,
+)
+from app.services.runtime_context import (
+    MODE_LIVE,
+    MODE_SANDBOX,
+    RuntimeContext,
+    get_runtime_context,
+    new_sandbox_instance_id,
+)
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/admin/runtime-context", tags=["业务运行上下文"])
+config_router = APIRouter(prefix="/api/config", tags=["业务配置"])
+
+
+def _require_super_admin(user: CurrentUser) -> None:
+    if "super_admin" not in user.roles:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="仅超级管理员可切换业务运行上下文",
+        )
+
+
+def _context_response(ctx: RuntimeContext) -> RuntimeContextResponse:
+    return RuntimeContextResponse(**ctx.to_dict())
+
+
+@config_router.get("/runtime-context", response_model=RuntimeContextResponse)
+async def get_current_runtime_context(
+    user: CurrentUser = Depends(get_current_user),
+) -> RuntimeContextResponse:
+    """返回当前登录用户门店的业务运行上下文。"""
+    return _context_response(get_runtime_context(user.site_id))
+
+
+@router.get("", response_model=RuntimeContextResponse)
+async def get_admin_runtime_context(
+    site_id: int = Query(..., ge=1),
+    user: CurrentUser = Depends(get_current_user),
+) -> RuntimeContextResponse:
+    """系统管理端按门店查看业务运行上下文。"""
+    _require_super_admin(user)
+    return _context_response(get_runtime_context(site_id))
+
+
+@router.get("/sites")
+async def list_runtime_sites(
+    user: CurrentUser = Depends(get_current_user),
+) -> list[dict]:
+    """列出可配置门店及其当前运行上下文。"""
+    _require_super_admin(user)
+    conn = get_connection()
+    try:
+        with conn.cursor(cursor_factory=RealDictCursor) as cur:
+            cur.execute(
+                """
+                SELECT s.site_id, s.site_name, s.site_code, s.is_active,
+                       c.mode, c.sandbox_date, c.sandbox_instance_id,
+                       c.ai_mode, c.status, c.updated_at
+                FROM biz.sites s
+                LEFT JOIN biz.site_runtime_context c ON c.site_id = s.site_id
+                ORDER BY s.is_active DESC, s.site_id
+                """
+            )
+            rows = cur.fetchall()
+        conn.commit()
+    except Exception:
+        conn.rollback()
+        raise
+    finally:
+        conn.close()
+
+    return [dict(row) for row in rows]
+
+
+@router.patch("", response_model=RuntimeSwitchResponse)
+async def switch_runtime_context(
+    body: RuntimeSwitchRequest,
+    user: CurrentUser = Depends(get_current_user),
+) -> RuntimeSwitchResponse:
+    """切换门店业务运行上下文。
+
+    切换前会终止当前运行中的 ETL、取消未完成 AI 触发记录。
+    `biz.trigger_jobs` 是全局调度表（无 site_id 列），不随单门店沙箱切换暂停；
+    多门店隔离完全通过 runtime_mode + sandbox_instance_id 实现。
+    """
+    _require_super_admin(user)
+
+    if body.mode == MODE_SANDBOX and body.sandbox_date is None:
+        raise HTTPException(status_code=422, detail="沙箱模式必须设置 sandbox_date")
+    if body.mode == MODE_LIVE and body.sandbox_date is not None:
+        raise HTTPException(status_code=422, detail="live 模式不能设置 sandbox_date")
+    if body.mode == MODE_SANDBOX and body.sandbox_date and body.sandbox_date > date.today():
+        raise HTTPException(status_code=422, detail="sandbox_date 不能晚于真实今天")
+
+    steps: list[RuntimeTransitionStep] = []
+    steps.extend(await _stop_runtime_activity(body.site_id))
+
+    conn = get_connection()
+    try:
+        with conn.cursor() as cur:
+            old_ctx = get_runtime_context(body.site_id, conn=conn)
+            sandbox_instance_id = None
+            if body.mode == MODE_SANDBOX:
+                if body.reset_sandbox or not old_ctx.sandbox_instance_id:
+                    sandbox_instance_id = new_sandbox_instance_id()
+                else:
+                    sandbox_instance_id = old_ctx.sandbox_instance_id
+
+            cur.execute(
+                """
+                INSERT INTO biz.site_runtime_context
+                    (site_id, mode, sandbox_date, sandbox_instance_id, ai_mode,
+                     status, updated_by, updated_at, reason)
+                VALUES (%s, %s, %s, %s, 'live', 'active', %s, NOW(), %s)
+                ON CONFLICT (site_id)
+                DO UPDATE SET
+                    mode = EXCLUDED.mode,
+                    sandbox_date = EXCLUDED.sandbox_date,
+                    sandbox_instance_id = EXCLUDED.sandbox_instance_id,
+                    ai_mode = EXCLUDED.ai_mode,
+                    status = EXCLUDED.status,
+                    updated_by = EXCLUDED.updated_by,
+                    updated_at = NOW(),
+                    reason = EXCLUDED.reason
+                """,
+                (
+                    body.site_id,
+                    body.mode,
+                    body.sandbox_date,
+                    sandbox_instance_id,
+                    user.user_id,
+                    body.reason,
+                ),
+            )
+
+            steps.append(RuntimeTransitionStep(
+                key="biz_triggers_unchanged",
+                title="保持业务触发器",
+                status="skipped",
+                count=0,
+                detail=(
+                    "biz.trigger_jobs 为全局调度表（无 site_id 列），单门店沙箱切换不影响其它门店；"
+                    "沙箱隔离由 runtime_mode + sandbox_instance_id 在数据写入层完成。"
+                ),
+            ))
+
+        conn.commit()
+    except Exception:
+        conn.rollback()
+        logger.exception("切换业务运行上下文失败: site_id=%s", body.site_id)
+        raise
+    finally:
+        conn.close()
+
+    ctx = get_runtime_context(body.site_id)
+    steps.append(RuntimeTransitionStep(
+        key="apply_context",
+        title="写入业务运行上下文",
+        status="success",
+        detail=(
+            f"当前模式={ctx.mode}，业务日期={ctx.business_date}"
+            + (f"，沙箱实例={ctx.sandbox_instance_id}" if ctx.is_sandbox else "")
+        ),
+    ))
+    return RuntimeSwitchResponse(context=_context_response(ctx), steps=steps)
+
+
+async def _stop_runtime_activity(site_id: int) -> list[RuntimeTransitionStep]:
+    """终止切换前仍在运行的 ETL/AI/队列活动。"""
+    steps: list[RuntimeTransitionStep] = []
+
+    # 1. 终止当前进程内 ETL 执行。
+    try:
+        from app.services.task_executor import task_executor
+
+        running_ids = task_executor.get_running_ids()
+        cancelled = 0
+        for execution_id in running_ids:
+            if await task_executor.cancel(execution_id):
+                cancelled += 1
+        steps.append(RuntimeTransitionStep(
+            key="cancel_etl_processes",
+            title="终止当前 ETL 执行",
+            status="success",
+            count=cancelled,
+            detail=f"检测到 {len(running_ids)} 个当前进程内执行，已发送取消信号。",
+        ))
+    except Exception as exc:
+        logger.exception("终止 ETL 执行失败")
+        steps.append(RuntimeTransitionStep(
+            key="cancel_etl_processes",
+            title="终止当前 ETL 执行",
+            status="warning",
+            detail=str(exc)[:300],
+        ))
+
+    # 2. 清理当前门店队列中未完成任务。
+    conn = get_connection()
+    try:
+        with conn.cursor() as cur:
+            cur.execute(
+                """
+                UPDATE task_queue
+                SET status = 'cancelled',
+                    finished_at = NOW(),
+                    error_message = COALESCE(error_message, '') || E'\n[runtime-context] 切换业务运行上下文时取消'
+                WHERE site_id = %s
+                  AND status IN ('pending', 'running')
+                """,
+                (site_id,),
+            )
+            queue_cancelled = cur.rowcount
+        conn.commit()
+        steps.append(RuntimeTransitionStep(
+            key="cancel_task_queue",
+            title="取消 ETL 队列",
+            status="success",
+            count=queue_cancelled,
+            detail="已取消当前门店 pending/running 的 task_queue 记录。",
+        ))
+    except Exception as exc:
+        conn.rollback()
+        logger.exception("取消 ETL 队列失败")
+        steps.append(RuntimeTransitionStep(
+            key="cancel_task_queue",
+            title="取消 ETL 队列",
+            status="warning",
+            detail=str(exc)[:300],
+        ))
+    finally:
+        conn.close()
+
+    # 3. 取消当前站点内存 AI 调用链，并标记未完成 ai_trigger_jobs。
+    try:
+        from app.ai.dispatcher import get_dispatcher
+
+        dispatcher = get_dispatcher()
+        cancelled = dispatcher.cancel_running(site_id)
+        steps.append(RuntimeTransitionStep(
+            key="cancel_ai_runtime",
+            title="取消当前 AI 调用链",
+            status="success",
+            count=cancelled,
+            detail="已取消当前进程内属于该门店的 AI 异步调用链。",
+        ))
+    except Exception as exc:
+        steps.append(RuntimeTransitionStep(
+            key="cancel_ai_runtime",
+            title="取消当前 AI 调用链",
+            status="warning",
+            detail=f"AI Dispatcher 不可用或取消失败：{str(exc)[:240]}",
+        ))
+
+    conn = get_connection()
+    try:
+        with conn.cursor() as cur:
+            cur.execute(
+                """
+                UPDATE biz.ai_trigger_jobs
+                SET status = 'cancelled',
+                    finished_at = NOW(),
+                    error_message = COALESCE(error_message, '') || E'\n[runtime-context] 切换业务运行上下文时取消'
+                WHERE site_id = %s
+                  AND status IN ('pending', 'running')
+                """,
+                (site_id,),
+            )
+            ai_cancelled = cur.rowcount
+        conn.commit()
+        steps.append(RuntimeTransitionStep(
+            key="cancel_ai_jobs",
+            title="标记未完成 AI 触发",
+            status="success",
+            count=ai_cancelled,
+            detail="已将当前门店 pending/running 的 ai_trigger_jobs 标记为 cancelled。",
+        ))
+    except Exception as exc:
+        conn.rollback()
+        logger.exception("标记 AI 触发失败")
+        steps.append(RuntimeTransitionStep(
+            key="cancel_ai_jobs",
+            title="标记未完成 AI 触发",
+            status="warning",
+            detail=str(exc)[:300],
+        ))
+    finally:
+        conn.close()
+
+    return steps
+

apps/backend/app/routers/admin_task_engine.py

@@ -310,6 +310,24 @@ async def reassign_task(
             )
 
         conn.commit()
+
+        # 触发 AI 任务分配链（App4 → App5）
+        try:
+            from app.services.trigger_scheduler import fire_event
+            fire_event(
+                "ai_task_assigned",
+                {
+                    "site_id": task["site_id"],
+                    "member_id": task["member_id"],
+                    "assistant_id": body.to_assistant_id,
+                },
+            )
+        except Exception:
+            logger.exception(
+                "触发 ai_task_assigned 事件失败: task_id=%s new_task_id=%s",
+                task_id, new_task_id,
+            )
+
         return ReassignResponse(success=True, new_task_id=new_task_id)
     except HTTPException:
         conn.rollback()

apps/backend/app/routers/internal_events.py

@@ -85,6 +85,33 @@ async def etl_completed_endpoint(
         logger.exception("ETL 编排 Step2 task_generator 失败")
         errors.append("task_generator failed")
 
+    # Step 3: 触发 AI 财务洞察预生成（App2 × 8 时间维度）
+    # 若请求未带 site_id，查询所有 active site 逐个触发
+    try:
+        from app.services.trigger_scheduler import fire_event
+
+        site_ids: list[int] = []
+        if body.site_id is not None:
+            site_ids = [body.site_id]
+        else:
+            from app.database import get_connection as _gc
+            _c = _gc()
+            try:
+                with _c.cursor() as _cur:
+                    _cur.execute("SELECT DISTINCT site_id FROM biz.trigger_jobs WHERE site_id IS NOT NULL")
+                    site_ids = [r[0] for r in _cur.fetchall()]
+                _c.commit()
+            finally:
+                _c.close()
+
+        for sid in site_ids:
+            try:
+                fire_event("ai_dws_completed", {"site_id": sid})
+            except Exception:
+                logger.exception("触发 ai_dws_completed 失败: site_id=%s", sid)
+    except Exception:
+        logger.exception("ai_dws_completed 事件批量触发失败")
+
     success = len(errors) == 0
     return EtlCompletedResponse(
         success=success,

apps/backend/app/routers/tenant_users.py

@@ -204,13 +204,17 @@ async def list_site_staff(
                     # assumptions: cfg_assistant_level_price 有 level_code→level_name 映射
                     # verify: 弹窗人员下拉显示如 "初级 - 张三 - 手机号 - 入职日期 YYYY-MM-DD"
                     # 先查等级映射配置表（feiqiu-data-rules 规则 6: 禁止硬编码）
+                    # CHANGE 2026-05-02 | 用 business_date 替代 CURRENT_DATE，沙箱按当时生效配置
+                    from app.services.runtime_context import as_runtime_today_param
+                    _ref_date = as_runtime_today_param(site_id)
                     cur.execute(
                         """
                         SELECT DISTINCT level_code, level_name
                           FROM dws.cfg_assistant_level_price
-                         WHERE effective_from <= CURRENT_DATE
-                           AND effective_to >= CURRENT_DATE
-                        """
+                         WHERE effective_from <= %s::date
+                           AND effective_to >= %s::date
+                        """,
+                        (_ref_date, _ref_date),
                     )
                     level_map = {row[0]: row[1] for row in cur.fetchall()}
 

apps/backend/app/routers/xcx_chat.py

@@ -244,27 +244,56 @@ async def chat_stream(
             )
 
             # 流式调用 DashScope Application API
-            async for chunk in client.call_app_stream(
+            # 返回 (text_chunk, session_id_or_none) 元组：累积最后一次 session_id 用于回写
+            latest_session_id: str | None = session_id
+            async for chunk_text, chunk_session_id in client.call_app_stream(
                 app_id=config.app_id_1_chat,
                 prompt=prompt,
                 session_id=session_id,
                 biz_params=biz_params,
             ):
-                full_reply_parts.append(chunk)
+                if chunk_session_id:
+                    latest_session_id = chunk_session_id
+                if not chunk_text:
+                    continue
+                full_reply_parts.append(chunk_text)
                 tokens_total += 1
                 # SSE trace: 每 10 个 token 记录一次
                 record_sse_token(token_count=1, total_tokens=tokens_total)
-                yield f"event: message\ndata: {json.dumps({'token': chunk}, ensure_ascii=False)}\n\n"
+                yield f"event: message\ndata: {json.dumps({'token': chunk_text}, ensure_ascii=False)}\n\n"
 
             # 流结束：拼接完整回复并持久化
             full_reply = "".join(full_reply_parts)
             estimated_tokens = len(full_reply)
 
+            # Phase 1.3：assistant 消息挂 reference_card（若用户从特定详情页入口发起对话）
+            try:
+                from app.ai.references import build_app1_reference_card
+                _ref_card = None
+                _pc = body.page_context or {}
+                _ctx_id = _pc.get("contextId") or _pc.get("taskId") or _pc.get("customerId") or _pc.get("coachId")
+                if body.source_page and _ctx_id:
+                    _ref_card = build_app1_reference_card(body.source_page, _ctx_id)
+            except Exception:
+                logger.warning("构建 reference_card 失败", exc_info=True)
+                _ref_card = None
+
             ai_msg_id, ai_created_at = svc._save_message(
-                body.chat_id, "assistant", full_reply, tokens_used=estimated_tokens,
+                body.chat_id, "assistant", full_reply,
+                tokens_used=estimated_tokens,
+                reference_card=_ref_card,
             )
             svc._update_session_metadata(body.chat_id, full_reply)
 
+            # multi-turn 启用：回写百炼返回的 session_id（若首次对话或服务端更新）
+            if latest_session_id and latest_session_id != session_id:
+                try:
+                    svc.save_session_id(body.chat_id, latest_session_id)
+                except Exception:
+                    logger.warning(
+                        "save_session_id 失败 chat_id=%s", body.chat_id, exc_info=True,
+                    )
+
             # 发送 done 事件
             done_data = json.dumps(
                 {"messageId": ai_msg_id, "createdAt": ai_created_at},

apps/backend/app/routers/xcx_runtime_clock.py

@@ -0,0 +1,61 @@
+# -*- coding: utf-8 -*-
+"""小程序业务时钟路由。
+
+仅用于小程序读取当前门店的"业务日 / 业务年月 / 模式"——sandbox 模式下，
+小程序的 performance / task-list / customer-records 等页面应以 RuntimeContext
+返回的业务时钟为准，禁止再用 ``new Date()`` 构造请求参数。
+
+端点：
+- GET /api/xcx/runtime/clock — 返回当前门店的业务时钟与运行模式（live / sandbox）。
+
+所有端点均需 JWT（approved 状态），但不要求特定模块权限。
+"""
+
+from __future__ import annotations
+
+from fastapi import APIRouter, Depends
+
+from app.auth.dependencies import CurrentUser
+from app.middleware.permission import require_approved
+from app.services.runtime_context import get_runtime_context
+from app.trace.decorators import trace_service
+
+router = APIRouter(prefix="/api/xcx/runtime", tags=["小程序业务时钟"])
+
+
+@router.get("/clock")
+@trace_service("获取业务时钟", "Get business clock")
+async def get_business_clock(
+    user: CurrentUser = Depends(require_approved),
+):
+    """返回当前门店的业务时钟。
+
+    返回示例（live）::
+
+        {
+            "mode": "live",
+            "business_date": "2026-05-02",
+            "business_year": 2026,
+            "business_month": 5,
+            "business_year_month": "2026-05",
+            "is_sandbox": false,
+            "sandbox_date": null
+        }
+
+    sandbox 模式下 ``business_date`` 等于配置的 ``sandbox_date``。
+    小程序页面应使用本接口结果替代 ``new Date()``，以确保 sandbox 模式下
+    展示和请求都对齐到 sandbox_date。
+    """
+    ctx = get_runtime_context(user.site_id)
+    bd = ctx.business_date
+    return {
+        "mode": ctx.mode,
+        "business_date": bd.isoformat(),
+        "business_year": bd.year,
+        "business_month": bd.month,
+        "business_year_month": f"{bd.year:04d}-{bd.month:02d}",
+        "business_now": ctx.business_now.isoformat(),
+        "is_sandbox": ctx.is_sandbox,
+        "sandbox_date": ctx.sandbox_date.isoformat() if ctx.sandbox_date else None,
+        "sandbox_instance_id": ctx.sandbox_instance_id,
+    }

apps/backend/app/schemas/admin_ai.py

@@ -196,6 +196,37 @@ class BatchRunConfirmResponse(BaseModel):
     status: str                         # "started"
 
 
+# ── 按需单 App 执行（/run/{app_type}）──────────────────────
+
+
+class RunAppRequest(BaseModel):
+    """按需执行单个 App 请求体。
+
+    context 字段根据 app_type 不同有不同约束：
+    - app2_finance: site_id + time_dimension + area（area 默认 all）
+    - app3_clue / app7_customer: site_id + member_id
+    - app4_analysis / app5_tactics: site_id + member_id + assistant_id
+    - app6_note: site_id + member_id + note_content + noted_by_name
+    - app8_consolidation: site_id + member_id
+    """
+    site_id: int
+    member_id: int | None = None
+    assistant_id: int | None = None
+    time_dimension: str | None = None
+    area: str | None = None             # App2 专用，默认 all
+    note_content: str | None = None
+    noted_by_name: str | None = None
+    noted_by_created_at: str | None = None
+
+
+class RunAppResponse(BaseModel):
+    """按需执行单个 App 响应。"""
+    app_type: str
+    success: bool
+    result: dict | None = None          # 百炼返回的 JSON（成功时）
+    error: str | None = None            # 错误描述（失败时）
+
+
 # ── 告警 ──────────────────────────────────────────────────
 
 
@@ -211,3 +242,64 @@ class AlertActionResponse(BaseModel):
     """告警操作（确认/忽略）响应。"""
     id: int
     alert_status: str
+
+
+# ── 触发器管理（biz.trigger_jobs）─────────────────────────
+
+
+class TriggerItem(BaseModel):
+    """触发器单条记录。"""
+    id: int
+    job_name: str
+    job_type: str
+    trigger_condition: str              # event / cron / interval
+    trigger_config: dict                # {"event_name": ...} 或 {"cron_expression": ...}
+    status: str                         # enabled / disabled
+    description: str | None = None
+    last_run_at: str | None = None
+    next_run_at: str | None = None
+    last_error: str | None = None
+
+
+class TriggerUpdateRequest(BaseModel):
+    """触发器更新请求（3 个字段至少填一个）。"""
+    status: str | None = None           # enabled / disabled
+    cron_expression: str | None = None  # 标准 5 段 cron
+    description: str | None = None
+
+
+# ── 预热进度（app2_finance 72 组合）───────────────────────
+
+
+class PrewarmMissingItem(BaseModel):
+    """缺失的预热组合项。"""
+    target_id: str                      # this_month__all
+    time_dimension: str
+    area: str
+
+
+class PrewarmProgressResponse(BaseModel):
+    """app2_finance 预热进度响应。"""
+    total: int                          # 固定 72
+    done: int
+    missing: list[PrewarmMissingItem]
+    last_updated: str | None = None
+
+
+# ── 手动事件触发（越过去重）───────────────────────────────
+
+
+class ManualTriggerRequest(BaseModel):
+    """手动触发 AI 事件请求。"""
+    event_type: str                     # consumption / dws_completed / note_created / task_assigned
+    site_id: int
+    member_id: int | None = None
+    assistant_id: int | None = None
+    payload: dict | None = None
+    is_forced: bool = True              # 默认跳过去重
+
+
+class ManualTriggerResponse(BaseModel):
+    """手动事件触发响应。"""
+    trigger_job_id: int
+    status: str = "pending"

apps/backend/app/schemas/runtime_context.py

@@ -0,0 +1,48 @@
+# -*- coding: utf-8 -*-
+"""业务运行上下文 API Schema。"""
+
+from __future__ import annotations
+
+from datetime import date, datetime
+from typing import Literal
+
+from pydantic import BaseModel, Field
+
+
+RuntimeMode = Literal["live", "sandbox"]
+AIMode = Literal["live"]
+
+
+class RuntimeContextResponse(BaseModel):
+    site_id: int
+    mode: RuntimeMode
+    business_day_start_hour: int
+    business_date: date
+    business_now: datetime
+    sandbox_date: date | None = None
+    sandbox_instance_id: str | None = None
+    ai_mode: AIMode = "live"
+    status: str = "active"
+    is_sandbox: bool = False
+
+
+class RuntimeTransitionStep(BaseModel):
+    key: str
+    title: str
+    status: Literal["success", "skipped", "warning", "failed"]
+    detail: str = ""
+    count: int = 0
+
+
+class RuntimeSwitchRequest(BaseModel):
+    site_id: int = Field(..., ge=1)
+    mode: RuntimeMode
+    sandbox_date: date | None = None
+    reset_sandbox: bool = True
+    reason: str | None = Field(default=None, max_length=500)
+
+
+class RuntimeSwitchResponse(BaseModel):
+    context: RuntimeContextResponse
+    steps: list[RuntimeTransitionStep]
+

apps/backend/app/services/ai/admin_service.py

@@ -35,9 +35,21 @@ class AdminAIService:
 
     # ── Dashboard ─────────────────────────────────────────
 
-    async def get_dashboard(self, site_id: int | None = None) -> dict:
-        """聚合所有 Dashboard 数据。"""
-        today_stats = await self._get_today_stats(site_id)
+    async def get_dashboard(
+        self,
+        site_id: int | None = None,
+        range_days: int | None = None,
+        date_from: str | None = None,
+        date_to: str | None = None,
+    ) -> dict:
+        """聚合所有 Dashboard 数据。
+
+        时间范围优先级：
+        1. 若 date_from / date_to 同时给出（指定日期）→ 闭区间 [from, to]
+        2. 若 range_days=N → [CURRENT_DATE - (N-1) days, 现在]
+        3. 默认 range_days=1（今日）
+        """
+        today_stats = await self._get_range_stats(site_id, range_days, date_from, date_to)
         trend_7d = await self._get_7d_trend(site_id)
         app_dist = await self._get_app_distribution(site_id)
         app_health = await self._get_app_health(site_id)
@@ -52,9 +64,32 @@ class AdminAIService:
             "app_health": app_health,
         }
 
-    async def _get_today_stats(self, site_id: int | None) -> dict:
-        """今日调用次数、成功率、Token 消耗、平均延迟。"""
-        site_clause, params = _site_filter(site_id)
+    async def _get_range_stats(
+        self,
+        site_id: int | None,
+        range_days: int | None,
+        date_from: str | None,
+        date_to: str | None,
+    ) -> dict:
+        """指定时间段内的调用次数、成功率、Token 消耗、平均延迟。
+
+        字段名沿用 today_* 前缀以兼容前端 DashboardResponse schema。
+        """
+        site_clause, site_params = _site_filter(site_id)
+
+        if date_from and date_to:
+            time_clause = "created_at >= %s::date AND created_at < (%s::date + INTERVAL '1 day')"
+            time_params: tuple = (date_from, date_to)
+        else:
+            days = range_days if range_days and range_days > 0 else 1
+            time_clause = (
+                "created_at >= CURRENT_DATE - (%s::int - 1) * INTERVAL '1 day' "
+                "AND created_at < CURRENT_DATE + INTERVAL '1 day'"
+            )
+            time_params = (days,)
+
+        params = time_params + site_params
+
         conn = get_connection()
         try:
             with conn.cursor() as cur:
@@ -67,8 +102,7 @@ class AdminAIService:
                         COALESCE(AVG(latency_ms) FILTER (WHERE latency_ms IS NOT NULL), 0)
                                                                           AS avg_latency
                     FROM biz.ai_run_logs
-                    WHERE created_at >= CURRENT_DATE
-                      AND created_at <  CURRENT_DATE + INTERVAL '1 day'
+                    WHERE {time_clause}
                       {site_clause}
                     """,
                     params,
@@ -466,6 +500,22 @@ class AdminAIService:
         finally:
             conn.close()
 
+        # Phase 1.4：广播 cache_invalidated 事件，admin-web / 小程序可实时刷新
+        if affected > 0:
+            try:
+                from app.ai.event_bus import AIEvent, get_event_bus
+                get_event_bus().publish(AIEvent(
+                    type="cache_invalidated",
+                    site_id=site_id,
+                    payload={
+                        "cache_type": app_type,
+                        "member_id": member_id,
+                        "affected": affected,
+                    },
+                ))
+            except Exception:
+                logger.debug("cache_invalidated 事件广播失败", exc_info=True)
+
         return affected
 
     # ── Token 预算 ────────────────────────────────────────
@@ -699,6 +749,140 @@ class AdminAIService:
 
         return "ignored"
 
+    # ── 触发器管理（biz.trigger_jobs）───────────────────────
+
+    async def list_triggers(self) -> list[dict]:
+        """列出所有 AI 相关触发器（job_type 以 ai_ 开头 + task_generator）。
+
+        返回字段：id / job_name / job_type / trigger_condition / trigger_config /
+                 status / description / last_run_at / next_run_at / last_error
+        """
+        conn = get_connection()
+        try:
+            with conn.cursor() as cur:
+                cur.execute(
+                    """
+                    SELECT id, job_name, job_type, trigger_condition,
+                           trigger_config, status, description,
+                           last_run_at, next_run_at, last_error
+                    FROM biz.trigger_jobs
+                    WHERE job_type LIKE 'ai_%' OR job_name = 'task_generator'
+                    ORDER BY trigger_condition DESC, job_name
+                    """
+                )
+                cols = [d[0] for d in cur.description]
+                rows = cur.fetchall()
+            conn.commit()
+        finally:
+            conn.close()
+        return [_row_to_dict(cols, r) for r in rows]
+
+    async def update_trigger(
+        self, trigger_id: int,
+        status_new: str | None = None,
+        cron_expression: str | None = None,
+        description: str | None = None,
+    ) -> dict:
+        """更新触发器：启用/禁用、修改 cron、改描述。
+
+        仅允许修改 ai_ 前缀或 task_generator 的触发器。
+        """
+        if status_new is not None and status_new not in ("enabled", "disabled"):
+            raise ValueError(f"非法 status: {status_new}")
+
+        sets: list[str] = []
+        params: list = []
+        if status_new is not None:
+            sets.append("status = %s")
+            params.append(status_new)
+        if cron_expression is not None:
+            sets.append("trigger_config = jsonb_set(trigger_config, '{cron_expression}', to_jsonb(%s::text))")
+            params.append(cron_expression)
+        if description is not None:
+            sets.append("description = %s")
+            params.append(description)
+
+        if not sets:
+            raise ValueError("至少修改一个字段")
+
+        params.append(trigger_id)
+        conn = get_connection()
+        try:
+            with conn.cursor() as cur:
+                cur.execute(
+                    f"""
+                    UPDATE biz.trigger_jobs
+                    SET {", ".join(sets)}
+                    WHERE id = %s
+                      AND (job_type LIKE 'ai_%%' OR job_name = 'task_generator')
+                    RETURNING id, job_name, job_type, trigger_condition,
+                              trigger_config, status, description,
+                              last_run_at, next_run_at, last_error
+                    """,
+                    params,
+                )
+                row = cur.fetchone()
+                if row is None:
+                    conn.rollback()
+                    raise ValueError("触发器不存在或不可修改")
+                cols = [d[0] for d in cur.description]
+            conn.commit()
+        except Exception:
+            conn.rollback()
+            raise
+        finally:
+            conn.close()
+        return _row_to_dict(cols, row)
+
+    # ── 预热进度（app2_finance 72 组合）──────────────────────
+
+    async def get_prewarm_progress(self, site_id: int) -> dict:
+        """查询 app2_finance 72 组合缓存进度。
+
+        返回：total=72, done=N, missing=[{time_dimension, area}], last_updated
+        """
+        time_dims = (
+            "this_month", "last_month", "this_week", "last_week",
+            "this_quarter", "last_quarter", "last_3_months", "last_6_months",
+        )
+        areas = (
+            "all", "hall", "hallA", "hallB", "hallC",
+            "vip", "snooker", "mahjong", "ktv",
+        )
+        expected = {f"{t}__{a}" for t in time_dims for a in areas}
+
+        conn = get_connection()
+        try:
+            with conn.cursor() as cur:
+                cur.execute(
+                    """
+                    SELECT target_id, max(created_at) AS last_updated
+                    FROM biz.ai_cache
+                    WHERE cache_type = 'app2_finance'
+                      AND site_id = %s
+                      AND target_id LIKE %s ESCAPE '\\'
+                    GROUP BY target_id
+                    """,
+                    (site_id, r'%\_\_%'),
+                )
+                rows = cur.fetchall()
+            conn.commit()
+        finally:
+            conn.close()
+
+        done_map = {r[0]: r[1] for r in rows}
+        missing = sorted(expected - set(done_map.keys()))
+        last = max(done_map.values()) if done_map else None
+        return {
+            "total": len(expected),
+            "done": len(expected & set(done_map.keys())),
+            "missing": [
+                {"target_id": m, "time_dimension": m.split("__")[0], "area": m.split("__")[1]}
+                for m in missing
+            ],
+            "last_updated": last.isoformat() if last else None,
+        }
+
 
 # ── 工具函数 ──────────────────────────────────────────────
 

apps/backend/app/services/board_service.py

@@ -195,6 +195,7 @@ from typing import Any
 from fastapi import HTTPException
 
 from app.services import fdw_queries
+from app.services.runtime_context import get_runtime_context, task_runtime_filter
 
 logger = logging.getLogger(__name__)
 
@@ -260,7 +261,8 @@ async def get_coach_board(
             detail="最近6个月不支持客源储值排序",
         )
 
-    start_date, end_date = _calc_date_range(time)
+    runtime_ctx = get_runtime_context(site_id)
+    start_date, end_date = _calc_date_range(time, ref_date=runtime_ctx.business_date)
     start_str = str(start_date)
     end_str = str(end_date)
 
@@ -415,20 +417,22 @@ def _query_coach_tasks(
 
     result: dict[int, dict] = {}
     try:
+        runtime_clause, runtime_params = task_runtime_filter(site_id, conn=conn)
         with conn.cursor() as cur:
             # 狭义召回+回访完成数：均从 coach_tasks 统计，status='completed' 表示助教亲自完成
             cur.execute(
-                """
+                f"""
                 SELECT assistant_id, task_type, COUNT(*) AS cnt
                 FROM biz.coach_tasks
                 WHERE assistant_id = ANY(%s)
                   AND site_id = %s
+                  {runtime_clause}
                   AND completed_at >= %s::date
                   AND completed_at < (%s::date + INTERVAL '1 day')::timestamptz
                   AND status = 'completed'
                 GROUP BY assistant_id, task_type
                 """,
-                (assistant_ids, site_id, start_date, end_date),
+                [assistant_ids, site_id, *runtime_params, start_date, end_date],
             )
             for row in cur.fetchall():
                 aid, task_type, cnt = row[0], row[1], row[2] or 0
@@ -470,13 +474,27 @@ def _batch_ideal_days(conn: Any, site_id: int, member_ids: list[int]) -> dict[in
     return result
 
 
-def _batch_coach_details(conn: Any, site_id: int, member_ids: list[int]) -> dict[int, list[dict]]:
-    """批量查询客户-助教服务明细（loyal 维度 coachDetails 用）。每个客户前 5 个。"""
+def _batch_coach_details(
+    conn: Any,
+    site_id: int,
+    member_ids: list[int],
+    *,
+    ref_date: date | None = None,
+) -> dict[int, list[dict]]:
+    """批量查询客户-助教服务明细（loyal 维度 coachDetails 用）。每个客户前 5 个。
+
+    ref_date 默认从 RuntimeContext 取业务日，用于把 60 天消费窗口的上界落到 ``ref_date`` 上，
+    避免 sandbox 模式下读到 sandbox_date 之后的真实消费。
+    """
     from app.services.fdw_queries import _fdw_context
+    from app.services.runtime_context import as_runtime_today_param
+
+    ref = ref_date or as_runtime_today_param(site_id, conn=conn)
     result: dict[int, list[dict]] = {mid: [] for mid in member_ids}
     try:
         with _fdw_context(conn, site_id) as cur:
             # CHANGE 2026-03-29 | coach_spend 改为从 dwd_assistant_service_log 聚合 60 天消费
+            # CHANGE 2026-05-02 | 用 ref_date（业务日）替代 CURRENT_DATE，沙箱不读「未来」
             cur.execute(
                 """
                 SELECT ri.member_id,
@@ -493,7 +511,8 @@ def _batch_coach_details(conn: Any, site_id: int, member_ids: list[int]) -> dict
                            SUM(ledger_amount) AS spend_60d
                     FROM app.v_dwd_assistant_service_log
                     WHERE is_delete = 0
-                      AND create_time >= CURRENT_DATE - INTERVAL '60 days'
+                      AND create_time >= (%s::date - INTERVAL '60 days')
+                      AND create_time <  (%s::date + INTERVAL '1 day')
                       AND tenant_member_id = ANY(%s)
                     GROUP BY tenant_member_id, site_assistant_id
                 ) s60 ON ri.member_id = s60.tenant_member_id
@@ -502,7 +521,7 @@ def _batch_coach_details(conn: Any, site_id: int, member_ids: list[int]) -> dict
                   AND (da.leave_status IS NULL OR da.leave_status = 0)
                 ORDER BY ri.member_id, ri.rs_display DESC
                 """,
-                (member_ids, member_ids),
+                (ref, ref, member_ids, member_ids),
             )
             for row in cur.fetchall():
                 mid = row[0]
@@ -690,7 +709,8 @@ async def get_finance_board(
     - area≠all 时 overview 覆盖逻辑保留
     - compare=1 时对上期执行同样缓存/日粒度逻辑
     """
-    start_date, end_date = _calc_date_range(time)
+    runtime_ctx = get_runtime_context(site_id)
+    start_date, end_date = _calc_date_range(time, ref_date=runtime_ctx.business_date)
     start_str = str(start_date)
     end_str = str(end_date)
 

apps/backend/app/services/chat_service.py

@@ -234,23 +234,14 @@ class ChatService:
                     INSERT INTO biz.ai_conversations
                         (user_id, nickname, app_id, site_id, context_type, context_id)
                     VALUES (%s, %s, %s, %s, %s, %s)
-                    RETURNING id, EXTRACT(EPOCH FROM created_at)::bigint
+                    RETURNING id
                     """,
                     (str(user_id), nickname, APP_ID, site_id, context_type, context_id),
                 )
-                result = cur.fetchone()
-                new_id = result[0]
-                created_ts = result[1]
-
-                # 生成 session_id 并回写（格式：conv_{id}_{timestamp}）
-                session_id = f"conv_{new_id}_{created_ts}"
-                cur.execute(
-                    """
-                    UPDATE biz.ai_conversations SET session_id = %s WHERE id = %s
-                    """,
-                    (session_id, new_id),
-                )
+                new_id = cur.fetchone()[0]
 
+                # session_id 初始保持 NULL，首次对话由百炼返回后再回写。
+                # 参见 P14 spec §2.3：后端不再自生 session_id，交由百炼云端管理。
                 conn.commit()
                 return new_id
         except Exception:
@@ -274,6 +265,34 @@ class ChatService:
         finally:
             conn.close()
 
+    @trace_service("保存百炼 session_id", "Save bailian session ID")
+    def save_session_id(self, chat_id: int, session_id: str) -> None:
+        """流式回复完成后，将百炼返回的 session_id 回写 ai_conversations。
+
+        multi-turn 启用：
+        - 首次对话 session_id=NULL → 百炼分配新 session → 这里回写
+        - 下次对话 get_session_id 返回该值 → 传给百炼关联历史上下文
+
+        幂等：同一对话多次调用覆盖最新 session_id（通常保持稳定）。
+        """
+        if not session_id:
+            return
+        conn = get_connection()
+        try:
+            with conn.cursor() as cur:
+                cur.execute(
+                    "UPDATE biz.ai_conversations SET session_id = %s WHERE id = %s",
+                    (session_id, chat_id),
+                )
+            conn.commit()
+        except Exception:
+            conn.rollback()
+            logger.warning(
+                "保存 session_id 失败: chat_id=%s", chat_id, exc_info=True,
+            )
+        finally:
+            conn.close()
+
     # ------------------------------------------------------------------
     # CHAT-2: 消息列表
     # ------------------------------------------------------------------
@@ -662,7 +681,10 @@ class ChatService:
         """查询客户近 30 天消费金额（items_sum 口径）。
 
         ⚠️ DWD-DOC 规则 1: 使用 ledger_amount（items_sum 口径），禁用 consume_money。
+        CHANGE 2026-05-02 | 用 business_date 替代 CURRENT_DATE，沙箱不读「未来」消费。
         """
+        from app.services.runtime_context import as_runtime_today_param
+        ref = as_runtime_today_param(site_id, conn=conn)
         with fdw_queries._fdw_context(conn, site_id) as cur:
             cur.execute(
                 """
@@ -670,16 +692,22 @@ class ChatService:
                 FROM app.v_dwd_assistant_service_log
                 WHERE tenant_member_id = %s
                   AND is_delete = 0
-                  AND create_time >= (CURRENT_DATE - INTERVAL '30 days')::timestamptz
+                  AND create_time >= (%s::date - INTERVAL '30 days')::timestamptz
+                  AND create_time <  (%s::date + INTERVAL '1 day')::timestamptz
                 """,
-                (member_id,),
+                (member_id, ref, ref),
             )
             row = cur.fetchone()
         return Decimal(str(row[0])) if row and row[0] is not None else None
 
     @staticmethod
     def _get_visit_count_30d(conn: Any, site_id: int, member_id: int) -> int | None:
-        """查询客户近 30 天到店次数。"""
+        """查询客户近 30 天到店次数。
+
+        CHANGE 2026-05-02 | 用 business_date 替代 CURRENT_DATE，沙箱不读「未来」到店。
+        """
+        from app.services.runtime_context import as_runtime_today_param
+        ref = as_runtime_today_param(site_id, conn=conn)
         with fdw_queries._fdw_context(conn, site_id) as cur:
             cur.execute(
                 """
@@ -687,9 +715,10 @@ class ChatService:
                 FROM app.v_dwd_assistant_service_log
                 WHERE tenant_member_id = %s
                   AND is_delete = 0
-                  AND create_time >= (CURRENT_DATE - INTERVAL '30 days')::timestamptz
+                  AND create_time >= (%s::date - INTERVAL '30 days')::timestamptz
+                  AND create_time <  (%s::date + INTERVAL '1 day')::timestamptz
                 """,
-                (member_id,),
+                (member_id, ref, ref),
             )
             row = cur.fetchone()
         return int(row[0]) if row and row[0] is not None else None

apps/backend/app/services/coach_service.py

@@ -147,7 +147,9 @@ async def get_coach_detail(coach_id: int, site_id: int) -> dict:
         if not assistant_info:
             raise HTTPException(status_code=404, detail="助教不存在")
 
-        now = datetime.date.today()
+        # 业务时间锚：sandbox 模式下用 business_date，避免读到 sandbox_date 之后真实绩效
+        from app.services.runtime_context import as_runtime_today_param
+        now = as_runtime_today_param(site_id, conn=conn)
 
         # 门店名称（用于小程序 banner 展示，跟随被查看助教所在门店）
         # 必须在所有 fdw 查询前执行：后续任意 fdw 查询失败会污染事务
@@ -713,7 +715,9 @@ def _build_history_months(
     4. 本月 estimated=True，历史月份 estimated=False
     5. 格式化：customers→"22人"，hours→"87.5h"，salary→"¥6,950"
     """
-    now = datetime.date.today()
+    # 业务时间锚：sandbox 模式下用 business_date 计算最近 6 个月
+    from app.services.runtime_context import as_runtime_today_param
+    now = as_runtime_today_param(site_id, conn=conn)
 
     # 生成最近 6 个月的月份列表（含本月）
     months: list[str] = []

apps/backend/app/services/customer_service.py

@@ -501,6 +501,9 @@ def _build_coach_tasks(
         logger.warning("批量查询助教信息失败", exc_info=True)
 
     # 批量查询 60 天统计（一次 FDW 查询）
+    # CHANGE 2026-05-02 | 用 business_date 替代 CURRENT_DATE，沙箱不读「未来」
+    from app.services.runtime_context import as_runtime_today_param
+    ref_date = as_runtime_today_param(site_id, conn=conn)
     stats_map: dict = {}
     try:
         with fdw_queries._fdw_context(conn, site_id) as cur:
@@ -513,10 +516,11 @@ def _build_coach_tasks(
                 WHERE tenant_member_id = %s
                   AND site_assistant_id = ANY(%s)
                   AND is_delete = 0
-                  AND create_time >= CURRENT_DATE - INTERVAL '60 days'
+                  AND create_time >= (%s::date - INTERVAL '60 days')::timestamptz
+                  AND create_time <  (%s::date + INTERVAL '1 day')::timestamptz
                 GROUP BY site_assistant_id
                 """,
-                (customer_id, assistant_ids),
+                (customer_id, assistant_ids, ref_date, ref_date),
             )
             for row in cur.fetchall():
                 svc = int(row[1]) if row[1] else 0

apps/backend/app/services/fdw_queries.py

@@ -80,7 +80,7 @@ def _get_etl_connection(site_id: int):
 @contextmanager
 def _fdw_context(conn: Any, site_id: int, *, etl_conn: Any = None):
     """
-    上下文管理器：直连 ETL 库 + SET LOCAL app.current_site_id。
+    上下文管理器：直连 ETL 库 + SET LOCAL app.current_site_id + app.current_business_date。
 
     ⚠️ 不使用 zqyy_app 的 fdw_etl.* foreign table，而是直连 ETL 库
     查询 app.v_* RLS 视图。原因：postgres_fdw 不传递自定义 GUC 参数
@@ -91,7 +91,31 @@ def _fdw_context(conn: Any, site_id: int, *, etl_conn: Any = None):
 
     CHANGE 2026-03-26 | ETL 连接复用：传入 etl_conn 时复用已有连接（不关闭），
     不传时新建连接并在 yield 后自动关闭。避免同一请求内多次新建连接（每次 ~2.6s）。
+    CHANGE 2026-05-02 | 同时设置 app.current_business_date / app.current_runtime_mode，
+    供 RLS 视图层（C 方案）做日期上界裁剪。conn=None 时降级 live。
     """
+    from app.services.runtime_context import (
+        MODE_LIVE,
+        MODE_SANDBOX,
+        get_runtime_context,
+    )
+
+    # 业务日：优先从 zqyy_app 业务库的 RuntimeContext 读取；conn 不可用时降级为系统今天
+    bd_str = ""
+    rt_mode = MODE_LIVE
+    try:
+        if conn is not None:
+            ctx = get_runtime_context(site_id, conn=conn)
+            bd_str = ctx.business_date.isoformat()
+            rt_mode = MODE_SANDBOX if ctx.is_sandbox else MODE_LIVE
+        else:
+            from datetime import date as _date
+            bd_str = _date.today().isoformat()
+    except Exception:
+        from datetime import date as _date
+        bd_str = _date.today().isoformat()
+        rt_mode = MODE_LIVE
+
     owned = etl_conn is None
     if owned:
         etl_conn = _get_etl_connection(site_id)
@@ -99,6 +123,8 @@ def _fdw_context(conn: Any, site_id: int, *, etl_conn: Any = None):
         with etl_conn.cursor() as cur:
             cur.execute("BEGIN")
             cur.execute("SET LOCAL app.current_site_id = %s", (str(site_id),))
+            cur.execute("SET LOCAL app.current_business_date = %s", (bd_str,))
+            cur.execute("SET LOCAL app.current_runtime_mode = %s", (rt_mode,))
             yield cur
         etl_conn.commit()
     finally:
@@ -180,33 +206,53 @@ def get_last_visit_days(
     """
     批量查询客户距上次到店天数。
 
-    来源: app.v_dws_member_consumption_summary.days_since_last（基于结算单）。
-    FIX: 原查 v_dwd_assistant_service_log 导致无助教服务的客户缺失到店记录。
+    来源: app.v_dws_member_consumption_summary。
     consumption_summary 按 stat_date 有多行快照，取最新一行。
 
+    CHANGE 2026-05-02 | 修复客户看板「最近到店」数据不准的问题：
+    - 旧版直接用 days_since_last（ETL 在 stat_date 那天预计算的快照值）。
+      若 ETL 没跑、跑得迟、或 sandbox_date 与 stat_date 不一致，结果就会严重失真。
+    - 新版改为实时计算：``business_date - last_consume_date``，
+      仅取 ``stat_date <= business_date`` 的快照行，沙箱模式下也能拿到一致结果。
+
     返回 {member_id: days_since_visit} 映射，无记录的会员不在结果中。
     """
     if not member_ids:
         return {}
 
+    from app.services.runtime_context import as_runtime_today_param
+
+    ref_date = as_runtime_today_param(site_id, conn=conn)
+
     result: dict[int, int | None] = {}
     with _fdw_context(conn, site_id, etl_conn=etl_conn) as cur:
         cur.execute(
             """
-            SELECT member_id, days_since_last
+            SELECT DISTINCT ON (member_id)
+                   member_id,
+                   last_consume_date,
+                   stat_date
             FROM app.v_dws_member_consumption_summary
             WHERE member_id = ANY(%s)
-              AND days_since_last IS NOT NULL
+              AND stat_date <= %s
             ORDER BY member_id, stat_date DESC
             """,
-            (member_ids,),
+            (member_ids, ref_date),
         )
-        seen: set[int] = set()
         for row in cur.fetchall():
             mid = row[0]
-            if mid not in seen:
-                seen.add(mid)
-                result[mid] = row[1]
+            last_consume = row[1]
+            if last_consume is None:
+                result[mid] = None
+                continue
+            try:
+                # last_consume_date 在 DWS 中是 date；少数实现可能给 timestamp，统一裁剪
+                if hasattr(last_consume, "date"):
+                    last_consume = last_consume.date()
+                days = (ref_date - last_consume).days
+                result[mid] = max(days, 0)
+            except Exception:
+                result[mid] = None
 
     return result
 
@@ -420,22 +466,33 @@ def batch_query_for_task_list(
 
             # 3. 最后到店天数（基于消费汇总表，口径=结算单）
             # FIX: 原查 v_dwd_assistant_service_log 导致无助教服务的客户缺失到店记录
+            # CHANGE 2026-05-02 | 实时按 business_date - last_consume_date 计算，
+            #                     不再依赖 ETL 预计算的 days_since_last（解决看板显示偏差）。
+            from app.services.runtime_context import as_runtime_today_param
+            _ref_date = as_runtime_today_param(site_id, conn=conn)
             cur.execute(
                 """
-                SELECT member_id, days_since_last
+                SELECT DISTINCT ON (member_id)
+                       member_id, last_consume_date, stat_date
                 FROM app.v_dws_member_consumption_summary
                 WHERE member_id = ANY(%s)
-                  AND days_since_last IS NOT NULL
+                  AND stat_date <= %s
                 ORDER BY member_id, stat_date DESC
                 """,
-                (member_ids,),
+                (member_ids, _ref_date),
             )
-            seen_members: set[int] = set()
             for row in cur.fetchall():
                 mid = row[0]
-                if mid not in seen_members:
-                    seen_members.add(mid)
-                    last_visit_map[mid] = row[1]
+                last_consume = row[1]
+                if last_consume is None:
+                    last_visit_map[mid] = None
+                    continue
+                try:
+                    if hasattr(last_consume, "date"):
+                        last_consume = last_consume.date()
+                    last_visit_map[mid] = max((_ref_date - last_consume).days, 0)
+                except Exception:
+                    last_visit_map[mid] = None
 
             # 4. RS 指数
             cur.execute(
@@ -486,10 +543,11 @@ def batch_query_for_task_list(
                 WHERE sl.site_assistant_id = %s
                   AND sl.tenant_member_id = ANY(%s)
                   AND sl.is_delete = 0
-                  AND sl.create_time >= (CURRENT_DATE - INTERVAL '60 days')::timestamptz
+                  AND sl.create_time >= (%s::date - INTERVAL '60 days')::timestamptz
+                  AND sl.create_time <  (%s::date + INTERVAL '1 day')::timestamptz
                 GROUP BY sl.tenant_member_id
                 """,
-                (assistant_id, member_ids),
+                (assistant_id, member_ids, _ref_date, _ref_date),
             )
             for row in cur.fetchall():
                 recent60d_map[row[0]] = {
@@ -559,15 +617,19 @@ def batch_query_for_task_list(
 
         # 8. 绩效档位配置（用于构建 tier_nodes + bonus_money 计算）
         # CHANGE 2026-03-24 | 增加 bonus_deduction_ratio 用于打赏课抽成差额计算
+        # CHANGE 2026-05-02 | 用 business_date 替代 CURRENT_DATE，沙箱按当时生效档位
+        from app.services.runtime_context import as_runtime_today_param as _rt_today
+        _ref_date = _rt_today(site_id, conn=conn)
         cur.execute(
             """
             SELECT tier_id, tier_code, tier_name, tier_level,
                    min_hours, max_hours, base_deduction, bonus_deduction_ratio
             FROM app.v_cfg_performance_tier
-            WHERE effective_from <= CURRENT_DATE
-              AND effective_to >= CURRENT_DATE
+            WHERE effective_from <= %s::date
+              AND effective_to >= %s::date
             ORDER BY tier_level
-            """
+            """,
+            (_ref_date, _ref_date),
         )
         tier_rows = cur.fetchall()
         performance_tiers = [
@@ -640,17 +702,21 @@ def get_performance_tiers(
 
     返回 [{tier_id, tier_code, tier_name, tier_level, min_hours, max_hours,
            base_deduction, bonus_deduction_ratio}, ...]。
+    CHANGE 2026-05-02 | 用 business_date 替代 CURRENT_DATE，沙箱按当时生效档位
     """
+    from app.services.runtime_context import as_runtime_today_param as _rt_today
+    ref_date = _rt_today(site_id, conn=conn)
     with _fdw_context(conn, site_id) as cur:
         cur.execute(
             """
             SELECT tier_id, tier_code, tier_name, tier_level,
                    min_hours, max_hours, base_deduction, bonus_deduction_ratio
             FROM app.v_cfg_performance_tier
-            WHERE effective_from <= CURRENT_DATE
-              AND effective_to >= CURRENT_DATE
+            WHERE effective_from <= %s::date
+              AND effective_to >= %s::date
             ORDER BY tier_level
-            """
+            """,
+            (ref_date, ref_date),
         )
         rows = cur.fetchall()
 
@@ -680,15 +746,18 @@ def get_level_map(conn: Any, site_id: int) -> dict[int, str]:
     查询失败时返回空 dict（调用方应优雅降级）。
     """
     try:
+        from app.services.runtime_context import as_runtime_today_param as _rt_today
+        ref_date = _rt_today(site_id, conn=conn)
         with _fdw_context(conn, site_id) as cur:
             cur.execute(
                 """
                 SELECT DISTINCT level_code, level_name
                 FROM app.v_cfg_assistant_level_price
-                WHERE effective_from <= CURRENT_DATE
-                  AND effective_to >= CURRENT_DATE
+                WHERE effective_from <= %s::date
+                  AND effective_to >= %s::date
                 ORDER BY level_code
-                """
+                """,
+                (ref_date, ref_date),
             )
             return {row[0]: row[1] for row in cur.fetchall()}
     except Exception:
@@ -1198,8 +1267,11 @@ def get_coach_60d_stats(
 
     来源: app.v_dwd_assistant_service_log。
     ⚠️ 废单排除: is_delete = 0。
+    CHANGE 2026-05-02 | 用 business_date 替代 CURRENT_DATE，沙箱不读「未来」60 天。
     返回 {service_count, total_hours, avg_hours}。
     """
+    from app.services.runtime_context import as_runtime_today_param
+    ref_date = as_runtime_today_param(site_id, conn=conn)
     with _fdw_context(conn, site_id) as cur:
         cur.execute(
             """
@@ -1212,9 +1284,10 @@ def get_coach_60d_stats(
             WHERE site_assistant_id = %s
               AND tenant_member_id = %s
               AND is_delete = 0
-              AND create_time >= (CURRENT_DATE - INTERVAL '60 days')::timestamptz
+              AND create_time >= (%s::date - INTERVAL '60 days')::timestamptz
+              AND create_time <  (%s::date + INTERVAL '1 day')::timestamptz
             """,
-            (assistant_id, member_id),
+            (assistant_id, member_id, ref_date, ref_date),
         )
         row = cur.fetchone()
     if not row:
@@ -1917,14 +1990,17 @@ def get_customer_board_recall(
         total = cur.fetchone()[0]
 
         # 分页数据
+        # CHANGE 2026-05-02 | elapsed_days/overdue_days 用 business_date 替代 CURRENT_DATE
+        from app.services.runtime_context import as_runtime_today_param as _rt_today
+        ref_date = _rt_today(site_id, conn=conn)
         offset = (page - 1) * page_size
         cur.execute(
             f"""
             SELECT wi.member_id,
                    dm.nickname,
                    wi.ideal_interval_days,
-                   CURRENT_DATE - wi.last_visit_time::date AS elapsed_days,
-                   (CURRENT_DATE - wi.last_visit_time::date) - COALESCE(wi.ideal_interval_days, 0) AS overdue_days,
+                   %s::date - wi.last_visit_time::date AS elapsed_days,
+                   (%s::date - wi.last_visit_time::date) - COALESCE(wi.ideal_interval_days, 0) AS overdue_days,
                    wi.visits_30d,
                    wi.display_score,
                    COALESCE(ca.balance, 0) AS balance
@@ -1937,11 +2013,11 @@ def get_customer_board_recall(
                 WHERE scd2_is_current = 1
                 GROUP BY tenant_member_id
             ) ca ON wi.member_id = ca.tenant_member_id
-            WHERE 1=1 {proj_clause}
+            WHERE wi.last_visit_time <= %s::date + INTERVAL '1 day' {proj_clause}
             ORDER BY wi.display_score DESC, wi.member_id
             LIMIT %s OFFSET %s
             """,
-            (*proj_params, page_size, offset),
+            (ref_date, ref_date, ref_date, *proj_params, page_size, offset),
         )
         items = []
         for row in cur.fetchall():
@@ -2165,6 +2241,10 @@ def get_customer_board_recharge(
         )
         total = cur.fetchone()[0]
 
+        # CHANGE 2026-05-02 | 60 天充值窗口、stat_date、pay_time 全部按 business_date 截断
+        from app.services.runtime_context import as_runtime_today_param
+        ref_date = as_runtime_today_param(site_id, conn=conn)
+
         offset = (page - 1) * page_size
         cur.execute(
             f"""
@@ -2173,7 +2253,8 @@ def get_customer_board_recharge(
                    MAX(ro.pay_time::date) AS last_recharge_date,
                    SUM(ro.pay_amount) AS recharge_amount,
                    COUNT(*) FILTER (
-                       WHERE ro.pay_time >= CURRENT_DATE - INTERVAL '60 days'
+                       WHERE ro.pay_time >= %s::date - INTERVAL '60 days'
+                         AND ro.pay_time <  %s::date + INTERVAL '1 day'
                    ) AS recharges_60d,
                    COALESCE(ca_agg.balance, 0) AS current_balance,
                    cs.days_since_last
@@ -2190,15 +2271,16 @@ def get_customer_board_recharge(
                 SELECT cs2.days_since_last
                 FROM app.v_dws_member_consumption_summary cs2
                 WHERE cs2.member_id = ro.member_id
+                  AND cs2.stat_date <= %s
                 ORDER BY cs2.stat_date DESC
                 LIMIT 1
             ) cs ON true
-            WHERE 1=1 {proj_clause}
+            WHERE ro.pay_time <= %s::date + INTERVAL '1 day' {proj_clause}
             GROUP BY ro.member_id, dm.nickname, ca_agg.balance, cs.days_since_last
             ORDER BY MAX(ro.pay_time::date) DESC, ro.member_id
             LIMIT %s OFFSET %s
             """,
-            (*proj_params, page_size, offset),
+            (ref_date, ref_date, ref_date, ref_date, *proj_params, page_size, offset),
         )
         items = []
         for row in cur.fetchall():
@@ -2228,6 +2310,13 @@ def get_customer_board_recent(
     不再硬编码为 0。来源: v_dws_member_visit_detail + v_dim_member + v_dws_member_winback_index。
     按 last_visit_date 降序。
     """
+    # CHANGE 2026-05-02 | 客户看板「最近到店」修复：
+    # 1) WHERE/COUNT 中的 30/60 天窗口按 business_date 计算，沙箱不读「未来」到店；
+    # 2) days_ago 用 business_date - last_visit_date，与窗口对齐。
+    from app.services.runtime_context import as_runtime_today_param
+
+    ref_date = as_runtime_today_param(site_id, conn=conn)
+
     proj_clause, proj_params = _project_filter_clause(project, "vd.member_id")
 
     with _fdw_context(conn, site_id) as cur:
@@ -2235,9 +2324,9 @@ def get_customer_board_recent(
             f"""
             SELECT COUNT(DISTINCT vd.member_id)
             FROM app.v_dws_member_visit_detail vd
-            WHERE 1=1 {proj_clause}
+            WHERE vd.visit_date <= %s {proj_clause}
             """,
-            proj_params,
+            (ref_date, *proj_params),
         )
         total = cur.fetchone()[0]
 
@@ -2248,11 +2337,11 @@ def get_customer_board_recent(
                 SELECT vd.member_id,
                        MAX(vd.visit_date) AS last_visit_date,
                        COUNT(*) AS total_visits,
-                       COUNT(*) FILTER (WHERE vd.visit_date >= CURRENT_DATE - INTERVAL '30 days') AS visits_30d,
-                       COUNT(*) FILTER (WHERE vd.visit_date >= CURRENT_DATE - INTERVAL '60 days') AS visits_60d,
+                       COUNT(*) FILTER (WHERE vd.visit_date >= %s::date - INTERVAL '30 days') AS visits_30d,
+                       COUNT(*) FILTER (WHERE vd.visit_date >= %s::date - INTERVAL '60 days') AS visits_60d,
                        AVG(vd.total_consume) AS avg_spend
                 FROM app.v_dws_member_visit_detail vd
-                WHERE 1=1 {proj_clause}
+                WHERE vd.visit_date <= %s {proj_clause}
                 GROUP BY vd.member_id
             )
             SELECT ma.member_id,
@@ -2271,14 +2360,13 @@ def get_customer_board_recent(
             ORDER BY ma.last_visit_date DESC, ma.member_id
             LIMIT %s OFFSET %s
             """,
-            (*proj_params, page_size, offset),
+            (ref_date, ref_date, ref_date, *proj_params, page_size, offset),
         )
         items = []
         for row in cur.fetchall():
             last_visit = row[2]
-            # CHANGE 2026-03-29 | 补充 days_ago（距今天数）和 visits_60d
-            from datetime import date as _date
-            days_ago = (_date.today() - last_visit).days if last_visit else None
+            # CHANGE 2026-05-02 | days_ago 按 business_date 计算，沙箱与窗口对齐
+            days_ago = (ref_date - last_visit).days if last_visit else None
             items.append({
                 "member_id": row[0],
                 "name": row[1] or "",
@@ -2378,6 +2466,10 @@ def get_customer_board_freq60(
     按 visit_count_60d 降序。
     CHANGE 2026-04-08 | Fix：同 spend60，DISTINCT ON 取最新快照。
     """
+    # CHANGE 2026-05-02 | freq60 全链路按 business_date 截断（stat_date <= ref_date + 8 周窗口）
+    from app.services.runtime_context import as_runtime_today_param
+    ref_date = as_runtime_today_param(site_id, conn=conn)
+
     proj_clause, proj_params = _project_filter_clause(project, "cs.member_id")
 
     with _fdw_context(conn, site_id) as cur:
@@ -2387,11 +2479,11 @@ def get_customer_board_freq60(
             FROM (
                 SELECT DISTINCT ON (cs.member_id) cs.member_id
                 FROM app.v_dws_member_consumption_summary cs
-                WHERE 1=1 {proj_clause}
+                WHERE cs.stat_date <= %s {proj_clause}
                 ORDER BY cs.member_id, cs.stat_date DESC
             ) sub
             """,
-            proj_params,
+            (ref_date, *proj_params),
         )
         total = cur.fetchone()[0]
 
@@ -2402,7 +2494,7 @@ def get_customer_board_freq60(
                 SELECT DISTINCT ON (cs.member_id)
                        cs.member_id, cs.visit_count_60d, cs.consume_amount_60d
                 FROM app.v_dws_member_consumption_summary cs
-                WHERE 1=1 {proj_clause}
+                WHERE cs.stat_date <= %s {proj_clause}
                 ORDER BY cs.member_id, cs.stat_date DESC
             )
             SELECT cs.member_id,
@@ -2415,7 +2507,7 @@ def get_customer_board_freq60(
             ORDER BY cs.visit_count_60d DESC, cs.member_id
             LIMIT %s OFFSET %s
             """,
-            (*proj_params, page_size, offset),
+            (ref_date, *proj_params, page_size, offset),
         )
         items = []
         member_ids = []
@@ -2436,21 +2528,31 @@ def get_customer_board_freq60(
 
         # 批量查询 8 周到店数据
         if member_ids:
-            weekly_map = _get_weekly_visits_batch(cur, member_ids)
+            weekly_map = _get_weekly_visits_batch(cur, member_ids, ref_date=ref_date)
             for item in items:
                 item["weekly_visits"] = weekly_map.get(item["member_id"], _empty_weekly())
 
     return {"items": items, "total": total, "page": page, "page_size": page_size}
 
 
-def _get_weekly_visits_batch(cur: Any, member_ids: list[int]) -> dict[int, list[dict]]:
+def _get_weekly_visits_batch(
+    cur: Any, member_ids: list[int], *, ref_date: Any = None,
+) -> dict[int, list[dict]]:
     """
     批量查询客户最近 8 周的到店次数（用于 freq60 维度柱状图）。
 
     CHANGE 2026-04-07 | Fix-5：数据源从 v_dwd_assistant_service_log 改为
     v_dwd_settlement_head（settle_type IN (1,3)），与汇总维度口径一致。
+    CHANGE 2026-05-02 | 8 周窗口锚定 ref_date（业务日），沙箱不读「未来」。
     返回 {member_id: [{val: int, pct: int}, ...]}，固定 8 个元素。
     """
+    from datetime import date as _date, timedelta as _timedelta
+
+    if ref_date is None:
+        ref_date = _date.today()
+    elif hasattr(ref_date, "date") and not isinstance(ref_date, _date):
+        ref_date = ref_date.date()
+
     cur.execute(
         """
         WITH weekly AS (
@@ -2460,14 +2562,15 @@ def _get_weekly_visits_batch(cur: Any, member_ids: list[int]) -> dict[int, list[
             FROM app.v_dwd_settlement_head
             WHERE member_id = ANY(%s)
               AND settle_type IN (1, 3)
-              AND pay_time >= CURRENT_DATE - INTERVAL '56 days'
+              AND pay_time >= %s::date - INTERVAL '56 days'
+              AND pay_time <  %s::date + INTERVAL '1 day'
             GROUP BY member_id, DATE_TRUNC('week', pay_time::date)
         )
         SELECT member_id, week_start, cnt
         FROM weekly
         ORDER BY member_id, week_start
         """,
-        (member_ids,),
+        (member_ids, ref_date, ref_date),
     )
 
     from collections import defaultdict
@@ -2477,11 +2580,9 @@ def _get_weekly_visits_batch(cur: Any, member_ids: list[int]) -> dict[int, list[
         week_key = row[1].date() if hasattr(row[1], 'date') else row[1]
         raw[row[0]][str(week_key)] = row[2]
 
-    # 生成最近 8 周的周一日期
-    from datetime import date, timedelta
-    today = date.today()
-    this_monday = today - timedelta(days=today.weekday())
-    weeks = [this_monday - timedelta(weeks=i) for i in range(7, -1, -1)]
+    # 生成最近 8 周的周一日期，以业务日为锚
+    this_monday = ref_date - _timedelta(days=ref_date.weekday())
+    weeks = [this_monday - _timedelta(weeks=i) for i in range(7, -1, -1)]
 
     result: dict[int, list[dict]] = {}
     for mid in member_ids:

apps/backend/app/services/note_service.py

@@ -259,6 +259,28 @@ async def create_note(
         import asyncio
         asyncio.create_task(_async_ai_score(note["id"], site_id, target_id, content))
 
+        # 触发 AI 备注分析链（App6 → App8）
+        # target_type='member' 时 target_id 即 member_id；'assistant' 时不触发（AI 只分析会员备注）
+        if target_type == "member":
+            try:
+                from app.services.trigger_scheduler import fire_event
+                fire_event(
+                    "ai_note_created",
+                    {
+                        "site_id": site_id,
+                        "member_id": target_id,
+                        "note_content": content,
+                        "noted_by_name": note.get("recorded_by_name")
+                            or note.get("user_nickname") or "",
+                        "noted_by_created_at": note.get("created_at") or "",
+                    },
+                )
+            except Exception:
+                logger.exception(
+                    "触发 ai_note_created 事件失败: note_id=%s member_id=%s",
+                    note["id"], target_id,
+                )
+
         return note
 
     except HTTPException:

apps/backend/app/services/recall_detector.py

@@ -22,6 +22,13 @@ import json
 import logging
 from datetime import timedelta
 
+from app.services.runtime_context import (
+    LIVE_INSTANCE_ID,
+    MODE_LIVE,
+    MODE_SANDBOX,
+    get_runtime_context,
+    task_runtime_filter,
+)
 from app.trace.decorators import trace_service
 
 logger = logging.getLogger(__name__)
@@ -141,6 +148,10 @@ def _process_site(conn, site_id: int) -> dict:
     resolved = 0
 
     from app.services.fdw_queries import _fdw_context
+    runtime_ctx = get_runtime_context(site_id, conn=conn)
+    runtime_now = runtime_ctx.business_now
+    runtime_mode = MODE_SANDBOX if runtime_ctx.is_sandbox else MODE_LIVE
+    sandbox_instance_id = runtime_ctx.sandbox_instance_id if runtime_ctx.is_sandbox else LIVE_INSTANCE_ID
 
     # ── 1. 获取本门店所有 MAIN 关系对 ──
     with _fdw_context(conn, site_id) as cur:
@@ -173,13 +184,14 @@ def _process_site(conn, site_id: int) -> dict:
               ON sl.order_settle_id = sh.order_settle_id
              AND sl.is_delete = 0
             WHERE sh.member_id = ANY(%s)
+              AND sh.pay_time <= %s
               AND (
                 sh.settle_type = 1
                 OR (sh.settle_type = 3 AND sl.order_assistant_type = 2)
               )
             GROUP BY sl.site_assistant_id, sh.member_id
             """,
-            (member_ids,),
+            (member_ids, runtime_now),
         )
         for row in cur.fetchall():
             settlement_map[(row[0], row[1])] = row[2]
@@ -190,6 +202,7 @@ def _process_site(conn, site_id: int) -> dict:
             SELECT sh.member_id, MAX(sh.pay_time) AS latest_pay_time
             FROM app.v_dwd_settlement_head sh
             WHERE sh.member_id = ANY(%s)
+              AND sh.pay_time <= %s
               AND (
                 sh.settle_type = 1
                 OR (sh.settle_type = 3 AND EXISTS (
@@ -201,7 +214,7 @@ def _process_site(conn, site_id: int) -> dict:
               )
             GROUP BY sh.member_id
             """,
-            (member_ids,),
+            (member_ids, runtime_now),
         )
         member_visited_map = {}
         for row in cur.fetchall():
@@ -209,16 +222,18 @@ def _process_site(conn, site_id: int) -> dict:
 
     # ── 3. 获取本门店所有 active 的召回/回访任务（用于匹配） ──
     active_tasks_map: dict[tuple[int, int], list] = {}  # (assistant_id, member_id) → [(id, task_type, created_at)]
+    runtime_clause, runtime_params = task_runtime_filter(site_id, conn=conn)
     with conn.cursor() as cur:
         cur.execute(
-            """
+            f"""
             SELECT id, assistant_id, member_id, task_type, created_at
             FROM biz.coach_tasks
             WHERE site_id = %s
+              {runtime_clause}
               AND status = 'active'
               AND task_type IN ('high_priority_recall', 'priority_recall', 'follow_up_visit')
             """,
-            (site_id,),
+            [site_id, *runtime_params],
         )
         for row in cur.fetchall():
             key = (row[1], row[2])
@@ -238,7 +253,7 @@ def _process_site(conn, site_id: int) -> dict:
         try:
             result = _process_pair(
                 conn, site_id, assistant_id, member_id,
-                latest_pay, active_tasks,
+                latest_pay, active_tasks, runtime_now, runtime_mode, sandbox_instance_id,
             )
             completed += result["completed"]
             events += result["events"]
@@ -257,25 +272,26 @@ def _process_site(conn, site_id: int) -> dict:
             with conn.cursor() as cur:
                 cur.execute("BEGIN")
                 cur.execute(
-                    """
+                    f"""
                     SELECT id, assistant_id, task_type, created_at
                     FROM biz.coach_tasks
                     WHERE site_id = %s AND member_id = %s
+                      {runtime_clause}
                       AND status = 'active'
                       AND task_type IN ('high_priority_recall', 'priority_recall')
                       AND created_at < %s
                     """,
-                    (site_id, member_id, pay_time),
+                    [site_id, member_id, *runtime_params, pay_time],
                 )
                 remaining = cur.fetchall()
                 for task_id, aid, task_type, _ in remaining:
                     cur.execute(
                         """
                         UPDATE biz.coach_tasks
-                        SET status = 'resolved', updated_at = NOW()
+                        SET status = 'resolved', updated_at = %s
                         WHERE id = %s AND status = 'active'
                         """,
-                        (task_id,),
+                        (runtime_now, task_id),
                     )
                     _insert_history(
                         cur, task_id,
@@ -308,6 +324,9 @@ def _process_pair(
     member_id: int,
     latest_pay_time,
     active_tasks: list[dict],
+    runtime_now,
+    runtime_mode: str,
+    sandbox_instance_id: str,
 ) -> dict:
     """
     处理单个 MAIN 关系对的召回检测。
@@ -339,14 +358,16 @@ def _process_pair(
         cur.execute(
             """
             INSERT INTO biz.recall_events
-                (site_id, assistant_id, member_id, pay_time, task_id, task_type)
-            VALUES (%s, %s, %s, %s, %s, %s)
-            ON CONFLICT (site_id, assistant_id, member_id, (date_trunc('day', pay_time AT TIME ZONE 'Asia/Shanghai')))
+                (site_id, assistant_id, member_id, pay_time, task_id, task_type,
+                 created_at, runtime_mode, sandbox_instance_id)
+            VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
+            ON CONFLICT (site_id, assistant_id, member_id, runtime_mode, sandbox_instance_id,
+                         (date_trunc('day', pay_time AT TIME ZONE 'Asia/Shanghai')))
             DO NOTHING
             RETURNING id
             """,
             (site_id, assistant_id, member_id, latest_pay_time,
-             event_task_id, event_task_type),
+             event_task_id, event_task_type, runtime_now, runtime_mode, sandbox_instance_id),
         )
         inserted = cur.fetchone()
         if inserted is None:
@@ -367,10 +388,10 @@ def _process_pair(
                     completed_at = %s,
                     completed_task_type = %s,
                     completion_type = 'auto',
-                    updated_at = NOW()
+                    updated_at = %s
                 WHERE id = %s AND status = 'active'
                 """,
-                (latest_pay_time, task["task_type"], task["id"]),
+                (latest_pay_time, task["task_type"], runtime_now, task["id"]),
             )
             _insert_history(
                 cur,
@@ -393,18 +414,19 @@ def _process_pair(
             SELECT id FROM biz.coach_tasks
             WHERE site_id = %s AND assistant_id = %s AND member_id = %s
               AND task_type = 'follow_up_visit' AND status = 'active'
+              AND runtime_mode = %s AND sandbox_instance_id = %s
             """,
-            (site_id, assistant_id, member_id),
+            (site_id, assistant_id, member_id, runtime_mode, sandbox_instance_id),
         )
         old_follow_ups = cur.fetchall()
         for (old_id,) in old_follow_ups:
             cur.execute(
                 """
                 UPDATE biz.coach_tasks
-                SET status = 'inactive', updated_at = NOW()
+                SET status = 'inactive', updated_at = %s
                 WHERE id = %s
                 """,
-                (old_id,),
+                (runtime_now, old_id),
             )
             _insert_history(
                 cur, old_id,
@@ -423,11 +445,14 @@ def _process_pair(
             """
             INSERT INTO biz.coach_tasks
                 (site_id, assistant_id, member_id, task_type, status,
-                 expires_at, created_at, updated_at)
-            VALUES (%s, %s, %s, 'follow_up_visit', 'active', %s, NOW(), NOW())
+                 expires_at, created_at, updated_at, runtime_mode, sandbox_instance_id)
+            VALUES (%s, %s, %s, 'follow_up_visit', 'active', %s, %s, %s, %s, %s)
             RETURNING id
             """,
-            (site_id, assistant_id, member_id, expires_at),
+            (
+                site_id, assistant_id, member_id, expires_at, runtime_now,
+                runtime_now, runtime_mode, sandbox_instance_id,
+            ),
         )
         new_follow_up_id = cur.fetchone()[0]
         _insert_history(

apps/backend/app/services/runtime_context.py

@@ -0,0 +1,263 @@
+# -*- coding: utf-8 -*-
+"""业务运行上下文与业务时钟服务。
+
+该模块是开发/测试沙箱的统一控制层：
+- live 模式：沿用真实系统日期和正式数据。
+- sandbox 模式：业务上假设今天是配置的历史日期，并用 sandbox_instance_id 隔离写入。
+"""
+
+from __future__ import annotations
+
+import uuid
+from dataclasses import dataclass
+from datetime import date, datetime, time, timedelta, timezone
+from typing import Any
+
+from app import config
+
+_LOCAL_TZ = timezone(timedelta(hours=8))
+MODE_LIVE = "live"
+MODE_SANDBOX = "sandbox"
+AI_MODE_LIVE = "live"
+LIVE_INSTANCE_ID = "live"
+
+
+@dataclass(frozen=True)
+class RuntimeContext:
+    """单门店当前业务运行上下文。"""
+
+    site_id: int
+    mode: str = MODE_LIVE
+    business_day_start_hour: int = config.BUSINESS_DAY_START_HOUR
+    sandbox_date: date | None = None
+    sandbox_instance_id: str | None = None
+    ai_mode: str = AI_MODE_LIVE
+    status: str = "active"
+
+    @property
+    def is_sandbox(self) -> bool:
+        return self.mode == MODE_SANDBOX and self.sandbox_date is not None
+
+    @property
+    def business_date(self) -> date:
+        if self.is_sandbox and self.sandbox_date is not None:
+            return self.sandbox_date
+        now = datetime.now(_LOCAL_TZ)
+        today = now.date()
+        if now.hour < self.business_day_start_hour:
+            return today - timedelta(days=1)
+        return today
+
+    @property
+    def business_now(self) -> datetime:
+        if not self.is_sandbox:
+            return datetime.now(_LOCAL_TZ)
+        now = datetime.now(_LOCAL_TZ)
+        return datetime.combine(self.business_date, now.timetz(), tzinfo=_LOCAL_TZ)
+
+    @property
+    def active_sandbox_instance_id(self) -> str | None:
+        if not self.is_sandbox:
+            return None
+        return self.sandbox_instance_id
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "site_id": self.site_id,
+            "mode": self.mode,
+            "business_day_start_hour": self.business_day_start_hour,
+            "business_date": self.business_date.isoformat(),
+            "business_now": self.business_now.isoformat(),
+            "sandbox_date": self.sandbox_date.isoformat() if self.sandbox_date else None,
+            "sandbox_instance_id": self.sandbox_instance_id,
+            "ai_mode": self.ai_mode,
+            "status": self.status,
+            "is_sandbox": self.is_sandbox,
+        }
+
+
+def new_sandbox_instance_id() -> str:
+    """生成新的沙箱实例 ID。"""
+    return f"sbx_{uuid.uuid4().hex[:24]}"
+
+
+def _default_context(site_id: int) -> RuntimeContext:
+    return RuntimeContext(site_id=site_id)
+
+
+def get_runtime_context(site_id: int, conn: Any | None = None) -> RuntimeContext:
+    """读取门店运行上下文。
+
+    表不存在或未配置时降级为 live，保证迁移前不影响正式链路。
+    """
+    own_conn = conn is None
+    if own_conn:
+        from app.database import get_connection
+
+        conn = get_connection()
+
+    try:
+        with conn.cursor() as cur:
+            try:
+                cur.execute(
+                    """
+                    SELECT mode, sandbox_date, sandbox_instance_id, ai_mode, status
+                    FROM biz.site_runtime_context
+                    WHERE site_id = %s
+                    """,
+                    (site_id,),
+                )
+            except Exception:
+                if own_conn:
+                    conn.rollback()
+                return _default_context(site_id)
+
+            row = cur.fetchone()
+        if own_conn:
+            conn.commit()
+    finally:
+        if own_conn:
+            conn.close()
+
+    if not row:
+        return _default_context(site_id)
+
+    mode, sandbox_date, sandbox_instance_id, ai_mode, status = row
+    if mode not in (MODE_LIVE, MODE_SANDBOX):
+        mode = MODE_LIVE
+    if mode == MODE_SANDBOX and (sandbox_date is None or not sandbox_instance_id):
+        mode = MODE_LIVE
+
+    return RuntimeContext(
+        site_id=site_id,
+        mode=mode,
+        sandbox_date=sandbox_date,
+        sandbox_instance_id=sandbox_instance_id,
+        ai_mode=ai_mode or AI_MODE_LIVE,
+        status=status or "active",
+    )
+
+
+def namespace_ai_target_id(site_id: int, target_id: str, conn: Any | None = None) -> str:
+    """按当前上下文转换 AI cache target_id。
+
+    前端和调用方继续使用原始 target_id；沙箱命名空间在后端统一处理。
+    """
+    ctx = get_runtime_context(site_id, conn=conn)
+    if not ctx.is_sandbox or not ctx.sandbox_instance_id:
+        return target_id
+    return f"{ctx.sandbox_instance_id}:{target_id}"
+
+
+def task_runtime_filter(
+    site_id: int,
+    *,
+    alias: str = "",
+    conn: Any | None = None,
+) -> tuple[str, list[Any]]:
+    """返回 coach_tasks 等表的运行上下文过滤条件。"""
+    ctx = get_runtime_context(site_id, conn=conn)
+    prefix = f"{alias}." if alias else ""
+    if ctx.is_sandbox and ctx.sandbox_instance_id:
+        return (
+            f" AND {prefix}runtime_mode = %s AND {prefix}sandbox_instance_id = %s",
+            [MODE_SANDBOX, ctx.sandbox_instance_id],
+        )
+    return (
+        f" AND COALESCE({prefix}runtime_mode, 'live') = %s "
+        f"AND COALESCE({prefix}sandbox_instance_id, %s) = %s",
+        [MODE_LIVE, LIVE_INSTANCE_ID, LIVE_INSTANCE_ID],
+    )
+
+
+def runtime_insert_columns(site_id: int, conn: Any | None = None) -> tuple[str, str, list[Any]]:
+    """返回 INSERT SQL 片段：列名、占位符和值。"""
+    ctx = get_runtime_context(site_id, conn=conn)
+    return (
+        "runtime_mode, sandbox_instance_id",
+        "%s, %s",
+        [
+            MODE_SANDBOX if ctx.is_sandbox else MODE_LIVE,
+            ctx.sandbox_instance_id if ctx.is_sandbox else LIVE_INSTANCE_ID,
+        ],
+    )
+
+
+def runtime_update_assignments(site_id: int, conn: Any | None = None) -> tuple[str, list[Any]]:
+    """返回 UPDATE SQL 片段，用于把运行上下文写回已有记录。"""
+    ctx = get_runtime_context(site_id, conn=conn)
+    return (
+        "runtime_mode = %s, sandbox_instance_id = %s",
+        [
+            MODE_SANDBOX if ctx.is_sandbox else MODE_LIVE,
+            ctx.sandbox_instance_id if ctx.is_sandbox else LIVE_INSTANCE_ID,
+        ],
+    )
+
+
+def as_runtime_now_param(site_id: int, conn: Any | None = None) -> datetime:
+    """返回可传给 SQL 的业务当前时间。"""
+    return get_runtime_context(site_id, conn=conn).business_now
+
+
+def as_runtime_today_param(site_id: int, conn: Any | None = None) -> date:
+    """返回可传给 SQL 的业务当前日期。"""
+    return get_runtime_context(site_id, conn=conn).business_date
+
+
+def as_runtime_year_month_param(site_id: int, conn: Any | None = None) -> str:
+    """返回 'YYYY-MM' 形式的业务年月，用于 performance 等月度查询。"""
+    bd = get_runtime_context(site_id, conn=conn).business_date
+    return f"{bd.year:04d}-{bd.month:02d}"
+
+
+def as_runtime_business_now_str(site_id: int, conn: Any | None = None, fmt: str = "%Y-%m-%d %H:%M:%S") -> str:
+    """返回业务当前时间的格式化字符串，用于 AI prompts 中的 current_time。"""
+    return get_runtime_context(site_id, conn=conn).business_now.strftime(fmt)
+
+
+def business_date_upper_bound_sql(
+    site_id: int,
+    *,
+    column: str,
+    alias: str = "",
+    cast: str | None = None,
+    conn: Any | None = None,
+) -> tuple[str, list[Any]]:
+    """返回业务日上界 SQL 片段。
+
+    sandbox 模式下，强制把 ``column`` 限制在业务日及之前（避免读到「未来」数据）。
+    live 模式下返回空片段，不影响任何逻辑。
+
+    cast 用于把 timestamp/timestamptz 列裁剪成日期再比较，例如 ``cast='date'``。
+    """
+    ctx = get_runtime_context(site_id, conn=conn)
+    if not ctx.is_sandbox:
+        return ("", [])
+    prefix = f"{alias}." if alias else ""
+    expr = f"{prefix}{column}"
+    if cast:
+        expr = f"({expr})::{cast}"
+    return (f" AND {expr} <= %s", [ctx.business_date])
+
+
+def apply_runtime_session_vars(conn: Any, ctx: RuntimeContext | None = None, *, site_id: int | None = None) -> None:
+    """在已有数据库连接上设置 ``app.current_business_date`` 等 GUC 变量。
+
+    供 RLS 视图层（C 方案）使用：视图通过 ``current_setting('app.current_business_date', true)``
+    读取业务日，再对事实/维度表做日期上界裁剪。
+
+    无论 live / sandbox 都设置该变量；live 下视图仍按真实 ``CURRENT_DATE`` 行为。
+    """
+    if ctx is None:
+        if site_id is None:
+            raise ValueError("apply_runtime_session_vars 需要 ctx 或 site_id 之一")
+        ctx = get_runtime_context(site_id, conn=conn)
+    bd = ctx.business_date.isoformat()
+    mode = MODE_SANDBOX if ctx.is_sandbox else MODE_LIVE
+    with conn.cursor() as cur:
+        cur.execute(
+            "SELECT set_config('app.current_business_date', %s, true), "
+            "set_config('app.current_runtime_mode', %s, true)",
+            (bd, mode),
+        )

apps/backend/app/services/task_expiry.py

@@ -11,6 +11,7 @@
 import json
 import logging
 
+from app.services.runtime_context import as_runtime_now_param, task_runtime_filter
 from app.trace.decorators import trace_service
 
 logger = logging.getLogger(__name__)
@@ -71,32 +72,42 @@ def run() -> dict:
 
     conn = _get_connection()
     try:
-        # 查询所有已过期的 active 任务
+        # 查询所有已过期的 active 任务。沙箱模式按业务时间判断，并只处理当前运行实例。
+        expired_tasks = []
         with conn.cursor() as cur:
-            cur.execute(
-                """
-                SELECT id, task_type
-                FROM biz.coach_tasks
-                WHERE expires_at IS NOT NULL
-                  AND expires_at < NOW()
-                  AND status = 'active'
-                """
-            )
-            expired_tasks = cur.fetchall()
+            cur.execute("SELECT site_id FROM biz.sites WHERE is_active = true")
+            site_ids = [row[0] for row in cur.fetchall()]
+            for site_id in site_ids:
+                runtime_now = as_runtime_now_param(site_id, conn=conn)
+                runtime_clause, runtime_params = task_runtime_filter(site_id, conn=conn)
+                cur.execute(
+                    f"""
+                    SELECT id, task_type, site_id
+                    FROM biz.coach_tasks
+                    WHERE site_id = %s
+                      {runtime_clause}
+                      AND expires_at IS NOT NULL
+                      AND expires_at < %s
+                      AND status = 'active'
+                    """,
+                    [site_id, *runtime_params, runtime_now],
+                )
+                expired_tasks.extend(cur.fetchall())
         conn.commit()
 
         # 逐条处理，每条独立事务
-        for task_id, task_type in expired_tasks:
+        for task_id, task_type, site_id in expired_tasks:
             try:
+                runtime_now = as_runtime_now_param(site_id, conn=conn)
                 with conn.cursor() as cur:
                     cur.execute("BEGIN")
                     cur.execute(
                         """
                         UPDATE biz.coach_tasks
-                        SET status = 'inactive', updated_at = NOW()
+                        SET status = 'inactive', updated_at = %s
                         WHERE id = %s AND status = 'active'
                         """,
-                        (task_id,),
+                        (runtime_now, task_id),
                     )
                     _insert_history(
                         cur,

apps/backend/app/services/task_generator.py

@@ -41,6 +41,13 @@ from dataclasses import dataclass
 from enum import IntEnum
 
 from app.trace.decorators import trace_service
+from app.services.runtime_context import (
+    LIVE_INSTANCE_ID,
+    MODE_LIVE,
+    MODE_SANDBOX,
+    get_runtime_context,
+    task_runtime_filter,
+)
 
 
 class TaskPriority(IntEnum):
@@ -189,6 +196,14 @@ import logging
 logger = logging.getLogger(__name__)
 
 
+def _runtime_values(conn, site_id: int):
+    """返回当前门店任务写入所需的运行上下文值。"""
+    ctx = get_runtime_context(site_id, conn=conn)
+    mode = MODE_SANDBOX if ctx.is_sandbox else MODE_LIVE
+    instance_id = ctx.sandbox_instance_id if ctx.is_sandbox else LIVE_INSTANCE_ID
+    return ctx, mode, instance_id, ctx.business_now
+
+
 def _get_connection():
     """延迟导入 get_connection，避免纯函数测试时触发模块级导入失败。"""
     from app.database import get_connection
@@ -210,7 +225,10 @@ def run() -> dict:
 
     返回: {"created": int, "replaced": int, "skipped": int, "transferred": int}
     """
+    from datetime import datetime, timezone
+
     stats = {"created": 0, "replaced": 0, "skipped": 0, "transferred": 0}
+    run_started_at = datetime.now(timezone.utc)
 
     conn = _get_connection()
     try:
@@ -265,6 +283,14 @@ def run() -> dict:
             )
         conn.commit()
 
+        # ── 6. 触发 AI 消费事件 — 对本次 run 新建的任务逐个触发 ai_consumption_settled
+        # 仅按 created_at >= run_started_at 过滤（精确锁定本次新建），避免误触发历史任务。
+        # dispatcher 内部按 (event, member_id, site_id, date) 去重，重复触发无害。
+        try:
+            _fire_ai_consumption_events(conn, run_started_at)
+        except Exception:
+            logger.exception("ai_consumption_settled 事件触发失败（不影响任务生成主流程）")
+
     finally:
         conn.close()
 
@@ -278,6 +304,54 @@ def run() -> dict:
     return stats
 
 
+def _fire_ai_consumption_events(conn, run_started_at) -> None:
+    """查询本次 run 新建的任务，对每条 (site_id, member_id, assistant_id) 触发 ai_consumption_settled。
+
+    has_assistant 恒为 True（任务必然绑定助教）。
+    dispatcher 去重确保每 member 每天 AI 链路至多跑一次。
+    """
+    from app.services.trigger_scheduler import fire_event
+
+    with conn.cursor() as cur:
+        cur.execute(
+            """
+            SELECT DISTINCT site_id, member_id, assistant_id
+            FROM biz.coach_tasks
+            WHERE created_at >= %s
+              AND member_id IS NOT NULL
+              AND assistant_id IS NOT NULL
+            """,
+            (run_started_at,),
+        )
+        pairs = cur.fetchall()
+    conn.commit()
+
+    triggered = 0
+    for row in pairs:
+        site_id, member_id, assistant_id = row[0], row[1], row[2]
+        try:
+            fire_event(
+                "ai_consumption_settled",
+                {
+                    "site_id": site_id,
+                    "member_id": member_id,
+                    "assistant_id": assistant_id,
+                    "has_assistant": True,
+                },
+            )
+            triggered += 1
+        except Exception:
+            logger.exception(
+                "触发 ai_consumption_settled 失败: site_id=%s member_id=%s",
+                site_id, member_id,
+            )
+
+    logger.info(
+        "ai_consumption_settled 触发完成: 新建任务去重后 %d 个 member，成功触发 %d 次",
+        len(pairs), triggered,
+    )
+
+
 def _run_for_site(conn, site_id: int, stats: dict) -> None:
     """
     单门店处理流程。
@@ -766,9 +840,10 @@ def _run_transfer_check(
     w_ms = params["transfer_score_w_ms"]
     w_ml = params["transfer_score_w_ml"]
 
-    from datetime import datetime, timezone
+    from app.services.runtime_context import as_runtime_now_param
 
-    now = datetime.now(timezone.utc)
+    # 业务时间锚：sandbox 模式下用 business_now，避免按真实时间把已转移很久的任务再算成候选
+    now = as_runtime_now_param(site_id, conn=conn)
 
     for task_id, from_assistant_id, member_id, task_type, transfer_count, created_at in candidates:
         # CHANGE 2026-03-29 | 用升级倍数判定是否触发转移
@@ -805,9 +880,7 @@ def _run_transfer_check(
             )
             entry_dates = {r[0]: r[1] for r in cur.fetchall()}
 
-        from datetime import datetime, timezone, timedelta
-
-        now = datetime.now(timezone.utc)
+        # 沿用上方 business_now，避免「真实今天」的入驻时间保护
         eligible = []
         for a in pool:
             aid = a["assistant_id"]

apps/backend/app/services/task_manager.py

@@ -37,6 +37,7 @@ from decimal import Decimal
 from fastapi import HTTPException
 
 from app.services import fdw_queries
+from app.services.runtime_context import get_runtime_context, task_runtime_filter
 from app.services.task_generator import compute_heart_icon
 from app.trace.decorators import trace_service
 
@@ -114,15 +115,17 @@ def _verify_task_ownership(
     - 不属于当前助教 → 403
     - required_status 不匹配 → 409
     """
+    runtime_clause, runtime_params = task_runtime_filter(site_id, conn=conn)
     with conn.cursor() as cur:
         cur.execute(
-            """
+            f"""
             SELECT id, task_type, status, is_pinned, abandon_reason,
                    assistant_id, site_id
             FROM biz.coach_tasks
             WHERE id = %s
+            {runtime_clause}
             """,
-            (task_id,),
+            [task_id, *runtime_params],
         )
         row = cur.fetchone()
 
@@ -166,22 +169,24 @@ async def get_task_list(user_id: int, site_id: int) -> list[dict]:
         assistant_id = _get_assistant_id(conn, user_id, site_id)
 
         # 查询有效 + 已放弃任务（abandoned 排最后）
+        runtime_clause, runtime_params = task_runtime_filter(site_id, conn=conn)
         with conn.cursor() as cur:
             cur.execute(
-                """
+                f"""
                 SELECT id, task_type, status, priority_score, is_pinned,
                        expires_at, created_at, member_id, abandon_reason
                 FROM biz.coach_tasks
                 WHERE site_id = %s
                   AND assistant_id = %s
                   AND status IN ('active', 'abandoned')
+                  {runtime_clause}
                 ORDER BY
                     CASE WHEN status = 'abandoned' THEN 1 ELSE 0 END ASC,
                     is_pinned DESC,
                     priority_score DESC NULLS LAST,
                     created_at ASC
                 """,
-                (site_id, assistant_id),
+                [site_id, assistant_id, *runtime_params],
             )
             tasks = cur.fetchall()
         conn.commit()
@@ -605,8 +610,9 @@ async def get_task_list_v2(
         # 构建排除条件：relationship_building + member_id 不在 RS 范围内
         # 当排除列表为空时不加额外条件
         exclude_clause = ""
-        query_params_count: list = [site_id, assistant_id, db_status]
-        query_params_page: list = [site_id, assistant_id, db_status]
+        runtime_clause, runtime_params = task_runtime_filter(site_id, conn=conn)
+        query_params_count: list = [site_id, assistant_id, db_status, *runtime_params]
+        query_params_page: list = [site_id, assistant_id, db_status, *runtime_params]
         if rb_exclude_member_ids:
             exclude_clause = (
                 " AND NOT (task_type = 'relationship_building' AND member_id = ANY(%s))"
@@ -621,6 +627,7 @@ async def get_task_list_v2(
                 SELECT COUNT(*)
                 FROM biz.coach_tasks
                 WHERE site_id = %s AND assistant_id = %s AND status = %s
+                {runtime_clause}
                 {exclude_clause}
                 """,
                 query_params_count,
@@ -636,6 +643,7 @@ async def get_task_list_v2(
                        expires_at, created_at, member_id, abandon_reason
                 FROM biz.coach_tasks
                 WHERE site_id = %s AND assistant_id = %s AND status = %s
+                {runtime_clause}
                 {exclude_clause}
                 ORDER BY is_pinned DESC,
                          priority_score DESC NULLS LAST,
@@ -669,9 +677,11 @@ async def get_task_list_v2(
         recent60d_map: dict[int, dict] = {}
         batch_data: dict | None = None
         try:
+            from app.services.runtime_context import as_runtime_today_param
+            _ref_date = as_runtime_today_param(site_id, conn=conn)
             batch_data = fdw_queries.batch_query_for_task_list(
                 conn, site_id, assistant_id, member_ids,
-                datetime.now().year, datetime.now().month,
+                _ref_date.year, _ref_date.month,
             )
             member_info_map = batch_data["member_info"]
             balance_map = batch_data["balance"]
@@ -685,7 +695,11 @@ async def get_task_list_v2(
         # ── 6. 查询 ai_cache 获取 aiSuggestion（优雅降级） ──
         ai_suggestion_map: dict[int, str] = {}
         try:
-            member_id_strs = [str(mid) for mid in member_ids]
+            runtime_ctx = get_runtime_context(site_id, conn=conn)
+            if runtime_ctx.is_sandbox and runtime_ctx.sandbox_instance_id:
+                member_id_strs = [f"{runtime_ctx.sandbox_instance_id}:{mid}" for mid in member_ids]
+            else:
+                member_id_strs = [str(mid) for mid in member_ids]
             with conn.cursor() as cur:
                 cur.execute(
                     """
@@ -706,7 +720,8 @@ async def get_task_list_v2(
                         result = row[1] if isinstance(row[1], dict) else {}
                         summary = result.get("summary", "")
                         if summary:
-                            ai_suggestion_map[int(target_id_str)] = summary
+                            raw_target = target_id_str.split(":", 1)[-1]
+                            ai_suggestion_map[int(raw_target)] = summary
             conn.commit()
         except Exception:
             logger.warning("查询 ai_cache aiSuggestion 失败", exc_info=True)
@@ -802,8 +817,11 @@ def build_performance_summary(
     当 batch_data 为 None 时（如无任务的空列表场景），回退到独立查询。
     课时/档位/客户数从 monthly_summary（每日更新）取实时数据，
     不再依赖月初结算的 salary_calc。收入仍从 salary_calc 取（如有）。
+
+    CHANGE 2026-05-02 | now 改用 RuntimeContext.business_date，沙箱不读「未来」月份。
     """
-    now = datetime.now()
+    from app.services.runtime_context import as_runtime_today_param
+    now = as_runtime_today_param(site_id, conn=conn)
     year, month = now.year, now.month
 
     if batch_data:
@@ -971,15 +989,17 @@ async def get_task_by_member(
     try:
         assistant_id = _get_assistant_id(conn, user_id, site_id)
 
+        runtime_clause, runtime_params = task_runtime_filter(site_id, conn=conn)
         with conn.cursor() as cur:
             cur.execute(
-                """
+                f"""
                 SELECT id, task_type
                 FROM biz.coach_tasks
                 WHERE site_id = %s AND assistant_id = %s AND member_id = %s
                   AND status = 'active'
+                  {runtime_clause}
                 """,
-                (site_id, assistant_id, member_id),
+                [site_id, assistant_id, member_id, *runtime_params],
             )
             rows = cur.fetchall()
 
@@ -1020,16 +1040,18 @@ async def get_task_detail(
         assistant_id = _get_assistant_id(conn, user_id, site_id)
 
         # ── 1. 查询任务基础信息 ──
+        runtime_clause, runtime_params = task_runtime_filter(site_id, conn=conn)
         with conn.cursor() as cur:
             cur.execute(
-                """
+                f"""
                 SELECT id, task_type, status, priority_score, is_pinned,
                        expires_at, created_at, member_id, abandon_reason,
                        assistant_id, site_id
                 FROM biz.coach_tasks
                 WHERE id = %s
+                {runtime_clause}
                 """,
-                (task_id,),
+                [task_id, *runtime_params],
             )
             row = cur.fetchone()
 
@@ -1090,6 +1112,12 @@ async def get_task_detail(
         # ── 3. 查询维客线索 ──
         retention_clues = []
         try:
+            runtime_ctx = get_runtime_context(site_id, conn=conn)
+            member_target_id = (
+                f"{runtime_ctx.sandbox_instance_id}:{member_id}"
+                if runtime_ctx.is_sandbox and runtime_ctx.sandbox_instance_id
+                else str(member_id)
+            )
             with conn.cursor() as cur:
                 cur.execute(
                     """
@@ -1136,7 +1164,7 @@ async def get_task_detail(
                       AND cache_type IN ('app4_analysis', 'app5_talking_points')
                     ORDER BY created_at DESC
                     """,
-                    (str(member_id), site_id),
+                    (member_target_id, site_id),
                 )
                 seen_types: set[str] = set()
                 for cache_row in cur.fetchall():
@@ -1173,8 +1201,10 @@ async def get_task_detail(
 
         # CHANGE 2026-03-25 | 统计范围：近60天；列表不限
         # 预估规则：当月且日期 ≤ 5号
-        from datetime import date, timedelta
-        today = date.today()
+        # CHANGE 2026-05-02 | today 改用 business_date，沙箱不读「未来」60 天
+        from datetime import timedelta
+        from app.services.runtime_context import as_runtime_today_param
+        today = as_runtime_today_param(site_id, conn=conn)
         cutoff_60d = today - timedelta(days=60)
         is_estimate_month = today.day <= 5
 

apps/backend/app/services/trigger_scheduler.py

@@ -10,7 +10,10 @@
 """
 from __future__ import annotations
 
+import asyncio
+import inspect
 import logging
+import threading
 from datetime import datetime, timedelta, timezone
 from typing import Any, Callable
 
@@ -19,6 +22,34 @@ from app.trace.decorators import trace_service
 logger = logging.getLogger(__name__)
 
 
+def _invoke_handler(handler: Callable, **kwargs: Any) -> Any:
+    """统一调用 handler，自动识别 sync / async。
+
+    - sync handler：直接返回结果
+    - async handler：
+      - 当前线程有 running loop → loop.create_task(coro)，后台异步执行
+      - 当前线程无 running loop → 新起 daemon 线程跑 asyncio.run(coro)，不阻塞调用方
+
+    说明：fire_event / check_scheduled_jobs 是 sync 函数，但部分 handler
+    （如 dispatcher 注册的 AI 事件 handler）是 async def，本包装器保证正确调度。
+    """
+    result = handler(**kwargs)
+    if not inspect.iscoroutine(result):
+        return result
+
+    try:
+        loop = asyncio.get_running_loop()
+        loop.create_task(result)
+        return None
+    except RuntimeError:
+        # 同步线程（无 running loop）：用后台线程异步执行 coroutine，不阻塞调用方
+        threading.Thread(
+            target=lambda coro=result: asyncio.run(coro),
+            daemon=True,
+        ).start()
+        return None
+
+
 def _get_connection():
     """延迟导入 get_connection，避免纯函数测试时触发模块级导入失败。"""
     from app.database import get_connection
@@ -89,7 +120,8 @@ def fire_event(event_name: str, payload: dict[str, Any] | None = None) -> int:
                 continue
             try:
                 # 将 job_id 传入 handler，handler 在最终 commit 前更新 last_run_at
-                handler(payload=payload, job_id=job_id)
+                # async handler 经 _invoke_handler 自动调度
+                _invoke_handler(handler, payload=payload, job_id=job_id)
                 executed += 1
             except Exception:
                 logger.exception("触发器 %s 执行失败", job_name)
@@ -136,7 +168,8 @@ def check_scheduled_jobs() -> int:
                 continue
             try:
                 # cron/interval handler 接受 conn + job_id，在最终 commit 前更新时间戳
-                handler(conn=conn, job_id=job_id)
+                # async handler 经 _invoke_handler 自动调度
+                _invoke_handler(handler, conn=conn, job_id=job_id)
                 # 计算 next_run_at 并更新（在 handler commit 后的新事务中）
                 next_run = _calculate_next_run(trigger_condition, trigger_config)
                 with conn.cursor() as cur:
@@ -276,7 +309,7 @@ def run_job_by_id(job_id: int) -> dict:
             return {"success": False, "message": f"任务 {job_name} 未注册处理器"}
 
         try:
-            handler()
+            _invoke_handler(handler)
             # 更新 last_run_at 和 next_run_at
             next_run = _calculate_next_run(trigger_condition, trigger_config)
             with conn.cursor() as cur:

apps/backend/app/ws/ai_events.py

@@ -0,0 +1,80 @@
+"""AI 事件 WebSocket 推送端点。
+
+提供：
+- /ws/ai-cache/{site_id} — 缓存更新 / 失效事件
+- /ws/ai-alerts/{site_id} — AI 告警事件（Phase 3.1）
+
+协议：
+- 客户端连接 → 服务端 accept → 订阅 EventBus → 持续 send_json 事件
+- 事件格式：{"type": "cache_updated|cache_invalidated|alert_created|...", "site_id": int, "payload": {...}}
+- 服务端关闭或客户端断开时清理订阅
+
+用 site_id=-1 表示全局订阅（收所有门店事件，admin-web 全局监控用）。
+"""
+
+from __future__ import annotations
+
+import logging
+
+from fastapi import APIRouter, WebSocket, WebSocketDisconnect
+
+from ..ai.event_bus import AIEvent, get_event_bus
+
+logger = logging.getLogger(__name__)
+
+ws_router = APIRouter()
+
+
+@ws_router.websocket("/ws/ai-cache/{site_id}")
+async def ws_ai_cache(websocket: WebSocket, site_id: int) -> None:
+    """AI 缓存事件推送。
+
+    site_id=-1 表示订阅全局（收所有门店的 cache_updated / cache_invalidated）。
+    """
+    await _serve_event_stream(websocket, site_id, endpoint="ai-cache")
+
+
+@ws_router.websocket("/ws/ai-alerts/{site_id}")
+async def ws_ai_alerts(websocket: WebSocket, site_id: int) -> None:
+    """AI 告警事件推送（Phase 3.1）。
+
+    site_id=-1 表示订阅全局告警。
+    事件 type: alert_created / alert_updated / budget_exceeded / circuit_opened。
+    """
+    await _serve_event_stream(websocket, site_id, endpoint="ai-alerts")
+
+
+async def _serve_event_stream(
+    websocket: WebSocket, site_id: int, endpoint: str,
+) -> None:
+    """共享事件流处理逻辑。"""
+    await websocket.accept()
+    # -1 映射为全局订阅（None）
+    subscribe_key: int | None = None if site_id == -1 else site_id
+    logger.info(
+        "WS %s 连接建立: site_id=%s", endpoint, subscribe_key if subscribe_key else "ALL",
+    )
+
+    bus = get_event_bus()
+    queue = await bus.subscribe(subscribe_key)
+
+    try:
+        while True:
+            event = await queue.get()
+            if event is None:
+                break
+            await websocket.send_json({
+                "type": event.type,
+                "site_id": event.site_id,
+                "payload": event.payload,
+            })
+    except WebSocketDisconnect:
+        logger.info("WS %s 客户端断开: site_id=%s", endpoint, subscribe_key)
+    except Exception:
+        logger.exception("WS %s 异常: site_id=%s", endpoint, subscribe_key)
+    finally:
+        await bus.unsubscribe(subscribe_key, queue)
+        try:
+            await websocket.close()
+        except Exception:
+            pass

apps/backend/pytest.ini

@@ -2,3 +2,4 @@
 testpaths = tests
 pythonpath = .
 asyncio_mode = auto
+norecursedirs = _archived _deleted

apps/etl/connectors/feiqiu/tasks/dws/finance_area_daily.py

@@ -24,6 +24,7 @@
     - 非 all 行现金流/卡消费/充值字段 = 0
     - hall 行 = 各具体区域之和（历史兼容）
     - all 行 = 各具体区域之和（收入/优惠），现金流/充值/卡消费来自 dws_finance_daily_summary
+      无台桌订单和补时长等 all-only 台区只合入 all，不合入具体区域
     - settle_type IN (1, 3) 过滤
     - discount_gift_card 使用赠送卡消费金额口径
 
@@ -107,6 +108,9 @@ _COUNT_FIELDS = {"order_count", "member_order_count"}
 
 _ZERO = Decimal("0")
 
+# 已知不属于看板 7 个具体区域、但应合入 all 的物理台区。
+_ALL_ONLY_AREA_NAMES = {"补时长", "虚拟台"}
+
 
 class FinanceAreaDailyTask(FinanceBaseTask):
     """
@@ -177,6 +181,7 @@ class FinanceAreaDailyTask(FinanceBaseTask):
         sql = f"""
             SELECT
                 {biz_expr}                          AS stat_date,
+                sh.table_id                         AS table_id,
                 dt.site_table_area_name             AS area_name,
                 sh.settle_type,
                 -- 收入
@@ -378,8 +383,9 @@ def transform_area_daily(
     )
     # 收集所有涉及的日期
     all_dates: set[date] = set()
-    # 未知区域名称计数（汇总后一次性输出，避免逐行 warning 产生大量日志噪音）
+    # 未知/无具体区域计数（汇总后一次性输出，避免逐行日志噪音）
     _unknown_area_counts: Dict[str, int] = defaultdict(int)
+    _all_only_area_counts: Dict[str, int] = defaultdict(int)
 
     for row in settlement_rows:
         sd = row.get("stat_date")
@@ -393,10 +399,15 @@ def transform_area_daily(
             continue
 
         area_name = row.get("area_name")
+        table_id = row.get("table_id")
         area_code = resolve_area_code(area_name)
 
         if area_code is None:
-            _unknown_area_counts[str(area_name)] += 1
+            unmatched_label = _format_unmatched_area_label(area_name, table_id)
+            if _is_all_only_area(area_name, table_id):
+                _all_only_area_counts[unmatched_label] += 1
+            else:
+                _unknown_area_counts[unmatched_label] += 1
 
         # 提取金额
         table_fee = safe_decimal_fn(row.get("table_fee_amount", 0))
@@ -479,11 +490,20 @@ def transform_area_daily(
         for k, v in fields.items():
             bucket[k] = bucket[k] + v
 
-    # 汇总输出未知区域名称（避免逐行 warning 刷屏）
+    # 汇总输出 all-only 区域（无台桌订单、补时长等），这些记录合入 all 属正常口径。
+    if _all_only_area_counts:
+        summary = ", ".join(f"'{k}': {v}次" for k, v in _all_only_area_counts.items())
+        logger.info(
+            "DWS_FINANCE_AREA_DAILY: 共 %d 条结算单无具体区域（已计入 all，不计入任何具体区域）: %s",
+            sum(_all_only_area_counts.values()),
+            summary,
+        )
+
+    # 汇总输出真正未知区域名称（避免逐行 warning 刷屏）
     if _unknown_area_counts:
         summary = ", ".join(f"'{k}': {v}次" for k, v in _unknown_area_counts.items())
         logger.warning(
-            "DWS_FINANCE_AREA_DAILY: 共 %d 条结算单区域未匹配（已计入 all 但不计入任何具体区域）: %s",
+            "DWS_FINANCE_AREA_DAILY: 共 %d 条结算单区域未匹配（已计入 all 但不计入任何具体区域，请检查 dim_table/AREA_LABEL_MAP）: %s",
             sum(_unknown_area_counts.values()),
             summary,
         )
@@ -618,4 +638,42 @@ def _safe_decimal(value: Any, default: Decimal = _ZERO) -> Decimal:
         return default
 
 
+def _is_all_only_area(area_name: Any, table_id: Any) -> bool:
+    """判断结算单是否属于无具体区域但应合入 all 的正常口径。
+
+    CHANGE 2026-05-02 | 扩大豁免规则，避免噪音 WARNING：
+    - "补时长" / "虚拟台" 的带数字/空格变体（如 "补时长2"、"虚拟台 1"）也算 all-only。
+    - 维表 site_table_area_name 为空（NULL）但有 table_id 的脏数据，归入 all-only INFO，
+      因为这通常是 dim_table SCD2 缺区域名而非真正映射缺口；金额仍合入 all 不丢失。
+      真正的「未知非空区域名」（如新店自定义命名未在 AREA_LABEL_MAP 中）才进 WARNING。
+    """
+    if area_name is None:
+        # 无 table_id：本来就没台桌，正常 all-only
+        # 有 table_id：维表区域名缺失，作为 dim_table 数据问题，仍归 all-only 但保留可观测性（INFO 行会带 'table_id=… None' 标签）
+        return True
+    if not isinstance(area_name, str):
+        return False
+    name = area_name.strip()
+    if not name:
+        return True
+    if name in _ALL_ONLY_AREA_NAMES:
+        return True
+    # 形如 "补时长2"、"补时长 3"、"虚拟台4" 等编号变体
+    for prefix in _ALL_ONLY_AREA_NAMES:
+        if name.startswith(prefix):
+            tail = name[len(prefix):].strip()
+            if not tail or tail.isdigit():
+                return True
+    return False
+
+
+def _format_unmatched_area_label(area_name: Any, table_id: Any) -> str:
+    """格式化未匹配区域日志标签，区分无台桌订单和维表缺口。"""
+    if area_name is None and not table_id:
+        return "无台桌"
+    if area_name is None:
+        return f"table_id={table_id}: None"
+    return str(area_name)
+
+
 __all__ = ["FinanceAreaDailyTask", "transform_area_daily"]

apps/etl/connectors/feiqiu/tasks/dws/task_engine.py

@@ -42,7 +42,10 @@ load_dotenv(_REPO_ROOT / ".env", override=False)
 
 logger = logging.getLogger(__name__)
 
-_TIMEOUT = (5, 30)
+# CHANGE 2026-05-02 | 旧值 (5, 30) 在 recall_completion_check / task_generator 这种长任务下
+# 经常 30s 读超时（实际处理 ~33s 以上）。临时止血提到 600s 与 flow_runner 对齐；
+# 长期方案是后端 /api/internal/run-job 改异步入队（参见 docs/database/changes/2026-05-02__sandbox_complete_refactor.md 已知未覆盖）
+_TIMEOUT = (10, 600)
 
 # HTTP 模式<E6A8A1><E5BC8F><EFBFBD>按顺序执行的后端任务
 _JOB_SEQUENCE = [

apps/miniprogram/miniprogram/components/ai-float-button/ai-float-button.ts

@@ -20,13 +20,47 @@ Component({
       type: Number,
       value: 200,
     },
+    /**
+     * Phase 2.3：来源页面标识（sourcePage），用于后端注入 page_context。
+     * 取值参考 backend page_context.py 的 SUPPORTED_PAGE_TYPES：
+     * board-finance / board-coach / board-customer / performance / task-list / my-profile 等。
+     * 为空时不传入 chat 页。
+     */
+    sourcePage: {
+      type: String,
+      value: '',
+    },
+    /**
+     * Phase 2.3：页面筛选参数（board-* 页面的 timeDimension/dimension/areaFilter 等），
+     * 将作为 JSON 字符串附加到 url，在 chat 页面解析后随 SSE 请求发给后端。
+     */
+    pageFilters: {
+      type: Object,
+      value: null as Record<string, string> | null,
+    },
   },
 
   methods: {
     onTap() {
       let url = this.data.targetUrl
+      const params: string[] = []
       if (this.data.customerId) {
-        url += `?customerId=${this.data.customerId}`
+        params.push(`customerId=${encodeURIComponent(this.data.customerId)}`)
+      }
+      if (this.data.sourcePage) {
+        params.push(`sourcePage=${encodeURIComponent(this.data.sourcePage)}`)
+      }
+      if (this.data.pageFilters && Object.keys(this.data.pageFilters).length > 0) {
+        try {
+          params.push(
+            `pageFilters=${encodeURIComponent(JSON.stringify(this.data.pageFilters))}`,
+          )
+        } catch {
+          // 非法 filters 忽略，不影响跳转
+        }
+      }
+      if (params.length > 0) {
+        url += (url.includes('?') ? '&' : '?') + params.join('&')
       }
       wx.navigateTo({
         url,

apps/miniprogram/miniprogram/pages/board-finance/board-finance.wxml

@@ -203,6 +203,8 @@
       <!-- AI 洞察 -->
       <!-- CHANGE 2026-03-12 | intent: H5 原型使用 SVG 机器人图标，不可用 emoji 替代；规范要求内联 SVG 导出为文件用 image 引用 -->
       <!-- CHANGE 2026-03-21 | P13 T6.1: AI 洞察改为动态渲染，移除硬编码文案 -->
+      <!-- CHANGE 2026-04-22 | AI 洞察改版：两段式（dim标题 + 正文），第3条起省略为1行，加"查看全部"按钮 + 覆盖大弹窗 -->
+      <!-- CHANGE 2026-04-22 seq11/12 置顶：AI 洞察区首屏为"本期总结"（健康度 + 跟踪），下方为明细 -->
       <view class="ai-insight-section">
         <view class="ai-insight-header">
           <view class="ai-insight-icon">
@@ -210,11 +212,108 @@
           </view>
           <text class="ai-insight-title">AI 智能洞察</text>
         </view>
-        <view class="ai-insight-body" wx:if="{{aiInsights.length > 0}}">
-          <text class="ai-insight-line" wx:for="{{aiInsights}}" wx:key="index"><text class="ai-insight-dim">{{item.icon}} </text>{{item.text}}</text>
+
+        <!-- 本期总结卡片：seq11(健康度评级) + seq12(跟踪指标) -->
+        <view class="ai-summary-card ai-summary-card--{{summaryLightType || 'neutral'}}" wx:if="{{aiInsightSummary.evaluation || aiInsightSummary.tracking}}">
+          <view class="ai-summary-head">
+            <view class="ai-summary-badge ai-summary-badge--{{summaryLightType || 'neutral'}}" wx:if="{{summaryLightLabel}}">
+              <text>{{summaryLightLabel}}</text>
+            </view>
+            <text class="ai-summary-head-title">本期总结</text>
+          </view>
+          <!-- 2026-04-22 v4：evaluation title 与顶部徽章语义重复，隐藏 title 仅展示 body -->
+          <view class="ai-summary-block" wx:if="{{aiInsightSummary.evaluation}}">
+            <view class="ai-summary-block-body ai-summary-block-body-clamp">
+              <text wx:for="{{aiInsightSummary.evaluation.bodySegs}}" wx:key="index" wx:for-item="seg" class="md-seg {{seg.bold ? 'md-bold' : ''}} {{seg.italic ? 'md-italic' : ''}}">{{seg.text}}</text>
+            </view>
+          </view>
+          <view class="ai-summary-divider" wx:if="{{aiInsightSummary.evaluation && aiInsightSummary.tracking}}"></view>
+          <view class="ai-summary-block ai-summary-block--tracking" wx:if="{{aiInsightSummary.tracking}}">
+            <text class="ai-summary-block-title">⏰ {{aiInsightSummary.tracking.title}}</text>
+            <view class="ai-summary-block-body ai-summary-block-body-clamp">
+              <text wx:for="{{aiInsightSummary.tracking.bodySegs}}" wx:key="index" wx:for-item="seg" class="md-seg {{seg.bold ? 'md-bold' : ''}} {{seg.italic ? 'md-italic' : ''}}">{{seg.text}}</text>
+            </view>
+          </view>
         </view>
-        <view class="ai-insight-body" wx:else>
-          <text class="ai-insight-line ai-insight-dim">暂无洞察数据</text>
+
+        <view class="ai-insight-body" wx:if="{{aiInsightDetails.length > 0}}">
+          <view class="ai-insight-details-label" wx:if="{{aiInsightSummary.evaluation || aiInsightSummary.tracking}}">
+            <text class="ai-insight-details-label-text">分板块明细洞察 · 仅展示前 3 条</text>
+          </view>
+          <!-- 2026-04-22 v3：seq 1/2/3 统一展示"标题 + 单行省略正文"，详情看弹窗 -->
+          <block wx:for="{{aiInsightDetails}}" wx:key="index" wx:if="{{index < 3}}">
+            <view class="ai-insight-item">
+              <view class="ai-insight-item-title">
+                <text class="ai-insight-item-seq">{{index + 1}}</text>
+                <text class="ai-insight-item-name">{{item.title}}</text>
+              </view>
+              <view class="ai-insight-item-body ai-insight-item-body-ellipsis">
+                <text wx:for="{{item.bodySegs}}" wx:key="index" wx:for-item="seg" class="md-seg {{seg.bold ? 'md-bold' : ''}} {{seg.italic ? 'md-italic' : ''}}">{{seg.text}}</text>
+              </view>
+            </view>
+          </block>
+          <!-- 2026-04-22 v3：只要有洞察就显示"查看全部"按钮，引导进弹窗看完整内容 -->
+          <view class="ai-insight-more" wx:if="{{aiInsightDetails.length > 0 || aiInsightSummary.evaluation}}" bindtap="openAllInsights" hover-class="ai-insight-more-hover">
+            <text class="ai-insight-more-text">查看全部 AI 洞察 ›</text>
+          </view>
+        </view>
+        <view class="ai-insight-body" wx:elif="{{!aiInsightSummary.evaluation && !aiInsightSummary.tracking}}">
+          <view class="ai-insight-item-body ai-insight-dim">暂无洞察数据</view>
+        </view>
+      </view>
+
+      <!-- AI 洞察全部查看弹窗：覆盖除底部 tab 外整个页面；header / 可滚动 body / 底部通栏按钮 -->
+      <view class="ai-modal-mask" wx:if="{{aiInsightsModalVisible}}" bindtap="closeAllInsights" catchtouchmove="_noop">
+        <view class="ai-modal" catchtap="_noop">
+          <view class="ai-modal-header">
+            <view class="ai-modal-title-wrap">
+              <view class="ai-insight-icon">
+                <image src="/assets/icons/ai-robot.svg" mode="aspectFit" class="ai-insight-icon-img" />
+              </view>
+              <text class="ai-modal-title">AI 智能洞察 · 共 {{aiInsights.length}} 条</text>
+            </view>
+            <view class="ai-modal-close" bindtap="closeAllInsights" hover-class="ai-modal-close-hover">
+              <text class="ai-modal-close-icon">✕</text>
+            </view>
+          </view>
+          <scroll-view scroll-y="{{true}}" class="ai-modal-body" enhanced="{{true}}" show-scrollbar="{{false}}" bounces="{{true}}">
+            <!-- 弹窗顶部：本期总结（seq11+seq12）- 同款 summary-card -->
+            <view class="ai-summary-card ai-summary-card--{{summaryLightType || 'neutral'}} ai-summary-card--modal" wx:if="{{aiInsightSummary.evaluation || aiInsightSummary.tracking}}">
+              <view class="ai-summary-head">
+                <view class="ai-summary-badge ai-summary-badge--{{summaryLightType || 'neutral'}}" wx:if="{{summaryLightLabel}}">
+                  <text>{{summaryLightLabel}}</text>
+                </view>
+                <text class="ai-summary-head-title">本期总结</text>
+              </view>
+              <view class="ai-summary-block" wx:if="{{aiInsightSummary.evaluation}}">
+                <view class="ai-summary-block-body">
+                  <text wx:for="{{aiInsightSummary.evaluation.bodySegs}}" wx:key="index" wx:for-item="seg" class="md-seg {{seg.bold ? 'md-bold' : ''}} {{seg.italic ? 'md-italic' : ''}}">{{seg.text}}</text>
+                </view>
+              </view>
+              <view class="ai-summary-divider" wx:if="{{aiInsightSummary.evaluation && aiInsightSummary.tracking}}"></view>
+              <view class="ai-summary-block ai-summary-block--tracking" wx:if="{{aiInsightSummary.tracking}}">
+                <text class="ai-summary-block-title">⏰ {{aiInsightSummary.tracking.title}}</text>
+                <view class="ai-summary-block-body">
+                  <text wx:for="{{aiInsightSummary.tracking.bodySegs}}" wx:key="index" wx:for-item="seg" class="md-seg {{seg.bold ? 'md-bold' : ''}} {{seg.italic ? 'md-italic' : ''}}">{{seg.text}}</text>
+                </view>
+              </view>
+            </view>
+
+            <view class="ai-modal-details-label" wx:if="{{(aiInsightSummary.evaluation || aiInsightSummary.tracking) && aiInsightDetails.length > 0}}">
+              <text class="ai-modal-details-label-text">分板块明细洞察</text>
+            </view>
+            <view class="ai-modal-item" wx:for="{{aiInsightDetails}}" wx:key="index">
+              <view class="ai-modal-item-title">
+                <text class="ai-modal-item-seq">{{index + 1}}</text>
+                <text class="ai-modal-item-name">{{item.title}}</text>
+              </view>
+              <view class="ai-modal-item-body">
+                <text wx:for="{{item.bodySegs}}" wx:key="index" wx:for-item="seg" class="md-seg {{seg.bold ? 'md-bold' : ''}} {{seg.italic ? 'md-italic' : ''}}">{{seg.text}}</text>
+              </view>
+            </view>
+            <view class="ai-modal-footer-space"></view>
+          </scroll-view>
+          <view class="ai-modal-footer" bindtap="closeAllInsights" hover-class="ai-modal-footer-hover">关闭</view>
         </view>
       </view>
     </view>

apps/miniprogram/miniprogram/pages/board-finance/board-finance.wxss

@@ -492,7 +492,7 @@ AI_CHANGELOG
   display: flex;
   align-items: center;
   gap: 14rpx;
-  margin-bottom: 22rpx;
+  margin-bottom: 30rpx;
 }
 
 /* CHANGE 2026-03-12 | intent: H5 原型 AI 图标为 SVG 机器人（24×24 → 42rpx），不可用 emoji 替代 */
@@ -545,6 +545,357 @@ AI_CHANGELOG
   color: rgba(255, 255, 255, 0.85);
 }
 
+/* CHANGE 2026-04-22 v2 | AI 洞察列表项：与弹窗同款（序号徽章 + 标题 + 缩进正文） */
+.ai-insight-item {
+  padding: 6rpx 0 10rpx 0;
+}
+
+.ai-insight-item-title {
+  display: flex;
+  align-items: center;
+  gap: 12rpx;
+  margin-bottom: 8rpx;
+}
+
+.ai-insight-item-seq {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  min-width: 32rpx;
+  height: 32rpx;
+  padding: 0 8rpx;
+  border-radius: 10rpx;
+  background: linear-gradient(135deg, #667eea, #764ba2);
+  color: #fff;
+  font-size: 20rpx;
+  font-weight: 600;
+}
+
+.ai-insight-item-name {
+  font-size: 26rpx;
+  font-weight: 600;
+  color: rgba(255, 255, 255, 0.95);
+  flex: 1;
+  overflow: hidden;
+  text-overflow: ellipsis;
+  white-space: nowrap;
+}
+
+.ai-insight-item-body {
+  display: block;
+  font-size: 24rpx;
+  line-height: 36rpx;
+  color: rgba(255, 255, 255, 0.78);
+  text-indent: 48rpx;
+}
+
+.ai-insight-item-body-ellipsis {
+  display: -webkit-box;
+  -webkit-box-orient: vertical;
+  -webkit-line-clamp: 1;
+  overflow: hidden;
+  text-overflow: ellipsis;
+}
+
+/* ===== 2026-04-22 seq11/12 置顶：本期总结（轻量版） ===== */
+/* 不用卡片容器，直接嵌入 AI 洞察区，用彩色小点 + 淡分隔区分层级 */
+.ai-summary-card {
+  margin: 0 24rpx 18rpx 0;
+  padding: 0 0 18rpx 0;
+  border-bottom: 2rpx dashed rgba(255, 255, 255, 0.1);
+}
+
+.ai-summary-card--modal {
+  margin: 0 0 14rpx 0;
+}
+
+/* 去掉左侧彩条，保留类名备用（无样式即不渲染） */
+.ai-summary-card--green,
+.ai-summary-card--yellow,
+.ai-summary-card--red,
+.ai-summary-card--neutral {
+  background: transparent;
+}
+
+.ai-summary-head {
+  display: flex;
+  align-items: baseline;       /* 徽章与"本期总结"按文字基线对齐（字号不同时看起来贴底） */
+  gap: 10rpx;
+  margin-bottom: 14rpx;
+}
+
+/* 徽章：去胶囊底，纯色粗字强调三色灯级别 */
+.ai-summary-badge {
+  display: inline-flex;
+  align-items: center;
+  font-size: 30rpx;
+  font-weight: 700;
+  letter-spacing: 1rpx;
+  padding: 0;
+  background: transparent !important;
+  box-shadow: none !important;
+}
+
+.ai-summary-badge--green { color: #4ade80; }
+.ai-summary-badge--yellow { color: #facc15; }
+.ai-summary-badge--red { color: #f87171; }
+.ai-summary-badge--neutral { color: rgba(255, 255, 255, 0.6); }
+
+.ai-summary-head-title {
+  font-size: 22rpx;
+  font-weight: 400;
+  color: rgba(255, 255, 255, 0.5);
+  letter-spacing: 1rpx;
+}
+
+.ai-summary-block {
+  display: flex;
+  flex-direction: column;
+  gap: 6rpx;
+}
+
+.ai-summary-block-title {
+  font-size: 25rpx;
+  font-weight: 600;
+  color: rgba(255, 255, 255, 0.88);
+  line-height: 36rpx;
+}
+
+.ai-summary-block-body {
+  font-size: 24rpx;
+  line-height: 36rpx;
+  color: rgba(255, 255, 255, 0.72);
+}
+
+/* 2026-04-22 v3：总结区 body 2 行省略，突出要点 */
+.ai-summary-block-body-clamp {
+  display: -webkit-box;
+  -webkit-box-orient: vertical;
+  overflow: hidden;
+  text-overflow: ellipsis;
+}
+
+.ai-summary-block--tracking {
+  margin-top: 14rpx;
+}
+.ai-summary-block--tracking .ai-summary-block-title {
+  color: rgba(251, 191, 36, 0.85);
+  font-weight: 500;
+}
+
+.ai-summary-divider {
+  display: none;
+}
+
+/* "分板块明细洞察"分组标签 */
+.ai-insight-details-label {
+  padding: 2rpx 0 12rpx 0;
+}
+
+.ai-insight-details-label-text {
+  font-size: 20rpx;
+  color: rgba(255, 255, 255, 0.42);
+  letter-spacing: 1rpx;
+}
+
+.ai-modal-details-label {
+  padding: 6rpx 0 8rpx 0;
+  margin-bottom: 4rpx;
+}
+
+.ai-modal-details-label-text {
+  font-size: 20rpx;
+  color: rgba(255, 255, 255, 0.42);
+  letter-spacing: 1rpx;
+}
+
+/* 2026-04-22 小程序 Markdown 内联样式：**加粗** / *倾斜* */
+.md-seg {
+  display: inline;
+}
+
+.md-bold {
+  font-weight: 700;
+  color: rgba(255, 255, 255, 0.98);
+}
+
+.md-italic {
+  font-style: italic;
+}
+
+/* 加粗同时倾斜时组合生效（class 拼接即可） */
+
+/* CHANGE 2026-04-22 v2 | "查看全部" 按钮居中 */
+.ai-insight-more {
+  margin: 10rpx 24rpx 0 0;
+  padding: 18rpx 24rpx;
+  text-align: center;
+  color: rgba(255, 255, 255, 0.88);
+  font-size: 26rpx;
+  background: rgba(255, 255, 255, 0.06);
+  border-radius: 12rpx;
+}
+
+.ai-insight-more-hover {
+  background: rgba(255, 255, 255, 0.12);
+}
+
+.ai-insight-more-text {
+  letter-spacing: 1rpx;
+}
+
+/* CHANGE 2026-04-22 | AI 全部洞察弹窗：覆盖除底部 tab 外整个页面 */
+.ai-modal-mask {
+  position: fixed;
+  top: 0;
+  left: 0;
+  right: 0;
+  bottom: 110rpx;              /* 避让自定义 tabBar 约 110rpx */
+  bottom: calc(110rpx + env(safe-area-inset-bottom));
+  background: rgba(0, 0, 0, 0.55);
+  z-index: 9998;
+  display: flex;
+  flex-direction: column;
+  justify-content: flex-end;
+}
+
+/* 2026-04-22 v5：fixed top+bottom 固定高（scroll-view 在 flex max-height 里渲染溢出，放弃 auto 高度） */
+.ai-modal {
+  position: fixed;
+  left: 24rpx;
+  right: 24rpx;
+  top: 40rpx;
+  bottom: calc(150rpx + env(safe-area-inset-bottom));   /* 110rpx tab + 40rpx 留白 */
+  background: #2e2e2e;
+  border-radius: 24rpx;
+  display: flex;
+  flex-direction: column;
+  overflow: hidden;
+  box-shadow: 0 12rpx 48rpx rgba(0, 0, 0, 0.45);
+  z-index: 9999;
+}
+
+.ai-modal-header {
+  flex-shrink: 0;
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  padding: 28rpx 28rpx 20rpx 28rpx;
+  border-bottom: 2rpx solid rgba(255, 255, 255, 0.08);
+}
+
+.ai-modal-title-wrap {
+  display: flex;
+  align-items: center;
+  gap: 14rpx;
+  flex: 1;
+  min-width: 0;
+}
+
+.ai-modal-title {
+  font-size: 28rpx;
+  font-weight: 600;
+  color: rgba(255, 255, 255, 0.95);
+  overflow: hidden;
+  text-overflow: ellipsis;
+  white-space: nowrap;
+}
+
+.ai-modal-close {
+  width: 52rpx;
+  height: 52rpx;
+  border-radius: 50%;
+  background: rgba(255, 255, 255, 0.08);
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  margin-left: 16rpx;
+}
+
+.ai-modal-close-hover {
+  background: rgba(255, 255, 255, 0.18);
+}
+
+.ai-modal-close-icon {
+  font-size: 28rpx;
+  color: rgba(255, 255, 255, 0.85);
+  line-height: 28rpx;
+}
+
+.ai-modal-body {
+  /* 2026-04-22 v5：modal 固定高度后 flex:1 1 0 分配剩余空间给 scroll-view */
+  flex: 1 1 0;
+  min-height: 0;
+  padding: 20rpx 28rpx 12rpx 28rpx;
+  box-sizing: border-box;
+}
+
+.ai-modal-item {
+  padding: 22rpx 0 22rpx 0;
+  border-bottom: 2rpx dashed rgba(255, 255, 255, 0.1);
+}
+
+.ai-modal-item:last-of-type {
+  border-bottom: none;
+}
+
+.ai-modal-item-title {
+  display: flex;
+  align-items: center;
+  gap: 12rpx;
+  margin-bottom: 10rpx;
+}
+
+.ai-modal-item-seq {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  min-width: 36rpx;
+  height: 36rpx;
+  padding: 0 10rpx;
+  border-radius: 18rpx;
+  background: linear-gradient(135deg, #667eea, #764ba2);
+  color: #fff;
+  font-size: 22rpx;
+  font-weight: 600;
+}
+
+.ai-modal-item-name {
+  font-size: 28rpx;
+  font-weight: 600;
+  color: rgba(255, 255, 255, 0.95);
+  flex: 1;
+}
+
+.ai-modal-item-body {
+  display: block;
+  font-size: 26rpx;
+  line-height: 40rpx;
+  color: rgba(255, 255, 255, 0.78);
+  text-indent: 48rpx;          /* 首行缩进，和 seq 徽章对齐阅读感 */
+}
+
+.ai-modal-footer-space {
+  height: 24rpx;
+}
+
+/* 2026-04-22 v3 | 弹窗底部整块作为关闭按钮：固定高度 100rpx，贯通整宽 */
+.ai-modal-footer {
+  flex-shrink: 0;
+  height: 100rpx;
+  line-height: 100rpx;
+  text-align: center;
+  font-size: 30rpx;
+  font-weight: 500;
+  color: #fff;
+  background: linear-gradient(135deg, #667eea, #764ba2);
+  letter-spacing: 8rpx;
+}
+
+.ai-modal-footer-hover {
+  opacity: 0.82;
+}
+
 /* ===== 通用表格边框容器 ===== */
 .table-bordered {
   border: 2rpx solid #e7e7e7;

apps/miniprogram/miniprogram/pages/chat/chat.ts

@@ -198,6 +198,12 @@ Page({
   /** 最后一次发送的用户消息内容（用于重试） */
   _lastUserContent: '',
 
+  /** SSE 断线重试次数 */
+  _sseRetryCount: 0,
+
+  /** SSE 最大自动重试次数 */
+  _SSE_MAX_RETRY: 2,
+
   onShow() {
     // 权限守卫：检查登录状态、账号禁用、角色权限
     checkPageAccess('pages/chat/chat')
@@ -227,10 +233,27 @@ Page({
       this.loadMessagesByContext('coach', options.coachId)
     } else if (options?.sourcePage) {
       // 看板类入口：保存来源页面和筛选参数
-      const filterKeys = ['timeDimension', 'areaFilter', 'dimension', 'typeFilter', 'projectFilter']
+      // Phase 2.3：优先解析 options.pageFilters（ai-float-button 传入的 JSON 字符串），
+      // 回退到单独键（旧入口兼容：timeDimension / areaFilter 等）
       const pageFilters: Record<string, string> = {}
-      for (const key of filterKeys) {
-        if (options[key]) pageFilters[key] = options[key]
+      if (options.pageFilters) {
+        try {
+          const parsed = JSON.parse(decodeURIComponent(options.pageFilters))
+          if (parsed && typeof parsed === 'object') {
+            for (const k of Object.keys(parsed)) {
+              const v = parsed[k]
+              if (v != null) pageFilters[k] = String(v)
+            }
+          }
+        } catch {
+          // JSON 解析失败忽略，回退到单键读取
+        }
+      }
+      if (Object.keys(pageFilters).length === 0) {
+        const filterKeys = ['timeDimension', 'areaFilter', 'dimension', 'typeFilter', 'projectFilter']
+        for (const key of filterKeys) {
+          if (options[key]) pageFilters[key] = options[key]
+        }
       }
       this.setData({ sourcePage: options.sourcePage, pageFilters })
       this.loadMessagesByContext(options.sourcePage, '')
@@ -418,6 +441,7 @@ Page({
       },
       // onDone: 流结束，更新消息 ID 和时间
       (messageId: number, createdAt: string) => {
+        this._sseRetryCount = 0
         this.setData({
           [`messages[${aiIndex}].id`]: String(messageId),
           [`messages[${aiIndex}].timestamp`]: createdAt,
@@ -477,8 +501,20 @@ Page({
         }
       },
       fail: () => {
-        // 网络错误或连接中断
-        if (this.data.isStreaming) {
+        // 网络错误或连接中断：无内容时指数退避重连
+        this._sseTask = null
+        if (!this.data.isStreaming) return
+        if (fullContent === '' && this._sseRetryCount < this._SSE_MAX_RETRY) {
+          this._sseRetryCount++
+          const delay = (2 ** this._sseRetryCount) * 1000
+          wx.showToast({ title: `重连中 ${this._sseRetryCount}/${this._SSE_MAX_RETRY}...`, icon: 'loading', duration: delay })
+          this.setData({
+            messages: this.data.messages.slice(0, aiIndex),
+            isStreaming: false,
+            streamingContent: '',
+          })
+          setTimeout(() => { this.triggerAIReply(chatId, content) }, delay)
+        } else {
           const errorContent = fullContent || '连接中断，请重试'
           this.setData({
             [`messages[${aiIndex}].content`]: errorContent,
@@ -487,7 +523,6 @@ Page({
           })
           wx.showToast({ title: '连接中断', icon: 'none', duration: 3000 })
         }
-        this._sseTask = null
       },
     } as WechatMiniprogram.RequestOption)
 
@@ -509,4 +544,19 @@ Page({
       }, 50)
     }, 50)
   },
+
+  /** 点击引用卡片：跳转到对应详情页（Phase 2.1） */
+  onRefCardTap(e: WechatMiniprogram.BaseEvent & { currentTarget: { dataset: { link?: string } } }) {
+    const link = e.currentTarget?.dataset?.link
+    if (!link || typeof link !== 'string') {
+      return
+    }
+    wx.navigateTo({
+      url: link,
+      fail: (err) => {
+        console.error('跳转引用详情失败', err)
+        wx.showToast({ title: '跳转失败', icon: 'none' })
+      },
+    })
+  },
 })

apps/miniprogram/miniprogram/pages/chat/chat.wxml

@@ -92,13 +92,18 @@
             <text class="bubble-text">{{item.content}}</text>
           </view>
           <!-- AI 侧引用卡片（后端 referenceCard 附加在 assistant 回复中）-->
-          <view class="inline-ref-card inline-ref-card--assistant" wx:if="{{item.referenceCard}}">
+          <view
+            class="inline-ref-card inline-ref-card--assistant {{item.referenceCard.link ? 'inline-ref-card--link' : ''}}"
+            wx:if="{{item.referenceCard}}"
+            data-link="{{item.referenceCard.link}}"
+            bindtap="onRefCardTap"
+          >
             <view class="inline-ref-header">
-              <text class="inline-ref-type">{{item.referenceCard.type === 'customer' ? '👤 客户' : '📋 记录'}}</text>
+              <text class="inline-ref-type">{{item.referenceCard.type === 'customer' ? '👤 客户' : item.referenceCard.type === 'assistant' ? '🧑\u200d🏫 助教' : item.referenceCard.type === 'task' ? '📋 任务' : '📋 记录'}}</text>
               <text class="inline-ref-title">{{fmt.safe(item.referenceCard.title)}}</text>
             </view>
             <text class="inline-ref-summary">{{fmt.safe(item.referenceCard.summary)}}</text>
-            <view class="inline-ref-data">
+            <view class="inline-ref-data" wx:if="{{item.referenceCard.dataList.length > 0}}">
               <view class="ref-data-item" wx:for="{{item.referenceCard.dataList}}" wx:for-item="entry" wx:key="key">
                 <text class="ref-data-key">{{fmt.safe(entry.key)}}</text>
                 <text class="ref-data-value">{{fmt.safe(entry.value)}}</text>

apps/miniprogram/miniprogram/pages/customer-detail/customer-detail.ts

@@ -4,7 +4,7 @@
 | 2026-03-23 | 角色路由+页面权限守卫 | onShow 添加 checkPageAccess 权限守卫 |
 */
 import { checkPageAccess } from '../../utils/auth-guard'
-import { fetchCustomerDetail } from '../../services/api'
+import { fetchCustomerDetail, fetchAICache } from '../../services/api'
 
 interface ConsumptionRecord {
   id: string
@@ -132,6 +132,7 @@ Page({
         }
       }
       this.setData({ pageState: 'normal' })
+      if (id) this._loadAIInsight(id)
     } catch (e) {
       console.error('[customer-detail] loadDetail 失败:', e)
       this.setData({ pageState: 'error' })
@@ -140,6 +141,23 @@ Page({
     }
   },
 
+  async _loadAIInsight(memberId: string) {
+    const cache = await fetchAICache('app7_customer_analysis', memberId)
+    if (!cache?.result_json) return
+    const rj = cache.result_json as any
+    const COLORS = ['blue', 'indigo', 'purple', 'red', 'orange', 'yellow'] as const
+    const strategies = Array.isArray(rj.strategies)
+      ? rj.strategies.map((s: any, i: number) => ({
+          color: COLORS[i % COLORS.length],
+          text: s.title || s.text || '',
+        }))
+      : []
+    this.setData({
+      'aiInsight.summary': rj.summary || '',
+      'aiInsight.strategies': strategies,
+    })
+  },
+
   onRetry() {
     const id = this.data.detail?.id || ''
     this.loadDetail(id)

apps/miniprogram/miniprogram/pages/customer-records/customer-records.ts

@@ -5,6 +5,8 @@
 */
 import { checkPageAccess } from '../../utils/auth-guard'
 import { fetchCustomerConsumptionRecords } from '../../services/api'
+// CHANGE 2026-05-02 | 业务时钟：sandbox 模式下用 business_year/month 替代 new Date()
+import { getBusinessClock } from '../../utils/runtime-clock'
 
 Page({
   data: {
@@ -38,11 +40,12 @@ Page({
     monthLoading: false,
   },
 
-  onLoad(options) {
+  async onLoad(options) {
     const id = options?.customerId || options?.id || ''
-    const now = new Date()
-    const currentYear = now.getFullYear()
-    const currentMonth = now.getMonth() + 1
+    // CHANGE 2026-05-02 | 默认当前年月走业务时钟，sandbox 模式按 sandbox_date 显示
+    const clock = await getBusinessClock()
+    const currentYear = clock.business_year
+    const currentMonth = clock.business_month
     this.setData({
       customerId: id,
       currentYear,

apps/miniprogram/miniprogram/pages/customer-service-records/customer-service-records.ts

@@ -5,6 +5,8 @@
 | 2026-03-27 | 任务A 前端改造 | 修复数据转换（duration/income/timeRange/table/recordType），去掉 loadCustomerInfo 改从 records 响应取客户信息，新增 monthIncome 展示 |
 */
 import { checkPageAccess } from '../../utils/auth-guard'
+// CHANGE 2026-05-02 | 业务时钟：sandbox 模式下用 business_year/month 替代 new Date()
+import { getBusinessClock } from '../../utils/runtime-clock'
 // CHANGE 2026-03-27 | 任务A A5: 去掉 fetchCustomerDetail，客户信息从 fetchCustomerRecords 响应中获取
 import { fetchCustomerRecords } from '../../services/api'
 import { formatCount } from '../../utils/money'
@@ -86,12 +88,12 @@ Page({
     monthLoading: false,
   },
 
-  onLoad(options) {
+  async onLoad(options) {
     const id = options?.customerId || options?.id || ''
-    // 默认当前年月
-    const now = new Date()
-    const currentYear = now.getFullYear()
-    const currentMonth = now.getMonth() + 1
+    // CHANGE 2026-05-02 | 默认当前年月走业务时钟，sandbox 模式按 sandbox_date 显示
+    const clock = await getBusinessClock()
+    const currentYear = clock.business_year
+    const currentMonth = clock.business_month
     this.setData({
       customerId: id,
       currentYear,

apps/miniprogram/miniprogram/pages/performance-records/performance-records.ts

@@ -11,6 +11,8 @@ import { nameToAvatarColor } from '../../utils/avatar-color'
 import { formatMoney, formatCount } from '../../utils/money'
 import { formatHours } from '../../utils/time'
 import { API_BASE } from '../../utils/config'
+// CHANGE 2026-05-02 | 业务时钟：sandbox 模式下用 business_year/month 替代 new Date()
+import { getBusinessClock } from '../../utils/runtime-clock'
 
 /** 中文课程类型 → 英文 CSS key（WXSS 不支持中文类名） */
 const COURSE_TAG_MAP: Record<string, string> = {
@@ -58,7 +60,7 @@ Page({
     coachRole: '',
     storeName: '',
 
-    /** 月份切换 */
+    /** 月份切换（onLoad 中改写为业务时钟当前年月） */
     currentYear: new Date().getFullYear(),
     currentMonth: new Date().getMonth() + 1,
     monthLabel: '',
@@ -83,12 +85,13 @@ Page({
     hasMore: false,
   },
 
-  onLoad() {
-    const now = new Date()
+  async onLoad() {
+    // CHANGE 2026-05-02 | 用业务时钟初始化年月，sandbox 模式按 sandbox_date 显示
+    const clock = await getBusinessClock()
     this.setData({
-      currentYear: now.getFullYear(),
-      currentMonth: now.getMonth() + 1,
-      monthLabel: `${now.getFullYear()}年${now.getMonth() + 1}月`,
+      currentYear: clock.business_year,
+      currentMonth: clock.business_month,
+      monthLabel: `${clock.business_year}年${clock.business_month}月`,
     })
     this.loadBanner()
     this.loadData()
@@ -140,11 +143,13 @@ Page({
     wx.showLoading({ title: '加载中...', mask: true })
 
     // 预估规则：当月且当前日期 ≤ 5号（全小程序统一）
-    const now = new Date()
+    // CHANGE 2026-05-02 | 用业务时钟，sandbox 模式按 sandbox_date 判断
+    const clock = await getBusinessClock()
     const { currentYear, currentMonth } = this.data
-    const isCurrentMonth = currentYear === now.getFullYear()
-      && currentMonth === now.getMonth() + 1
-      && now.getDate() <= 5
+    const businessDay = parseInt(clock.business_date.slice(8, 10), 10) || 1
+    const isCurrentMonth = currentYear === clock.business_year
+      && currentMonth === clock.business_month
+      && businessDay <= 5
 
     try {
       const res = await fetchPerformanceRecords({
@@ -243,7 +248,7 @@ Page({
   },
 
   /** 切换月份 */
-  switchMonth(e: WechatMiniprogram.TouchEvent) {
+  async switchMonth(e: WechatMiniprogram.TouchEvent) {
     const direction = e.currentTarget.dataset.direction as 'prev' | 'next'
     let { currentYear, currentMonth } = this.data
 
@@ -255,11 +260,13 @@ Page({
       if (currentMonth > 12) { currentMonth = 1; currentYear++ }
     }
 
-    const now = new Date()
-    const nowYear = now.getFullYear()
-    const nowMonth = now.getMonth() + 1
+    // CHANGE 2026-05-02 | 用业务时钟，sandbox 模式下不允许"翻到 sandbox_date 之后"
+    const clock = await getBusinessClock()
+    const nowYear = clock.business_year
+    const nowMonth = clock.business_month
+    const businessDay = parseInt(clock.business_date.slice(8, 10), 10) || 1
     const canGoNext = currentYear < nowYear || (currentYear === nowYear && currentMonth < nowMonth)
-    const isCurrentMonth = currentYear === nowYear && currentMonth === nowMonth && now.getDate() <= 5
+    const isCurrentMonth = currentYear === nowYear && currentMonth === nowMonth && businessDay <= 5
 
     // 月份切换重置分页到第 1 页
     this.setData({

apps/miniprogram/miniprogram/pages/performance/performance.ts

@@ -10,6 +10,8 @@ import { fetchMe, fetchPerformanceOverview } from '../../services/api'
 import { nameToAvatarColor } from '../../utils/avatar-color'
 // CHANGE 2026-03-27 | 头像：需要 API_BASE 构建头像完整 URL
 import { API_BASE } from '../../utils/config'
+// CHANGE 2026-05-02 | 业务时钟：sandbox 模式下用 business_year/month 替代 new Date()
+import { getBusinessClock } from '../../utils/runtime-clock'
 
 /** 中文课程类型 → 英文 CSS key（WXSS 不支持中文类名） */
 const COURSE_TAG_MAP: Record<string, string> = {
@@ -118,15 +120,16 @@ Page({
     this.setData({ pageState: 'loading' })
     wx.showLoading({ title: '加载中...', mask: true })
 
-    // G2：当月预估判断
-    const now = new Date()
-    const nowYear = now.getFullYear()
-    const nowMonth = now.getMonth() + 1
+    // CHANGE 2026-05-02 | G2 当月预估判断改用业务时钟（sandbox 模式按 sandbox_date 判断）
+    const clock = await getBusinessClock()
+    const nowYear = clock.business_year
+    const nowMonth = clock.business_month
+    const businessDay = parseInt(clock.business_date.slice(8, 10), 10) || 1
     // TODO: 联调时从接口参数或页面参数获取 year/month
     const year = nowYear
     const month = nowMonth
     // CHANGE 2026-03-24 | 预估规则：当月且当前日期 ≤ 5号才显示"预估"
-    const isCurrentMonth = year === nowYear && month === nowMonth && now.getDate() <= 5
+    const isCurrentMonth = year === nowYear && month === nowMonth && businessDay <= 5
 
     try {
       // 并行请求用户信息和绩效概览

apps/miniprogram/miniprogram/pages/task-list/task-list.ts

@@ -20,6 +20,8 @@ import { fetchTasks, fetchMe, pinTask, unpinTask, abandonTask, restoreTask, crea
 import { formatMoney } from '../../utils/money'
 import { formatDeadline } from '../../utils/time'
 import { formatStorageLevel } from '../../utils/storage-level'
+// CHANGE 2026-05-02 | 业务时钟：sandbox 模式下用 business_year/month 替代 new Date()
+import { getBusinessClock } from '../../utils/runtime-clock'
 // CHANGE 2026-03-27 | 头像：需要 API_BASE 构建头像完整 URL
 import { API_BASE } from '../../utils/config'
 import {
@@ -386,9 +388,11 @@ Page({
       }
 
       // G2: 当月预估判断
-      const now = new Date()
-      const nowYear = now.getFullYear()
-      const nowMonth = now.getMonth() + 1
+      // CHANGE 2026-05-02 | 用业务时钟，sandbox 模式按 sandbox_date 判断
+      const clock = await getBusinessClock()
+      const nowYear = clock.business_year
+      const nowMonth = clock.business_month
+      const businessDay = parseInt(clock.business_date.slice(8, 10), 10) || 1
       const incomeMonth = perfData.incomeMonth
       let dataYear = nowYear
       let dataMonth = nowMonth
@@ -397,7 +401,7 @@ Page({
         if (parts) dataMonth = parseInt(parts[1], 10)
       }
       // CHANGE 2026-03-24 | 预估规则：当月且当前日期 ≤ 5号才显示"预估"（全小程序统一）
-      const isCurrentMonth = dataYear === nowYear && dataMonth === nowMonth && now.getDate() <= 5
+      const isCurrentMonth = dataYear === nowYear && dataMonth === nowMonth && businessDay <= 5
 
       this.setData({
         pageState: totalCount > 0 ? 'normal' : 'empty',

apps/miniprogram/miniprogram/services/api.ts

@@ -35,6 +35,31 @@ export async function fetchMe(): Promise<ApiUserInfo> {
   return request({ url: '/api/xcx/me', method: 'GET', needAuth: true })
 }
 
+// ============================================
+// 业务时钟（沙箱支持）
+// ============================================
+
+export interface RuntimeClock {
+  mode: 'live' | 'sandbox'
+  business_date: string // YYYY-MM-DD
+  business_year: number
+  business_month: number
+  business_year_month: string // YYYY-MM
+  business_now: string
+  is_sandbox: boolean
+  sandbox_date: string | null
+  sandbox_instance_id: string | null
+}
+
+/**
+ * 获取当前门店的业务时钟（live 真实日，sandbox 模拟日）。
+ * 沙箱模式下，小程序所有依赖"当前年月"的请求都应使用此结果，
+ * 避免直接 ``new Date()`` 导致与后端 sandbox_date 不一致。
+ */
+export async function fetchRuntimeClock(): Promise<RuntimeClock> {
+  return request({ url: '/api/xcx/runtime/clock', method: 'GET', needAuth: true })
+}
+
 // ============================================
 // 任务模块
 // ============================================
@@ -413,6 +438,26 @@ export async function sendChatMessage(chatId: string, content: string): Promise<
 // 配置模块
 // ============================================
 
+/** AI 缓存查询（Phase 2.5） */
+export async function fetchAICache(cacheType: string, targetId: string): Promise<{
+  result_json: Record<string, any> | null;
+  score: number | null;
+} | null> {
+  try {
+    const data = await request({
+      url: `/api/ai/cache/${cacheType}`,
+      method: 'GET',
+      data: { target_id: targetId },
+      needAuth: true,
+    })
+    if (!data) return null
+    const d = data as any
+    return { result_json: d.result_json ?? null, score: d.score ?? null }
+  } catch {
+    return null
+  }
+}
+
 /** 项目类型筛选器列表（CONFIG-1） */
 // CHANGE 2026-03-20 | R3 修复：value 改为数据库 category_code，fallback 与后端一致
 export async function fetchSkillTypes(): Promise<Array<{ value: string; text: string; icon?: string }>> {

apps/miniprogram/miniprogram/utils/runtime-clock.ts

@@ -0,0 +1,83 @@
+// 业务时钟缓存
+//
+// sandbox 模式下，小程序的 performance / task-list / customer-records 等页面
+// 需要按"业务日"而不是"真实今天"构造请求参数。
+//
+// 用法：
+//   import { getBusinessClock, getBusinessYearMonth } from '../../utils/runtime-clock'
+//   const clock = await getBusinessClock()
+//   wx.request({ url: ..., data: { year: clock.business_year, month: clock.business_month } })
+//
+// 缓存策略：
+// - 单例 in-memory cache，最多 60 秒；过期后自动重新拉取。
+// - 切换沙箱后，建议页面调用 `clearBusinessClockCache()` 主动失效。
+
+import { fetchRuntimeClock, type RuntimeClock } from '../services/api'
+
+const TTL_MS = 60_000 // 60 秒缓存，足以覆盖一次页面进入
+
+let cached: { value: RuntimeClock; ts: number } | null = null
+let inflight: Promise<RuntimeClock> | null = null
+
+/** 主动清空业务时钟缓存（沙箱切换、登出后调用）。 */
+export function clearBusinessClockCache(): void {
+  cached = null
+  inflight = null
+}
+
+/** 拉取业务时钟（可能命中缓存）。失败时降级为本地"今天"。 */
+export async function getBusinessClock(force = false): Promise<RuntimeClock> {
+  const now = Date.now()
+  if (!force && cached && now - cached.ts < TTL_MS) {
+    return cached.value
+  }
+  if (inflight) {
+    return inflight
+  }
+  inflight = (async () => {
+    try {
+      const clock = await fetchRuntimeClock()
+      cached = { value: clock, ts: Date.now() }
+      return clock
+    } catch (err) {
+      console.warn('[runtime-clock] 拉取业务时钟失败，降级为本地时间', err)
+      return localFallback()
+    } finally {
+      inflight = null
+    }
+  })()
+  return inflight
+}
+
+/** 便捷方法：返回业务年月 (YYYY-MM)。 */
+export async function getBusinessYearMonth(): Promise<{ year: number; month: number; label: string }> {
+  const clock = await getBusinessClock()
+  return {
+    year: clock.business_year,
+    month: clock.business_month,
+    label: `${clock.business_year}年${clock.business_month}月`,
+  }
+}
+
+/** 便捷方法：返回业务日 (YYYY-MM-DD)。 */
+export async function getBusinessDate(): Promise<string> {
+  return (await getBusinessClock()).business_date
+}
+
+function localFallback(): RuntimeClock {
+  const d = new Date()
+  const year = d.getFullYear()
+  const month = d.getMonth() + 1
+  const ymd = `${year}-${String(month).padStart(2, '0')}-${String(d.getDate()).padStart(2, '0')}`
+  return {
+    mode: 'live',
+    business_date: ymd,
+    business_year: year,
+    business_month: month,
+    business_year_month: `${year}-${String(month).padStart(2, '0')}`,
+    business_now: d.toISOString(),
+    is_sandbox: false,
+    sandbox_date: null,
+    sandbox_instance_id: null,
+  }
+}