0.0.0

• Used The Verge as our playground
• Use a Python script calling feedparser. We can feed an RSS feed into it, and have it extract whatever fields we want. The Verge only has 10 articles in its field, for other ones, we might need some logic that includes the data, and either here or in step two filters to only a certain timeframe (last 24 hours?). It extracts these URLs into a txt file
• Use a js script using a headless browser called puppeteer. Takes the URLs from feedparser, and then dumps the contents of the article into individual txt files
  • This also worked using curl, which is another option. Curl won't grab anything rendered in javascript (so short codes etc), but that's likely a non issue for this kind of job. Curl also returns the full html, so uses more tokens, and that potentially impacts the results and that's why I didn't use it
• Then call Claudes Haiku model, for cost efficiency, for each article on there and ask it for the summary in the format we want.
• Created a Python script then to just run each script sequentially, so it's a one click process
• For now, this creates txt files every step of the way. Powering a website likely requires another approach, but will get to that later
• For now, the proof of concept works and actually automated even more than I expected

Full Changelog: https://github.com/jfcostello/article-summarizer/commits/0.0.0