Description

Leverages Gemini AI and TMDB to provide personalized recommendations, built with Next.js 13 + TypeScript.

How I Made It

• Developed using Next.js 13 with App Router and TypeScript for type-safe, server-side rendering.
• Implemented Tailwind CSS for responsive design and custom animations.
• Integrated Google's Gemini AI for intelligent content analysis and recommendations.
• Connected to TMDB API for comprehensive movie and TV show data.
• Used Prisma with PostgreSQL for efficient data management.
• Implemented user authentication with NextAuth.js.
• Deployed on Vercel with automated CI/CD pipeline.

Challenges Faced

• Optimizing AI response parsing for accurate movie recommendations.
• Managing complex state for multi-user recommendation sessions.
• Implementing efficient caching strategies for API responses.
• Handling multiple language support and regional content preferences.

Key Wins

• Created an intuitive UI for a solo mode. (Coded future options to build a group movie selection mode)
• Achieved high accuracy in personalized recommendations.
• Implemented robust error handling and fallback mechanisms.
• Successfully integrated multiple external APIs with rate limiting.
• Developed a scalable architecture for future feature additions.