Reel Favorites
(01)
Overview
Reel Favorites is a personalized movie discovery platform helping film enthusiasts find their next favorite movies. In a world overflowing with streaming options, Reel Favorites cuts through the noise to connect users with films they'll truly enjoy based on their unique taste profile.
(02)
Challenge
Modern viewers face "choice paralysis" with thousands of streaming options across multiple platforms. Finding quality content that matches personal preferences has become increasingly difficult, leading to wasted time and disappointing viewing experiences.
(03)
Strategy
Reel Favorites creates a unified discovery experience analyzing user preferences to provide highly targeted recommendations. The platform integrates four distinct APIs:
TMDB API: Comprehensive movie metadata and images
YouTube API: Trailers, interviews, behind-the-scenes content
OpenAI API: Recommendation engine analyzing favorites and patterns
Firebase: User profiles, favorites, and generated recommendations
This multi-API architecture required careful orchestration for performance while providing seamless user experience.
(04)
Technical Solution
Frontend: Next.js with React (SSR for performance)
Styling: Tailwind CSS with dark theme
Authentication: Firebase Authentication
Database: Firestore for profiles and recommendations
APIs: TMDB, YouTube, OpenAI integration
State: React Context with custom hooks
Key features include real-time search, rich media display with embedded trailers, AI-powered recommendations, and cross-device responsive design.
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