Table of Contents
As part of the February 22 ITC final Project Team 1 decided to build an app to recommend playlist based on free text inputs
Here's why:
Let us paint you a picture.
You’re at the beach, with your friends. You’re enjoying an ice-cold (well, lukewarm) beer. The only thing missing to complete the scene are some phat tasty tunes. You open Spotify, trying to find some music that will make the moment perfect. But you don’t have any ‘beach’ playlists! And you’re not going to trust some rando to pick music for you!
Enter Moodika.
Principal languages / libraries:
- Python
- MySQL
- Streamlit
- PyTorch
Here we will describe instructions for the offline version.
Install all the required libraries by installing the requirements.
- requirements.txt
pip install -r requirements.txt
Below is an example of how you can instruct your audience on installing and setting up your app. This template doesn't rely on any external dependencies or services.
- Get your Spotify Credentials by following the tutorial here: https://www.youtube.com/watch?v=WHugvJ0YR5I
- Clone the repo
git clone https://github.com/noamgoldberg/Moodika.git
- Install all the required libraries by installing the requirements.
- requirements.txt
pip install -r requirements.txt
-
Update
config.pywith your credentials for both Spotify Ids and Database -
Run the Model A or Model B
The differences in the architecture of the 2 Models are summarized in the below pictures.
- Implement Model A
- Implement Model B
- Deploy Model A
- Deploy Model B
- Improve App based on feedbacks
- Merge both Models to improve the generation
- Multi-language Support
- Add Additional Templates w/ Examples
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the NDS License.
Sam, Doron, Noam - spotifydatascience@gmail.com
Project Link: https://github.com/noamgoldberg/Moodika