This ASP.NET Core MVC application integrates with the Spotify API to fetch audio features of recently played tracks. It sends these features to a Flask API hosting a machine learning model, which predicts the user's mood (e.g., happy, sad) based on listening habits.
Spotify API Integration: Retrieves audio features like valence, energy, and tempo. Mood Prediction: Uses a Flask API model to predict emotional states. Interactive Dashboard: Displays mood insights on the web interface.
Model: There is no models for a now.
View: ASP.NET Core MVC views display user mood predictions and data.
Controller: Manages data flow between Spotify, Flask API, and the frontend.
ModelApiPKL.py: Flask API hosts the machine learning model for mood prediction.
mood_prediction_model.pkl: This file contains a machine learning model trained to predict users' moods. The model is trained on data derived from users' music listening habits and makes predictions about their emotional state.
Prerequisites .NET SDK Python & Flask Spotify Developer Account
Clone the Repository
git clone https://github.com/OguzhanTekeli06/SpotifyMoodAnalyzer
Configure Spotify API. Set up Client ID and Secret in the app configuration.From your spotifyapi app.
python ModelApi.py
Start project
dotnet run
Usage Log in via Spotify to fetch recent audio data. The app displays your mood based on audio features.
The Flask API model processes audio features for mood predictions using machine learning.
Licensed under MIT.