Movies Recommendation System

• Description
• Prerequisites
• Installation
• Usage
• Contributing

Description

This is a project for the subject Artificial Intelligence in Marketing. The goal of this project is to collect movie data from the TMDB API, process it, and build a recommendation system using content-based filtering. Finally, the system visualizes and displays information for movies similar to the input movie.

Prerequisites

1. Python
2. TMDB API_KEY. Sign up at TMDB page.

Installation

1. Clone the Repository

git clone https://github.com/truongvude/recommendation_system.git
cd recommendation_system

2. Set up a Virtual Environment:

python -m venv .venv
source .venv/bin/activate   # For Unix/macOS
# or
.venv\Scripts\activate      # For Windows

3. Install Dependencies

pip install -r requirements.txt

4. Configure Environment Variables

Create your .env file using the provided example:

mv .env_example .env

Then open .env and insert your TMDB API key:

nano .env   # Or use any text editor of your choice

Usage

1. Run main.py

python3 src/main.py

2. Run app.py with Streamlit

streamlit run src/app.py

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.