feat(analytics): 看板管理化补强——员工活跃排行表+预警行动入口卡片

管理者反馈「纯汇总数字看不到有用信息」:overview 载荷扩
staff_ranking(全员行:msg_total rollup 优先/空表回退 msg_daily_stats
聚合,active_* 两路径统一走 msg_daily_stats 窗内 distinct peer——
stat_daily_staff 的 active_* 是当日快照,跨日 SUM/MAX 语义皆错;
call_cnt 按 user_id 落窗直查;环比同期对齐)+ actions(该回未回 2h/
真流失 30d/敏感词 pending,复用已测试查询路径各取 total)。

前端看板:toolbar 下三张可点行动卡(0 灰显仍可点,直达处置页,
随 channel 切换刷新)+ 趋势卡下员工排行表(max-height 420 滚动,
未映射小 tag,环比色同卡片惯例 None 显 '-')。

测试 574→577 全绿(rollup 聚合/回退/行动计数三新);build 过。

Co-Authored-By: Claude Code <noreply@anthropic.com>

yunke-server/app/analytics/metrics.py

@@ -19,6 +19,7 @@ from app.db.models import (
     Message,
     MsgDailyStats,
     PhoneCall,
+    SensitiveHit,
     Staff,
     StatDailyStaff,
 )
@@ -264,6 +265,189 @@ async def anomaly(session: AsyncSession, channel: str) -> dict | None:
     return None
 
 
+async def staff_ranking(
+    session: AsyncSession, *, channel: str, scope: str,
+) -> list[dict]:
+    """员工活跃排行(A2 核心子集,2026-09-07 管理者反馈补强)。
+
+    口径:msg_total=stat_daily_staff 聚合(空表回退 msg_daily_stats+映射,
+    同 _active_staff 模式);call_cnt=phone_call 按 user_id 落窗直查(3k 行
+    小表);环比=与 _prev_scope_days 同期对比(None=前窗无数据);名字取
+    staff.name,无 staff 行/未映射账号回退 user_id 原值标 unmapped。
+    排序 msg_total desc + user_id asc 决胜。返回全部行(员工 ~41)。
+
+    active_friends/active_rooms 两路径统一从 msg_daily_stats 算窗内
+    COUNT(DISTINCT peer)(映射合并到员工后,同 recompute_days 模式):
+    stat_daily_staff 的 active_* 是**当日快照**,跨日 SUM 会重复计数、
+    MAX 只是峰值,皆非「窗内活跃去重数」——rollup 只供 msg_total,
+    避免两路径语义分叉。
+    """
+    days = scope_day_keys(scope, today_key())
+    amap = await account_map(session, channel)
+
+    # 活跃客户/群 + 回退 msg_total:落窗拉行,Python 侧映射后按 user 去重
+    # (COUNT(DISTINCT peer) 必须在「账号合并到员工」之后——同人多账号
+    # 跨账号去重,写 SQL 反而绕且踩 only_full_group_by)
+    rows = (
+        await session.execute(
+            sa.select(
+                MsgDailyStats.owner_account_id,
+                MsgDailyStats.peer_kind,
+                MsgDailyStats.peer_id,
+                MsgDailyStats.send_cnt,
+                MsgDailyStats.recv_cnt,
+            ).where(
+                MsgDailyStats.channel == channel, MsgDailyStats.day.in_(days)
+            )
+        )
+    ).all()
+    act: dict[str, dict[str, set]] = {}
+    msg_fallback: dict[str, int] = {}
+    for owner, kind, peer, s, r in rows:
+        uid = amap.get(owner, owner)
+        a = act.setdefault(uid, {"friends": set(), "rooms": set()})
+        if kind == "friend":  # 显式分支:未来新 kind 跳过,不误入 rooms
+            a["friends"].add(peer)
+        elif kind == "room":
+            a["rooms"].add(peer)
+        msg_fallback[uid] = msg_fallback.get(uid, 0) + int(s or 0) + int(r or 0)
+
+    use_rollup = await _staff_rows(session)
+    if use_rollup:
+        rollup = (
+            await session.execute(
+                sa.select(
+                    StatDailyStaff.user_id,
+                    sa.func.coalesce(
+                        sa.func.sum(
+                            StatDailyStaff.msg_sent + StatDailyStaff.msg_recv
+                        ),
+                        0,
+                    ),
+                )
+                .where(
+                    StatDailyStaff.channel == channel,
+                    StatDailyStaff.day.in_(days),
+                )
+                .group_by(StatDailyStaff.user_id)
+            )
+        ).all()
+        msg_total = {uid: int(v) for uid, v in rollup}
+    else:
+        msg_total = msg_fallback
+
+    # 通话:按 user_id 落窗直查(窗口换算同 _call_count 写法)
+    calls: dict[str, int] = {}
+    if days:
+        lo, _ = day_bounds_ms(days[0])
+        hi_start, _ = day_bounds_ms(days[-1])
+        call_rows = (
+            await session.execute(
+                sa.select(PhoneCall.user_id, sa.func.count())
+                .where(
+                    PhoneCall.user_id.is_not(None),
+                    PhoneCall.start_call_time.is_not(None),
+                    PhoneCall.start_call_time >= lo,
+                    PhoneCall.start_call_time < hi_start + 86_400_000,
+                )
+                .group_by(PhoneCall.user_id)
+            )
+        ).all()
+        calls = {uid: int(v) for uid, v in call_rows}
+
+    # 环比:同期对齐前窗(仅周/月;今日 vs 昨日全天会误导,与 overview 同口径)
+    prev_total: dict[str, int] = {}
+    if scope in ("week", "month"):
+        prev_days = _prev_scope_days(scope, days)
+        if use_rollup:
+            prev_rows = (
+                await session.execute(
+                    sa.select(
+                        StatDailyStaff.user_id,
+                        sa.func.coalesce(
+                            sa.func.sum(
+                                StatDailyStaff.msg_sent + StatDailyStaff.msg_recv
+                            ),
+                            0,
+                        ),
+                    )
+                    .where(
+                        StatDailyStaff.channel == channel,
+                        StatDailyStaff.day.in_(prev_days),
+                    )
+                    .group_by(StatDailyStaff.user_id)
+                )
+            ).all()
+            prev_total = {uid: int(v) for uid, v in prev_rows}
+        else:
+            prev_rows = (
+                await session.execute(
+                    sa.select(
+                        MsgDailyStats.owner_account_id,
+                        sa.func.coalesce(
+                            sa.func.sum(
+                                MsgDailyStats.send_cnt + MsgDailyStats.recv_cnt
+                            ),
+                            0,
+                        ),
+                    )
+                    .where(
+                        MsgDailyStats.channel == channel,
+                        MsgDailyStats.day.in_(prev_days),
+                    )
+                    .group_by(MsgDailyStats.owner_account_id)
+                )
+            ).all()
+            for owner, v in prev_rows:
+                uid = amap.get(owner, owner)  # 同人多账号累加,不覆盖
+                prev_total[uid] = prev_total.get(uid, 0) + int(v)
+
+    # 名字/未映射:staff 几十行全拉;映射值集=在册员工 user_id 全集
+    staff_names = {
+        uid: name
+        for uid, name in (
+            await session.execute(sa.select(Staff.user_id, Staff.name))
+        ).all()
+    }
+    mapped_uids = set(amap.values())
+
+    out = []
+    for uid in sorted(set(msg_total) | set(act) | set(calls),
+                      key=lambda u: (-msg_total.get(u, 0), u)):
+        cur, prev = msg_total.get(uid, 0), prev_total.get(uid, 0)
+        out.append({
+            "user_id": uid,
+            "name": staff_names.get(uid) or uid,
+            "unmapped": uid not in staff_names and uid not in mapped_uids,
+            "msg_total": cur,
+            "active_friends": len(act[uid]["friends"]) if uid in act else 0,
+            "active_rooms": len(act[uid]["rooms"]) if uid in act else 0,
+            "call_cnt": calls.get(uid, 0),
+            "msg_delta": round((cur - prev) / prev, 3) if cur and prev else None,
+        })
+    return out
+
+
+async def action_counts(session: AsyncSession, *, channel: str) -> dict:
+    """预警行动入口计数(看板顶部卡片):复用已测试的查询路径,各取 total。"""
+    un = await unreplied(session, channel=channel, hours=2, page=1, page_size=1)
+    ch = await churn(session, channel=channel, kind="real", tier=30, min_msgs=5,
+                     page=1, page_size=1)
+    pending = (
+        await session.execute(
+            sa.select(sa.func.count()).select_from(SensitiveHit).where(
+                SensitiveHit.channel == channel,
+                SensitiveHit.disposition == "pending",
+            )
+        )
+    ).scalar_one()
+    return {
+        "unreplied_2h": int(un["total"]),
+        "churn_real_30d": int(ch["total"]),
+        "sensitive_pending": int(pending),
+    }
+
+
 async def overview(
     session: AsyncSession, *, channel: str, scope: str, trend_days: int = 30
 ) -> dict[str, Any]:
@@ -341,6 +525,8 @@ async def overview(
         "cards": cards,
         "trend": trend,
         "anomaly": await anomaly(session, channel),
+        "staff_ranking": await staff_ranking(session, channel=channel, scope=scope),
+        "actions": await action_counts(session, channel=channel),
     }