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from datetime import date, datetime, timedelta |
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import json |
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import lxml.html |
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from lxml.cssselect import CSSSelector |
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import time |
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from openai import OpenAI |
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import requests |
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import xmltodict |
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tabooWords = ['deletion', 'rape', 'rapist', 'abuse', 'minor'] |
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recentArticles = [] |
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dateForArticle = {} |
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today = date.today() |
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for days in range(5, 12): |
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tdate = (today - timedelta(days=days)) |
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tstamp = tdate.strftime("%B_%d,_%Y") |
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r = requests.get(f"https://en.wikinews.org/wiki/Category:{tstamp}") |
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contents = lxml.html.fromstring(r.content) |
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selAnchor = CSSSelector('a') |
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for linkEl in selAnchor(contents): |
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link = str(linkEl.get('href')) |
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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: |
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recentArticles.append(link) |
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dateForArticle[link] = tdate.strftime("%Y/%m/%d") |
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time.sleep(1) |
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client = OpenAI() |
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outputs = [] |
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for article in recentArticles: |
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print(article) |
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r = requests.get(f"https://en.wikinews.org{article}") |
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contents = lxml.html.fromstring(r.content) |
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selMain = CSSSelector('.mw-body-content p') |
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plaintxt = "" |
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for para in selMain(contents): |
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c = para.text_content() |
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if 'pre-publication review' in c or 'last amended' in c: |
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continue |
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plaintxt += c + "\n" |
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if 'Have an opinion' in plaintxt: |
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plaintxt = plaintxt[:plaintxt.index('Have an opinion')] |
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plaintxt = plaintxt.strip() |
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block = False |
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for taboo in tabooWords: |
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if taboo in plaintxt.lower(): |
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block = True |
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if block: |
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print("Article marked for deletion or about subject sensitive for AI summarization") |
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continue |
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dt = dateForArticle[article] |
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selAnchor = CSSSelector('a[rel="nofollow"]') |
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foundElements = selAnchor(contents) |
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articleLinks = [] |
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for el in foundElements: |
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link = el.get('href') |
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linkblocks = ['/wiki/', '.com/intent/tweet', 'creativecommons.org/licenses', 'facebook.com/sharer.php', 'mailto:', 'reddit.com/submit', 'linkedin.com/shareArticle'] |
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block = False |
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for blocker in linkblocks: |
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if blocker in link.lower(): |
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block = True |
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if block: |
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continue |
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articleLinks.append(link) |
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qs = [] |
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response = client.chat.completions.create( |
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model="gpt-4o", |
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messages=[ |
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{ |
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"role": "system", |
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"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' }]", |
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}, |
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{ |
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"role": "user", |
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"content": f"Here's the article: \n{plaintxt}", |
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}, |
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], |
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) |
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reply = response.choices[0].message.content |
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reply = reply[reply.index('[') : reply.rindex(']') + 1] |
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qs = json.loads(reply) |
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for q in qs: |
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if q["answer"] not in q["choices"]: |
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continue |
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outputs.append({ |
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"question_date": dt, |
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"question_url": f"https://en.wikinews.org{article}", |
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"question_sentence": q["question"], |
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"links": articleLinks, |
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"choices": q["choices"], |
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"answer_text": q["answer"], |
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"answer": [ q["choices"].index(q["answer"]) ], |
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}) |
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time.sleep(1) |
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tstamp = datetime.now().strftime("%Y%m%d") |
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with open(f"./{tstamp}_qa_public.jsonl", "w") as fi: |
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for idx, op in enumerate(outputs): |
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op["question_id"] = f"{tstamp}_{idx}" |
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op["question_source"] = "WikiNews" |
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fi.write(json.dumps(op) + "\n") |
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