# -*- coding: utf-8 -*-
"""一次性脚本：把高优 156 cell 铺成 156 × 3 lens × 6 工具类型约束 = 2808 条 query。

输入：
  - 同目录 judged_matrix.json：拿 actions/types，确定 156 个 score==3 的 (action, type) cell
  - 同目录 type_action_scores.json：兜底拿 score；现有 high_priority_queries.json 用来回填 gemini_q
输出：
  - high_priority_queries_full.json：扁平 queries 数组，按 (cell, lens, constraint) 顺序

约束 6 档：null（无约束）+ {AI 模型, 桌面 APP, 云端 Web, API·CLI, 插件扩展}
lens 后缀：工序→教程 / 工具→工具 / 能力→技巧

注意：模态约束（文/图/视频/音频）已废弃，不再列入。runs/ 下历史模态文件夹保留作旧实验，
新表索引体系跟它们不挂钩；runs_to_full_mapping.json 的 unmatched 段会标出来。
"""
import json
from pathlib import Path

HERE = Path(__file__).parent
SRC_HP = HERE.parent / "high_priority_queries.json"  # 原 468 条，用它的 gemini_q
JM = HERE / "judged_matrix.json"
TAS = HERE / "type_action_scores.json"
OUT = HERE / "high_priority_queries_full.json"

LENS_SUFFIX = {"工序": "教程", "工具": "工具", "能力": "技巧"}

# (首词, constraint dict)；首词为 None 表示无约束
CONSTRAINTS = [
    (None, None),
    ("AI",   {"kind": "工具类型", "value": "AI 模型",   "限定词": "AI"}),
    ("软件", {"kind": "工具类型", "value": "桌面 APP",  "限定词": "软件"}),
    ("在线", {"kind": "工具类型", "value": "云端 Web",  "限定词": "在线"}),
    ("代码", {"kind": "工具类型", "value": "API·CLI",   "限定词": "代码"}),
    ("插件", {"kind": "工具类型", "value": "插件扩展",  "限定词": "插件"}),
]


def main():
    jm = json.load(open(JM, encoding="utf-8"))
    actions = jm["actions"]            # 27 条；带 name / l1 / (l2)
    types = jm["types"]                # 50 条；带 name / l1
    act_l1 = {a["name"]: a["l1"] for a in actions}

    tas = json.load(open(TAS, encoding="utf-8"))["scores"]
    # 取 score==3 的 (type, action) cell，对齐 high_priority_queries.json 的"156 高优"集合
    cells = []
    for t in types:
        for a in actions:
            rec = tas.get(t["name"], {}).get(a["name"])
            if rec and rec.get("score") == 3:
                cells.append((a["name"], t["name"]))

    # 从原文件读 gemini_q：以 (action, type) 为键，每 cell 取首条
    gemini_by_cell = {}
    if SRC_HP.exists():
        for it in json.load(open(SRC_HP, encoding="utf-8"))["queries"]:
            key = (it["action"], it["type"])
            gemini_by_cell.setdefault(key, it.get("gemini_q", ""))

    # 生成：cell × lens × constraint
    queries = []
    for action, type_ in cells:
        for lens, suffix in LENS_SUFFIX.items():
            for qual, cons in CONSTRAINTS:
                tokens = [qual, action, type_, suffix] if qual else [action, type_, suffix]
                queries.append({
                    "q": " ".join(tokens),
                    "lens": lens,
                    "type": type_,
                    "action": action,
                    "action_l1": act_l1.get(action, ""),
                    "score": 3,
                    "constraint": cons,
                    "gemini_q": gemini_by_cell.get((action, type_), ""),
                })

    out = {
        "_doc": (
            "高优先级 query 全展开：156 cell × 3 lens × 6 工具类型约束 = 2808 条。"
            "lens 后缀 工序→教程 / 工具→工具 / 能力→技巧；约束 6 档 = 无约束 + 5 工具类型。"
            "模态约束已废弃，runs/ 下历史模态 q 文件夹不在本索引内。"
            "gemini_q 按 (action, type) cell 复用同一句，跨 lens / 约束不变。"
        ),
        "model": "gemini-3.1-flash-lite",
        "threshold": 3,
        "lenses": list(LENS_SUFFIX),
        "tool_constraints": [c["value"] if c else None for _, c in CONSTRAINTS],
        "cells": len(cells),
        "per_cell": len(LENS_SUFFIX) * len(CONSTRAINTS),   # 18
        "total": len(queries),
        "queries": queries,
    }
    with open(OUT, "w", encoding="utf-8") as f:
        json.dump(out, f, ensure_ascii=False, indent=2)

    # 自检：156 × 3 × 6 = 2808
    assert len(cells) == 156, f"cells={len(cells)} 不是 156，检查 type_action_scores 阈值"
    expected = 156 * 3 * 6
    assert len(queries) == expected, f"queries={len(queries)} != {expected}"

    # 抽样打印
    print(f"✅ cells={len(cells)}  queries={len(queries)}  -> {OUT}")
    print()
    print("== 抽样：第 1 个 cell 的 18 条 ==")
    for q in queries[:18]:
        cv = (q["constraint"] or {}).get("value", "")
        print(f"  [{q['lens']}/{cv or '无约束':6}] {q['q']}")


if __name__ == "__main__":
    main()