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🎬 FlixMood - AI Content Recommendation System

Streamlit App Live Demo Python License

Netflix–YouTube–Spotify Style Recommender with Mood-Aware AI Recommendations

🌐 Try the Live Demo →

🎯 What is FlixMood?

FlixMood is an AI-powered content recommendation system that understands your mood, context, and preferences to suggest the perfect movie or TV show. Just like how Netflix and Spotify personalize your experience!

✨ Key Features

Feature Description
🎭 Mood-Based Recommendations Select your current mood and get personalized suggestions
🕐 Time-Aware Recommendations adapt to time of day (morning, afternoon, evening, night)
👥 Context-Aware Different suggestions for solo watching, date night, family time, or friend parties
⚡ Energy Matching High adrenaline, relaxed vibes, intense & deep, or light & fun
🎲 Surprise Me! Random pick with a fun balloon animation
📱 Screen Size Tips Smart suggestions based on your viewing device
🔀 Hybrid AI Engine Combines SVD + TF-IDF for optimal accuracy

🏗️ System Architecture

┌─────────────────────────────────────────────────────────────┐
│                       USER INPUT                             │
│  Mood 🎭  │  Context 👥  │  Energy ⚡  │  Filters 🎚️        │
└─────────────────────────┬───────────────────────────────────┘
                          │
                          ▼
┌─────────────────────────────────────────────────────────────┐
│                  AI RECOMMENDATION ENGINE                    │
├─────────────────────────────────────────────────────────────┤
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────────────┐  │
│  │     SVD     │  │   TF-IDF    │  │   Mood Mapping     │  │
│  │ Collaborative│  │  Content    │  │   + Time Context   │  │
│  │  Filtering  │  │   Based     │  │   + Energy Boost   │  │
│  └──────┬──────┘  └──────┬──────┘  └─────────┬───────────┘  │
│         └────────────────┼────────────────────┘              │
│                          ▼                                   │
│              ┌───────────────────┐                           │
│              │  HYBRID ENSEMBLE  │                           │
│              │   (Weighted Mix)  │                           │
│              └─────────┬─────────┘                           │
└────────────────────────┼────────────────────────────────────┘
                         ▼
        ┌────────────────────────────────────┐
        │    🎬 PERSONALIZED RECOMMENDATIONS  │
        │    with Match Percentage Scores    │
        └────────────────────────────────────┘

🛠️ Technology Stack

Component Technology
Frontend Streamlit with Custom CSS
ML/AI Scikit-learn, NumPy, Pandas
Visualization Plotly, Seaborn
Algorithms SVD (Matrix Factorization), TF-IDF
Dataset Netflix Shows (6,234 titles)

🚀 Quick Start

Local Installation

# Clone the repository
git clone https://github.com/YOUR_USERNAME/flixmood.git
cd flixmood

# Install dependencies
pip install -r requirements.txt

# Run the app
streamlit run app.py

Access the App

Open your browser and navigate to: http://localhost:8501

📊 Dataset

Using Netflix Shows dataset from Kaggle:

  • 6,234 Movies & TV Shows
  • 500 Synthetic Users (for collaborative filtering)
  • 13,000+ Ratings

📈 Model Performance

Metric Value Description
RMSE ~1.38 Root Mean Square Error
Accuracy ~72% Prediction accuracy
Coverage 95%+ Catalog coverage

🎭 Mood Categories

Mood Genre Mapping
😊 Happy & Uplifting Comedies, Family, Animation
😢 Emotional & Moving Dramas, Romance, Independent
😱 Thrilling & Scary Horror, Thrillers, Crime
🤔 Mind-Bending Sci-Fi, Fantasy, Documentary
💪 Action Packed Action, Adventure, Martial Arts
❤️ Romantic Romance, Romantic Comedy
👨‍👩‍👧‍👦 Family Friendly Kids, Animation, Family
🧠 Educational Documentary, Science, History
😎 Casual & Chill Stand-Up, Reality, Variety

🌐 Deployment

Deploy to Streamlit Cloud (Free)

  1. Push your code to GitHub
  2. Go to share.streamlit.io
  3. Connect your repository
  4. Select app.py as main file
  5. Deploy! 🚀

Environment Variables

No environment variables required! The app automatically downloads the dataset.

📁 Project Structure

flixmood/
├── app.py                 # Main Streamlit application
├── requirements.txt       # Python dependencies
├── README.md              # This file
├── .streamlit/
│   └── config.toml        # Streamlit configuration
├── src/
│   ├── data_loader.py     # Dataset handling
│   ├── eda.py             # Exploratory analysis
│   ├── collaborative.py   # SVD recommender
│   ├── content_based.py   # TF-IDF recommender
│   ├── hybrid.py          # Ensemble methods
│   └── evaluation.py      # Metrics
├── data/                  # Generated data
└── models/                # Saved models

📝 License

MIT License - feel free to use and modify!

🙏 Acknowledgments

  • Netflix Shows Dataset by Shivam Bansal
  • Streamlit for the amazing framework
  • Scikit-learn community
Built with ❤️ for IIT Project
FlixMood - Because every mood deserves the perfect movie!