131 lines
6.2 KiB
Python
131 lines
6.2 KiB
Python
import json
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from flask_app.main.通义千问long import upload_file, qianwen_long
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from flask_app.main.json_utils import clean_json_string
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def combine_technical_and_business(data, target_values1, target_values2):
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extracted_data = {} # 根级别存储所有数据
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technical_found = False
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business_found = False
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def extract_nested(data, parent_key='', is_technical=False, is_business=False):
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nonlocal technical_found, business_found
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if isinstance(data, dict):
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for key, value in data.items():
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current_key = f"{parent_key}.{key}" if parent_key else key
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# 检查是否为技术标的内容
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if any(target in key for target in target_values1): #模糊匹配
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if not is_technical:
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# 直接存储在根级别
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extracted_data[key] = value
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technical_found = True
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# 标记为技术标内容并停止进一步处理这个分支
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continue
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# 检查是否为商务标的内容
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elif any(target in key for target in target_values2):
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if not is_business:
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# 存储在'商务标'分类下
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if '商务标' not in extracted_data:
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extracted_data['商务标'] = {}
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extracted_data['商务标'][key] = value
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business_found = True
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# 标记为商务标内容并停止进一步处理这个分支
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continue
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# 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
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if isinstance(value, dict) or isinstance(value, list):
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extract_nested(value, current_key, is_technical, is_business)
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elif isinstance(data, list):
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for index, item in enumerate(data):
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extract_nested(item, f"{parent_key}[{index}]", is_technical, is_business)
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# 开始从顶级递归搜索
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extract_nested(data)
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# 处理未找到匹配的情况
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if not technical_found:
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extracted_data['技术标'] = ''
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if not business_found:
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extracted_data['商务标'] = ''
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return extracted_data
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def get_evaluation_standards(truncate_file):
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file_id = upload_file(truncate_file)
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user_query = "根据该文档中的评标办法前附表，请你列出该文件的技术标，商务标，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'技术标'中新增子键名'备注'存放该信息。如果评分内容不是这3个，则返回文档中给定的评分内容以及它的评分要求，都以json的格式返回结果。请不要回答有关形式、资格、响应性评审标准的内容"
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evaluation_res = qianwen_long(file_id, user_query)
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cleaned_evaluation_res = clean_json_string(evaluation_res)
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include = ['一包', '二包', '三包', '四包', '五包']
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target_values1 = ['技术标', '技术部分', '设计', '实施', '方案']
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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',
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'资格', '奖项', '认证', '荣誉']
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updated_jsons = {}
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for key in cleaned_evaluation_res.keys():
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if any(item in key for item in include):
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inner_dict = cleaned_evaluation_res[key]
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# 将处理后的结果存储到updated_jsons中，每个包名为键
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updated_jsons[key] = combine_technical_and_business(inner_dict, target_values1, target_values2)
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# 将updated_jsons转换为JSON格式
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evaluation_combined_res = json.dumps(updated_jsons, ensure_ascii=False, indent=4)
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return evaluation_combined_res
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def combine_technical_and_business(data, target_values1, target_values2):
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extracted_data = {} # 根级别存储所有数据
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technical_found = False
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business_found = False
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def extract_nested(data, parent_key='', is_technical=False, is_business=False):
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nonlocal technical_found, business_found
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if isinstance(data, dict):
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for key, value in data.items():
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current_key = f"{parent_key}.{key}" if parent_key else key
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# 检查是否为技术标的内容
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if any(target in key for target in target_values1):
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if not is_technical:
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# 直接存储在根级别
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extracted_data[key] = value
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technical_found = True
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# 标记为技术标内容并停止进一步处理这个分支
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continue
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# 检查是否为商务标的内容
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elif any(target in key for target in target_values2):
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if not is_business:
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# 存储在'商务标'分类下
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if '商务标' not in extracted_data:
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extracted_data['商务标'] = {}
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extracted_data['商务标'][key] = value
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business_found = True
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# 标记为商务标内容并停止进一步处理这个分支
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continue
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# 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
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if isinstance(value, dict) or isinstance(value, list):
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extract_nested(value, current_key, is_technical, is_business)
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elif isinstance(data, list):
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for index, item in enumerate(data):
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extract_nested(item, f"{parent_key}[{index}]", is_technical, is_business)
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# 开始从顶级递归搜索
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extract_nested(data)
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# 处理未找到匹配的情况
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if not technical_found:
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extracted_data['技术标'] = ''
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if not business_found:
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extracted_data['商务标'] = ''
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return extracted_data
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if __name__ == "__main__":
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truncate_file="C:\\Users\\Administrator\\Desktop\\货物标\\output2\\招标文件(107国道)_evaluation_method.pdf"
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res=get_evaluation_standards(truncate_file)
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cleaned_res=clean_json_string(res).get("") |