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utils/utils.py

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+def extract_names_from_json(file_path):
+    import json
+
+    with open(file_path, 'r', encoding='utf-8') as file:
+        data = json.load(file)
+
+    # 确保数据是一个列表
+    if isinstance(data, list):
+        names = [item.get("name") for item in data if "name" in item]
+        return names
+    else:
+        raise ValueError("JSON 文件的格式应为包含对象的列表")
+
+# list 生成 问题类别
+def define_suffix(input_str, fields):
+    import re
+    # 定义要检测的字段列表
+    # fields = [
+    #     "xzwb", "bxqd2", "bpz17", "zwqd", "bwpw", "BJGX", "bt2", "BDQ3", "BT2",
+    #     "gec5", "BDY3", "dwg", "bwpwz", "BDD3", "bt1", "bphq18", "zwzj", "bczc2",
+    #     "BPQ", "BPY", "BDQ3", "SXZB23", "SXZ", "xzwb2", "bpz17", "bwpw", "BJGX",
+    #     "bt1", "bpz17", "SXZB23", ".SXZ",
+    # ]
+
+    # 构建正则表达式模式，匹配大小写不敏感且前面可能带有.
+    # 去掉 \b 以允许字段是其他字符串的一部分
+    pattern = r'(?:\.?)(' + '|'.join(re.escape(field) for field in fields) + r')'
+
+    # 使用 re.IGNORECASE 标志来忽略大小写
+    if re.search(pattern, input_str, re.IGNORECASE):
+        return ['后缀名问题']
+    else:
+        return ['未知']
+
+def output_suffix(input_str, fields):
+    import re
+    pattern = r'(?:\.?)(' + '|'.join(re.escape(field) for field in fields) + r')'
+
+    matches = re.findall(pattern, input_str, re.IGNORECASE)
+
+    return matches[0]
+
+# str提取后缀名str
+def match_suffix(input_str, fields):
+    import re
+
+    pattern = r'(?:\.?)(' + '|'.join(re.escape(field) for field in fields) + r')'
+
+    matches = re.findall(pattern, input_str, re.IGNORECASE)
+
+    return matches[0] if matches else '未知'
+
+# 将pydantic的str类型转为model
+def str_to_pydantic(class_str):
+    from pydantic import BaseModel, Field
+
+    namespace = {}
+    # exec(class_str, globals(), namespace)
+    exec(class_str, {"BaseModel": BaseModel, "Field": Field}, namespace)
+    return namespace[list(namespace.keys())[0]]
+
+# 将pydantic的str类型转为template的input str
+def parse_pydantic_fields(class_str):
+    import ast
+
+    tree = ast.parse(class_str)
+    fields = {}
+
+    for node in ast.walk(tree):
+        if isinstance(node, ast.ClassDef):  # 找到类定义
+            for body_item in node.body:
+                if isinstance(body_item, ast.AnnAssign):  # 找到字段定义
+                    field_name = body_item.target.id
+                    fields[field_name] = ''  # 设为空值，可改为空字符串 ""
+    formatted_str = "\n".join([f"'{key}': ," for key in fields.keys()])
+
+    return formatted_str
+
+# 后缀名chains 后处理
+def extract_values(json_str):
+    import re
+    # 使用正则匹配 JSON 中的值
+    matches = re.findall(r'"(?:一级意图|二级意图)"\s*:\s*"([^"]+)"', json_str)
+
+    # 替换双引号为单引号
+    return [match.replace('"', "'") for match in matches]
+
+# 意图 槽位结构str返回
+def check_and_return(intention_result, parser):
+    key = intention_result[0]  # 获取 `intention_result` 的第一个值
+    value_lv1 = None
+    value_lv2 = None
+
+    # 检查 `pydantic_dict_lv1`
+    if key in parser.pydantic_dict_lv1:
+        temp_value_lv1 = parser.pydantic_dict_lv1[key]
+        if len(temp_value_lv1) >= 35:
+            value_lv1 = temp_value_lv1
+
+    # 检查 `pydantic_dict_lv2`
+    for item in parser.pydantic_dict_lv2:
+        for i in item:
+            intention_tuple = tuple(intention_result)
+            if intention_tuple in i:
+                temp_value_lv2 = i[intention_tuple]
+                if len(temp_value_lv2) >= 35:
+                    value_lv2 = temp_value_lv2
+
+    return [value_lv1, value_lv2]
+
+
+
+
+""" --------------------------------------------- 其他工具 --------------------------------------------- """
+
+def transform_json(input_file: str, output_file: str):
+    import json
+
+    """
+    读取JSON文件并转换格式后保存
+    :param input_file: 输入的JSON文件路径
+    :param output_file: 输出的JSON文件路径
+    """
+    try:
+        with open(input_file, 'r', encoding='utf-8') as f:
+            data = json.load(f)
+
+        transformed_data = [
+            {
+                "name": item["name"],
+                "synonymous": [],
+                "description": {
+                    "software_name": item["software_name"],
+                    "works_category": item["works_category"]
+                }
+            } for item in data
+        ]
+
+        with open(output_file, 'w', encoding='utf-8') as f:
+            json.dump(transformed_data, f, ensure_ascii=False, indent=2)
+
+        print(f"转换完成，结果已保存至 {output_file}")
+    except Exception as e:
+        print(f"转换失败: {e}")
+
+
+def extract_required_values(data, result=None):
+    """
+    递归查找 JSON 数据中所有包含 "_required" 的键，并返回对应的值。
+    :param data: 输入的 JSON 数据（字典或列表）
+    :param result: 结果列表（用于递归）
+    :return: 包含所有符合条件值的列表
+    """
+    if result is None:
+        result = []
+
+    if isinstance(data, dict):
+        for key, value in data.items():
+            if "name_required" in key:
+                result.append(value)
+            if isinstance(value, (dict, list)):
+                extract_required_values(value, result)
+    elif isinstance(data, list):
+        for item in data:
+            extract_required_values(item, result)
+
+    return result