Inspiration: To provide a tldr for articles which I would not want to spend too much time reading the whole thing
What it does: Currently it is an api that you can paste in the article and will receive back the summary. Our eventual goal is that it acts as a web extension that can automatically detect texts in an article and provide a summary upon opening a page.
How I built it: With python and heroku currently.
Challenges I ran into: I cannot train a model due to resource control. We also did not have enough time to package it as an extension as we ran into the "arduino" problem and we wanted to learn about arduino so we spent some time on that :)
Accomplishments that I'm proud of: First time packaging a python app to be served.
What I learned: Flask, different text summarization techniques (which is currently not as available as racism/translation/conversational models)
What's next for Text summarizer 1.0: Better model, web extension
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