from docx import Document
from paddlenlp import Taskflow
from pprint import pprint
from qwen_agent.agents import Assistant
import re
import json_repair
import time
tagTask = Taskflow("ner")
prompt='''
.上述文本判断地名是否正确，你可以使用工具利用互联网查询，你只能在[正确,错误,简称,未知]三种选项中选择答案,回答格式[{“placeName”:“地名”,"回答":"答案"},{“placeName”:“地名”,"回答":"答案"}]，不做过多的解释,严格按回答格式作答;
不做过多的解释,严格按回答格式作答;
'''
# prompt='''
# .请回答以上问题，
# ,回答格式[{“placeName”:"原文","回答":"答案"},{“placeName”:"原文","回答":"答案"}]，不做过多的解释,严格按回答格式作答;
# 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',
                # description='使用RAG检索并回答，支持文件类型：PDF/Word/PPT/TXT/HTML。'
                )
#获取全文内容
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
    print("placeNameTask",len(words))
    text = '\n'.join(words)

    # 将文本写入txt文件
    with open("checkPlaceName.txt", 'w', encoding='utf-8') as txt_file:
        txt_file.write(text)

#得到全文和地名有关的内容
def placeNameTask(text):
    res = tagTask(text)
    print(res)
    placeList = []
    isplace = False
    for zuhe in res:
        # 上一个的地名,这一个还是地名，就和上一个相加代替这个

        if isplace:
            name = placeList[len(placeList) - 1]
            if zuhe[1].find("组织机构类")>=0 or zuhe[1].find("世界地区类")>=0:# or zuhe[1] == "ns"
                isplace = True
                new_text = zuhe[0].replace("\n", "")
                placeList[len(placeList) - 1] = name + new_text
                continue
        if zuhe[1].find("组织机构类")>=0 or zuhe[1].find("世界地区类")>=0:
            isplace = True
            new_text = zuhe[0].replace("\n", "")
            placeList.append(new_text)
        else:
            isplace = False
    placeList=list(dict.fromkeys(placeList))
    return placeList
#主方法
def checkPlaceName(filename):
    getDocxToTextAll(filename)
    start_time=time.time()
    error_places = []
    for batch in read_file_in_batches('checkPlaceName.txt'):
        res=process_batch(batch)
        if(len(res)>0):
            error_places.extend(res)

    pprint(error_places)
    end_time = time.time()
    # 计算执行时间
    elapsed_time = end_time - start_time
    print(f"checkPlaceName程序执行时间: {elapsed_time} 秒")
    return error_places

def read_file_in_batches(file_path, batch_size=5000):
    """
    分批读取文本文件
    :param file_path: 文件路径
    :param batch_size: 每批处理的字符数
    :return: 生成器，每次返回一批文本
    """
    with open(file_path, 'r', encoding='utf-8') as file:
        batch = []
        char_count = 0
        for line in file:
            batch.append(line)
            char_count += len(line)
            if char_count >= batch_size:
                yield ''.join(batch)
                batch = []
                char_count = 0
        if batch:
            yield ''.join(batch)

def process_batch(batch):
    """
    处理一批文本
    :param batch: 一批文本
    """
    # 在这里添加你的处理逻辑

    # sentences = re.split(r'[。\n]', batch)
    # sentences = [sentence.strip() for sentence in sentences if sentence.strip()]
    propnList=placeNameTask(batch)
    # words=[]
    # for placeName in propnList:
    #     word="原文：{},先从分析原文是否含有错误地名，若含有错误地名，请回答包含错误地名，若不包含错误地名，请从【具体的公司或组织名称,非具体的公司或组织名称,与政府有关的公司或组织名称,其他组织名称，地名】中选择最合适的一个作为答案".format(placeName)
    #     words.append(word)  
    propnStr = ",".join(propnList)
    print("placeNameTask",propnStr)
    messages = [{'role': 'user', 'content': [{'text': propnStr + prompt}]}]
    runList = []
    for rsp in bot.run(messages):
        runList.append(rsp)
    data = runList[len(runList) - 1][0]["content"]
    print("placeNameTask",data)
    parsed_data = json_repair.loads(data.replace('`', ''))

    # 遍历列表
    for item in parsed_data:
        print(f"地名: {item['placeName']}, 回答: {item['回答']}")

    # 如果需要进一步操作，例如只关注“正确”的回答
    error_places = [place for place in parsed_data if place['回答'] == '错误']
    print("placeNameTask",error_places)
    if len(error_places)>0:
        for t in error_places:
            keyword= t['placeName']
        # 查找包含关键字的段落
            paragraphs = re.findall(r'.*?' + re.escape(keyword) + r'.*?\n', batch)
            t["yuanwen"]=paragraphs[0]
        return error_places
    else:
        return error_places