Project developed as part of the Software Engineering course.
Dobby is a web-based media recommendation platform designed to help users discover new movies and TV shows based on their preferences, watch history, and community interactions.
The system integrates a Next.js frontend, a Python FastAPI microservice for personalized recommendations, and a Supabase backend for authentication, data storage, and user management.
Key features include:
- Personalized content recommendations.
- User-friendly interface with modern UI components built using Tailwind CSS and shadcn/ui.
- Secure authentication and data management through Supabase.
- Integration with external APIs (e.g., TMDB) for movie and series data.
- Modular architecture that allows scalable development and deployment.
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User Authentication & Profiles
- Users can register, log in, and manage their profiles.
- Store user preferences and interaction history.
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Media Browsing & Search
- Users can search for movies and TV shows.
- Fetch and display metadata (title, poster, genre, rating) via the TMDB API.
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User interactivy
- Users are able to send messages and recommend movies/shows to each other.
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Recommendation System
- Generate personalized movie recommendations based on user history and similarity metrics.
- Python microservice handles data processing and returns recommendations via REST API.
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Favorites & Watchlist Management
- Users can add media to their favorites or watchlist.
- Data synchronized with Supabase backend.
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Responsive Frontend
- Modern and accessible UI built in Next.js with responsive design for mobile and desktop.
Matija Akrap – matija.akrap@fer.unizg.hr
Jurica Šlibar – jurica.slibar@fer.unizg.hr
Fran Kramberger – fran.kramberger@fer.unizg.hr
Luka Volarević – luka.volarevic@fer.unizg.hr
Helena Floreani – helena.floreani@fer.unizg.hr
Nora Milolović – nora.milolovic@fer.unizg.hr
David Grabovac – david.grabovac@fer.unizg.hr
This repository contains Open Educational Resources (OER) and is licensed under the Creative Commons license, allowing you to use and share the material under the following terms: Attribution must be given to the authors,
Commercial use is not permitted,
Derivative works must be shared under the same license.Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
