本文目录一览：
openai使用了不受支持的协议
您想问的是openai是否使用了不受支持的协议吗？没有。
OpenAI在发表出版物和研究成果时，遵从开放许可证，如MIT、Apache等，同样也积极寻求合适的许可证，以便公开分享和使用OpenAI的研究成果。因此，OpenAI在使用协议和许可证上一直都非常谨慎和规范，以避免出现不受支持的协议。
OpenAI是一家人工智能研究机构，OpenAI的研究成果和出版物都得到了广泛关注和应用。在使用开源软件和开放许可证的同时，OpenAI也十分重视知识产权保护，避免侵犯他人的知识产权。对于任何可能存在违反协议的情况，OpenAI都会积极采取措施进行调查和处理。
openai能当爬虫使吗
你好，可以的，Spinning Up是OpenAI开源的面向初学者的深度强化学习资料，其中列出了105篇深度强化学习领域非常经典的文章， 见 Spinning Up：
博主使用Python爬虫自动爬取了所有文章，而且爬下来的文章也按照网页的分类自动分类好。
见下载资源：Spinning Up Key Papers
源码如下：
import os
import time
import urllib.request as url_re
import requests as rq
from bs4 import BeautifulSoup as bf
'''Automatically download all the key papers recommended by OpenAI Spinning Up.
See more info on:
Dependency:
bs4, lxml
'''
headers = {
'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.131 Safari/537.36'
}
spinningup_url = ''
paper_id = 1
def download_pdf(pdf_url, pdf_path):
"""Automatically download PDF file from Internet
Args:
pdf_url (str): url of the PDF file to be downloaded
pdf_path (str): save routine of the downloaded PDF file
"""
if os.path.exists(pdf_path): return
try:
with url_re.urlopen(pdf_url) as url:
pdf_data = url.read()
with open(pdf_path, "wb") as f:
f.write(pdf_data)
except: # fix link at [102]
pdf_url = r""
with url_re.urlopen(pdf_url) as url:
pdf_data = url.read()
with open(pdf_path, "wb") as f:
f.write(pdf_data)
time.sleep(10) # sleep 10 seconds to download next
def download_from_bs4(papers, category_path):
"""Download papers from Spinning Up
Args:
papers (bs4.element.ResultSet): 'a' tags with paper link
category_path (str): root dir of the paper to be downloaded
"""
global paper_id
print("Start to ownload papers from catagory {}...".format(category_path))
for paper in papers:
paper_link = paper['href']
if not paper_link.endswith('.pdf'):
if paper_link[8:13] == 'arxiv':
# paper_link = ""
paper_link = paper_link[:18] + 'pdf' + paper_link[21:] + '.pdf' # arxiv link
elif paper_link[8:18] == 'openreview': # openreview link
# paper_link = ""
paper_link = paper_link[:23] + 'pdf' + paper_link[28:]
elif paper_link[14:18] == 'nips': # neurips link
paper_link = ""
else: continue
paper_name = '[{}] '.format(paper_id) + paper.string + '.pdf'
if ':' in paper_name:
paper_name = paper_name.replace(':', '_')
if '?' in paper_name:
paper_name = paper_name.replace('?', '')
paper_path = os.path.join(category_path, paper_name)
download_pdf(paper_link, paper_path)
print("Successfully downloaded {}!".format(paper_name))
paper_id += 1
print("Successfully downloaded all the papers from catagory {}!".format(category_path))
def _save_html(html_url, html_path):
"""Save requested HTML files
Args:
html_url (str): url of the HTML page to be saved
html_path (str): save path of HTML file
"""
html_file = rq.get(html_url, headers=headers)
with open(html_path, "w", encoding='utf-8') as h:
h.write(html_file.text)
def download_key_papers(root_dir):
"""Download all the key papers, consistent with the categories listed on the website
Args:
root_dir (str): save path of all the downloaded papers
"""
# 1. Get the html of Spinning Up
spinningup_html = rq.get(spinningup_url, headers=headers)
# 2. Parse the html and get the main category ids
soup = bf(spinningup_html.content, 'lxml')
# _save_html(spinningup_url, 'spinningup.html')
# spinningup_file = open('spinningup.html', 'r', encoding="UTF-8")
# spinningup_handle = spinningup_file.read()
# soup = bf(spinningup_handle, features='lxml')
category_ids = []
categories = soup.find(name='div', attrs={'class': 'section', 'id': 'key-papers-in-deep-rl'}).\
find_all(name='div', attrs={'class': 'section'}, recursive=False)
for category in categories:
category_ids.append(category['id'])
# 3. Get all the categories and make corresponding dirs
category_dirs = []
if not os.path.exitis(root_dir):
os.makedirs(root_dir)
for category in soup.find_all(name='h2'):
category_name = list(category.children)[0].string
if ':' in category_name: # replace ':' with '_' to get valid dir name
category_name = category_name.replace(':', '_')
category_path = os.path.join(root_dir, category_name)
category_dirs.append(category_path)
if not os.path.exists(category_path):
os.makedirs(category_path)
# 4. Start to download all the papers
print("Start to download key papers...")
for i in range(len(category_ids)):
category_path = category_dirs[i]
category_id = category_ids[i]
content = soup.find(name='div', attrs={'class': 'section', 'id': category_id})
inner_categories = content.find_all('div')
if inner_categories != []:
for category in inner_categories:
category_id = category['id']
inner_category = category.h3.text[:-1]
inner_category_path = os.path.join(category_path, inner_category)
if not os.path.exists(inner_category_path):
os.makedirs(inner_category_path)
content = soup.find(name='div', attrs={'class': 'section', 'id': category_id})
papers = content.find_all(name='a',attrs={'class': 'reference external'})
download_from_bs4(papers, inner_category_path)
else:
papers = content.find_all(name='a',attrs={'class': 'reference external'})
download_from_bs4(papers, category_path)
print("Download Complete!")
if __name__ == "__main__":
root_dir = "key-papers"
download_key_papers(root_dir)
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openai国内如何使用
用法如下。
OpenAI在国内也有不少的普及应用，大家都知道OpenAI是一家人工智能学习开发公司，成立于2015年，由ElonMusk，GregBrockman，IlyaSutskever和SamAltman等四位创始人共同创办。OpenAI的主要目标是使AI技术的发展走向更平衡、更公平的方向，探索人工智能在各个领域的应用，帮助人们了解AI技术，以便更好地应用它们。
openai独享一人一号，每个都带api密钥key。
怎么用openai写论文
要使用openai写论文首先是要安装好al小助手，要下载al text generator 的插件，然后安装并且配置好ai小助手，接着是要生成和管理apl的密钥了，也就是登录的密码，然后在使用ai编辑器编辑文件文本，最后通过数据元方式输出就可以了。
openai怎么调中文
1、首先进入电脑屏幕操控界面，打开OPENIV，单击红框。
2、其次点击openIVoptions。
3、然后点击language后出现语言设置界面。
4、最后设置界面会弹出各种语言的选择栏，选择简体中文按close即可。
