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# pip install openai lxml cssselector requests xmltodict
from datetime import date, datetime, timedelta
import json
import lxml.html
from lxml.cssselect import CSSSelector
import time
from openai import OpenAI
import requests
import xmltodict
tabooWords = ['deletion', 'rape', 'rapist', 'abuse', 'minor']
# load from WikiNews English recent days (not yet published)
recentArticles = []
dateForArticle = {}
today = date.today()
for days in range(5, 12):
tdate = (today - timedelta(days=days))
tstamp = tdate.strftime("%B_%d,_%Y")
r = requests.get(f"https://en.wikinews.org/wiki/Category:{tstamp}")
contents = lxml.html.fromstring(r.content)
selAnchor = CSSSelector('a')
for linkEl in selAnchor(contents):
link = str(linkEl.get('href'))
if link[:6] == '/wiki/' and '/Special:' not in link and '/Category:' not in link and 'Main_Page' not in link and 'Help:' not in link and 'Wikinews:' not in link and 'File:' not in link:
recentArticles.append(link)
dateForArticle[link] = tdate.strftime("%Y/%m/%d")
time.sleep(1)
client = OpenAI()
outputs = []
for article in recentArticles:
print(article)
r = requests.get(f"https://en.wikinews.org{article}")
contents = lxml.html.fromstring(r.content)
selMain = CSSSelector('.mw-body-content p')
plaintxt = ""
for para in selMain(contents):
c = para.text_content()
if 'pre-publication review' in c or 'last amended' in c:
continue
plaintxt += c + "\n"
if 'Have an opinion' in plaintxt:
plaintxt = plaintxt[:plaintxt.index('Have an opinion')]
plaintxt = plaintxt.strip()
block = False
for taboo in tabooWords:
if taboo in plaintxt.lower():
block = True
if block:
print("Article marked for deletion or about subject sensitive for AI summarization")
continue
dt = dateForArticle[article]
selAnchor = CSSSelector('a[rel="nofollow"]')
foundElements = selAnchor(contents)
articleLinks = []
for el in foundElements:
link = el.get('href')
linkblocks = ['/wiki/', '.com/intent/tweet', 'creativecommons.org/licenses', 'facebook.com/sharer.php', 'mailto:', 'reddit.com/submit', 'linkedin.com/shareArticle']
block = False
for blocker in linkblocks:
if blocker in link.lower():
block = True
if block:
continue
articleLinks.append(link)
qs = []
response = client.chat.completions.create(
model="gpt-4o",
messages=[
{
"role": "system",
"content": "You will be provided with an article from today's news. Provide 3-5 multiple choice questions based on the content of the article, especially newly-introduced facts or knowledge. Don't make the correct answer any more specific, numeric, or realistic compared to the others.\n Respond in JSON format: [{ question: 'Who was elected president of Sesame Street?', choices: ['Big Bird', 'Donald Duck'], answer: 'Big Bird' }]",
},
{
"role": "user",
"content": f"Here's the article: \n{plaintxt}",
},
],
)
reply = response.choices[0].message.content
reply = reply[reply.index('[') : reply.rindex(']') + 1]
qs = json.loads(reply)
for q in qs:
if q["answer"] not in q["choices"]:
continue
outputs.append({
"question_date": dt,
"question_url": f"https://en.wikinews.org{article}",
"question_sentence": q["question"],
"links": articleLinks,
"choices": q["choices"],
"answer_text": q["answer"],
"answer": [ q["choices"].index(q["answer"]) ],
})
time.sleep(1)
tstamp = datetime.now().strftime("%Y%m%d")
with open(f"./{tstamp}_qa_public.jsonl", "w") as fi:
for idx, op in enumerate(outputs):
op["question_id"] = f"{tstamp}_{idx}"
op["question_source"] = "WikiNews"
fi.write(json.dumps(op) + "\n")
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