import json

from flask_app.main.json_utils import clean_json_string
from flask_app.main.通义千问long import upload_file, qianwen_long

# def combine_technical_and_business(data, target_values1, target_values2):
#     extracted_data = {}  # 根级别存储所有数据
#     technical_found = False
#     business_found = False
#
#     def extract_nested(data, parent_key='', is_technical=False, is_business=False):
#         nonlocal technical_found, business_found
#         if isinstance(data, dict):
#             for key, value in data.items():
#                 current_key = f"{parent_key}.{key}" if parent_key else key
#
#                 # 检查是否为技术标的内容
#                 if any(target in key for target in target_values1):
#                     if not is_technical:
#                         # 直接存储在根级别
#                         extracted_data[key] = value
#                         technical_found = True
#                         # 标记为技术标内容并停止进一步处理这个分支
#                         continue
#
#                 # 检查是否为商务标的内容
#                 elif any(target in key for target in target_values2):
#                     if not is_business:
#                         # 存储在'商务标'分类下
#                         if '商务标' not in extracted_data:
#                             extracted_data['商务标'] = {}
#                         extracted_data['商务标'][key] = value
#                         business_found = True
#                         # 标记为商务标内容并停止进一步处理这个分支
#                         continue
#
#                 # 如果当前值是字典或列表，且不在技术或商务分类下，继续递归搜索
#                 if isinstance(value, dict) or isinstance(value, list):
#                     extract_nested(value, current_key, is_technical, is_business)
#
#         elif isinstance(data, list):
#             for index, item in enumerate(data):
#                 extract_nested(item, f"{parent_key}[{index}]", is_technical, is_business)
#
#     # 开始从顶级递归搜索
#     extract_nested(data)
#
#     # 处理未找到匹配的情况
#     if not technical_found:
#         extracted_data['技术标'] = ''
#     if not business_found:
#         extracted_data['商务标'] = ''
#
#     return extracted_data

def combine_technical_and_business(data, target_values):
  extracted_data = {}  # 根级别存储所有数据
  technical_found = False
  business_found = False

  def extract_nested(data, parent_key='', is_technical=False, is_business=False):
    nonlocal technical_found, business_found
    if isinstance(data, dict):
      for key, value in data.items():
        current_key = f"{parent_key}.{key}" if parent_key else key

        # 检查是否为技术标的内容
        if any(target in key for target in target_values):
          if not is_technical:
            extracted_data[key] = value
            technical_found = True
            continue

        # 默认其他所有内容都归为商务标
        else:
          if not is_business:
            if '商务评分' not in extracted_data:
              extracted_data['商务评分'] = {}
            extracted_data['商务评分'][key] = value
            business_found = True
            continue

        if isinstance(value, dict) or isinstance(value, list):
          extract_nested(value, current_key, is_technical, is_business)

    elif isinstance(data, list):
      for index, item in enumerate(data):
        extract_nested(item, f"{parent_key}[{index}]", is_technical, is_business)

  extract_nested(data)

  if not technical_found:
    extracted_data['技术评分'] = ''
  if not business_found:
    extracted_data['商务评分'] = ''

  return extracted_data
def combine_evaluation_standards(truncate2):
    # 商务标、技术标评分项：千问
    file_id = upload_file(truncate2)
    user_query_2 = (
        "根据该文档中的评标办法前附表，请你列出该文件的技术评分，商务评分，投标报价评审标准以及它们对应的具体评分要求，若对应内容中存在其他信息，在键名如'技术评分'中新增子键名'备注'存放该信息。如果评分内容（因素）不是这3个，则返回文档中给定的评分内容（因素）以及它的评分要求。请以json格式返回结果，不要回答有关形式、资格、响应性评审标准的内容")
    evaluation_res = qianwen_long(file_id, user_query_2)
    target_values1 = ['技术标','技术部分','设计', '实施',"技术评分"]
    # target_values2=['投标报价','商务标','商务部分','报价部分','业绩','信誉','分值','计算公式','信用','人员','资格','奖项','认证','荣誉']
    # update_json=combine_technical_and_business(clean_json_string(evaluation_res),target_values1,target_values2)
    update_json = combine_technical_and_business(clean_json_string(evaluation_res), target_values1)
    # evaluation_combined_res = json.dumps(update_json,ensure_ascii=False,indent=4)
    # return evaluation_combined_res
    return update_json              #商务标技术标整合
if __name__ == "__main__":
    truncate2="C:\\Users\\Administrator\\Desktop\\fsdownload\d2a70f3d-5648-4971-9c1f-87d877285304\\ztbfile_evaluation_method.pdf"
    evaluation_standards_res=combine_evaluation_standards(truncate2)
    # 从结果中提取"商务标"和"技术标"
    technical_standards = {"技术评分": evaluation_standards_res.get("技术评分", {})}
    commercial_standards = {"商务评分": evaluation_standards_res.get("商务评分", {})}
    # 返回技术标和商务标
    print(json.dumps(technical_standards,ensure_ascii=False,indent=4))
    print(json.dumps(commercial_standards, ensure_ascii=False, indent=4))