104 lines
3.6 KiB
Python
104 lines
3.6 KiB
Python
"""调用可观测面板后端 API（媒体/LLM 调用归因）。
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路由前缀: /app/api/admin/observability
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数据来源: token_usage_logs（Phase 2.2 已加 trace_id 列，可经 X-Trace-Id 关联请求链路）。
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"""
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from datetime import datetime, timedelta
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from fastapi import APIRouter, Query, Depends
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from ...database import get_db
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from ..auth import get_current_user
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from sqlalchemy import text
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from sqlalchemy.orm import Session
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router = APIRouter()
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@router.get("/summary")
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async def observability_summary(
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days: int = Query(30, description="统计天数"),
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db: Session = Depends(get_db),
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user=Depends(get_current_user),
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):
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"""媒体/LLM 调用归因：总览 + 按模型 + 按用户 + 每日趋势 + 最近调用(trace_id 下钻)。"""
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since = datetime.now() - timedelta(days=days)
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totals = db.execute(text("""
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SELECT COUNT(*),
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COALESCE(SUM(total_tokens), 0),
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COALESCE(SUM(cost), 0),
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COUNT(DISTINCT user_id)
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FROM token_usage_logs WHERE created_at >= :since
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"""), {"since": since}).fetchone()
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by_model = db.execute(text("""
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SELECT model_name, COUNT(*), COALESCE(SUM(total_tokens), 0), COALESCE(SUM(cost), 0)
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FROM token_usage_logs WHERE created_at >= :since
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GROUP BY model_name ORDER BY COALESCE(SUM(total_tokens), 0) DESC
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"""), {"since": since}).fetchall()
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by_user = db.execute(text("""
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SELECT t.user_id, u.username, COUNT(*), COALESCE(SUM(t.total_tokens), 0), COALESCE(SUM(t.cost), 0)
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FROM token_usage_logs t LEFT JOIN users u ON u.id = t.user_id
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WHERE t.created_at >= :since
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GROUP BY t.user_id, u.username ORDER BY COALESCE(SUM(t.total_tokens), 0) DESC LIMIT 20
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"""), {"since": since}).fetchall()
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daily = db.execute(text("""
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SELECT DATE(created_at) AS d, COALESCE(SUM(total_tokens), 0), COALESCE(SUM(cost), 0), COUNT(*)
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FROM token_usage_logs WHERE created_at >= :since
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GROUP BY DATE(created_at) ORDER BY d
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"""), {"since": since}).fetchall()
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recent = db.execute(text("""
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SELECT trace_id, model_name, total_tokens, cost, created_at
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FROM token_usage_logs WHERE created_at >= :since
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ORDER BY created_at DESC LIMIT 50
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"""), {"since": since}).fetchall()
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return {
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"totals": {
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"calls": int(totals[0] or 0),
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"tokens": int(totals[1] or 0),
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"cost": float(totals[2] or 0),
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"users": int(totals[3] or 0),
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},
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"by_model": [
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{
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"model_name": m[0] or "unknown",
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"calls": int(m[1] or 0),
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"tokens": int(m[2] or 0),
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"cost": float(m[3] or 0),
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}
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for m in by_model
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],
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"by_user": [
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{
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"user_id": u[0],
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"username": u[1] or u[0],
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"calls": int(u[2] or 0),
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"tokens": int(u[3] or 0),
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"cost": float(u[4] or 0),
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}
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for u in by_user
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],
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"daily": [
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{
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"date": str(d[0]),
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"tokens": int(d[1] or 0),
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"cost": float(d[2] or 0),
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"calls": int(d[3] or 0),
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}
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for d in daily
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],
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"recent": [
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{
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"trace_id": r[0],
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"model_name": r[1] or "unknown",
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"tokens": int(r[2] or 0),
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"cost": float(r[3] or 0),
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"created_at": r[4].strftime("%Y-%m-%d %H:%M:%S") if r[4] else None,
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}
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for r in recent
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],
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}
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