119 lines
5.7 KiB
Python
119 lines
5.7 KiB
Python
import json
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from flask_app.main.json_utils import clean_json_string
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from flask_app.main.通义千问long import upload_file, qianwen_long
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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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#
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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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#
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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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#
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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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#
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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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#
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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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#
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# # 开始从顶级递归搜索
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# extract_nested(data)
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#
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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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#
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# return extracted_data
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def combine_technical_and_business(data, target_values):
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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_values):
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if not is_technical:
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extracted_data[key] = value
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technical_found = True
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continue
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# 默认其他所有内容都归为商务标
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else:
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if not is_business:
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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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continue
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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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extract_nested(data)
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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 combine_evaluation_standards(truncate2):
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# 商务标、技术标评分项：千问
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file_id = upload_file(truncate2)
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user_query_2 = (
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"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_2)
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target_values1 = ['技术标','技术部分','设计', '实施']
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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','资格','奖项','认证','荣誉']
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# update_json=combine_technical_and_business(clean_json_string(evaluation_res),target_values1,target_values2)
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update_json = combine_technical_and_business(clean_json_string(evaluation_res), target_values1)
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# evaluation_combined_res = json.dumps(update_json,ensure_ascii=False,indent=4)
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# return evaluation_combined_res
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return update_json #商务标技术标整合
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if __name__ == "__main__":
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truncate2="C:\\Users\\Administrator\\Desktop\\fsdownload\\0883895c-e61f-4a99-9308-697fca1d4b77\\ztbfile_evaluation_method.pdf"
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evaluation_standards_res=combine_evaluation_standards(truncate2)
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# 从结果中提取"商务标"和"技术标"
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technical_standards = {"技术标": evaluation_standards_res.get("技术标", {})}
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commercial_standards = {"商务标": evaluation_standards_res.get("商务标", {})}
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# 返回技术标和商务标
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print(json.dumps(technical_standards,ensure_ascii=False,indent=4))
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print(json.dumps(commercial_standards, ensure_ascii=False, indent=4)) |