Reel Rec

Reel Rec - A Movie Recommendation AI designed to change the way movie enthusiasts discover and enjoy favorite films.

Table of Contents

• Overview
• Requirement Specifications/Tech Stack
• Installation
• Screenshots
• Usage
• License
• Attributions
• Planned Future Updates
• Contributing
• Contact

Overview

Reel Rec is a content-based recommendation AI developed as a web application using Django & Tailwind CSS for smooth user experience. Users also signup and receive movie recommendations by simply selecting a movie they're familiar with without restrictions on genre, actor, release date, or film industry & receive Personalized Recommendations. After receiving the recommendations, users have the option to view movie details, watch the trailer through YouTube.

Requirement Specifications / Tech Stack

• Languages: Python, Javascript
• Frameworks: Tailwind CSS & Django
• Database: MySQL
• Libraries: Barba JS & GSAP
• API: TMDB API

Installation

There are two ways to setup Reel-Rec on your local machine.

1. Easy Install using Batch Script [Windows only] (Recommended)

1. Clone the repository:

   git clone https://github.com/MohitBharambe/Reel-Rec.git
   

2. Run the following commands in the terminal:

   cd Reel-Rec
   install.bat
   

3. The Script will automatically create a virtual environment, install the required dependencies & start the app.

2. Manual Installation [Windows, MacOS, Linux]

1. Clone the repository:

   git clone https://github.com/MohitBharambe/Reel-Rec.git
   cd Reel-Rec
   

2. Create & Activate a Virtual Environment (optional):

   python -m venv env # Create
   source env/bin/activate  # for MACOS
   env\Scripts\activate # for Windows
   

3. Install the requirements:

   pip install -r requirements.txt
   

4. In MySQL Shell, Create a database named reel_rec:

   create database reel_rec;
   

5. Create a .env file at the root level of the directory with the following variables and assign the respective values:

   SECRET_KEY=<any_random_alphanumeric_key>
   MYSQL_USER=<your_mysql_user>
   MYSQL_PASSWORD=<your_mysql_password>
   bearer_token=<your_tmdb_bearer_token>
   

6. Inside the Models directory Run the algorithm.ipynb file Using Jupyter Notebook to generate the Model's files.

7. Perform migrations:

   python manage.py makemigrations
   python manage.py migrate
   

8. Create a Admin User(optional):

   python manage.py createsuperuser
   

9. Run the server:

   python manage.py runserver
   

10. If the shell output is Similar to the one below , The app can now be accessed at http://127.0.0.1:8000

    Watching for file changes with StatReloader
    Performing system checks...
    
    System check identified no issues (0 silenced).
    December 10, 2024 - 15:44:16
    Django version 5.1.4, using settings 'Reel_Rec.settings'
    Starting development server at http://127.0.0.1:8000/
    Quit the server with CTRL-BREAK.
    

Screenshots

1 - Select familiar Movies

2 - Get Recommendations

FAQ Page

Usage

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Attributions

This product uses the TMDB API but is not endorsed or certified by TMDB.

• TMDB API
• Dataset Used

Planned Future Updates

• Get Recommendations based on User's Mood.
• Add a feature to save favorite movies.

Contributing

Thank you for considering contributing to Reel Rec! refer the contributing.md file for making a contribution.

Contact

• Github:

  https://github.com/MohitBharambe

• Email Address:

  mohitbharambe0@outlook.com