tzt
1aaa05cacc
- gateway/sense/promotion.py：PromotionTable 状态机（candidate/promoted/demoted）
* 晋升门：n_total>=n_min 且 通过率>=promote_lb 且 soak 浸泡期满足
* 退化：promoted 期间通过率<demote_lb 自动降级；降级后可凭数据恢复
* 一票否决：tier=T3 观察不进通过率统计，已晋升者立即降级
* 持久化 sense_promotion 表（CREATE IF NOT EXISTS 幂等）
- grader：live 模式对已晋升标签的 T2 决策（无 T3 信号/非 fallback）升级 T1，
hard_gates.promotion_applied 如实标注；T1/T3/fallback 路径不受影响
- 回填链路：T1 审计抽样带 promo:<label> 标签 -> 人工 verdict approve=ok
经 /review/{id} 提交时回填晋升表（失败不影响审核主流程）
- 双闸门语义：conformal 阈值保证单条决策风险率，晋升表保证标签级接管节奏；
collect 数据不足（n_min 未满）不晋升，全部迁移可经 T-X4 留痕审计
pytest 474 passed（T-X4 后 466 + 8）
82 lines
3.7 KiB
Python
82 lines
3.7 KiB
Python
"""云端评判式晋升表（T-X5，采纳 cortiq promotion.rs，与 conformal 双闸门）。
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定位：conformal 阈值给出「分对率 >= 1-α」的统计保证（单条查询粒度），
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本表在其之上给出「某类任务（label）可由本地档接管」的**节奏自动化**：
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- 观察：人工核验 verdict（approve=ok）等质量信号按 label 累计通过率；
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- 晋升：n_total >= n_min 且 通过率 >= promote_lb 且 soak 浸泡期满足
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-> state=promoted（此后 grader 对该 label 的 T2 决策可升级 T1）；
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- 退化：promoted 期间通过率 < demote_lb -> demoted（自动回退分级路径）；
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- 一票否决：tier=T3（高复杂度/仓库级）观察不进通过率统计，且若已晋升
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立即降级——与 cortiq "HIGH tier escalation is served by the cloud" 同构。
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灰度纪律（沿用 D-G7）：collect 数据不足（n_min 未满）不得晋升；
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全部状态迁移可由 T-X4 的决策留痕审计。
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"""
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from __future__ import annotations
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import time
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from typing import Any, Dict, Optional
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def promotion_label(consumer: str, domain: str = "") -> str:
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"""晋升粒度：消费方×领域（domain 缺省归 general；调用方可传更细粒度）。"""
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return f"{consumer or 'default'}:{domain or 'general'}"
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class PromotionTable:
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"""标签晋升状态机（candidate / promoted / demoted；持久化于 sense_promotion）。"""
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def __init__(self, store, now=None, n_min: int = 20, promote_lb: float = 0.95,
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soak_days: float = 3.0, demote_lb: float = 0.85,
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high_tier_veto: bool = True):
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self.store = store
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self._now = now or (lambda: time.time())
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self.n_min = max(1, int(n_min))
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self.promote_lb = float(promote_lb)
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self.demote_lb = float(demote_lb)
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self.soak_s = float(soak_days) * 86400.0
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self.high_tier_veto = bool(high_tier_veto)
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def observe(self, label: str, ok: bool, tier: str = "",
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ts: Optional[float] = None) -> Dict[str, Any]:
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"""记录一次质量信号并推进状态机；返回迁移后的行。"""
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ts = float(ts) if ts is not None else float(self._now())
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row = self.store.get_promotion(label) or {
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"label": label, "n_total": 0, "n_ok": 0, "state": "candidate",
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"first_ts": int(ts), "promoted_ts": 0, "last_ts": 0}
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# 一票否决：T3 观察不进通过率统计；已晋升者立即降级
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if self.high_tier_veto and str(tier).upper() == "T3":
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row["last_ts"] = int(ts)
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if row["state"] == "promoted":
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row["state"] = "demoted"
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row["promoted_ts"] = 0
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self.store.upsert_promotion(row)
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return row
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row["n_total"] = int(row["n_total"]) + 1
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row["n_ok"] = int(row["n_ok"]) + (1 if ok else 0)
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row["last_ts"] = int(ts)
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rate = row["n_ok"] / row["n_total"] if row["n_total"] else 0.0
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soaked = (ts - int(row["first_ts"])) >= self.soak_s
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if row["state"] == "promoted":
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if row["n_total"] >= self.n_min and rate < self.demote_lb:
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row["state"] = "demoted" # 退化自动降级
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row["promoted_ts"] = 0
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else:
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# candidate / demoted 共用同一晋升门（降级后可凭数据恢复）
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if row["n_total"] >= self.n_min and rate >= self.promote_lb and soaked:
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row["state"] = "promoted"
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row["promoted_ts"] = int(ts)
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self.store.upsert_promotion(row)
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return row
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def is_promoted(self, label: str) -> bool:
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row = self.store.get_promotion(label)
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return bool(row) and row["state"] == "promoted"
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def snapshot(self, label: str) -> Optional[Dict[str, Any]]:
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return self.store.get_promotion(label)
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