81 lines
4.7 KiB
Python
81 lines
4.7 KiB
Python
# -*- encoding:utf-8 -*-
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import json
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import threading
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import time
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import concurrent.futures
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from flask_app.general.json_utils import clean_json_string, add_outer_key
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from flask_app.general.通用功能函数 import process_judge_questions, aggregate_basic_info
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from flask_app.general.llm.多线程提问 import read_questions_from_file, multi_threading
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from flask_app.general.llm.通义千问long import upload_file
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from flask_app.old_version.判断是否分包等_old import merge_json_to_list
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from flask_app.general.投标人须知正文提取指定内容 import extract_from_notice
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from flask_app.货物标.提取采购需求main import fetch_procurement_reqs
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def get_base_info(merged_baseinfo_path,clause_path,invalid_path):
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file_id = upload_file(merged_baseinfo_path)
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baseinfo_file_path='flask_app/static/提示词/基本信息货物标.txt'
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# baseinfo_file_path = r'D:\flask_project\flask_app\static\提示词\基本信息货物标.txt'
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questions = read_questions_from_file(baseinfo_file_path)
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baseinfo_results = multi_threading(questions, "", file_id, 2) # 1代表使用百炼rag 2代表使用qianwen-long
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baseinfo_list = [clean_json_string(res) for _, res in baseinfo_results] if baseinfo_results else []
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chosen_numbers, merged = merge_json_to_list(baseinfo_list.pop()) #取出并处理最后一个回答 '是否xxx'
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baseinfo_list.append(merged)
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judge_file_path = 'flask_app/static/提示词/是否相关问题.txt'
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# judge_file_path =r'D:\flask_project\flask_app\static\提示词\是否相关问题.txt'
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with concurrent.futures.ThreadPoolExecutor(max_workers=2) as executor:
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# 提交两个任务
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future1 = executor.submit(process_judge_questions, judge_file_path, chosen_numbers, invalid_path,baseinfo_list)
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future2 = executor.submit(extract_from_notice, merged_baseinfo_path, clause_path, 3) #重新招标
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# 等待两个任务完成并获取结果
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future1.result() # process_judge_questions 直接修改 baseinfo_list，不需要返回值
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rebidding_situation = future2.result()
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update_json = add_outer_key(rebidding_situation, "重新招标、不再招标和终止招标")
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baseinfo_list.append(update_json)
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return baseinfo_list
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def combine_basic_info(merged_baseinfo_path, procurement_path,clause_path,invalid_path):
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baseinfo_list = []
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temp_list = []
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procurement_reqs = {}
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# 定义一个线程函数来获取基础信息
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def get_base_info_thread(): #传统的基础信息提取
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nonlocal temp_list
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temp_list = get_base_info(merged_baseinfo_path,clause_path,invalid_path)
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# 定义一个线程函数来获取采购需求
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def fetch_procurement_reqs_thread(): #采购要求提取
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nonlocal procurement_reqs
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procurement_reqs = fetch_procurement_reqs(procurement_path,invalid_path)
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# 创建并启动获取基础信息的线程
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thread1 = threading.Thread(target=get_base_info_thread)
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thread1.start()
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# 等待一秒后启动获取采购需求的线程
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time.sleep(1)
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thread2 = threading.Thread(target=fetch_procurement_reqs_thread)
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thread2.start()
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# 等待两个线程都完成
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thread1.join()
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thread2.join()
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# 合并结果
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baseinfo_list += temp_list # temp_list 是一个列表
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baseinfo_list.append(procurement_reqs) # procurement_reqs 是一个字典
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aggregated_baseinfo = aggregate_basic_info(baseinfo_list,'goods') #重新组织基础信息结构
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return {"基础信息": aggregated_baseinfo}
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if __name__ == "__main__":
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start_time=time.time()
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# baseinfo_file_path = "C:\\Users\\Administrator\\Desktop\\货物标\\truncate_all\\ztbfile_merged_baseinfo\\ztbfile_merged_baseinfo_3-31.pdf"
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merged_baseinfo_path=r"D:\flask_project\flask_app\static\output\output1\ecd3374a-a19e-475e-a4dd-e803a3bc1fbf\ztbfile_merged_baseinfo.pdf"
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# procurement_file_path = "C:\\Users\\Administrator\\Desktop\\fsdownload\\b4601ea1-f087-4fa2-88ae-336ad4d8e1e9\\tmp\\ztbfile_procurement.pdf"
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clause_path=r'D:\flask_project\flask_app\static\output\output1\ecd3374a-a19e-475e-a4dd-e803a3bc1fbf\clause1.json'
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invalid_path=r"D:\flask_project\flask_app\static\output\output1\ecd3374a-a19e-475e-a4dd-e803a3bc1fbf\ztbfile.docx"
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procurement_path=r'D:\flask_project\flask_app\static\output\output1\ecd3374a-a19e-475e-a4dd-e803a3bc1fbf\ztbfile_procurement.pdf'
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# res = combine_basic_info(merged_baseinfo_path, procurement_file_path,clause_path)
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res=combine_basic_info(merged_baseinfo_path,procurement_path,clause_path,invalid_path)
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print("------------------------------------")
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print(json.dumps(res, ensure_ascii=False, indent=4))
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end_time=time.time()
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print("elasped time:"+str(end_time-start_time))
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