Spaces:
Paused
Paused
File size: 6,583 Bytes
785893b bf3eb0b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 |
from request_llm.bridge_chatgpt import predict_no_ui
from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down, get_conf
import re, requests, unicodedata, os
def download_arxiv_(url_pdf):
if 'arxiv.org' not in url_pdf:
if ('.' in url_pdf) and ('/' not in url_pdf):
new_url = 'https://arxiv.org/abs/'+url_pdf
print('下载编号:', url_pdf, '自动定位:', new_url)
# download_arxiv_(new_url)
return download_arxiv_(new_url)
else:
print('不能识别的URL!')
return None
if 'abs' in url_pdf:
url_pdf = url_pdf.replace('abs', 'pdf')
url_pdf = url_pdf + '.pdf'
url_abs = url_pdf.replace('.pdf', '').replace('pdf', 'abs')
title, other_info = get_name(_url_=url_abs)
paper_id = title.split()[0] # '[1712.00559]'
if '2' in other_info['year']:
title = other_info['year'] + ' ' + title
known_conf = ['NeurIPS', 'NIPS', 'Nature', 'Science', 'ICLR', 'AAAI']
for k in known_conf:
if k in other_info['comment']:
title = k + ' ' + title
download_dir = './gpt_log/arxiv/'
os.makedirs(download_dir, exist_ok=True)
title_str = title.replace('?', '?')\
.replace(':', ':')\
.replace('\"', '“')\
.replace('\n', '')\
.replace(' ', ' ')\
.replace(' ', ' ')
requests_pdf_url = url_pdf
file_path = download_dir+title_str
# if os.path.exists(file_path):
# print('返回缓存文件')
# return './gpt_log/arxiv/'+title_str
print('下载中')
proxies, = get_conf('proxies')
r = requests.get(requests_pdf_url, proxies=proxies)
with open(file_path, 'wb+') as f:
f.write(r.content)
print('下载完成')
# print('输出下载命令:','aria2c -o \"%s\" %s'%(title_str,url_pdf))
# subprocess.call('aria2c --all-proxy=\"172.18.116.150:11084\" -o \"%s\" %s'%(download_dir+title_str,url_pdf), shell=True)
x = "%s %s %s.bib" % (paper_id, other_info['year'], other_info['authors'])
x = x.replace('?', '?')\
.replace(':', ':')\
.replace('\"', '“')\
.replace('\n', '')\
.replace(' ', ' ')\
.replace(' ', ' ')
return './gpt_log/arxiv/'+title_str, other_info
def get_name(_url_):
import os
from bs4 import BeautifulSoup
print('正在获取文献名!')
print(_url_)
# arxiv_recall = {}
# if os.path.exists('./arxiv_recall.pkl'):
# with open('./arxiv_recall.pkl', 'rb') as f:
# arxiv_recall = pickle.load(f)
# if _url_ in arxiv_recall:
# print('在缓存中')
# return arxiv_recall[_url_]
proxies, = get_conf('proxies')
res = requests.get(_url_, proxies=proxies)
bs = BeautifulSoup(res.text, 'html.parser')
other_details = {}
# get year
try:
year = bs.find_all(class_='dateline')[0].text
year = re.search(r'(\d{4})', year, re.M | re.I).group(1)
other_details['year'] = year
abstract = bs.find_all(class_='abstract mathjax')[0].text
other_details['abstract'] = abstract
except:
other_details['year'] = ''
print('年份获取失败')
# get author
try:
authors = bs.find_all(class_='authors')[0].text
authors = authors.split('Authors:')[1]
other_details['authors'] = authors
except:
other_details['authors'] = ''
print('authors获取失败')
# get comment
try:
comment = bs.find_all(class_='metatable')[0].text
real_comment = None
for item in comment.replace('\n', ' ').split(' '):
if 'Comments' in item:
real_comment = item
if real_comment is not None:
other_details['comment'] = real_comment
else:
other_details['comment'] = ''
except:
other_details['comment'] = ''
print('年份获取失败')
title_str = BeautifulSoup(
res.text, 'html.parser').find('title').contents[0]
print('获取成功:', title_str)
# arxiv_recall[_url_] = (title_str+'.pdf', other_details)
# with open('./arxiv_recall.pkl', 'wb') as f:
# pickle.dump(arxiv_recall, f)
return title_str+'.pdf', other_details
@CatchException
def 下载arxiv论文并翻译摘要(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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……"
import glob
import os
# 基本信息:功能、贡献者
chatbot.append(["函数插件功能?", CRAZY_FUNCTION_INFO])
yield chatbot, history, '正常'
# 尝试导入依赖,如果缺少依赖,则给出安装建议
try:
import pdfminer, bs4
except:
report_execption(chatbot, history,
a = f"解析项目: {txt}",
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```。")
yield chatbot, history, '正常'
return
# 清空历史,以免输入溢出
history = []
# 提取摘要,下载PDF文档
try:
pdf_path, info = download_arxiv_(txt)
except:
report_execption(chatbot, history,
a = f"解析项目: {txt}",
b = f"下载pdf文件未成功")
yield chatbot, history, '正常'
return
# 翻译摘要等
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)}"
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}'
chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
yield chatbot, history, '正常'
msg = '正常'
# ** gpt request **
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
chatbot[-1] = (i_say_show_user, gpt_say)
history.append(i_say_show_user); history.append(gpt_say)
yield chatbot, history, msg
# 写入文件
import shutil
# 重置文件的创建时间
shutil.copyfile(pdf_path, f'./gpt_log/{os.path.basename(pdf_path)}'); os.remove(pdf_path)
res = write_results_to_file(history)
chatbot.append(("完成了吗?", res + "\n\nPDF文件也已经下载"))
yield chatbot, history, msg
|