🎬 CineMind - Your Personal Cinema Companion

A modern, AI-powered movie recommendation app that understands your mood and story preferences. Built with Next.js 16, featuring a cinematic dark theme and emotionally intelligent recommendations.

✨ Features

• Story-Based Recommendations - Choose from 10 unique story types like "Revenge & Passion", "Forbidden Romance", "Brilliant Minds"
• Rotating Daily Picks - Fresh recommendations that change every 6 hours
• Multi-Industry Support - Hollywood, Bollywood, South Indian, Korean, and International cinema
• 10+ Indian Languages - Hindi, Tamil, Telugu, Malayalam, Kannada, and more
• Cinematic UI - Premium dark theme with film grain, vignette effects, and smooth animations
• Smart Ranking Engine - Multi-signal scoring with story alignment, quality metrics, and freshness

🚀 Getting Started

Prerequisites

• Node.js 18+
• npm or yarn
• TMDB API Key (Get one here)
• OMDb API Key (Get one here)

Installation

1. Clone the repository:

git clone https://github.com/rupesh1787/CineMind.git
cd CineMind/cinemind

2. Install dependencies:

npm install

3. Create a .env.local file in the root directory:

TMDB_API_KEY=your_tmdb_api_key_here
OMDB_API_KEY=your_omdb_api_key_here

4. Run the development server:

npm run dev

5. Open http://localhost:3000 in your browser.

🏗️ Tech Stack

• Framework: Next.js 16 with App Router
• Language: TypeScript
• Styling: Tailwind CSS 4.0
• APIs: TMDB (The Movie Database), OMDb
• Deployment: Vercel (recommended)

📁 Project Structure

cinemind/
├── app/                    # Next.js app router pages
│   ├── api/               # API routes
│   │   ├── movie/[id]/    # Movie details endpoint
│   │   ├── recommend/     # AI recommendation engine
│   │   └── top/           # Trending & daily picks
│   ├── movie/[id]/        # Movie detail page
│   ├── results/           # Recommendations results page
│   └── page.tsx           # Home page
├── lib/                    # Core logic
│   ├── recommendationEngine.ts   # Main orchestrator
│   ├── storyIntelligence.ts     # Story pattern matching
│   ├── candidatePool.ts         # Multi-source fetching
│   ├── rankingEngine.ts         # Weighted scoring
│   └── curation.ts              # Result organization
├── components/             # React components
├── types/                  # TypeScript definitions
└── data/                   # Static data (genres, moods)

🎯 How It Works

1. Story Selection - Choose 1-2 story types that match your mood
2. Preference Tuning - Set your vibe, time available, language, and cinema world
3. AI Curation - The engine analyzes 150+ candidates using:
   • Theme pattern matching
   • Quality signals (IMDb rating, vote count, popularity)
   • Freshness scoring
   • Runtime fit
   • Regional relevance
4. Personalized Results - Get your top pick, story matches, hidden gems, and a surprise pick

🌐 Deployment

Deploy to Vercel (Recommended)

1. Push to GitHub
2. Import to Vercel
3. Add environment variables (TMDB_API_KEY, OMDB_API_KEY)
4. Deploy!

Manual Deployment

npm run build
npm start

🔑 Environment Variables

Variable	Description	Required
TMDB_API_KEY	The Movie Database API key	Yes
OMDB_API_KEY	Open Movie Database API key	Yes

📝 License

This project is open source and available under the MIT License.

🙏 Acknowledgments

• TMDB for the movie database
• OMDb for IMDb ratings
• Vercel for hosting

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Built with ❤️ for movie lovers