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| 1 | +#!/usr/bin/env python |
| 2 | +# vim:fileencoding=utf-8 |
| 3 | +__license__ = 'GPL v3' |
| 4 | +__copyright__ = '2026, Jordan Shelley' |
| 5 | + |
| 6 | +import json |
| 7 | + |
| 8 | +from calibre.web.feeds.news import BasicNewsRecipe |
| 9 | + |
| 10 | +BASE = 'https://briefing-service.wholemind.workers.dev/v1/briefings/' |
| 11 | + |
| 12 | +SECTIONS = ( |
| 13 | + ('ai', 'AI Briefing'), |
| 14 | + ('labs', 'Frontier Labs'), |
| 15 | + ('finance', 'Markets'), |
| 16 | + ('sports', 'US Sports'), |
| 17 | + ('soccer', 'European Football'), |
| 18 | + ('us', 'US News'), |
| 19 | + ('world', 'World News'), |
| 20 | +) |
| 21 | + |
| 22 | + |
| 23 | +class BriefingService(BasicNewsRecipe): |
| 24 | + title = 'Briefing Service' |
| 25 | + __author__ = 'Jordan Shelley' |
| 26 | + description = ( |
| 27 | + 'Hourly LLM-ranked news briefings: AI, frontier labs, markets, ' |
| 28 | + 'US sports, European football, US and world news' |
| 29 | + ) |
| 30 | + publisher = 'Briefing Service' |
| 31 | + category = 'news, ai, finance, sports' |
| 32 | + language = 'en' |
| 33 | + publication_type = 'newspaper' |
| 34 | + oldest_article = 1 |
| 35 | + max_articles_per_feed = 30 |
| 36 | + no_stylesheets = True |
| 37 | + timefmt = '' |
| 38 | + auto_cleanup = True |
| 39 | + use_embedded_content = False |
| 40 | + remove_empty_feeds = True |
| 41 | + ignore_duplicate_articles = {'url'} |
| 42 | + cover_url = BASE + 'ai/pages/0.png' |
| 43 | + |
| 44 | + def parse_index(self): |
| 45 | + feeds = [] |
| 46 | + for key, name in SECTIONS: |
| 47 | + try: |
| 48 | + raw = self.index_to_soup(BASE + key + '/summary', raw=True) |
| 49 | + data = json.loads(raw) |
| 50 | + except Exception as e: |
| 51 | + self.log.warn('Failed to fetch section', name, ':', e) |
| 52 | + continue |
| 53 | + ranked_at = (data.get('ranked_at') or '')[:16].replace('T', ' ') |
| 54 | + items = [] |
| 55 | + if data.get('lead'): |
| 56 | + items.append(data['lead']) |
| 57 | + items.extend(data.get('stories') or []) |
| 58 | + items.extend(data.get('research') or []) |
| 59 | + articles = [] |
| 60 | + for story in items: |
| 61 | + url = story.get('link') |
| 62 | + if not url: |
| 63 | + continue |
| 64 | + desc = story.get('summary') or '' |
| 65 | + src = story.get('source') |
| 66 | + if src: |
| 67 | + desc = '{} [{}]'.format(desc, src).strip() |
| 68 | + articles.append({ |
| 69 | + 'title': story.get('headline') or url, |
| 70 | + 'url': url, |
| 71 | + 'date': story.get('published') or ranked_at, |
| 72 | + 'description': desc, |
| 73 | + }) |
| 74 | + if articles: |
| 75 | + title = data.get('name') or name |
| 76 | + if ranked_at: |
| 77 | + title = '{} ({} UTC)'.format(title, ranked_at) |
| 78 | + feeds.append((title, articles)) |
| 79 | + return feeds |
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