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🎬 Movie Website

Background

Welcome to the Movie Website project! Dive into a world where you can watch movie trailers, provided you have a subscription, and enjoy personalized movie recommendations. Our recommendation system uses gradient episodic memory model to ensure real-time updates and the most relevant suggestions.

🌟 Features

  • Exclusive Trailer Access: Only subscribed users can enjoy our movie trailers.
  • Smart Recommendations: Our system delivers personalized movie recommendations using advanced machine learning techniques.

Contributors

📚 Table of Contents

🚀 Installation

Prerequisites

Make sure you have the following installed:

  • Docker
  • Miniconda
  • Nodejs

Steps

  1. Clone the Repository

    git clone https://github.com/Vnn04/movie_website.git
    cd movie_website
  2. Set Up the Server

    • Navigate to the server directory:
      cd server
    • Run the server using Docker Compose:
      docker-compose up
  3. Set Up the Recommendation System

    • Navigate to the recommendationSystem directory:
      cd ../recommendationSystem
    • Create a new Conda environment and activate it:
      conda create --name mlops-env python=3.12
      conda activate mlops-env
    • Install the required libraries:
      pip install -r requirement.txt
    • Run the application:
      python app.py
  4. Finalize the Server Setup

    • First, in folder server add file .env and paste content in file .env.example into it, fill the missing infomation. with MAIL_USERNAME= your_email (Your email has 2-layer security) MAIL_PASSWORD= your_password(app passwrod or your password of your email), MAIL_FROM_ADDRESS= your_email (Your email has 2-layer security), SECRET_API_GG_IMG_KEY= your_api_google_image_key.
    • Navigate back to the server directory:
      cd ../server
    • Install the necessary Node.js packages:
      npm install
    • Start the server:
      npm start
    • Open your browser and go to http://localhost:8080 to view the application.

📖 Usage

Once installed, launch the application by navigating to http://localhost:8080. Users can sign up, subscribe, and start watching exclusive movie trailers. Our recommendation system will tailor suggestions to each user's preferences based on their viewing history.

🛠️ Technologies Used

  • Frontend: HTML, CSS, JavaScript
  • Backend: Node.js, Express
  • Database: Mysql
  • Recommendation: Python, Gradient Episodic Memory
  • Containerization: Docker
  • Environment Management: Conda

🤝 Contributing

We welcome contributions from the community! If you have ideas to enhance the Movie Website, follow these steps:

  1. Fork the repository.
  2. Create a new branch (git checkout -b feature/your-feature).
  3. Make your changes and commit them (git commit -m 'Add new feature').
  4. Push the changes to your branch (git push origin feature/your-feature).
  5. Open a Pull Request for review.

Please ensure your contributions adhere to our coding standards and include necessary tests.

📜 License

This project is licensed under the MIT License. For more details, see the LICENSE file.


Thank you for choosing Movie Website! We hope you enjoy an exceptional, personalized movie trailer experience.