Playlist Generator

GIF
Output (puts it directly in the user's Spotify Account)
Login Page
Data input
Success Page

Inspiration

We all met last year when we took CS1110. While we coded and studied together, we would always listen to music like rap and RNB. In fact, music is how we got closer as friends. We wanted to find a way to combine the two, so that's how we thought of Music Generator.

What it does

The user enters keywords that correlate with their desired genre of music and the AI will use those keywords to construct a playlist with music in that specific genre. Music AI is for people who don't want to spend hours making an optimal playlist but it also recommends new music that may fit their taste

How we built it

We divided the project into two main parts: the backend and the frontend. For the backend, we used Python to handle the AI-driven playlist generation. We employed libraries to analyze the user's input keywords and match them with a database of songs by genre and theme. On the frontend, we built the interface using HTML, CSS, and JavaScript to ensure a seamless user experience. JavaScript helped us handle dynamic user interactions, such as taking the keywords and sending them to the backend for processing. CSS was used to style the interface, making it visually appealing and easy to navigate. Lastly, we ensured smooth communication between the frontend and backend using RESTful APIs, which allowed us to send user input to the Python AI model and retrieve the generated playlist in real-time.

Challenges we ran into

The challenges we ran into were dividing the tasks since all of us use different languages and frameworks. We all specialize in either front end or back and so we just use the language that the majority use and helped others catch up when needed.

Accomplishments that we're proud of -- This was our first project where we used some form of complicated AI to implement, but we are really proud of it. Additionally, we used many different coding languages, some of which we have never used, which we are proud of.

What we learned

We learned that collaborating on a main objective as a group makes working more efficient. We got to hear different perspectives and apply it to our project. Overall, it was a great experience collaborating on a project with obstacles and we will apply those lessons for future projects.