143 lines
7.3 KiB
Python
143 lines
7.3 KiB
Python
# -*- encoding:utf-8 -*-
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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 remove_unknown_scores(data):
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if isinstance(data, dict):
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return {
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k: remove_unknown_scores(v)
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for k, v in data.items()
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if not (k == "评分" and v in ["未知", "/", ""])
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}
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elif isinstance(data, list):
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return [remove_unknown_scores(item) for item in data]
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else:
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return data
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def combine_technical_and_business(data, target_values):
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data=remove_unknown_scores(data)
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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 '商务评分' not in extracted_data:
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extracted_data['商务评分'] = {}
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extracted_data['商务评分'][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['技术评分'] = ''
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if not business_found:
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extracted_data['商务评分'] = ''
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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")
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user_query_2 = (
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"""
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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，请以json格式返回结果，请在这三大块评分中分别用若干键值对表示具体要求，其内层的键名为'评分'及'要求'，若这三大块评分中存在其他信息，则在相应评分大块中新增键名'备注'存放该信息，键值为具体的要求，否则不需要。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）以及它们的具体评分要求。不要回答有关形式、资格、响应性评审标准的内容，若存在未知信息，填充'未知'。以下为示例输出：
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"技术评分": {
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"主要监理岗位的职责": {
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"评分": "4分",
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"要求": "1、总监理工程师的职责全面、清晰、合理得 1.2-2分；一般的1.2分。2、其他主要监理人员及岗位的职责全面、清晰、合理得 1.2-2分；一般的 1.2分。"
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}
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}
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"""
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)
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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',"技术评分"]
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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\\招标文件\\招标test文件夹\\zbtest1_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 = {"技术评分": evaluation_standards_res.get("技术评分", {})}
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commercial_standards = {"商务评分": evaluation_standards_res.get("商务评分", {})}
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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)) |