"""
关键点检索工具 - 根据输入的点在图数据库中查找所有关联的点

用于 Agent 执行时自主调取关联关键点数据。
"""

import json
import os
from pathlib import Path
from typing import Any, Dict, Optional

# 完整图数据库文件路径（包含 edges）
GRAPH_FULL_DATA_PATH = os.getenv(
    "GRAPH_FULL_DATA_PATH",
    # str(Path(__file__).parent.parent / "data/library/item_graph/item_graph_full_all_levels.json")
    str(Path(__file__).parent.parent / "data/家有大志/topic_point_data/point_classification_results.json")
)

# 缓存图数据，避免重复加载
_graph_full_cache: Optional[Dict[str, Any]] = None


def _load_graph_full() -> Dict[str, Any]:
    """加载完整图数据（带缓存，包含 edges）"""
    global _graph_full_cache
    if _graph_full_cache is None:
        with open(GRAPH_FULL_DATA_PATH, 'r', encoding='utf-8') as f:
            _graph_full_cache = json.load(f)
    return _graph_full_cache

if __name__ == "__main__":
    graph = _load_graph_full()
    data = {}

    for post, value1 in graph.items():
        for point_type, points_list in value1.items():
            for point_item in points_list:
                for dimension, dimension_list in point_item.items():
                    if dimension in ["实质", "形式", "意图"] and isinstance(dimension_list, list):
                        for point in dimension_list:
                            name = point.get("名称")
                            if name:
                                data[name] = {
                                    "名称": name,
                                    "类型": point_type,
                                    "维度": dimension
                                }
    # 输出到文件
    output_path = Path(__file__).parent.parent / "data/家有大志/topic_point_data/point_classification_results_trans.json"
    with open(output_path, 'w', encoding='utf-8') as f:
        json.dump(data, f, ensure_ascii=False, indent=2)

    print(f"数据已输出到: {output_path}")