Tired of spending hours trying to find a song that perfectly captures this specific feeling you just can't put your finger on ( ╥ω╥ ) ? Look no further! With discOvery, not only can you discover songs that capture this specific feeling, you can also share what song makes you feel a certain way as well. ☆ ～('▽^人)
Our web app, discOvery, combines elements of a music streaming service interface and collaborative web apps. Our app prompts users on a daily basis to share songs that they think best describe these prompts. Other users will be able to see suggestions in their feeds while using the app.
- Daily Prompt: Each day, users receive a new prompt (all users will have the same prompt) to choose a song that best describes that prompt. This daily prompt utilises the OpenAI api to generate each prompt.
- Discovery Feed: Users will be able to view the responses of other users who have suggested their own song to that best describes the prompt of the day.
- Song Snippets: Snippets of the songs the user discovers on the app will be available to listen to while in the app. However, some songs don't have a snippet available and the user will instead be given to opportunity to access the song through Spotify Web.
- Basic User Profile: Users will be able to sign up with an email, password, and display name.
- Cloud Storage: User data will be stored in the cloud which offers many benefits such as data security.
- Streaks: The user's streak will increment each consecutive day they suggest a song based on the daily prompt. Their streak will reset to zero if the user doesn't suggest a song for the daily prompt.
- Save Discovered Songs: The user will be able to "like" a song from their Discovery Feed and will be able to access these songs from their user profile.
- No supported for small screens at the moment (e.g. mobile devices, tablets, small windows)
- Crrently not supported on Safari
In order to run the project on your own machine, you must have access to both the frontend and backend .env files, and
run both the frontend and backend.
To run the frontend please see the README here. To run the backend please see the
README here!
United by our love for music, we want to bring fellow music lovers a web app to share their favourite tunes! ♫
- From Team Amber Antelopes ♫✧♪
- Michelle Lie
- Lia Arroyo
- Tuan Le
- Ariel Wang
- Amisha Singh
- Atharva Arankalle
