feat: 优化用量查询分页和热力图性能

- 用量查询接口添加 limit/offset 分页参数支持
- 热力图统计从实时查询 Usage 表改为读取预计算的 StatsDaily/StatsUserDaily 表
- 修复 avg_response_time_ms 为 0 时被错误跳过的问题

frontend/src/api/me.ts

@@ -75,6 +75,16 @@ export interface ModelSummary {
   actual_total_cost_usd?: number  // 倍率消耗（仅管理员可见）
 }
 
+// 提供商统计接口
+export interface ProviderSummary {
+  provider: string
+  requests: number
+  total_tokens: number
+  total_cost_usd: number
+  success_rate: number | null
+  avg_response_time_ms: number | null
+}
+
 // 使用统计响应接口
 export interface UsageResponse {
   total_requests: number
@@ -87,6 +97,13 @@ export interface UsageResponse {
   quota_usd: number | null
   used_usd: number
   summary_by_model: ModelSummary[]
+  summary_by_provider?: ProviderSummary[]
+  pagination?: {
+    total: number
+    limit: number
+    offset: number
+    has_more: boolean
+  }
   records: UsageRecordDetail[]
   activity_heatmap?: ActivityHeatmap | null
 }
@@ -175,6 +192,8 @@ export const meApi = {
   async getUsage(params?: {
     start_date?: string
     end_date?: string
+    limit?: number
+    offset?: number
   }): Promise<UsageResponse> {
     const response = await apiClient.get<UsageResponse>('/api/users/me/usage', { params })
     return response.data

src/api/user_me/routes.py

@@ -104,9 +104,11 @@ async def get_my_usage(
     request: Request,
     start_date: Optional[datetime] = None,
     end_date: Optional[datetime] = None,
+    limit: int = Query(100, ge=1, le=200, description="每页记录数，默认100，最大200"),
+    offset: int = Query(0, ge=0, le=2000, description="偏移量，用于分页，最大2000"),
     db: Session = Depends(get_db),
 ):
-    adapter = GetUsageAdapter(start_date=start_date, end_date=end_date)
+    adapter = GetUsageAdapter(start_date=start_date, end_date=end_date, limit=limit, offset=offset)
     return await pipeline.run(adapter=adapter, http_request=request, db=db, mode=adapter.mode)
 
 
@@ -471,6 +473,8 @@ class ToggleMyApiKeyAdapter(AuthenticatedApiAdapter):
 class GetUsageAdapter(AuthenticatedApiAdapter):
     start_date: Optional[datetime]
     end_date: Optional[datetime]
+    limit: int = 100
+    offset: int = 0
 
     async def handle(self, context):  # type: ignore[override]
         db = context.db
@@ -553,7 +557,7 @@ class GetUsageAdapter(AuthenticatedApiAdapter):
             stats["total_cost_usd"] += item["total_cost_usd"]
             # 假设 summary 中的都是成功的请求
             stats["success_count"] += item["requests"]
-            if item.get("avg_response_time_ms"):
+            if item.get("avg_response_time_ms") is not None:
                 stats["total_response_time_ms"] += item["avg_response_time_ms"] * item["requests"]
                 stats["response_time_count"] += item["requests"]
 
@@ -582,7 +586,10 @@ class GetUsageAdapter(AuthenticatedApiAdapter):
             query = query.filter(Usage.created_at >= self.start_date)
         if self.end_date:
             query = query.filter(Usage.created_at <= self.end_date)
-        usage_records = query.order_by(Usage.created_at.desc()).limit(100).all()
+
+        # 计算总数用于分页
+        total_records = query.count()
+        usage_records = query.order_by(Usage.created_at.desc()).offset(self.offset).limit(self.limit).all()
 
         avg_resp_query = db.query(func.avg(Usage.response_time_ms)).filter(
             Usage.user_id == user.id,
@@ -608,6 +615,13 @@ class GetUsageAdapter(AuthenticatedApiAdapter):
             "used_usd": user.used_usd,
             "summary_by_model": summary_by_model,
             "summary_by_provider": summary_by_provider,
+            # 分页信息
+            "pagination": {
+                "total": total_records,
+                "limit": self.limit,
+                "offset": self.offset,
+                "has_more": self.offset + self.limit < total_records,
+            },
             "records": [
                 {
                     "id": r.id,

src/services/usage/service.py

@@ -1027,7 +1027,12 @@ class UsageService:
         window_days: int = 365,
         include_actual_cost: bool = False,
     ) -> Dict[str, Any]:
-        """按天统计请求活跃度，用于渲染热力图。"""
+        """按天统计请求活跃度，用于渲染热力图。
+
+        优化策略：
+        - 历史数据从预计算的 StatsDaily/StatsUserDaily 表读取
+        - 只有"今天"的数据才实时查询 Usage 表
+        """
 
         def ensure_timezone(value: datetime) -> datetime:
             if value.tzinfo is None:
@@ -1041,54 +1046,109 @@ class UsageService:
             ensure_timezone(start_date) if start_date else end_dt - timedelta(days=window_days - 1)
         )
 
-        # 对齐到自然日的开始/结束，避免遗漏边界数据
+        # 对齐到自然日的开始/结束
-        start_dt = start_dt.replace(hour=0, minute=0, second=0, microsecond=0)
+        start_dt = datetime.combine(start_dt.date(), datetime.min.time(), tzinfo=timezone.utc)
-        end_dt = end_dt.replace(hour=23, minute=59, second=59, microsecond=999999)
+        end_dt = datetime.combine(end_dt.date(), datetime.max.time(), tzinfo=timezone.utc)
-
-        from src.utils.database_helpers import date_trunc_portable
-
-        bind = db.get_bind()
-        dialect = bind.dialect.name if bind is not None else "sqlite"
-        day_bucket = date_trunc_portable(dialect, "day", Usage.created_at).label("day")
-
-        columns = [
-            day_bucket,
-            func.count(Usage.id).label("requests"),
-            func.sum(Usage.total_tokens).label("total_tokens"),
-            func.sum(Usage.total_cost_usd).label("total_cost_usd"),
-        ]
-
-        if include_actual_cost:
-            columns.append(func.sum(Usage.actual_total_cost_usd).label("actual_total_cost_usd"))
-
-        query = db.query(*columns).filter(Usage.created_at >= start_dt, Usage.created_at <= end_dt)
-
-        if user_id:
-            query = query.filter(Usage.user_id == user_id)
-
-        query = query.group_by(day_bucket).order_by(day_bucket)
-        rows = query.all()
-
-        def normalize_period(value: Any) -> str:
-            if value is None:
-                return ""
-            if isinstance(value, str):
-                return value[:10]
-            if isinstance(value, datetime):
-                return value.date().isoformat()
-            return str(value)
 
+        today = now.date()
+        today_start_dt = datetime.combine(today, datetime.min.time(), tzinfo=timezone.utc)
         aggregated: Dict[str, Dict[str, Any]] = {}
-        for row in rows:
-            key = normalize_period(row.day)
-            aggregated[key] = {
-                "requests": int(row.requests or 0),
-                "total_tokens": int(row.total_tokens or 0),
-                "total_cost_usd": float(row.total_cost_usd or 0.0),
-            }
-            if include_actual_cost:
-                aggregated[key]["actual_total_cost_usd"] = float(row.actual_total_cost_usd or 0.0)
 
+        # 1. 从预计算表读取历史数据（不包括今天）
+        if user_id:
+            from src.models.database import StatsUserDaily
+
+            hist_query = db.query(StatsUserDaily).filter(
+                StatsUserDaily.user_id == user_id,
+                StatsUserDaily.date >= start_dt,
+                StatsUserDaily.date < today_start_dt,
+            )
+            for row in hist_query.all():
+                key = (
+                    row.date.date().isoformat()
+                    if isinstance(row.date, datetime)
+                    else str(row.date)[:10]
+                )
+                aggregated[key] = {
+                    "requests": row.total_requests or 0,
+                    "total_tokens": (
+                        (row.input_tokens or 0)
+                        + (row.output_tokens or 0)
+                        + (row.cache_creation_tokens or 0)
+                        + (row.cache_read_tokens or 0)
+                    ),
+                    "total_cost_usd": float(row.total_cost or 0.0),
+                }
+                # StatsUserDaily 没有 actual_total_cost 字段，用户视图不需要倍率成本
+        else:
+            from src.models.database import StatsDaily
+
+            hist_query = db.query(StatsDaily).filter(
+                StatsDaily.date >= start_dt,
+                StatsDaily.date < today_start_dt,
+            )
+            for row in hist_query.all():
+                key = (
+                    row.date.date().isoformat()
+                    if isinstance(row.date, datetime)
+                    else str(row.date)[:10]
+                )
+                aggregated[key] = {
+                    "requests": row.total_requests or 0,
+                    "total_tokens": (
+                        (row.input_tokens or 0)
+                        + (row.output_tokens or 0)
+                        + (row.cache_creation_tokens or 0)
+                        + (row.cache_read_tokens or 0)
+                    ),
+                    "total_cost_usd": float(row.total_cost or 0.0),
+                }
+                if include_actual_cost:
+                    aggregated[key]["actual_total_cost_usd"] = float(
+                        row.actual_total_cost or 0.0  # type: ignore[attr-defined]
+                    )
+
+        # 2. 实时查询今天的数据（如果在查询范围内）
+        if today >= start_dt.date() and today <= end_dt.date():
+            today_start = datetime.combine(today, datetime.min.time(), tzinfo=timezone.utc)
+            today_end = datetime.combine(today, datetime.max.time(), tzinfo=timezone.utc)
+
+            if include_actual_cost:
+                today_query = db.query(
+                    func.count(Usage.id).label("requests"),
+                    func.sum(Usage.total_tokens).label("total_tokens"),
+                    func.sum(Usage.total_cost_usd).label("total_cost_usd"),
+                    func.sum(Usage.actual_total_cost_usd).label("actual_total_cost_usd"),
+                ).filter(
+                    Usage.created_at >= today_start,
+                    Usage.created_at <= today_end,
+                )
+            else:
+                today_query = db.query(
+                    func.count(Usage.id).label("requests"),
+                    func.sum(Usage.total_tokens).label("total_tokens"),
+                    func.sum(Usage.total_cost_usd).label("total_cost_usd"),
+                ).filter(
+                    Usage.created_at >= today_start,
+                    Usage.created_at <= today_end,
+                )
+
+            if user_id:
+                today_query = today_query.filter(Usage.user_id == user_id)
+
+            today_row = today_query.first()
+            if today_row and today_row.requests:
+                aggregated[today.isoformat()] = {
+                    "requests": int(today_row.requests or 0),
+                    "total_tokens": int(today_row.total_tokens or 0),
+                    "total_cost_usd": float(today_row.total_cost_usd or 0.0),
+                }
+                if include_actual_cost:
+                    aggregated[today.isoformat()]["actual_total_cost_usd"] = float(
+                        today_row.actual_total_cost_usd or 0.0
+                    )
+
+        # 3. 构建返回结果
         days: List[Dict[str, Any]] = []
         cursor = start_dt.date()
         end_date_only = end_dt.date()