feat(api): 增加 LLM 统计路由
将 LLM 使用情况统计的 API 路由注册到主应用程序中,以便通过 `/api/statistic` 路径访问相关统计数据。
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115
src/api/statistic_router.py
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115
src/api/statistic_router.py
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from datetime import datetime, timedelta
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from typing import Any, Literal
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from fastapi import APIRouter, HTTPException, Query
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from src.chat.utils.statistic import (
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COST_BY_MODEL,
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COST_BY_MODULE,
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COST_BY_TYPE,
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COST_BY_USER,
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IN_TOK_BY_MODEL,
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IN_TOK_BY_MODULE,
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IN_TOK_BY_TYPE,
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IN_TOK_BY_USER,
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OUT_TOK_BY_MODEL,
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OUT_TOK_BY_MODULE,
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OUT_TOK_BY_TYPE,
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OUT_TOK_BY_USER,
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REQ_CNT_BY_MODEL,
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REQ_CNT_BY_MODULE,
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REQ_CNT_BY_TYPE,
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REQ_CNT_BY_USER,
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TOTAL_COST,
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TOTAL_REQ_CNT,
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TOTAL_TOK_BY_MODEL,
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TOTAL_TOK_BY_MODULE,
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TOTAL_TOK_BY_TYPE,
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TOTAL_TOK_BY_USER,
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StatisticOutputTask,
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)
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from src.common.logger import get_logger
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logger = get_logger("LLM统计API")
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router = APIRouter()
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@router.get("/llm/stats")
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async def get_llm_stats(
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period_type: Literal["fixed", "daily", "custom"] = Query(
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"daily", description="查询的时间段类型: 'fixed' (固定), 'daily' (按天), 'custom' (自定义)"
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),
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days: int = Query(1, ge=1, description="当 period_type 为 'daily' 时,指定查询过去多少天的数据"),
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start_time_str: str = Query(None, description="当 period_type 为 'custom' 时,指定查询的开始时间 (ISO 8601)"),
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end_time_str: str = Query(None, description="当 period_type 为 'custom' 时,指定查询的结束时间 (ISO 8601)"),
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group_by: Literal["model", "module", "user", "type"] = Query("model", description="按指定维度对结果进行分组"),
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):
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"""
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获取大模型使用情况的统计信息。
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"""
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try:
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now = datetime.now()
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start_time, end_time = None, now
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if period_type == "daily":
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start_time = now - timedelta(days=days)
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elif period_type == "custom":
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if not start_time_str or not end_time_str:
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raise HTTPException(status_code=400, detail="自定义时间段必须提供开始和结束时间")
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try:
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start_time = datetime.fromisoformat(start_time_str)
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end_time = datetime.fromisoformat(end_time_str)
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except ValueError:
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raise HTTPException(status_code=400, detail="无效的日期时间格式,请使用ISO 8601格式")
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elif period_type == "fixed":
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# 预设的固定时间段,这里以最近一小时为例
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start_time = now - timedelta(hours=1)
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if start_time is None:
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raise HTTPException(status_code=400, detail="无法确定查询的起始时间")
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# 调用统计函数
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stats_data = await StatisticOutputTask._collect_model_request_for_period([("custom", start_time)])
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period_stats = stats_data.get("custom", {})
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if not period_stats:
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return {"period": {"start": start_time.isoformat(), "end": end_time.isoformat()}, "data": {}}
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# 根据 group_by 参数选择对应的数据
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key_mapping = {
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"model": (REQ_CNT_BY_MODEL, COST_BY_MODEL, IN_TOK_BY_MODEL, OUT_TOK_BY_MODEL, TOTAL_TOK_BY_MODEL),
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"module": (
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REQ_CNT_BY_MODULE,
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COST_BY_MODULE,
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IN_TOK_BY_MODULE,
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OUT_TOK_BY_MODULE,
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TOTAL_TOK_BY_MODULE,
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),
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"user": (REQ_CNT_BY_USER, COST_BY_USER, IN_TOK_BY_USER, OUT_TOK_BY_USER, TOTAL_TOK_BY_USER),
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"type": (REQ_CNT_BY_TYPE, COST_BY_TYPE, IN_TOK_BY_TYPE, OUT_TOK_BY_TYPE, TOTAL_TOK_BY_TYPE),
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}
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req_key, cost_key, in_tok_key, out_tok_key, total_tok_key = key_mapping[group_by]
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details_by_group = {}
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for group_name, count in period_stats.get(req_key, {}).items():
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details_by_group[group_name] = {
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"requests": count,
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"cost": period_stats.get(cost_key, {}).get(group_name, 0),
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"input_tokens": period_stats.get(in_tok_key, {}).get(group_name, 0),
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"output_tokens": period_stats.get(out_tok_key, {}).get(group_name, 0),
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"total_tokens": period_stats.get(total_tok_key, {}).get(group_name, 0),
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}
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return {
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"period": {"start": start_time.isoformat(), "end": end_time.isoformat()},
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"total_requests": period_stats.get(TOTAL_REQ_CNT, 0),
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"total_cost": period_stats.get(TOTAL_COST, 0),
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"details_by_group": details_by_group,
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}
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except HTTPException as e:
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raise e
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except Exception as e:
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logger.error(f"获取LLM统计信息失败: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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