Project case study

AI Music Application

A cross-platform music application combining a Flutter client, authenticated FastAPI services, media management, and voice-enabled interactions.

View source
Placeholder mobile application interface for the AI Music Application

Overview

Product purpose and implementation.

The application brings playback, discovery, personal libraries, playlists, profiles, and subscription-oriented screens into one mobile experience.

Its public repository separates the Flutter feature modules from a Python API layer, with dedicated models and routes for users, songs, favorites, playlists, requests, and subscriptions.

Verified capabilities

Features visible in the product or source.

Music playback

Includes audio playback, background audio, waveform presentation, volume controls, and a sleep timer.

Accounts and profiles

Provides sign-up, sign-in, password recovery, profile editing, and authenticated application flows.

Libraries and playlists

Supports favorites, playlists, playlist songs, song browsing, artist views, and local persistence.

Voice and administration

Contains speech-to-text voice assistance plus administrative song upload, update, request, and user views.

Structure

How the product is organized.

  1. 01 / Mobile client

    Flutter and Dart feature modules with Riverpod state management, audio services, Hive, and shared preferences.

  2. 02 / API services

    Python FastAPI routes handle authentication, songs, uploads, favorites, playlists, and account workflows.

  3. 03 / Data and media

    SQLAlchemy models organize application data while Cloudinary-backed workflows store uploaded songs and thumbnails.

Technology and delivery

Tools matched to the product.

The stack and capabilities are based on the public repository. The current portfolio image remains a placeholder until real application screenshots are added.

  • Flutter
  • Dart
  • Riverpod
  • Python
  • FastAPI
  • SQLAlchemy
  • Cloudinary
  • Hive