The problem Tessa solves

In India and many other countries, downloading a torrent is a very difficult process starting from the search itself. The ISPs and the government restrict access to popular torrent search engines like torrentz, the piratebay, kickass torrents. Even for downloading Linux .iso files it is extremely difficult to find good sources of torrents, We created a search engine for torrents based on the Ethereum, called Tessa. People can search for torrents and can download the magnets. We used IPFS to store the magnet links and stored the link, along with some keywords related to the content as a hash in the blockchain, so that it can be searched and retrieved later.

The idea eventually is to create an ecosystem in which people are incentivized to contribute torrent links and seed them, so that more people share files via torrents, making torrents more accessible. Many people do not use torrent for this same reason that they are not quite user-friendly, and hence our hack tries to resolve this problem.

Making torrents more accessible, easy to use and eventually incentivize the users who are invested in the ecosystem so as to make the torrent sharing space a universal and wonderful method to share files and data.

Challenges we ran into

Setting up IPFS with each node having the entire content, hence we ended using an abstraction layer over it which in our case was OrbitDB which is still in alpha.

We used Torus for users to easily add torrents to the system, but we faced a few issues:
We found the documentation quite lacking. It would have been great if it was mentioned what data can be accessed to the DApp after the user signs in.
We also faced issues in integrating torus to our react frontend

We also tried to use the DAOstack and improve upon the same initially but found the codebase to daunting to use, and was not able set up a dev environment even after trying it for hours.

We also think it would have been better if there was matic explorer for deploying on test net.

Devising a searching algorithm using keywords.