188 lines
6.6 KiB
Python
188 lines
6.6 KiB
Python
from toolbox import update_ui
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from request_llm.bridge_chatgpt import predict_no_ui
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from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down, get_conf
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import re, requests, unicodedata, os
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def download_arxiv_(url_pdf):
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if 'arxiv.org' not in url_pdf:
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if ('.' in url_pdf) and ('/' not in url_pdf):
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new_url = 'https://arxiv.org/abs/'+url_pdf
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print('下载编号：', url_pdf, '自动定位：', new_url)
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# download_arxiv_(new_url)
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return download_arxiv_(new_url)
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else:
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print('不能识别的URL！')
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return None
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if 'abs' in url_pdf:
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url_pdf = url_pdf.replace('abs', 'pdf')
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url_pdf = url_pdf + '.pdf'
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url_abs = url_pdf.replace('.pdf', '').replace('pdf', 'abs')
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title, other_info = get_name(_url_=url_abs)
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paper_id = title.split()[0] # '[1712.00559]'
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if '2' in other_info['year']:
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title = other_info['year'] + ' ' + title
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known_conf = ['NeurIPS', 'NIPS', 'Nature', 'Science', 'ICLR', 'AAAI']
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for k in known_conf:
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if k in other_info['comment']:
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title = k + ' ' + title
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download_dir = './gpt_log/arxiv/'
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os.makedirs(download_dir, exist_ok=True)
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title_str = title.replace('?', '？')\
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.replace(':', '：')\
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.replace('\"', '“')\
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.replace('\n', '')\
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.replace(' ', ' ')\
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.replace(' ', ' ')
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requests_pdf_url = url_pdf
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file_path = download_dir+title_str
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# if os.path.exists(file_path):
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# print('返回缓存文件')
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# return './gpt_log/arxiv/'+title_str
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print('下载中')
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proxies, = get_conf('proxies')
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r = requests.get(requests_pdf_url, proxies=proxies)
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with open(file_path, 'wb+') as f:
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f.write(r.content)
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print('下载完成')
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# print('输出下载命令：','aria2c -o \"%s\" %s'%(title_str,url_pdf))
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# subprocess.call('aria2c --all-proxy=\"172.18.116.150:11084\" -o \"%s\" %s'%(download_dir+title_str,url_pdf), shell=True)
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x = "%s %s %s.bib" % (paper_id, other_info['year'], other_info['authors'])
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x = x.replace('?', '？')\
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.replace(':', '：')\
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.replace('\"', '“')\
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.replace('\n', '')\
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.replace(' ', ' ')\
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.replace(' ', ' ')
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return './gpt_log/arxiv/'+title_str, other_info
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def get_name(_url_):
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import os
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from bs4 import BeautifulSoup
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print('正在获取文献名！')
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print(_url_)
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# arxiv_recall = {}
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# if os.path.exists('./arxiv_recall.pkl'):
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# with open('./arxiv_recall.pkl', 'rb') as f:
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# arxiv_recall = pickle.load(f)
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# if _url_ in arxiv_recall:
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# print('在缓存中')
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# return arxiv_recall[_url_]
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proxies, = get_conf('proxies')
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res = requests.get(_url_, proxies=proxies)
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bs = BeautifulSoup(res.text, 'html.parser')
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other_details = {}
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# get year
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try:
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year = bs.find_all(class_='dateline')[0].text
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year = re.search(r'(\d{4})', year, re.M | re.I).group(1)
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other_details['year'] = year
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abstract = bs.find_all(class_='abstract mathjax')[0].text
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other_details['abstract'] = abstract
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except:
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other_details['year'] = ''
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print('年份获取失败')
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# get author
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try:
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authors = bs.find_all(class_='authors')[0].text
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authors = authors.split('Authors:')[1]
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other_details['authors'] = authors
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except:
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other_details['authors'] = ''
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print('authors获取失败')
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# get comment
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try:
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comment = bs.find_all(class_='metatable')[0].text
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real_comment = None
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for item in comment.replace('\n', ' ').split(' '):
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if 'Comments' in item:
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real_comment = item
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if real_comment is not None:
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other_details['comment'] = real_comment
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else:
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other_details['comment'] = ''
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except:
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other_details['comment'] = ''
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print('年份获取失败')
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title_str = BeautifulSoup(
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res.text, 'html.parser').find('title').contents[0]
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print('获取成功：', title_str)
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# arxiv_recall[_url_] = (title_str+'.pdf', other_details)
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# with open('./arxiv_recall.pkl', 'wb') as f:
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# pickle.dump(arxiv_recall, f)
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return title_str+'.pdf', other_details
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@CatchException
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def 下载arxiv论文并翻译摘要(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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CRAZY_FUNCTION_INFO = "下载arxiv论文并翻译摘要，函数插件作者[binary-husky]。正在提取摘要并下载PDF文档……"
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import glob
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import os
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# 基本信息：功能、贡献者
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chatbot.append(["函数插件功能？", CRAZY_FUNCTION_INFO])
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yield from update_ui(chatbot=chatbot, history=history)
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# 尝试导入依赖，如果缺少依赖，则给出安装建议
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try:
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import pdfminer, bs4
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except:
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report_execption(chatbot, history,
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a = f"解析项目: {txt}",
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b = f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pdfminer beautifulsoup4```。")
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yield from update_ui(chatbot=chatbot, history=history)
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return
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# 清空历史，以免输入溢出
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history = []
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# 提取摘要，下载PDF文档
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try:
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pdf_path, info = download_arxiv_(txt)
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except:
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report_execption(chatbot, history,
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a = f"解析项目: {txt}",
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b = f"下载pdf文件未成功")
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yield from update_ui(chatbot=chatbot, history=history)
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return
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# 翻译摘要等
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i_say = f"请你阅读以下学术论文相关的材料，提取摘要，翻译为中文。材料如下：{str(info)}"
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i_say_show_user = f'请你阅读以下学术论文相关的材料，提取摘要，翻译为中文。论文：{pdf_path}'
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chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
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yield from update_ui(chatbot=chatbot, history=history)
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msg = '正常'
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# ** gpt request **
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
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chatbot[-1] = (i_say_show_user, gpt_say)
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history.append(i_say_show_user); history.append(gpt_say)
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yield from update_ui(chatbot=chatbot, history=chatbot, msg=msg)
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# 写入文件
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import shutil
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# 重置文件的创建时间
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shutil.copyfile(pdf_path, f'./gpt_log/{os.path.basename(pdf_path)}'); os.remove(pdf_path)
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res = write_results_to_file(history)
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chatbot.append(("完成了吗？", res + "\n\nPDF文件也已经下载"))
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yield from update_ui(chatbot=chatbot, history=chatbot, msg=msg)
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