The purpose of this program is to recommend the movie title that the user should watch next, based on the similarity to the movie they have just watched. It makes a suggestion from a list of movies available in a file.
The program makes this suggestion of what to watch next based on word vector similarity of the description of the available movies to the movie watched.
There are two different ways to run the program: using Docker or a virtual environment.
You can either use docker on your desktop or by using Docker Playground. Descriptions for using both options are included.
Run container using Desktop
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If you don't already have Docker installed on your desktop, install Docker on your desktop.
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Once installed, enter the following command in the terminal:
docker run -i bonolor/movie-watch_next-ai
Run container using Docker Playground
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Go to Docker Playground at the following link and enter "Start": https://labs.play-with-docker.com/.
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Add a new instance.
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Enter the following command in the terminal:
docker run -i bonolor/movie-watch_next-ai
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Download the followiing files in the repository.
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Create a project folder named "watch_next".
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Move and save the downloaded files to the watch_next folder.
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Open your local Integrated Development Environment (IDE) such as VSCode.
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Add the watch_next folder to your IDE.
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In the same parent directory, create a virtual environment named .venv by entering the following command in the terminal (use relevant python version):
python3.11 -m venv .venv
- Activate the virtual environment using the following command (for macOS):
source .venv/bin/activate
- Once the virtual environment is created and activated, enter the following command to move into the garden_ai directory (if you are not already in the directory):
cd watch_next
- Run the requirements.txt file to install all the relevant packages:
pip install -r requirements.txt
- If prompted to upgrade pip, enter:
pip install --upgrade pip
- Install language model:
python -m spacy download en_core_web_md
Note: Check to ensure that the virtual environment has been activated
- Select watch_next.py and run the program.
Movie description of movie just watched:
Available movies the program analyses to find the most similar to the movie just watched:
Output recommended movie to watch next:
This program has been developed by Bonolo Ramasedi.
This project is not licensed and is intended for display purposes only. All rights reserved. No usage, distribution, or modification rights are granted.