TL:DR

Do you ever find yourself looking at a wall of text with no desire to read? Life's too short for convoluted jargon. TL:DR gives you this time back, thanks to co:here's natural language processing.

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Inspiration

We felt that there was a lack of accessible academia and analytics on text data.

What it does

It takes in a text or youtube comment section that the user inputs and spits out a quick TL;DR summary of what the text is saying and give us a quick statistical breakdown.

How we built it

We used python, co:here api, Youtube data api v3, and flask to develop our project. Python was our language of choice as we implemented the two api's. Flask was used for our web development.

Challenges we ran into

INTERNET,

Accomplishments that we're proud of

Learning to use API's

What we learned

There are a lot of cool API's out there that can do many cool things.

What's next for TL:DR

We would like to further develop our project website and work out all the little bugs. One of our ideas is to combine cohere and data science to provide in-depth analytics about a piece of text such as a distribution of sentence sentiment

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