114 lines
4.4 KiB
Python
114 lines
4.4 KiB
Python
#!/usr/bin/env python3
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"""select_output_strategy.py — auto 输出决策器（方案 §4.6.5，策略 single-first-v1）。
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规则（首版）：
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1. 用户明确目的（--purpose learning|reference|workflow|distribution）优先；
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2. 未明确目的时：至少 3 个能力通过晋级门、且晋级门触发验证达到预注册阈值（TBD-after-baseline，
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基线前该分支不启用）→ 推荐 pack；
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3. 其他情况一律推荐 single（single-first）。
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输出可解释 decision report（output-decision.schema.json）。默认值只是推荐，不能取消用户显式选择。
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"""
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from __future__ import annotations
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import argparse
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent))
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from cangjie_common import dump_json, load_yaml # noqa: E402
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from compile_single import active_capabilities, promoted_capabilities # noqa: E402
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POLICY = "single-first-v1"
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PURPOSE_TO_MODE = {
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"learning": "single",
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"reference": "single",
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"workflow": "pack",
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"distribution": "pack",
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}
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def decide(bundle_dir: Path, requested: str, purpose: str | None, *, trigger_validation_ready: bool = False) -> dict:
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bundle = load_yaml(bundle_dir / "verified.yaml")
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caps = active_capabilities(bundle)
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promoted = promoted_capabilities(bundle)
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budget = int(bundle.get("promotion_budget", 8))
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reasons: list[str] = []
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if requested in ("single", "pack"):
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selected = requested
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reasons.append(f"用户显式选择 {requested}，auto 决策器不覆盖用户选择")
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elif purpose:
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selected = PURPOSE_TO_MODE[purpose]
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reasons.append(f"用户目的为 {purpose} → {selected}")
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elif len(promoted) >= 3 and trigger_validation_ready:
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selected = "pack"
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reasons.append(f"{len(promoted)} 个能力通过晋级门（>=3）且触发验证达到预注册阈值")
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else:
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selected = "single"
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if len(promoted) >= 3:
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reasons.append(
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f"{len(promoted)} 个能力通过晋级门，但触发验证阈值为 TBD-after-baseline 尚未启用；"
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"按 single-first 原则先推荐 single，拆分由使用证据驱动"
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)
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else:
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reasons.append(f"仅 {len(promoted)} 个能力通过晋级门（<3），不满足 pack 推荐条件")
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alternative = (
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f"compact pack（1 个来源路由入口 + {len(promoted)} 个晋级 Skill，共 {1 + len(promoted)} 个可发现入口）"
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if selected == "single"
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else f"single（1 个入口 + {len(caps)} 张内部能力卡）"
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)
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return {
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"schema_version": 1,
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"requested": requested,
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"selected": selected,
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"decision_policy": POLICY,
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"skill_budget": budget,
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"promoted_count": len(promoted),
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"capability_count": len(caps),
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"reasons": reasons,
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"alternative": alternative,
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"user_confirmed": requested != "auto",
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"preserve_strategy_on_update": True,
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}
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def render_report(decision: dict, bundle_dir: Path) -> str:
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bundle = load_yaml(bundle_dir / "verified.yaml")
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return f"""# 输出策略决策报告
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推荐：**{decision['selected']}**（requested: {decision['requested']}，策略 {decision['decision_policy']}）
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理由：
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{chr(10).join(f'- {r}' for r in decision['reasons'])}
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产物：{'1 个 Skill + ' + str(decision['capability_count']) + ' 张内部能力卡 + 章节/术语/速查 references' if decision['selected'] == 'single' else f"1 个来源路由入口 + {decision['promoted_count']} 个晋级 Skill（共 {1 + decision['promoted_count']} 个可发现入口）"}
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备选：{decision['alternative']}
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> 来源：{bundle['book']['title']}（{decision['capability_count']} 个 active 能力，晋级预算 {decision['skill_budget']}）
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> 请回答：按推荐 / 改成 single / 改成 pack。默认值只是推荐，不会取消你的显式选择。
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"""
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def main() -> int:
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ap = argparse.ArgumentParser(description=__doc__)
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ap.add_argument("--bundle", required=True)
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ap.add_argument("--requested", choices=["auto", "single", "pack"], default="auto")
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ap.add_argument("--purpose", choices=list(PURPOSE_TO_MODE), default=None)
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ap.add_argument("--out-json", default=None)
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args = ap.parse_args()
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decision = decide(Path(args.bundle), args.requested, args.purpose)
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print(render_report(decision, Path(args.bundle)))
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if args.out_json:
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dump_json(Path(args.out_json), decision)
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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