"""按版本化模型价格重算历史 usage_events，默认只输出 dry-run 汇总。 示例： .venv/Scripts/python.exe scripts/reprice_usage.py --from 2026-08-16T16:00:00Z .venv/Scripts/python.exe scripts/reprice_usage.py --from 2026-08-16T16:00:00Z \ --apply --confirm APPLY_DEEPSEEK_REPRICE 脚本不加载 .env；调用方必须显式提供 ZCBOT_DB_URL。生产写入前先核对 dry-run 输出和 打印的脱敏目标。缺少 cache_hit_tokens 的旧辅助调用按全部未命中估算并留标记。 """ from __future__ import annotations import argparse import os from collections import defaultdict from datetime import datetime, timezone from decimal import Decimal from pathlib import Path import sys from typing import Any from sqlalchemy import select from sqlalchemy.engine import make_url ROOT = Path(__file__).resolve().parents[1] if str(ROOT) not in sys.path: sys.path.insert(0, str(ROOT)) from core.capabilities import ModelCapabilities # noqa: E402 from core.pricing import calculate_chat_cost, pricing_snapshot, resolve_chat_price # noqa: E402 from core.storage import session_scope # noqa: E402 from core.storage.models import UsageEvent # noqa: E402 DEFAULT_PROFILES = ("deepseek_v4.flash", "deepseek_v4.pro") COST_KINDS = {"chat", "prompt_optimize", "context_fold", "task_title", "kb_ingest"} CONFIRM_TEXT = "APPLY_DEEPSEEK_REPRICE" PRICE_SNAPSHOT_KEYS = { "pricing_revision", "pricing_source", "pricing_source_url", "pricing_currency", "pricing_at", "price_tier", "fx_to_cny", "input_price_per_mtoken", "cache_hit_price_per_mtoken", "output_price_per_mtoken", "input_cost_cny", "cache_hit_cost_cny", "output_cost_cny", } def _parse_datetime(value: str) -> datetime: dt = datetime.fromisoformat(value.strip().replace("Z", "+00:00")) if dt.tzinfo is None: dt = dt.replace(tzinfo=timezone.utc) return dt.astimezone(timezone.utc) def _args() -> argparse.Namespace: p = argparse.ArgumentParser(description="重算历史模型成本（默认 dry-run）") p.add_argument("--from", dest="from_at", required=True, type=_parse_datetime) p.add_argument("--profile", action="append", dest="profiles") p.add_argument("--apply", action="store_true", help="事务内写回；默认只预览") p.add_argument("--rollback", action="store_true", help="恢复本 revision 保存的旧成本") p.add_argument("--confirm", default="", help=f"写入确认串：{CONFIRM_TEXT}") return p.parse_args() def _target() -> str: raw = os.environ.get("ZCBOT_DB_URL", "").strip() if not raw: raise RuntimeError("ZCBOT_DB_URL is not set") return make_url(raw).render_as_string(hide_password=True) def main() -> int: args = _args() if args.apply and args.rollback: raise SystemExit("[ERR] --apply 与 --rollback 不能同时使用") if (args.apply or args.rollback) and args.confirm != CONFIRM_TEXT: raise SystemExit(f"[ERR] 写入必须传 --confirm {CONFIRM_TEXT}") profiles = tuple(args.profiles or DEFAULT_PROFILES) caps_by_profile = { profile: ModelCapabilities.load(profile, ROOT / "config" / "models") for profile in profiles } revisions = { period.get("revision") for caps in caps_by_profile.values() for period in caps.pricing.get("periods", []) if period.get("revision") } target = _target() mode = "ROLLBACK" if args.rollback else ("APPLY" if args.apply else "DRY-RUN") print(f"[INFO] mode={mode} target={target} from={args.from_at.isoformat()}") print(f"[INFO] profiles={','.join(profiles)} revisions={','.join(sorted(revisions))}") summary: dict[tuple[str, str], dict[str, Any]] = defaultdict( lambda: { "rows": 0, "estimated": 0, "old": Decimal("0"), "new": Decimal("0"), "estimated_old": Decimal("0"), "estimated_new": Decimal("0"), } ) estimated_by_kind: dict[tuple[str, str], dict[str, Any]] = defaultdict( lambda: {"rows": 0, "old": Decimal("0"), "new": Decimal("0")} ) changed = 0 with session_scope() as s: events = s.execute( select(UsageEvent).where( UsageEvent.model_profile.in_(profiles), UsageEvent.kind.in_(COST_KINDS), UsageEvent.created_at >= args.from_at, ).order_by(UsageEvent.created_at, UsageEvent.event_id) ).scalars().all() for event in events: units = dict(event.units or {}) caps = caps_by_profile[event.model_profile] if args.rollback: if units.get("repricing_revision") not in revisions: continue previous = units.get("previous_cost_cny") if previous is None: continue old = Decimal(str(event.cost_cny or 0)) new = Decimal(str(previous)) previous_pricing = units.get("previous_pricing_units") or {} for price_key in PRICE_SNAPSHOT_KEYS: units.pop(price_key, None) if isinstance(previous_pricing, dict): units.update(previous_pricing) for key in list(units): if ( key.startswith("repricing_") or key in {"previous_cost_cny", "previous_pricing_units"} ): units.pop(key, None) key = (event.model_profile, "rollback") else: quote = resolve_chat_price(caps.pricing, occurred_at=event.created_at) if quote is None or units.get("repricing_revision") == quote.revision: continue tokens_in = int(units.get("tokens_in") or 0) tokens_out = int(units.get("tokens_out") or 0) # 旧主循环一直提取 DeepSeek cache usage，但 record_chat_usage 的 # extra_units 会省略值为 0 的字段，所以 chat 缺 key 可判定为零命中； # 旧辅助调用没有提取缓存明细，缺 key 才是真正的不确定。 has_cache = "cache_hit_tokens" in units or event.kind == "chat" cache_hit = int(units.get("cache_hit_tokens") or 0) breakdown = calculate_chat_cost( quote, prompt_tokens=tokens_in, completion_tokens=tokens_out, cache_hit_tokens=cache_hit, ) old = Decimal(str(event.cost_cny or 0)) new = breakdown.total_cny previous_pricing = { key: units[key] for key in PRICE_SNAPSHOT_KEYS if key in units } units.update(pricing_snapshot(quote, breakdown)) units.update({ "repricing_revision": quote.revision, "previous_cost_cny": float(old), "repriced_at": datetime.now(timezone.utc).isoformat(), "repricing_time_basis": "usage_event.created_at", "repricing_estimated": not has_cache, "previous_pricing_units": previous_pricing, }) key = (event.model_profile, quote.tier) if not has_cache: summary[key]["estimated"] += 1 summary[key]["estimated_old"] += old summary[key]["estimated_new"] += new uncertain = estimated_by_kind[(event.model_profile, event.kind)] uncertain["rows"] += 1 uncertain["old"] += old uncertain["new"] += new bucket = summary[key] bucket["rows"] += 1 bucket["old"] += old bucket["new"] += new changed += 1 if args.apply or args.rollback: event.cost_cny = new.quantize(Decimal("0.000001")) event.units = units if not (args.apply or args.rollback): s.rollback() total_old = Decimal("0") total_new = Decimal("0") for (profile, tier), item in sorted(summary.items()): total_old += item["old"] total_new += item["new"] print( f"[INFO] {profile} tier={tier} rows={item['rows']} " f"estimated={item['estimated']} old={item['old']:.6f} " f"new={item['new']:.6f} delta={(item['new'] - item['old']):.6f} " f"estimated_delta={(item['estimated_new'] - item['estimated_old']):.6f}" ) for (profile, kind), item in sorted(estimated_by_kind.items()): print( f"[WARN] estimated profile={profile} kind={kind} rows={item['rows']} " f"old={item['old']:.6f} new={item['new']:.6f} " f"delta={(item['new'] - item['old']):.6f}" ) print( f"[OK] rows={changed} old={total_old:.6f} new={total_new:.6f} " f"delta={(total_new - total_old):.6f} mode={mode}" ) return 0 if __name__ == "__main__": raise SystemExit(main())