mirror of https://github.com/Mai-with-u/MaiBot.git
feat: 添加统计数据API路由以支持统计信息的获取
墨梓柒
parent
ab1ef9536b
commit
6307d92acc
|
|
@ -5,6 +5,7 @@ from typing import Optional
|
|||
from src.common.logger import get_logger
|
||||
from .token_manager import get_token_manager
|
||||
from .config_routes import router as config_router
|
||||
from .statistics_routes import router as statistics_router
|
||||
|
||||
logger = get_logger("webui.api")
|
||||
|
||||
|
|
@ -13,6 +14,8 @@ router = APIRouter(prefix="/api/webui", tags=["WebUI"])
|
|||
|
||||
# 注册配置管理路由
|
||||
router.include_router(config_router)
|
||||
# 注册统计数据路由
|
||||
router.include_router(statistics_router)
|
||||
|
||||
|
||||
class TokenVerifyRequest(BaseModel):
|
||||
|
|
|
|||
|
|
@ -0,0 +1,329 @@
|
|||
"""统计数据 API 路由"""
|
||||
from fastapi import APIRouter, HTTPException
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import Dict, Any, List
|
||||
from datetime import datetime, timedelta
|
||||
from collections import defaultdict
|
||||
|
||||
from src.common.logger import get_logger
|
||||
from src.common.database.database_model import LLMUsage, OnlineTime, Messages
|
||||
|
||||
logger = get_logger("webui.statistics")
|
||||
|
||||
router = APIRouter(prefix="/statistics", tags=["statistics"])
|
||||
|
||||
|
||||
class StatisticsSummary(BaseModel):
|
||||
"""统计数据摘要"""
|
||||
total_requests: int = Field(0, description="总请求数")
|
||||
total_cost: float = Field(0.0, description="总花费")
|
||||
total_tokens: int = Field(0, description="总token数")
|
||||
online_time: float = Field(0.0, description="在线时间（秒）")
|
||||
total_messages: int = Field(0, description="总消息数")
|
||||
total_replies: int = Field(0, description="总回复数")
|
||||
avg_response_time: float = Field(0.0, description="平均响应时间")
|
||||
cost_per_hour: float = Field(0.0, description="每小时花费")
|
||||
tokens_per_hour: float = Field(0.0, description="每小时token数")
|
||||
|
||||
|
||||
class ModelStatistics(BaseModel):
|
||||
"""模型统计"""
|
||||
model_name: str
|
||||
request_count: int
|
||||
total_cost: float
|
||||
total_tokens: int
|
||||
avg_response_time: float
|
||||
|
||||
|
||||
class TimeSeriesData(BaseModel):
|
||||
"""时间序列数据"""
|
||||
timestamp: str
|
||||
requests: int = 0
|
||||
cost: float = 0.0
|
||||
tokens: int = 0
|
||||
|
||||
|
||||
class DashboardData(BaseModel):
|
||||
"""仪表盘数据"""
|
||||
summary: StatisticsSummary
|
||||
model_stats: List[ModelStatistics]
|
||||
hourly_data: List[TimeSeriesData]
|
||||
daily_data: List[TimeSeriesData]
|
||||
recent_activity: List[Dict[str, Any]]
|
||||
|
||||
|
||||
@router.get("/dashboard", response_model=DashboardData)
|
||||
async def get_dashboard_data(hours: int = 24):
|
||||
"""
|
||||
获取仪表盘统计数据
|
||||
|
||||
Args:
|
||||
hours: 统计时间范围（小时），默认24小时
|
||||
|
||||
Returns:
|
||||
仪表盘数据
|
||||
"""
|
||||
try:
|
||||
now = datetime.now()
|
||||
start_time = now - timedelta(hours=hours)
|
||||
|
||||
# 获取摘要数据
|
||||
summary = await _get_summary_statistics(start_time, now)
|
||||
|
||||
# 获取模型统计
|
||||
model_stats = await _get_model_statistics(start_time)
|
||||
|
||||
# 获取小时级时间序列数据
|
||||
hourly_data = await _get_hourly_statistics(start_time, now)
|
||||
|
||||
# 获取日级时间序列数据（最近7天）
|
||||
daily_start = now - timedelta(days=7)
|
||||
daily_data = await _get_daily_statistics(daily_start, now)
|
||||
|
||||
# 获取最近活动
|
||||
recent_activity = await _get_recent_activity(limit=10)
|
||||
|
||||
return DashboardData(
|
||||
summary=summary,
|
||||
model_stats=model_stats,
|
||||
hourly_data=hourly_data,
|
||||
daily_data=daily_data,
|
||||
recent_activity=recent_activity
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"获取仪表盘数据失败: {e}")
|
||||
raise HTTPException(status_code=500, detail=f"获取统计数据失败: {str(e)}") from e
|
||||
|
||||
|
||||
async def _get_summary_statistics(start_time: datetime, end_time: datetime) -> StatisticsSummary:
|
||||
"""获取摘要统计数据"""
|
||||
summary = StatisticsSummary()
|
||||
|
||||
# 查询 LLM 使用记录
|
||||
llm_records = list(
|
||||
LLMUsage.select()
|
||||
.where(LLMUsage.timestamp >= start_time)
|
||||
.where(LLMUsage.timestamp <= end_time)
|
||||
)
|
||||
|
||||
total_time_cost = 0.0
|
||||
time_cost_count = 0
|
||||
|
||||
for record in llm_records:
|
||||
summary.total_requests += 1
|
||||
summary.total_cost += record.cost or 0.0
|
||||
summary.total_tokens += (record.prompt_tokens or 0) + (record.completion_tokens or 0)
|
||||
|
||||
if record.time_cost and record.time_cost > 0:
|
||||
total_time_cost += record.time_cost
|
||||
time_cost_count += 1
|
||||
|
||||
# 计算平均响应时间
|
||||
if time_cost_count > 0:
|
||||
summary.avg_response_time = total_time_cost / time_cost_count
|
||||
|
||||
# 查询在线时间
|
||||
online_records = list(
|
||||
OnlineTime.select()
|
||||
.where(
|
||||
(OnlineTime.start_timestamp >= start_time) |
|
||||
(OnlineTime.end_timestamp >= start_time)
|
||||
)
|
||||
)
|
||||
|
||||
for record in online_records:
|
||||
start = max(record.start_timestamp, start_time)
|
||||
end = min(record.end_timestamp, end_time)
|
||||
if end > start:
|
||||
summary.online_time += (end - start).total_seconds()
|
||||
|
||||
# 查询消息数量
|
||||
messages = list(
|
||||
Messages.select()
|
||||
.where(Messages.time >= start_time.timestamp())
|
||||
.where(Messages.time <= end_time.timestamp())
|
||||
)
|
||||
|
||||
summary.total_messages = len(messages)
|
||||
# 简单统计：如果 reply_to 不为空，则认为是回复
|
||||
summary.total_replies = len([m for m in messages if m.reply_to])
|
||||
|
||||
# 计算派生指标
|
||||
if summary.online_time > 0:
|
||||
online_hours = summary.online_time / 3600.0
|
||||
summary.cost_per_hour = summary.total_cost / online_hours
|
||||
summary.tokens_per_hour = summary.total_tokens / online_hours
|
||||
|
||||
return summary
|
||||
|
||||
|
||||
async def _get_model_statistics(start_time: datetime) -> List[ModelStatistics]:
|
||||
"""获取模型统计数据"""
|
||||
model_data = defaultdict(lambda: {
|
||||
'request_count': 0,
|
||||
'total_cost': 0.0,
|
||||
'total_tokens': 0,
|
||||
'time_costs': []
|
||||
})
|
||||
|
||||
records = list(
|
||||
LLMUsage.select()
|
||||
.where(LLMUsage.timestamp >= start_time)
|
||||
)
|
||||
|
||||
for record in records:
|
||||
model_name = record.model_assign_name or record.model_name or "unknown"
|
||||
model_data[model_name]['request_count'] += 1
|
||||
model_data[model_name]['total_cost'] += record.cost or 0.0
|
||||
model_data[model_name]['total_tokens'] += (record.prompt_tokens or 0) + (record.completion_tokens or 0)
|
||||
|
||||
if record.time_cost and record.time_cost > 0:
|
||||
model_data[model_name]['time_costs'].append(record.time_cost)
|
||||
|
||||
# 转换为列表并排序
|
||||
result = []
|
||||
for model_name, data in model_data.items():
|
||||
avg_time = sum(data['time_costs']) / len(data['time_costs']) if data['time_costs'] else 0.0
|
||||
result.append(ModelStatistics(
|
||||
model_name=model_name,
|
||||
request_count=data['request_count'],
|
||||
total_cost=data['total_cost'],
|
||||
total_tokens=data['total_tokens'],
|
||||
avg_response_time=avg_time
|
||||
))
|
||||
|
||||
# 按请求数排序
|
||||
result.sort(key=lambda x: x.request_count, reverse=True)
|
||||
return result[:10] # 返回前10个
|
||||
|
||||
|
||||
async def _get_hourly_statistics(start_time: datetime, end_time: datetime) -> List[TimeSeriesData]:
|
||||
"""获取小时级统计数据"""
|
||||
# 创建小时桶
|
||||
hourly_buckets = defaultdict(lambda: {'requests': 0, 'cost': 0.0, 'tokens': 0})
|
||||
|
||||
records = list(
|
||||
LLMUsage.select()
|
||||
.where(LLMUsage.timestamp >= start_time)
|
||||
.where(LLMUsage.timestamp <= end_time)
|
||||
)
|
||||
|
||||
for record in records:
|
||||
# 获取小时键（去掉分钟和秒）
|
||||
hour_key = record.timestamp.replace(minute=0, second=0, microsecond=0)
|
||||
hour_str = hour_key.isoformat()
|
||||
|
||||
hourly_buckets[hour_str]['requests'] += 1
|
||||
hourly_buckets[hour_str]['cost'] += record.cost or 0.0
|
||||
hourly_buckets[hour_str]['tokens'] += (record.prompt_tokens or 0) + (record.completion_tokens or 0)
|
||||
|
||||
# 填充所有小时（包括没有数据的）
|
||||
result = []
|
||||
current = start_time.replace(minute=0, second=0, microsecond=0)
|
||||
while current <= end_time:
|
||||
hour_str = current.isoformat()
|
||||
data = hourly_buckets.get(hour_str, {'requests': 0, 'cost': 0.0, 'tokens': 0})
|
||||
result.append(TimeSeriesData(
|
||||
timestamp=hour_str,
|
||||
requests=data['requests'],
|
||||
cost=data['cost'],
|
||||
tokens=data['tokens']
|
||||
))
|
||||
current += timedelta(hours=1)
|
||||
|
||||
return result
|
||||
|
||||
|
||||
async def _get_daily_statistics(start_time: datetime, end_time: datetime) -> List[TimeSeriesData]:
|
||||
"""获取日级统计数据"""
|
||||
daily_buckets = defaultdict(lambda: {'requests': 0, 'cost': 0.0, 'tokens': 0})
|
||||
|
||||
records = list(
|
||||
LLMUsage.select()
|
||||
.where(LLMUsage.timestamp >= start_time)
|
||||
.where(LLMUsage.timestamp <= end_time)
|
||||
)
|
||||
|
||||
for record in records:
|
||||
# 获取日期键
|
||||
day_key = record.timestamp.replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
day_str = day_key.isoformat()
|
||||
|
||||
daily_buckets[day_str]['requests'] += 1
|
||||
daily_buckets[day_str]['cost'] += record.cost or 0.0
|
||||
daily_buckets[day_str]['tokens'] += (record.prompt_tokens or 0) + (record.completion_tokens or 0)
|
||||
|
||||
# 填充所有天
|
||||
result = []
|
||||
current = start_time.replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
while current <= end_time:
|
||||
day_str = current.isoformat()
|
||||
data = daily_buckets.get(day_str, {'requests': 0, 'cost': 0.0, 'tokens': 0})
|
||||
result.append(TimeSeriesData(
|
||||
timestamp=day_str,
|
||||
requests=data['requests'],
|
||||
cost=data['cost'],
|
||||
tokens=data['tokens']
|
||||
))
|
||||
current += timedelta(days=1)
|
||||
|
||||
return result
|
||||
|
||||
|
||||
async def _get_recent_activity(limit: int = 10) -> List[Dict[str, Any]]:
|
||||
"""获取最近活动"""
|
||||
records = list(
|
||||
LLMUsage.select()
|
||||
.order_by(LLMUsage.timestamp.desc())
|
||||
.limit(limit)
|
||||
)
|
||||
|
||||
activities = []
|
||||
for record in records:
|
||||
activities.append({
|
||||
'timestamp': record.timestamp.isoformat(),
|
||||
'model': record.model_assign_name or record.model_name,
|
||||
'request_type': record.request_type,
|
||||
'tokens': (record.prompt_tokens or 0) + (record.completion_tokens or 0),
|
||||
'cost': record.cost or 0.0,
|
||||
'time_cost': record.time_cost or 0.0,
|
||||
'status': record.status
|
||||
})
|
||||
|
||||
return activities
|
||||
|
||||
|
||||
@router.get("/summary")
|
||||
async def get_summary(hours: int = 24):
|
||||
"""
|
||||
获取统计摘要
|
||||
|
||||
Args:
|
||||
hours: 统计时间范围（小时）
|
||||
"""
|
||||
try:
|
||||
now = datetime.now()
|
||||
start_time = now - timedelta(hours=hours)
|
||||
summary = await _get_summary_statistics(start_time, now)
|
||||
return summary
|
||||
except Exception as e:
|
||||
logger.error(f"获取统计摘要失败: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e)) from e
|
||||
|
||||
|
||||
@router.get("/models")
|
||||
async def get_model_stats(hours: int = 24):
|
||||
"""
|
||||
获取模型统计
|
||||
|
||||
Args:
|
||||
hours: 统计时间范围（小时）
|
||||
"""
|
||||
try:
|
||||
now = datetime.now()
|
||||
start_time = now - timedelta(hours=hours)
|
||||
stats = await _get_model_statistics(start_time)
|
||||
return stats
|
||||
except Exception as e:
|
||||
logger.error(f"获取模型统计失败: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e)) from e
|
||||
Loading…
Reference in New Issue