chachong/main1.py_改造qwen

# coding=utf-8
import sys
import re

import baidu
import model_scope
import mysql_pool
from pymysql.converters import escape_string
import cosin_similarity
import pandas as pd
import datetime
import requests
import glm_utils
from threading import Thread


wdys1 = {
    "项目名称": "xmmc",
    "现状问题": "xzwt",
    "系统基础": "xtjc",
    "项目目标": "xmmb",
    "预期绩效": "yqjx",
    "建设需求": "jsxq",
    "数据需求": "sjxq",
    "安全需求": "aqxq",
    "业务领域": "ywly",
    "核心业务": "hxyw",
    "业务需求": "ywxq",
    "业务协同": "ywxt",
    "建设层级": "jscj",
    "用户范围": "yhfw",
    "目标群体": "mbqt",
    "建设内容": "jsnr",
    "功能模块": "gnmk",
    "数据共享": "sjgx",
    "智能要素": "znys"
}
wdys2 = {
    "xmmc": "项目名称",
    "xzwt": "现状问题",
    "xtjc": "系统基础",
    "xmmb": "项目目标",
    "yqjx": "预期绩效",
    "jsxq": "建设需求",
    "sjxq": "数据需求",
    "aqxq": "安全需求",
    "ywly": "业务领域",
    "hxyw": "核心业务",
    "ywxq": "业务需求",
    "ywxt": "业务协同",
    "jscj": "建设层级",
    "yhfw": "用户范围",
    "mbqt": "目标群体",
    "jsnr": "建设内容",
    "gnmk": "功能模块",
    "sjgx": "数据共享",
    "znys": "智能要素"
}
gnmkys = {
    "gnmc": "功能名称",
    "gnms": "功能描述"
}


def getFlag():
    data_dict = {}
    df = pd.read_excel("0825.xlsx")
    data = df.values
    data = list(pd.Series(data[:, 1]).dropna())
    for d in data:
        try:
            wd = re.search("(.*?)（.*?%）", d).group(1).strip()
            wdc = wdys1.get(wd)
            if wdc:
                qz = re.search(".*?（(.*?%)）", d).group(1)
                data_dict[wdc] = qz
        except:
            pass
    return data_dict


def gong_neng_mo_kuai(mysql, dl, data, er_title, str_dict_new):
    nlp = model_scope.Bert_nlp("corom")
    # 将excel文件中的所有第三维度内容进行拼接
    str_dict = {}
    for et in er_title:
        for d in data:
            if d[1] == et:
                if str_dict.get(et):
                    str_dict[et] = str_dict.get(et) + d[3]
                else:
                    str_dict[et] = d[3]

    for k, v in str_dict.items():
        mysql.sql_change_msg(
            """insert into idc_project_module (project_id, check_duplicate_count, module_name, module_content, create_time, update_time, tag) value(%d, 1, "%s", "%s", "%s", "%s", "模块")""" % (
                int(dl[0]), k, v, str(datetime.datetime.now())[:-7], str(datetime.datetime.now())[:-7]))

    module_id_list = mysql.sql_select_many(
        """select project_module_id, module_name, module_content  from idc_project_module where project_id=%d""" % dl[
            0])
    data_list = []
    for mil in module_id_list:
        data_dict = {}
        data_dict["project_module_id"] = mil.get("project_module_id")
        data_dict["gnmc"] = mil.get("module_name")
        data_dict["gnms"] = mil.get("module_content")
        data_list.append(data_dict)
    for i in data_list:
        # where xmmc = '南浔区信息化项目全生命周期管理系统'
        gnmk_copy1 = mysql.sql_select_many("""select * from user_history_module_data """)
        if gnmk_copy1:
            # desc_info_list = []
            # for gc in gnmk_copy1:
            #     if gc.get("xmmc") != dl[2]:
            #         desc_info_list.append(gc.get("gnms"))
            # similarity, s1, s2, idx = nlp.main(i.get("gnms"), desc_info_list)
            # if idx == -1:
            #     continue

            for gc in gnmk_copy1:
                desc = glm_utils.qwenResult(i.get("gnms"), gc.get("gnms"))
                similarity_result, count = similarity_result_check(desc)
                similarity = count
                mysql.sql_change_msg(
                    """insert into idc_project_module_check (project_module_id, module_name, project_name, company_name, create_time, update_time, similarity_result) value(%d, "%s", "%s", "%s", "%s", "%s", "%s")"""
                    % (
                        i.get("project_module_id"), escape_string(gc.get("gnmc")), escape_string(gc.get("xmmc")), "",
                        str(datetime.datetime.now())[:-7],
                        str(datetime.datetime.now())[:-7], similarity_result))
                dup_module_id = mysql.cur.lastrowid
                check_module_info(mysql, gc, dl, i, dup_module_id, similarity)


def check_module_info(mysql, gc, dl, pro, dup_module_id, score):
    total_similarity1 = 0
    total_similarity2 = 0
    for j in ["gnmc", "gnms"]:
        # 循环遍历每一个模块名称
        content_x = gc.get(j)
        content_y = pro.get(j)
        if content_x and content_y:
            if j == "gnmc":
                # print("功能名称对比")
                similarity, check_desc = glm_utils.AutoDLResult(f"""请帮我分析以下两段重复语句重复的地方: \n第一段话是:'{content_y}', \n ----------------- \n 第二段话是:'{content_x}'""")
                # # 相似度相加
                if similarity is None:
                    similarity = 0
                print(f"similarity is {similarity}")
                total_similarity1 += similarity/100
                mysql.sql_change_msg(
                    """insert into idc_project_module_check_detail (dup_module_id, project_name, module_content, dup_module_content, similarity, dimension, create_time, update_time, check_desc) value (%d, "%s", "%s", "%s", %f, "%s", "%s", "%s", "%s")"""
                    % (dup_module_id, dl[2], escape_string(content_y), escape_string(content_x), similarity,
                       "功能名称",
                       str(datetime.datetime.now())[:-7], str(datetime.datetime.now())[:-7], escape_string(check_desc)))
            else:
                check_desc = glm_utils.AutoDLResultNoNum(f"""请帮我分析以下两段重复语句重复的地方: \n第一段话是:'{content_y}', \n ----------------- \n 第二段话是:'{content_x}'""")
                similarity = score
                # 相似度相加 gnms
                total_similarity2 += similarity
                module_content = pro.get("gnms")
                dup_module_content = gc.get("gnms")
                mysql.sql_change_msg(
                    """insert into idc_project_module_check_detail (dup_module_id, project_name, module_content, dup_module_content, similarity, dimension, create_time, update_time, check_desc) value (%d, "%s", "%s", "%s", %f, "%s", "%s", "%s", "%s")"""
                    % (dup_module_id, dl[2], escape_string(module_content), escape_string(dup_module_content),
                       similarity,
                       "功能模块描述",
                       str(datetime.datetime.now())[:-7], str(datetime.datetime.now())[:-7],
                       escape_string(check_desc)))

    mysql.sql_change_msg("""update idc_project_module_check set similarity=%f where dup_module_id=%d""" % (
        total_similarity1 + total_similarity2, dup_module_id))


def project_check(data_list):
    mysql = mysql_pool.ConnMysql()
    # mysql.sql_select_many("""select * from mkgjc""")
    # 读取历史数据
    xmnr_count = len(mysql.sql_select_many("""select * from user_history_data"""))
    gnmk_count = len(mysql.sql_select_many("""select * from user_history_module_data"""))

    nlp = model_scope.Bert_nlp("corom")

    # 遍历excel存储路径
    for dl in data_list:
        # path = "0825-丽水系统查重维度1.xlsx"
        # 读取路径下的excel
        print(dl,dl[1])
        df = pd.read_excel(dl[1])
        data = df.values
        # 将excel文件中的所有维度内容进行拼接
        join_str = ""
        str_dict = {}
        gnmk_str = []
        title = ""
        er_title = set()
        for d in data:
            # if pd.notnull(d[0]):
            #     title = d[0]
            #     if title == "功能模块":
            #         er_title.add(d[1])
            #     join_str = ""
            #     for i in d[1:]:
            #         if pd.notnull(i):
            #             join_str += str(i)
            #     str_dict[wdys1.get(title)] = join_str
            if pd.notnull(d[0]):
                title = d[0]
                if title == "功能模块":
                    er_title.add(d[1])
                join_str = ""
                for i in d[1:]:
                    if pd.notnull(i):
                        join_str += str(i)
                        if title == "功能模块":
                            if i == '功能描述':
                                continue
                            else:
                                gnmk_str.append(i)
                str_dict[wdys1.get(title)] = join_str
            else:
                if title == "功能模块":
                    er_title.add(d[1])
                for i in d[1:]:
                    if pd.notnull(i):
                        join_str += str(i)
                str_dict[wdys1.get(title)] = str_dict.get(wdys1.get(title)) + join_str
        # print(str_dict)
        gnmk = ",".join(gnmk_str)
        str_dict['gnmk'] = gnmk
        mysql.sql_change_msg(
            """insert into user_data (xmmc, xzwt, xtjc, xmmb, yqjx, jsxq, sjxq, aqxq, ywly, hxyw, ywxq, ywxt, jscj, yhfw, mbqt, jsnr, gnmk, sjgx, znys) value ("%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s")"""
            % (dl[0], str_dict.get("xzwt") if str_dict.get("xzwt") else None,
               str_dict.get("xtjc") if str_dict.get("xtjc") else None,
               str_dict.get("xmmb") if str_dict.get("xmmb") else None,
               str_dict.get("yqjx") if str_dict.get("yqjx") else None,
               str_dict.get("jsxq") if str_dict.get("jsxq") else None,
               str_dict.get("sjxq") if str_dict.get("sjxq") else None,
               str_dict.get("aqxq") if str_dict.get("aqxq") else None,
               str_dict.get("ywly") if str_dict.get("ywly") else None,
               str_dict.get("hxyw") if str_dict.get("hxyw") else None,
               str_dict.get("ywxq") if str_dict.get("ywxq") else None,
               str_dict.get("ywxt") if str_dict.get("ywxt") else None,
               str_dict.get("jscj") if str_dict.get("jscj") else None,
               str_dict.get("yhfw") if str_dict.get("yhfw") else None,
               str_dict.get("mbqt") if str_dict.get("mbqt") else None,
               str_dict.get("jsnr") if str_dict.get("jsnr") else None,
               str_dict.get("gnmk") if str_dict.get("gnmk") else None,
               str_dict.get("sjgx") if str_dict.get("sjgx") else None,
               str_dict.get("znys") if str_dict.get("znys") else None))
        # 或取所有的xmnr_copy1   where xmmc = '南浔区信息化项目全生命周期管理系统'
        xmnr_copy1 = mysql.sql_select_many("""select * from user_history_data where xmmc = '富阳未来社区（乡村）一体化数智平台' """)
        # 对比xmnr_copy1和xmnr维度是否都有
        if xmnr_copy1:
            # threads = [Thread(target=check_project_info, args=(mysql, dl, xc, str_dict)) for xc in xmnr_copy1]
            # for t in threads:
            #     t.start()
            #
            # for t in threads:
            #     t.join()
            # pro_ths = []
            # for xc in xmnr_copy1:
            #     # check_project_info(mysql, dl, xc, str_dict)
            #     p = Thread(target=check_project_info, args=(mysql, dl, xc, str_dict))
            #     pro_ths.append(p)
            #     p.start()
            # for p in pro_ths:
            #     p.join()
            xmnr_copy1_new = []
            for xc in xmnr_copy1:
                if xc["xmmc"] == str_dict.get("xmmc"):
                    continue
                check_project_info(mysql, dl, xc, str_dict, nlp)

            # 找出相识对最高的项目通过glm分析


        mysql.sql_change_msg(
            """update idc_project set dup_status=3, one_vote_veto_status=1, self_check_status=1, history_project_count=%d ,module_count=%d where project_id=%d""" % (
                xmnr_count, gnmk_count, dl[0]))
        gong_neng_mo_kuai(mysql, dl, data, er_title, str_dict)


def check_project_info(mysql, dl, xc, str_dict, nlp):
    total_keywords = {}
    total_similarity = 0
    dup_count = 0
    # 保存相加后的相似度到idc_project_check
    mysql.sql_change_msg(
        """insert into idc_project_check (project_id, dup_project_name, file_path, company_name, create_year, project_tag, project_range_tag, project_area, create_time, update_time) value ("%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s")"""
        % (dl[0], escape_string(xc.get("xmmc")), escape_string(dl[1]), "", "", "需求相似、业务相似", "历史项目", "",
           str(datetime.datetime.now())[:-7], str(datetime.datetime.now())[:-7]))
    dup_id = mysql.cur.lastrowid
    for x in list(xc.keys())[1:]:
        content_x = xc.get(x)
        content_y = str_dict.get(x)
        if content_x and content_y:
            if x == 'gnmk':
                continue
            elif x == 'jsnr':
                continue
            else:
                dup_count += 1
    if ((xc['gnmk'] == 'None' or xc['gnmk'] is None or str.strip(xc['gnmk']) == '') and (str_dict['gnmk'] is None or str.strip(str_dict['gnmk']) == '')) and (
            not xc['jsnr'] is None and xc['jsnr'] != 'None' and not str_dict['jsnr'] is None and len(str.strip(str_dict['jsnr'])) > 0):
        for x in list(xc.keys())[1:]:
            content_x = xc.get(x)
            content_y = str_dict.get(x)
            if content_x and content_y:
                if x == 'gnmk':
                    # 循环遍历每一个维度
                    # contents_y = []
                    # contents_y.append(content_y)
                    # similarity, content1, content2, idx = nlp.main(content_x, contents_y)

                    desc = glm_utils.qwenResult(content_y, content_x)
                    similarity_result, count = similarity_result_check(desc)
                    similarity = count * 0
                    # print("**************相似度: %.2f%%" % similarity, "关键词: %s" % keywords_y)
                    # 相似度相加
                    total_similarity += similarity
                    function_content = content_y
                    dup_function_content = content_x
                    # 保存每个维度对应的相似度到idc_project_check_detail
                    mysql.sql_change_msg(
                        """insert into idc_project_check_detail (dup_id, dimension, similarity, function_content, dup_function_content, create_time, update_time, similarity_result) value (%d, "%s", %f, "%s", "%s", "%s", "%s", "%s")"""
                        % (dup_id, wdys2.get(x), similarity, escape_string(function_content),
                           escape_string(dup_function_content), str(datetime.datetime.now())[:-7],
                           str(datetime.datetime.now())[:-7], similarity_result))
                elif x == 'jsnr':
                    # 循环遍历每一个维度
                    # contents_y = []
                    # contents_y.append(content_y)
                    # similarity, content1, content2, idx = nlp.main(content_x, contents_y)

                    desc = glm_utils.qwenResult(content_y, content_x)
                    similarity_result, count = similarity_result_check(desc)
                    similarity = count * 40
                    # print("**************相似度: %.2f%%" % similarity, "关键词: %s" % keywords_y)
                    # 相似度相加
                    total_similarity += similarity

                    function_content = content_y
                    dup_function_content = content_x
                    # 保存每个维度对应的相似度到idc_project_check_detail
                    mysql.sql_change_msg(
                        """insert into idc_project_check_detail (dup_id, dimension, similarity, function_content, dup_function_content, create_time, update_time, similarity_result) value (%d, "%s", %f, "%s", "%s", "%s", "%s", "%s")"""
                        % (dup_id, wdys2.get(x), similarity, escape_string(function_content),
                           escape_string(dup_function_content), str(datetime.datetime.now())[:-7],
                           str(datetime.datetime.now())[:-7], similarity_result))
                else:
                    # 循环遍历每一个维度
                    # contents_y = []
                    # contents_y.append(content_y)
                    # similarity, content1, content2, idx = nlp.main(content_x, contents_y)

                    desc = glm_utils.qwenResult(content_y, content_x)
                    similarity_result, count = similarity_result_check(desc)
                    similarity = count * (60 / dup_count)
                    # print("**************相似度: %.2f%%" % similarity, "关键词: %s" % keywords_y)
                    # 相似度相加
                    total_similarity += similarity

                    function_content = content_y
                    dup_function_content = content_x

                    # 保存每个维度对应的相似度到idc_project_check_detail
                    mysql.sql_change_msg(
                        """insert into idc_project_check_detail (dup_id, dimension, similarity, function_content, dup_function_content, create_time, update_time, similarity_result) value (%d, "%s", %f, "%s", "%s", "%s", "%s", "%s")"""
                        % (dup_id, wdys2.get(x), similarity, escape_string(function_content),
                           escape_string(dup_function_content), str(datetime.datetime.now())[:-7],
                           str(datetime.datetime.now())[:-7], similarity_result))
    elif ((xc['jsnr'] == 'None' or xc['jsnr'] is None or str.strip(xc['jsnr']) == '') and (str_dict['jsnr'] is None or str.strip(str_dict['jsnr']) == '')) and (
            not xc['gnmk'] is None and xc['gnmk'] != 'None' and not str_dict['gnmk'] is None and len(str.strip(str_dict['gnmk'])) > 0):
        for x in list(xc.keys())[1:]:
            content_x = xc.get(x)
            content_y = str_dict.get(x)
            if content_x and content_y:
                if x == 'gnmk':
                    # 循环遍历每一个维度
                    # contents_y = []
                    # contents_y.append(content_y)
                    # similarity, content1, content2, idx = nlp.main(content_x, contents_y)

                    desc = glm_utils.qwenResult(content_y, content_x)
                    similarity_result, count = similarity_result_check(desc)

                    similarity = count * 50
                    # print("**************相似度: %.2f%%" % similarity, "关键词: %s" % keywords_y)
                    # 相似度相加
                    total_similarity += similarity

                    function_content = content_y
                    dup_function_content = content_x
                    # 保存每个维度对应的相似度到idc_project_check_detail
                    mysql.sql_change_msg(
                        """insert into idc_project_check_detail (dup_id, dimension, similarity, function_content, dup_function_content, create_time, update_time, similarity_result) value (%d, "%s", %f, "%s", "%s", "%s", "%s", "%s")"""
                        % (dup_id, wdys2.get(x), similarity, escape_string(function_content),
                           escape_string(dup_function_content), str(datetime.datetime.now())[:-7],
                           str(datetime.datetime.now())[:-7], similarity_result))
                elif x == 'jsnr':
                    # 循环遍历每一个维度
                    # contents_y = []
                    # contents_y.append(content_y)
                    # similarity, content1, content2, idx = nlp.main(content_x, contents_y)

                    desc = glm_utils.qwenResult(content_y, content_x)
                    similarity_result, count = similarity_result_check(desc)

                    similarity = count * 0
                    # print("**************相似度: %.2f%%" % similarity, "关键词: %s" % keywords_y)
                    # 相似度相加
                    total_similarity += similarity

                    function_content = content_y
                    dup_function_content = content_x
                    # 保存每个维度对应的相似度到idc_project_check_detail
                    mysql.sql_change_msg(
                        """insert into idc_project_check_detail (dup_id, dimension, similarity, function_content, dup_function_content, create_time, update_time, similarity_result) value (%d, "%s", %f, "%s", "%s", "%s", "%s", "%s")"""
                        % (dup_id, wdys2.get(x), similarity, escape_string(function_content),
                           escape_string(dup_function_content), str(datetime.datetime.now())[:-7],
                           str(datetime.datetime.now())[:-7], similarity_result))
                else:
                    # 循环遍历每一个维度
                    # contents_y = []
                    # contents_y.append(content_y)
                    # similarity, content1, content2, idx = nlp.main(content_x, contents_y)

                    desc = glm_utils.qwenResult(content_y, content_x)
                    similarity_result, count = similarity_result_check(desc)

                    similarity = count * (50 / dup_count)
                    # print("**************相似度: %.2f%%" % similarity, "关键词: %s" % keywords_y)
                    # 相似度相加
                    total_similarity += similarity

                    function_content = content_y
                    dup_function_content = content_x
                    # 保存每个维度对应的相似度到idc_project_check_detail
                    mysql.sql_change_msg(
                        """insert into idc_project_check_detail (dup_id, dimension, similarity, function_content, dup_function_content, create_time, update_time, similarity_result) value (%d, "%s", %f, "%s", "%s", "%s", "%s", "%s")"""
                        % (dup_id, wdys2.get(x), similarity, escape_string(function_content),
                           escape_string(dup_function_content), str(datetime.datetime.now())[:-7],
                           str(datetime.datetime.now())[:-7], similarity_result))
    else:
        for x in list(xc.keys())[1:]:
            content_x = xc.get(x)
            content_y = str_dict.get(x)
            if content_x and content_y:
                if x == 'gnmk':
                    # 循环遍历每一个维度
                    # contents_y = []
                    # contents_y.append(content_y)
                    # similarity, content1, content2, idx = nlp.main(content_x, contents_y)
                    desc = glm_utils.qwenResult(content_y, content_x)
                    similarity_result, count = similarity_result_check(desc)

                    similarity = count * 50

                    # 相似度相加
                    total_similarity += similarity

                    function_content = content_y
                    dup_function_content = content_x
                    # 保存每个维度对应的相似度到idc_project_check_detail
                    mysql.sql_change_msg(
                        """insert into idc_project_check_detail (dup_id, dimension, similarity, function_content, dup_function_content, create_time, update_time, similarity_result) value (%d, "%s", %f, "%s", "%s", "%s", "%s", "%s")"""
                        % (dup_id, wdys2.get(x), similarity, escape_string(function_content),
                           escape_string(dup_function_content), str(datetime.datetime.now())[:-7],
                           str(datetime.datetime.now())[:-7], similarity_result))
                elif x == 'jsnr':
                    # 循环遍历每一个维度
                    # contents_y = []
                    # contents_y.append(content_y)
                    # similarity, content1, content2, idx = nlp.main(content_x, contents_y)

                    desc = glm_utils.qwenResult(content_y, content_x)
                    similarity_result, count = similarity_result_check(desc)

                    similarity = count * 40
                    # 相似度相加
                    total_similarity += similarity

                    function_content = content_y
                    dup_function_content = content_x
                    # 保存每个维度对应的相似度到idc_project_check_detail
                    mysql.sql_change_msg(
                        """insert into idc_project_check_detail (dup_id, dimension, similarity, function_content, dup_function_content, create_time, update_time, similarity_result) value (%d, "%s", %f, "%s", "%s", "%s", "%s", "%s")"""
                        % (dup_id, wdys2.get(x), similarity, escape_string(function_content),
                           escape_string(dup_function_content), str(datetime.datetime.now())[:-7],
                           str(datetime.datetime.now())[:-7], similarity_result))
                else:
                    # 循环遍历每一个维度
                    # contents_y = []
                    # contents_y.append(content_y)
                    # similarity, content1, content2, idx = nlp.main(content_x, contents_y)

                    desc = glm_utils.qwenResult(content_y, content_x)
                    similarity_result, count = similarity_result_check(desc)

                    similarity = count * (10 / dup_count)
                    # print("**************相似度: %.2f%%" % similarity, "关键词: %s" % keywords_y)
                    # 相似度相加
                    total_similarity += similarity

                    function_content = content_y
                    dup_function_content = content_x
                    # 保存每个维度对应的相似度到idc_project_check_detail
                    mysql.sql_change_msg(
                        """insert into idc_project_check_detail (dup_id, dimension, similarity, function_content, dup_function_content, create_time, update_time, similarity_result) value (%d, "%s", %f, "%s", "%s", "%s", "%s", "%s")"""
                        % (dup_id, wdys2.get(x), similarity, escape_string(function_content),
                           escape_string(dup_function_content), str(datetime.datetime.now())[:-7],
                           str(datetime.datetime.now())[:-7], similarity_result))

    mysql.sql_change_msg(
        """update idc_project_check set similarity=%f where dup_id=%d""" % (total_similarity, dup_id))


if __name__ == "__main__":
    all_path = requests.get("http://127.0.0.1:19099/check/duplicates/%s" % 599).json()
    # print(all_path)

    # dict1 = {k:v for k, v in sorted(dict.items(), key= lambda item : item[1])}
    # print(dict1)

    data_list = []
    for ap in all_path.get("data"):
        # if os.path.exists(ap.get("file_path")):
            data_list.append((ap.get("project_id"), ap.get("file_path"), ap.get("project_name")))
    print(data_list)
    # data_list = [(11, r"C:\Users\HUAWEI\PycharmProjects\nlp\dup_check\0825-丽水系统查重维度1.xlsx", "水路运输综合监管系统建设项目.xls")]
    data_list = [(11, r"D:\ningda\dup_check2\dup_check\0825-丽水系统查重维度1.xlsx", "水路运输综合监管系统建设项目.xls")]
    project_check(data_list)


# 对比相似度
def similarity_result_check(desc):
    similarity_result = ""
    similarity_result_count = 0
    if len(desc) > 7:
        if desc[6:7] == "高":
            similarity_result = "非常相似"
            similarity_result_count = 90
        elif desc[6:7] == "中":
            similarity_result = "比较相似"
            similarity_result_count = 60
        elif desc[6:7] == "低":
            similarity_result = "相似度低"
            similarity_result_count = 30
    return similarity_result, similarity_result_count