# -*- coding:utf-8 -*-
import time
from docx import  Document
from paddlenlp import Taskflow
from qwen_agent.agents import Assistant
import re
import json_repair
import math
from docx.opc.pkgreader import _SerializedRelationships, _SerializedRelationship
from docx.opc.oxml import parse_xml


def load_from_xml_v2(baseURI, rels_item_xml):
    """
    Return |_SerializedRelationships| instance loaded with the
    relationships contained in *rels_item_xml*. Returns an empty
    collection if *rels_item_xml* is |None|.
    """
    srels = _SerializedRelationships()
    if rels_item_xml is not None:
        rels_elm = parse_xml(rels_item_xml)
        for rel_elm in rels_elm.Relationship_lst:
            if rel_elm.target_ref in ('../NULL', 'NULL'):
                continue
            srels._srels.append(_SerializedRelationship(baseURI, rel_elm))
    return srels


_SerializedRelationships.load_from_xml = load_from_xml_v2


import logging
import logging.config

log_config = {
    'version': 1,
    'disable_existing_loggers': False,
    'formatters': {
        'standard': {
            'format': '%(asctime)s - %(name)s - %(levelname)s - %(message)s',
        },
    },
    'handlers': {
        'console': {
            'class': 'logging.StreamHandler',
            'formatter': 'standard',
            'level': logging.INFO,
        },
        'file': {
            'class': 'logging.FileHandler',
            'filename': 'Logger.log',
            'formatter': 'standard',
            'level': logging.INFO,
        },
    },
    'loggers': {
        '': {
            'handlers': ['console', 'file'],
            'level': logging.INFO,
            'propagate': True,
        },
    }
}

logging.config.dictConfig(log_config)

logger = logging.getLogger("checkCompanyName")
prompt = '''
.根据上述文本判断，是否为具体的公司或组织名称，你可以使用工具利用互联网查询，
你只能在[具体的公司或组织名称,公益组织,简称,统称,泛化组织,政府单位,机关单位,学校，行业类型，其他]选项中选择答案,
回答格式[{“companyName”：“名称”,"回答":"答案"}，{“companyName”：“名称”,"回答":"答案"}]，不做过多的解释,严格按回答格式作答;
'''
llm_cfg = {
    #'model': 'qwen1.5-72b-chat',
    'model':"qwen2-72b",
    'model_server': 'http://127.0.0.1:1025/v1',  # base_url, also known as api_base
    # 'api_key': 'sk-ea89cf04431645b185990b8af8c9bb13',
}
bot = Assistant(llm=llm_cfg,
                name='Assistant',
                # system_message="你是一个地理专家，可以准确的判断地理位置，如果你不确定，可以使用工具"
                )

def getDocxToTextAll(name):
    docxPath=name
    document = Document(docxPath)
    # 逐段读取docx文档的内容
    levelList=[]
    words=[]
    addStart = False
    levelText=""
    i = 0
    for paragraph in document.paragraphs:
        # 判断该段落的标题级别
        # 这里用isTitle()临时代表，具体见下文介绍的方法
        text = paragraph.text
        if text.strip():#非空判断
            # print("非空")
            words.append(text)
    # 将所有段落文本拼接成一个字符串，并用换行符分隔
    text = '\n'.join(words)

    # 将文本写入txt文件
    with open("checkCompanyName.txt", 'w', encoding='utf-8') as txt_file:
        txt_file.write(text)
def companyNameTask(text):
    yield "文档公司或组织名称检查---启动中...."
    wordtag  = Taskflow("knowledge_mining",device_id=0)
    batchNum=20
    sentences = re.split(r'[。\n]', text)
    # 去掉空字符
    sentences = [sentence.strip() for sentence in sentences if sentence.strip()]
    # 计算总字符数
    total_chars = len(sentences)

    # 计算有多少份
    num_chunks = math.ceil(total_chars / batchNum)

    # 按batchNum字为一份进行处理
    chunks = [sentences[i:i + batchNum] for i in range(0, total_chars, batchNum)]
    placeList = []
    # 打印每一份的内容
    for i, chunk in enumerate(chunks):
        yield f"文档公司或组织名称检查---文档解析进度:{i + 1}/{num_chunks}"

        wenBen=".".join(chunk)
        try:
            res = wordtag(wenBen)
        except Exception as e:
            logging.warning(chunk)
            logging.warning("文档公司或组织名称检查---词类分析出错",e)
            continue
        isplace = False
        for zuhe in res[0]['items']:
            # 上一个的地名,这一个还是地名，就和上一个相加代替这个
            zhi = zuhe.get("wordtag_label")
            if isplace:
                name = placeList[len(placeList) - 1]
                if zhi.find("组织机构类") >= 0:  # or zuhe[1] == "ns"
                    isplace = True
                    new_text = zuhe['item'].replace("\n", "")
                    placeList[len(placeList) - 1] = name + new_text
                    continue
            if zhi.find("组织机构类") >= 0:
                isplace = True
                new_text = zuhe['item'].replace("\n", "")
                placeList.append(new_text)
            else:
                isplace = False
    # 打印总份数
    yield "文档公司或组织名称检查---文档解析完成"
    placeList=list(dict.fromkeys(placeList))
    yield placeList
def checkCompanyName(filename):
    yield f"文档公司或组织名称检查---开始处理文档..."
    try:
        getDocxToTextAll(filename)
    except Exception as e:
        logging.warning(e)
        yield "文档公司或组织名称检查---文档无法打开，请检查文档内容"
        return
    with open("checkCompanyName.txt", "r", encoding='utf-8') as f:
        gettext = f.read()
    yield f"文档公司或组织名称检查---开始解析文档..."  # 每次生成一个数字就发送
    for item in companyNameTask(gettext):
        if isinstance(item, str):
            yield item
        else:
            final_list = item  # 获取最终结果
    propnStr = ",".join(final_list)
    messages = [{'role': 'user', 'content': [{'text': propnStr+prompt}]}]
    runList = []
    yield f"文档公司或组织名称检查---结果生成中..."  # 每次生成一个数字就发送
    cishu = 0
    for rsp in bot.run(messages):
        runList.append(rsp)
        if cishu > 3:
            cishu = 0
        yield "文档公司或组织名称检查---结果生成中" + '.' * cishu
        cishu += 1
    data = runList[len(runList) - 1][0]["content"]
    parsed_data = json_repair.loads(data.replace('`', ''))
    error_places=[]
    for place in parsed_data:
        try:
            if place['回答'] == '非泛化的公司或组织名称':
                error_places.append(place)
        except Exception as e:
            logging.warning(place)
            logging.warning("文档公司或组织名称检查---组织提出出错",e)
            continue
    logging.info(error_places)
    returnInfo = "发现异常公司或组织名称<br>"
    if len(error_places)>0:
        for t in error_places:
            keyword= t['companyName'].replace("\n","")
        # 查找包含关键字的段落
            paragraphs = re.findall(r'.*?' + re.escape(keyword) + r'.*?\n', gettext)
            t["yuanwen"]=paragraphs[0]
            yuanwen = paragraphs[0].replace(keyword, f"**{keyword}**").replace("\n","")
            returnInfo += "原文：" + yuanwen + "<br>异常公司或组织名称：**" + keyword + "**！请注意" + "<br>"
        logging.info(returnInfo)
        yield returnInfo
    else:
        yield "**未发现异常公司或组织名称**<br>"