Inspiration
As part of the team-building exercise they had us fill in mad-libs from copypastas. We thought, why not cut out the work for the organizers since it's obviously an arduous task to decide which profane words to remove from "SCAV bothers me"
What it does
It uses google cloud's part-of-speech tagger, along with NLTK's stopwords, to decide which words are candidates for removal and replacement with blanks.
How we built it
We used the Google Cloud Natural Language API to tag the parts of speech in a copypasta, then used our super secret algorithm (it's not that secret)
Challenges we ran into
WHY WON'T APP ENGINE RUN WHY DOES GOOGLE HATE US
Accomplishments that we're proud of
We made a pretty tacky site that accomplishes exactly what we want, we built a flask api and a script that uses NLP to do something totally useless but wonderful. It brings us a lot of joy.
What we learned
Learning about the different components of web apps, the stages (and frustrations) of deploying to GCP. The joys of the NLP API.
What's next for pastalibs
Stable deployment
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