feat(openai): 极致优化 OAuth 链路并补齐性能守护
- 优化 /v1/responses 热路径,减少重复解析与不必要拷贝\n- 优化并发与 token 竞争路径并补齐运行指标\n- 补充 OpenAI/Ops 相关单元测试与回归用例\n- 新增灰度阈值守护与压测脚本,支撑发布验收
This commit is contained in:
213
tools/perf/openai_oauth_gray_guard.py
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213
tools/perf/openai_oauth_gray_guard.py
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#!/usr/bin/env python3
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"""OpenAI OAuth 灰度阈值守护脚本。
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用途:
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- 拉取 Ops 指标阈值配置与 Dashboard Overview 实时数据
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- 对比 P99 TTFT / 错误率 / SLA
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- 作为 6.2 灰度守护的自动化门禁(退出码可直接用于 CI/CD)
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退出码:
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- 0: 指标通过
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- 1: 请求失败/参数错误
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- 2: 指标超阈值(建议停止扩量并回滚)
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"""
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from __future__ import annotations
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import argparse
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import json
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import sys
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import urllib.error
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import urllib.parse
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import urllib.request
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from dataclasses import dataclass
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from typing import Any, Dict, List, Optional
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@dataclass
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class GuardThresholds:
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sla_percent_min: Optional[float]
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ttft_p99_ms_max: Optional[float]
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request_error_rate_percent_max: Optional[float]
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upstream_error_rate_percent_max: Optional[float]
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@dataclass
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class GuardSnapshot:
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sla: Optional[float]
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ttft_p99_ms: Optional[float]
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request_error_rate_percent: Optional[float]
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upstream_error_rate_percent: Optional[float]
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def build_headers(token: str) -> Dict[str, str]:
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headers = {"Accept": "application/json"}
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if token.strip():
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headers["Authorization"] = f"Bearer {token.strip()}"
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return headers
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def request_json(url: str, headers: Dict[str, str]) -> Dict[str, Any]:
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req = urllib.request.Request(url=url, method="GET", headers=headers)
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try:
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with urllib.request.urlopen(req, timeout=15) as resp:
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raw = resp.read().decode("utf-8")
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return json.loads(raw)
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except urllib.error.HTTPError as e:
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body = e.read().decode("utf-8", errors="replace")
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raise RuntimeError(f"HTTP {e.code}: {body}") from e
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except urllib.error.URLError as e:
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raise RuntimeError(f"request failed: {e}") from e
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def parse_envelope_data(payload: Dict[str, Any]) -> Dict[str, Any]:
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if not isinstance(payload, dict):
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raise RuntimeError("invalid response payload")
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if payload.get("code") != 0:
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raise RuntimeError(f"api error: code={payload.get('code')} message={payload.get('message')}")
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data = payload.get("data")
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if not isinstance(data, dict):
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raise RuntimeError("invalid response data")
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return data
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def parse_thresholds(data: Dict[str, Any]) -> GuardThresholds:
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return GuardThresholds(
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sla_percent_min=to_float_or_none(data.get("sla_percent_min")),
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ttft_p99_ms_max=to_float_or_none(data.get("ttft_p99_ms_max")),
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request_error_rate_percent_max=to_float_or_none(data.get("request_error_rate_percent_max")),
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upstream_error_rate_percent_max=to_float_or_none(data.get("upstream_error_rate_percent_max")),
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)
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def parse_snapshot(data: Dict[str, Any]) -> GuardSnapshot:
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ttft = data.get("ttft") if isinstance(data.get("ttft"), dict) else {}
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return GuardSnapshot(
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sla=to_float_or_none(data.get("sla")),
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ttft_p99_ms=to_float_or_none(ttft.get("p99_ms")),
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request_error_rate_percent=to_float_or_none(data.get("error_rate")),
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upstream_error_rate_percent=to_float_or_none(data.get("upstream_error_rate")),
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)
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def to_float_or_none(v: Any) -> Optional[float]:
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if v is None:
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return None
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try:
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return float(v)
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except (TypeError, ValueError):
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return None
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def evaluate(snapshot: GuardSnapshot, thresholds: GuardThresholds) -> List[str]:
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violations: List[str] = []
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if thresholds.sla_percent_min is not None and snapshot.sla is not None:
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if snapshot.sla < thresholds.sla_percent_min:
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violations.append(
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f"SLA 低于阈值: actual={snapshot.sla:.2f}% threshold={thresholds.sla_percent_min:.2f}%"
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)
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if thresholds.ttft_p99_ms_max is not None and snapshot.ttft_p99_ms is not None:
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if snapshot.ttft_p99_ms > thresholds.ttft_p99_ms_max:
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violations.append(
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f"TTFT P99 超阈值: actual={snapshot.ttft_p99_ms:.2f}ms threshold={thresholds.ttft_p99_ms_max:.2f}ms"
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)
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if (
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thresholds.request_error_rate_percent_max is not None
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and snapshot.request_error_rate_percent is not None
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and snapshot.request_error_rate_percent > thresholds.request_error_rate_percent_max
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):
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violations.append(
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"请求错误率超阈值: "
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f"actual={snapshot.request_error_rate_percent:.2f}% "
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f"threshold={thresholds.request_error_rate_percent_max:.2f}%"
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)
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if (
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thresholds.upstream_error_rate_percent_max is not None
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and snapshot.upstream_error_rate_percent is not None
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and snapshot.upstream_error_rate_percent > thresholds.upstream_error_rate_percent_max
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):
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violations.append(
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"上游错误率超阈值: "
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f"actual={snapshot.upstream_error_rate_percent:.2f}% "
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f"threshold={thresholds.upstream_error_rate_percent_max:.2f}%"
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)
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return violations
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def main() -> int:
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parser = argparse.ArgumentParser(description="OpenAI OAuth 灰度阈值守护")
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parser.add_argument("--base-url", required=True, help="服务地址,例如 http://127.0.0.1:5231")
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parser.add_argument("--admin-token", default="", help="Admin JWT(可选,按部署策略)")
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parser.add_argument("--platform", default="openai", help="平台过滤,默认 openai")
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parser.add_argument("--time-range", default="30m", help="时间窗口: 5m/30m/1h/6h/24h/7d/30d")
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parser.add_argument("--group-id", default="", help="可选 group_id")
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args = parser.parse_args()
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base = args.base_url.rstrip("/")
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headers = build_headers(args.admin_token)
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try:
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threshold_url = f"{base}/api/v1/admin/ops/settings/metric-thresholds"
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thresholds_raw = request_json(threshold_url, headers)
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thresholds = parse_thresholds(parse_envelope_data(thresholds_raw))
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query = {"platform": args.platform, "time_range": args.time_range}
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if args.group_id.strip():
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query["group_id"] = args.group_id.strip()
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overview_url = (
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f"{base}/api/v1/admin/ops/dashboard/overview?"
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+ urllib.parse.urlencode(query)
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)
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overview_raw = request_json(overview_url, headers)
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snapshot = parse_snapshot(parse_envelope_data(overview_raw))
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print("[OpenAI OAuth Gray Guard] 当前快照:")
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print(
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json.dumps(
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{
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"sla": snapshot.sla,
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"ttft_p99_ms": snapshot.ttft_p99_ms,
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"request_error_rate_percent": snapshot.request_error_rate_percent,
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"upstream_error_rate_percent": snapshot.upstream_error_rate_percent,
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},
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ensure_ascii=False,
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indent=2,
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)
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)
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print("[OpenAI OAuth Gray Guard] 阈值配置:")
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print(
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json.dumps(
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{
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"sla_percent_min": thresholds.sla_percent_min,
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"ttft_p99_ms_max": thresholds.ttft_p99_ms_max,
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"request_error_rate_percent_max": thresholds.request_error_rate_percent_max,
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"upstream_error_rate_percent_max": thresholds.upstream_error_rate_percent_max,
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},
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ensure_ascii=False,
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indent=2,
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)
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)
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violations = evaluate(snapshot, thresholds)
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if violations:
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print("[OpenAI OAuth Gray Guard] 检测到阈值违例:")
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for idx, line in enumerate(violations, start=1):
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print(f" {idx}. {line}")
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print("[OpenAI OAuth Gray Guard] 建议:停止扩量并执行回滚。")
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return 2
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print("[OpenAI OAuth Gray Guard] 指标通过,可继续观察或按计划扩量。")
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return 0
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except Exception as exc:
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print(f"[OpenAI OAuth Gray Guard] 执行失败: {exc}", file=sys.stderr)
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return 1
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if __name__ == "__main__":
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raise SystemExit(main())
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