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refactor: 移除 Python 后端源码，全面迁移至 Rust gateway 架构
- 删除全部 Python 源码 (src/) 及 Alembic 迁移脚本，归档至 _deprecated_py_src/ - 重构 Rust gateway ai_pipeline: 拆分 planner/finalize 模块，新增 contracts/adaptation 层 - 重组 handlers 模块为 admin/public/proxy/internal/shared 子模块结构 - 新增 executor 模块，引入 Rust 原生数据库迁移 (aether-data/migrations) - 简化 CI/Docker 构建流程，移除 base image 二级构建，统一为单一 app image - 移除 Python 相关基础设施文件 (entrypoint.sh, gunicorn_conf.py, Dockerfile.base)
This commit is contained in:
fawney19
578
_deprecated_py_src/services/usage/query.py
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578
_deprecated_py_src/services/usage/query.py
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@@ -0,0 +1,578 @@
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from __future__ import annotations
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from dataclasses import dataclass
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from datetime import datetime, timedelta, timezone
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from typing import TYPE_CHECKING, Any
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from sqlalchemy import case, func
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from sqlalchemy.orm import Session
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if TYPE_CHECKING:
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from sqlalchemy.sql.elements import ColumnElement
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from src.core.logger import logger
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from src.models.database import ApiKey, Usage, User
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def input_context_expr() -> ColumnElement[int]:
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"""计算缓存命中率口径下的总输入上下文 token 数。
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为了与 usage 表中“输入 tokens + 缓存读取 tokens”的展示口径保持一致，
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聚合统计统一使用 `input_tokens + cache_read_input_tokens` 作为分母。
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"""
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return Usage.input_tokens + Usage.cache_read_input_tokens
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@dataclass(slots=True)
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class RequestBalanceCheckResult:
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allowed: bool
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message: str
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remaining: float | None
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class UsageQueryMixin:
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"""查询/统计相关方法"""
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# 热力图缓存键前缀（依赖 TTL 自动过期，用户角色变更时主动清除）
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HEATMAP_CACHE_KEY_PREFIX = "activity_heatmap"
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@classmethod
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def _get_heatmap_cache_key(cls, user_id: str | None, include_actual_cost: bool) -> str:
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"""生成热力图缓存键"""
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cost_suffix = "with_cost" if include_actual_cost else "no_cost"
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if user_id:
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return f"{cls.HEATMAP_CACHE_KEY_PREFIX}:user:{user_id}:{cost_suffix}"
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else:
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return f"{cls.HEATMAP_CACHE_KEY_PREFIX}:admin:all:{cost_suffix}"
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@classmethod
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async def clear_user_heatmap_cache(cls, user_id: str) -> None:
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"""
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清除用户的热力图缓存（用户角色变更时调用）
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Args:
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user_id: 用户ID
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"""
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from src.clients.redis_client import get_redis_client
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redis_client = await get_redis_client(require_redis=False)
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if not redis_client:
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return
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# 清除该用户的所有热力图缓存（with_cost 和 no_cost）
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keys_to_delete = [
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cls._get_heatmap_cache_key(user_id, include_actual_cost=True),
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cls._get_heatmap_cache_key(user_id, include_actual_cost=False),
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]
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for key in keys_to_delete:
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try:
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await redis_client.delete(key)
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logger.debug("已清除热力图缓存: {}", key)
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except Exception as e:
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logger.warning("清除热力图缓存失败: {}, error={}", key, e)
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@classmethod
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async def get_cached_heatmap(
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cls,
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db: Session,
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user_id: str | None = None,
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include_actual_cost: bool = False,
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) -> dict[str, Any]:
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"""
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获取带缓存的热力图数据
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缓存策略：
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- TTL: 10分钟（CacheTTL.ACTIVITY_HEATMAP = 600）
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- 仅依赖 TTL 自动过期，新使用记录最多延迟 10 分钟出现
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- 用户角色变更时通过 clear_user_heatmap_cache() 主动清除
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Args:
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db: 数据库会话
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user_id: 用户ID，None 表示获取全局热力图（管理员）
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include_actual_cost: 是否包含实际成本
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Returns:
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热力图数据字典
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"""
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import json
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from src.clients.redis_client import get_redis_client
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from src.config.constants import CacheTTL
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cache_key = cls._get_heatmap_cache_key(user_id, include_actual_cost)
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cache_ttl = CacheTTL.ACTIVITY_HEATMAP
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redis_client = await get_redis_client(require_redis=False)
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# 尝试从缓存获取
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if redis_client:
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try:
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cached = await redis_client.get(cache_key)
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if cached:
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try:
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return json.loads(cached) # type: ignore[no-any-return]
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except json.JSONDecodeError as e:
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logger.warning(
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"热力图缓存解析失败，删除损坏缓存: {}, error={}", cache_key, e
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)
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try:
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await redis_client.delete(cache_key)
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except Exception:
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pass
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except Exception as e:
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logger.error("读取热力图缓存出错: {}, error={}", cache_key, e)
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# 从数据库查询
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result = cls.get_daily_activity(
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db=db,
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user_id=user_id,
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window_days=365,
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include_actual_cost=include_actual_cost,
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)
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# 保存到缓存（失败不影响返回结果）
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if redis_client:
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try:
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await redis_client.setex(
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cache_key,
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cache_ttl,
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json.dumps(result, ensure_ascii=False, default=str),
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)
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except Exception as e:
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logger.warning("保存热力图缓存失败: {}, error={}", cache_key, e)
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return result
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@staticmethod
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def check_request_balance_details(
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db: Session,
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user: User,
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estimated_tokens: int = 0,
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estimated_cost: float = 0,
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api_key: ApiKey | None = None,
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) -> RequestBalanceCheckResult:
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"""Return a structured balance-check result."""
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from src.services.wallet import WalletService
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wallet_access = WalletService.check_request_allowed(
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db,
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user=None if (api_key and api_key.is_standalone) else user,
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api_key=api_key,
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)
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snapshot = wallet_access.balance_snapshot
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if snapshot is None:
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snapshot = wallet_access.remaining
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remaining = float(snapshot) if snapshot is not None else None
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if wallet_access.allowed:
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return RequestBalanceCheckResult(True, "OK", remaining)
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if wallet_access.message in {"钱包欠费，请先充值", "账户欠费，请先充值"}:
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if api_key and api_key.is_standalone:
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return RequestBalanceCheckResult(False, "Key欠费，请先调账或充值", remaining)
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return RequestBalanceCheckResult(False, "账户欠费，请先充值", remaining)
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if wallet_access.message == "钱包不可用":
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if api_key and api_key.is_standalone:
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return RequestBalanceCheckResult(False, "Key钱包不可用", remaining)
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return RequestBalanceCheckResult(False, "钱包不可用", remaining)
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if api_key and api_key.is_standalone:
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if remaining is None:
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return RequestBalanceCheckResult(False, "Key余额不足", remaining)
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return RequestBalanceCheckResult(
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False, f"Key余额不足（剩余: ${remaining:.2f}）", remaining
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)
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# Admin users are already allowed in WalletService.check_request_allowed.
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if remaining is None:
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return RequestBalanceCheckResult(False, wallet_access.message or "余额不足", remaining)
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return RequestBalanceCheckResult(False, f"余额不足（剩余: ${remaining:.2f}）", remaining)
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@staticmethod
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def check_request_balance(
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db: Session,
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user: User,
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estimated_tokens: int = 0,
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estimated_cost: float = 0,
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api_key: ApiKey | None = None,
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) -> tuple[bool, str]:
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"""Check whether the request passes balance rules."""
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result = UsageQueryMixin.check_request_balance_details(
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db,
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user,
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estimated_tokens=estimated_tokens,
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estimated_cost=estimated_cost,
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api_key=api_key,
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)
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return result.allowed, result.message
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@staticmethod
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def get_usage_summary(
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db: Session,
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user_id: str | None = None,
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api_key_id: str | None = None,
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start_date: datetime | None = None,
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end_date: datetime | None = None,
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group_by: str | None = "day", # day, week, month, None(不按时间分桶)
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) -> list[dict[str, Any]]:
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"""获取使用汇总"""
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query = db.query(Usage)
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# 过滤掉 pending/streaming 状态的请求（尚未完成的请求不应计入统计）
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query = query.filter(Usage.status.notin_(["pending", "streaming"]))
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if user_id:
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query = query.filter(Usage.user_id == user_id)
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if api_key_id:
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query = query.filter(Usage.api_key_id == api_key_id)
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if start_date:
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query = query.filter(Usage.created_at >= start_date)
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if end_date:
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query = query.filter(Usage.created_at < end_date)
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select_columns = [Usage.provider_name, Usage.model]
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group_columns = [Usage.provider_name, Usage.model]
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if group_by is not None:
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from src.utils.database_helpers import date_trunc_portable
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bind = db.bind
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dialect = bind.dialect.name if bind is not None else "sqlite"
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if group_by == "day":
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date_func = date_trunc_portable(dialect, "day", Usage.created_at)
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elif group_by == "week":
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date_func = date_trunc_portable(dialect, "week", Usage.created_at)
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elif group_by == "month":
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date_func = date_trunc_portable(dialect, "month", Usage.created_at)
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else:
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date_func = date_trunc_portable(dialect, "day", Usage.created_at)
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select_columns.insert(0, date_func.label("period"))
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group_columns.insert(0, date_func)
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summary = db.query(
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*select_columns,
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func.count(Usage.id).label("requests"),
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func.sum(Usage.input_tokens).label("input_tokens"),
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func.sum(Usage.output_tokens).label("output_tokens"),
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func.sum(Usage.total_tokens).label("total_tokens"),
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func.sum(Usage.cache_read_input_tokens).label("cache_read_tokens"),
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func.sum(Usage.cache_creation_input_tokens).label("cache_creation_tokens"),
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func.sum(input_context_expr()).label("total_input_context"),
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func.sum(Usage.total_cost_usd).label("total_cost_usd"),
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func.sum(Usage.actual_total_cost_usd).label("actual_total_cost_usd"),
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func.sum(case((Usage.status_code == 200, 1), else_=0)).label("success_count"),
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func.avg(Usage.response_time_ms).label("avg_response_time"),
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func.sum(
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case(
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(
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(Usage.status_code == 200) & Usage.response_time_ms.isnot(None),
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Usage.response_time_ms,
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),
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else_=0,
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)
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).label("success_response_time_sum"),
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func.sum(
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case(
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((Usage.status_code == 200) & Usage.response_time_ms.isnot(None), 1),
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else_=0,
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)
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).label("success_response_time_count"),
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)
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# 过滤掉 pending/streaming 状态的请求（与上方明细查询一致）
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summary = summary.filter(Usage.status.notin_(["pending", "streaming"]))
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if user_id:
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summary = summary.filter(Usage.user_id == user_id)
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if api_key_id:
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summary = summary.filter(Usage.api_key_id == api_key_id)
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if start_date:
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summary = summary.filter(Usage.created_at >= start_date)
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if end_date:
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summary = summary.filter(Usage.created_at < end_date)
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summary = summary.group_by(*group_columns).all()
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return [
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{
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"period": getattr(row, "period", None),
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"provider": row.provider_name,
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"model": row.model,
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"requests": row.requests,
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"input_tokens": row.input_tokens,
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"output_tokens": row.output_tokens,
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"total_tokens": row.total_tokens,
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"cache_read_tokens": int(row.cache_read_tokens or 0),
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"cache_creation_tokens": int(row.cache_creation_tokens or 0),
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"total_input_context": int(row.total_input_context or 0),
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"total_cost_usd": float(row.total_cost_usd or 0.0),
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"actual_total_cost_usd": float(row.actual_total_cost_usd or 0.0),
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"success_count": int(row.success_count or 0),
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"avg_response_time_ms": (
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float(row.avg_response_time) if row.avg_response_time else 0
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),
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"success_response_time_sum_ms": float(row.success_response_time_sum or 0.0),
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"success_response_time_count": int(row.success_response_time_count or 0),
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}
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for row in summary
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]
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@staticmethod
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def get_daily_activity(
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db: Session,
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user_id: str | None = None,
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start_date: datetime | None = None,
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end_date: datetime | None = None,
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window_days: int = 365,
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include_actual_cost: bool = False,
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) -> dict[str, Any]:
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"""按天统计请求活跃度，用于渲染热力图。
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优化策略：
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- 历史数据从预计算的 StatsDaily/StatsUserDaily 表读取
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- 只有"今天"的数据才实时查询 Usage 表
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"""
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def ensure_timezone(value: datetime) -> datetime:
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if value.tzinfo is None:
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return value.replace(tzinfo=timezone.utc)
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return value.astimezone(timezone.utc)
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# 如果调用方未指定时间范围，则默认统计最近 window_days 天
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now = datetime.now(timezone.utc)
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end_dt = ensure_timezone(end_date) if end_date else now
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start_dt = (
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ensure_timezone(start_date) if start_date else end_dt - timedelta(days=window_days - 1)
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)
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# 对齐到自然日的开始/结束
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start_dt = datetime.combine(start_dt.date(), datetime.min.time(), tzinfo=timezone.utc)
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end_dt = datetime.combine(end_dt.date(), datetime.max.time(), tzinfo=timezone.utc)
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today = now.date()
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today_start_dt = datetime.combine(today, datetime.min.time(), tzinfo=timezone.utc)
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aggregated: dict[str, dict[str, Any]] = {}
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# 1. 从预计算表读取历史数据（不包括今天）
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if user_id:
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from src.models.database import StatsUserDaily
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hist_query = db.query(StatsUserDaily).filter(
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StatsUserDaily.user_id == user_id,
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StatsUserDaily.date >= start_dt,
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StatsUserDaily.date < today_start_dt,
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)
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for row in hist_query.all():
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key = (
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row.date.date().isoformat()
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if isinstance(row.date, datetime)
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else str(row.date)[:10]
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)
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aggregated[key] = {
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"requests": row.total_requests or 0,
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"total_tokens": (
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(row.input_tokens or 0)
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+ (row.output_tokens or 0)
|
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+ (row.cache_creation_tokens or 0)
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+ (row.cache_read_tokens or 0)
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),
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"total_cost_usd": float(row.total_cost or 0.0),
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}
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# StatsUserDaily 没有 actual_total_cost 字段，用户视图不需要倍率成本
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else:
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from src.models.database import StatsDaily
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hist_query = db.query(StatsDaily).filter(
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StatsDaily.date >= start_dt,
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StatsDaily.date < today_start_dt,
|
||||
)
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for row in hist_query.all():
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key = (
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row.date.date().isoformat()
|
||||
if isinstance(row.date, datetime)
|
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else str(row.date)[:10]
|
||||
)
|
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aggregated[key] = {
|
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"requests": row.total_requests or 0,
|
||||
"total_tokens": (
|
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(row.input_tokens or 0)
|
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+ (row.output_tokens or 0)
|
||||
+ (row.cache_creation_tokens or 0)
|
||||
+ (row.cache_read_tokens or 0)
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||||
),
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"total_cost_usd": float(row.total_cost or 0.0),
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||||
}
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if include_actual_cost:
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aggregated[key]["actual_total_cost_usd"] = float(
|
||||
row.actual_total_cost or 0.0 # type: ignore[attr-defined]
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||||
)
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||||
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||||
# 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()
|
||||
max_requests = 0
|
||||
|
||||
while cursor <= end_date_only:
|
||||
iso_date = cursor.isoformat()
|
||||
stats = aggregated.get(iso_date, {})
|
||||
requests = stats.get("requests", 0)
|
||||
total_tokens = stats.get("total_tokens", 0)
|
||||
total_cost = stats.get("total_cost_usd", 0.0)
|
||||
|
||||
entry: dict[str, Any] = {
|
||||
"date": iso_date,
|
||||
"requests": requests,
|
||||
"total_tokens": total_tokens,
|
||||
"total_cost": total_cost,
|
||||
}
|
||||
|
||||
if include_actual_cost:
|
||||
entry["actual_total_cost"] = stats.get("actual_total_cost_usd", 0.0)
|
||||
|
||||
days.append(entry)
|
||||
max_requests = max(max_requests, requests)
|
||||
cursor += timedelta(days=1)
|
||||
|
||||
return {
|
||||
"start_date": start_dt.date().isoformat(),
|
||||
"end_date": end_dt.date().isoformat(),
|
||||
"total_days": len(days),
|
||||
"max_requests": max_requests,
|
||||
"days": days,
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def get_top_users(
|
||||
db: Session,
|
||||
limit: int = 10,
|
||||
start_date: datetime | None = None,
|
||||
end_date: datetime | None = None,
|
||||
order_by: str = "cost", # cost, tokens, requests
|
||||
) -> list[dict[str, Any]]:
|
||||
"""获取使用量最高的用户"""
|
||||
|
||||
query = (
|
||||
db.query(
|
||||
User.id,
|
||||
User.email,
|
||||
User.username,
|
||||
func.count(Usage.id).label("requests"),
|
||||
func.sum(Usage.total_tokens).label("tokens"),
|
||||
func.sum(Usage.total_cost_usd).label("cost_usd"),
|
||||
)
|
||||
.join(Usage, User.id == Usage.user_id)
|
||||
.filter(Usage.user_id.isnot(None))
|
||||
)
|
||||
|
||||
if start_date:
|
||||
query = query.filter(Usage.created_at >= start_date)
|
||||
if end_date:
|
||||
query = query.filter(Usage.created_at <= end_date)
|
||||
|
||||
query = query.group_by(User.id, User.email, User.username)
|
||||
|
||||
# 排序
|
||||
if order_by == "cost":
|
||||
query = query.order_by(func.sum(Usage.total_cost_usd).desc())
|
||||
elif order_by == "tokens":
|
||||
query = query.order_by(func.sum(Usage.total_tokens).desc())
|
||||
else:
|
||||
query = query.order_by(func.count(Usage.id).desc())
|
||||
|
||||
results = query.limit(limit).all()
|
||||
|
||||
return [
|
||||
{
|
||||
"user_id": row.id,
|
||||
"email": row.email,
|
||||
"username": row.username,
|
||||
"requests": row.requests,
|
||||
"tokens": row.tokens,
|
||||
"cost_usd": float(row.cost_usd),
|
||||
}
|
||||
for row in results
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def cleanup_old_usage_records(
|
||||
db: Session, days_to_keep: int = 90, batch_size: int = 1000
|
||||
) -> int:
|
||||
"""清理旧的使用记录（分批删除避免长事务锁定）
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
days_to_keep: 保留天数，默认 90 天
|
||||
batch_size: 每批删除数量，默认 1000 条
|
||||
|
||||
Returns:
|
||||
删除的总记录数
|
||||
"""
|
||||
cutoff_date = datetime.now(timezone.utc) - timedelta(days=days_to_keep)
|
||||
total_deleted = 0
|
||||
|
||||
while True:
|
||||
# 查询待删除的 ID（使用新索引 idx_usage_user_created）
|
||||
batch_ids = (
|
||||
db.query(Usage.id).filter(Usage.created_at < cutoff_date).limit(batch_size).all()
|
||||
)
|
||||
|
||||
if not batch_ids:
|
||||
break
|
||||
|
||||
# 批量删除
|
||||
deleted_count = (
|
||||
db.query(Usage)
|
||||
.filter(Usage.id.in_([row.id for row in batch_ids]))
|
||||
.delete(synchronize_session=False)
|
||||
)
|
||||
db.commit()
|
||||
total_deleted += deleted_count
|
||||
|
||||
logger.debug("清理使用记录: 本批删除 {} 条", deleted_count)
|
||||
|
||||
logger.info("清理使用记录: 共删除 {} 条超过 {} 天的记录", total_deleted, days_to_keep)
|
||||
|
||||
return total_deleted
|
||||
Reference in New Issue
Block a user