PopcornPicks

PopcornPicks is a movie recommender web app built with Streamlit. Select a movie you like and get personalized recommendations with detailed information and posters.

Features

• Movie selection from a curated list
• Top 5 similar movie recommendations
• Movie details: overview, genres, rating, release date, runtime, and poster
• Direct links to TMDb pages

Project Structure

.
├── app.py                # Main Streamlit app
├── requirements.txt      # Python dependencies
├── setup.sh              # Heroku setup script
├── procfile              # Heroku process file
├── .slugignore           # Heroku slugignore file
├── assets/
│   └── more_info.jpg     # Fallback image
├── models/
│   ├── movies_dict.pkl   # Movie metadata
│   └── similarity.pkl    # Similarity matrix
└── ml-model-training/    # Model training notebooks and data (not deployed)

Getting Started

Local Development

1. Clone the repository

   git clone <repo-url>
   cd movie-recommender-app

2. Install dependencies

   pip install -r requirements.txt

3. Run the app

   streamlit run app.py

Deploy on Heroku

1. Ensure you have a Heroku account and the Heroku CLI installed.

2. Login to Heroku

   heroku login

3. Create a new Heroku app

   heroku create your-app-name

4. Deploy

   git push heroku main

Notes

• The ml-model-training folder contains Jupyter notebooks and raw data for model building. It is excluded from deployment.
• The app uses precomputed model files in the models/ directory.

License

This project is for educational purposes.