from collections import defaultdict from datetime import datetime, timedelta from typing import Any, Literal from fastapi import APIRouter, HTTPException, Query from src.common.database.compatibility import db_get from src.common.database.core.models import LLMUsage from src.common.logger import get_logger from src.config.config import model_config logger = get_logger("LLM统计API") router = APIRouter() # 定义统计数据的键,以减少魔法字符串 TOTAL_REQ_CNT = "total_requests" TOTAL_COST = "total_cost" REQ_CNT_BY_TYPE = "requests_by_type" REQ_CNT_BY_USER = "requests_by_user" REQ_CNT_BY_MODEL = "requests_by_model" REQ_CNT_BY_MODULE = "requests_by_module" IN_TOK_BY_TYPE = "in_tokens_by_type" IN_TOK_BY_USER = "in_tokens_by_user" IN_TOK_BY_MODEL = "in_tokens_by_model" IN_TOK_BY_MODULE = "in_tokens_by_module" OUT_TOK_BY_TYPE = "out_tokens_by_type" OUT_TOK_BY_USER = "out_tokens_by_user" OUT_TOK_BY_MODEL = "out_tokens_by_model" OUT_TOK_BY_MODULE = "out_tokens_by_module" TOTAL_TOK_BY_TYPE = "tokens_by_type" TOTAL_TOK_BY_USER = "tokens_by_user" TOTAL_TOK_BY_MODEL = "tokens_by_model" TOTAL_TOK_BY_MODULE = "tokens_by_module" COST_BY_TYPE = "costs_by_type" COST_BY_USER = "costs_by_user" COST_BY_MODEL = "costs_by_model" COST_BY_MODULE = "costs_by_module" async def _collect_stats_in_period(start_time: datetime, end_time: datetime) -> dict[str, Any]: """在指定时间段内收集LLM使用统计信息""" records = await db_get( model_class=LLMUsage, filters={"timestamp": {"$gte": start_time, "$lt": end_time}}, ) if not records: return {} # 创建一个从 model_identifier 到 name 的映射 model_identifier_to_name_map = {model.model_identifier: model.name for model in model_config.models} stats: dict[str, Any] = { TOTAL_REQ_CNT: 0, TOTAL_COST: 0.0, REQ_CNT_BY_TYPE: defaultdict(int), REQ_CNT_BY_USER: defaultdict(int), REQ_CNT_BY_MODEL: defaultdict(int), REQ_CNT_BY_MODULE: defaultdict(int), IN_TOK_BY_TYPE: defaultdict(int), IN_TOK_BY_USER: defaultdict(int), IN_TOK_BY_MODEL: defaultdict(int), IN_TOK_BY_MODULE: defaultdict(int), OUT_TOK_BY_TYPE: defaultdict(int), OUT_TOK_BY_USER: defaultdict(int), OUT_TOK_BY_MODEL: defaultdict(int), OUT_TOK_BY_MODULE: defaultdict(int), TOTAL_TOK_BY_TYPE: defaultdict(int), TOTAL_TOK_BY_USER: defaultdict(int), TOTAL_TOK_BY_MODEL: defaultdict(int), TOTAL_TOK_BY_MODULE: defaultdict(int), COST_BY_TYPE: defaultdict(float), COST_BY_USER: defaultdict(float), COST_BY_MODEL: defaultdict(float), COST_BY_MODULE: defaultdict(float), } for record in records: if not isinstance(record, dict): continue stats[TOTAL_REQ_CNT] += 1 request_type = record.get("request_type") or "unknown" user_id = record.get("user_id") or "unknown" # 从数据库获取的是真实模型名 (model_identifier) real_model_name = record.get("model_name") or "unknown" module_name = request_type.split(".")[0] if "." in request_type else request_type # 尝试通过真实模型名找到配置文件中的模型名 config_model_name = model_identifier_to_name_map.get(real_model_name, real_model_name) prompt_tokens = record.get("prompt_tokens") or 0 completion_tokens = record.get("completion_tokens") or 0 total_tokens = prompt_tokens + completion_tokens cost = 0.0 try: # 使用配置文件中的模型名来获取模型信息 model_info = model_config.get_model_info(config_model_name) if model_info: input_cost = (prompt_tokens / 1000000) * model_info.price_in output_cost = (completion_tokens / 1000000) * model_info.price_out cost = round(input_cost + output_cost, 6) except KeyError as e: logger.info(str(e)) logger.warning(f"模型 '{config_model_name}' (真实名称: '{real_model_name}') 在配置中未找到，成本计算将使用默认值 0.0") stats[TOTAL_COST] += cost # 按类型统计 stats[REQ_CNT_BY_TYPE][request_type] += 1 stats[IN_TOK_BY_TYPE][request_type] += prompt_tokens stats[OUT_TOK_BY_TYPE][request_type] += completion_tokens stats[TOTAL_TOK_BY_TYPE][request_type] += total_tokens stats[COST_BY_TYPE][request_type] += cost # 按用户统计 stats[REQ_CNT_BY_USER][user_id] += 1 stats[IN_TOK_BY_USER][user_id] += prompt_tokens stats[OUT_TOK_BY_USER][user_id] += completion_tokens stats[TOTAL_TOK_BY_USER][user_id] += total_tokens stats[COST_BY_USER][user_id] += cost # 按模型统计 (使用配置文件中的名称) stats[REQ_CNT_BY_MODEL][config_model_name] += 1 stats[IN_TOK_BY_MODEL][config_model_name] += prompt_tokens stats[OUT_TOK_BY_MODEL][config_model_name] += completion_tokens stats[TOTAL_TOK_BY_MODEL][config_model_name] += total_tokens stats[COST_BY_MODEL][config_model_name] += cost # 按模块统计 stats[REQ_CNT_BY_MODULE][module_name] += 1 stats[IN_TOK_BY_MODULE][module_name] += prompt_tokens stats[OUT_TOK_BY_MODULE][module_name] += completion_tokens stats[TOTAL_TOK_BY_MODULE][module_name] += total_tokens stats[COST_BY_MODULE][module_name] += cost return stats @router.get("/llm/stats") async def get_llm_stats( period_type: Literal[ "daily", "custom", "last_hour", "last_24_hours", "last_7_days", "last_30_days" ] = Query("daily", description="查询的时间段类型"), 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"), start_time_str: str = Query(None, description="当 period_type 为 'custom' 时,指定查询的开始时间 (ISO 8601)"), end_time_str: str = Query(None, description="当 period_type 为 'custom' 时,指定查询的结束时间 (ISO 8601)"), group_by: Literal["model", "module", "user", "type"] = Query("model", description="按指定维度对结果进行分组"), ): """ 获取大模型使用情况的统计信息。 """ try: now = datetime.now() end_time = now start_time = None if period_type == "daily": start_time = now - timedelta(days=days) elif period_type == "last_hour": start_time = now - timedelta(hours=1) elif period_type == "last_24_hours": start_time = now - timedelta(days=1) elif period_type == "last_7_days": start_time = now - timedelta(days=7) elif period_type == "last_30_days": start_time = now - timedelta(days=30) elif period_type == "custom": if not start_time_str or not end_time_str: raise HTTPException(status_code=400, detail="自定义时间段必须提供开始和结束时间") try: start_time = datetime.fromisoformat(start_time_str) end_time = datetime.fromisoformat(end_time_str) except ValueError: raise HTTPException(status_code=400, detail="无效的日期时间格式,请使用ISO 8601格式") if start_time is None: raise HTTPException(status_code=400, detail="无法确定查询的起始时间") period_stats = await _collect_stats_in_period(start_time, end_time) if not period_stats: return {"period": {"start": start_time.isoformat(), "end": end_time.isoformat()}, "data": {}} key_mapping = { "model": (REQ_CNT_BY_MODEL, COST_BY_MODEL, IN_TOK_BY_MODEL, OUT_TOK_BY_MODEL, TOTAL_TOK_BY_MODEL), "module": ( REQ_CNT_BY_MODULE, COST_BY_MODULE, IN_TOK_BY_MODULE, OUT_TOK_BY_MODULE, TOTAL_TOK_BY_MODULE, ), "user": (REQ_CNT_BY_USER, COST_BY_USER, IN_TOK_BY_USER, OUT_TOK_BY_USER, TOTAL_TOK_BY_USER), "type": (REQ_CNT_BY_TYPE, COST_BY_TYPE, IN_TOK_BY_TYPE, OUT_TOK_BY_TYPE, TOTAL_TOK_BY_TYPE), } req_key, cost_key, in_tok_key, out_tok_key, total_tok_key = key_mapping[group_by] details_by_group = {} for group_name, count in period_stats.get(req_key, {}).items(): details_by_group[group_name] = { "requests": count, "cost": period_stats.get(cost_key, {}).get(group_name, 0), "input_tokens": period_stats.get(in_tok_key, {}).get(group_name, 0), "output_tokens": period_stats.get(out_tok_key, {}).get(group_name, 0), "total_tokens": period_stats.get(total_tok_key, {}).get(group_name, 0), } return { "period": {"start": start_time.isoformat(), "end": end_time.isoformat()}, "total_requests": period_stats.get(TOTAL_REQ_CNT, 0), "total_cost": period_stats.get(TOTAL_COST, 0), "details_by_group": details_by_group, } except HTTPException as e: raise e except Exception as e: logger.error(f"获取LLM统计信息失败: {e}") raise HTTPException(status_code=500, detail=str(e))