Pond's Neural Nets

Pond is developing a large AI model using on-chain data with a team of world-leading AI experts and embedded its processed token on-chain graphical structure results into a Farcaster framework. The purpose is to showcase results and enable users to discern potential on-chain opportunities, thereby allowing them to vote based on their research and knowledge regarding which token will likely exhibit the best performance.

The model can be used as a foundation model of crypto to help other projects unlock their new business models and develop new features and provide a new way for Farcaster users to interact with on-chain opportunities - not only with token discovery, but also can be recommendation of users on other protocols, prediction markets and more.

1. Retrieve alpha rate data calculated for three tokens selected weekly and each token's pond through API requests.
2. Use d3 to plot the data into a line graph in SVG format.
3. Convert the SVG format into a base64 image.
4. Finally, return the base64 image and corresponding text as a frame in frames.js, along with three action buttons for user voting.
5. After users vote, submit the voting results and FID (Frame ID) to the backend via API.
6. Once the voting period ends, filter the winning FID and display a button to redeem points. Clicking it will guide users to claim their rewards. (Uncertain about the relevance, might not need to mention.)