DanDovhun / Title-Classer

TitleClasser is an AI powered tool to help newspapers, blogging services and writters classify content into categories

TitleClasser

Address: https://title-classer-43bc9ae7d642.herokuapp.com/

Description

The purpose of this project is to automate classification of articles into a specific category. The size of the text can vary from the first paragraph to the entire article.

Our labels are:

• 0 (Politics)
• 1 (Sport)
• 2 (Technology)
• 3 (Entertainment)
• 4 (Business)

To classify the articles we're using logistic regression with the help One-vs-Rest method since the output isn't a simple binary classification of yes or no, a placemement into one of 5 labels.

Run

1.) Clone directory

Via SSH:

git clone [e-mail]:AI-Project-Reexam/TitleClasser.git

Via HTTPS:

git clone https://github.com/AI-Project-Reexam/TitleClasser.git

Run

Move to the app folder:

cd path/to/TitleClasser/app

a.) Docker

Assuming you already have docker installed on your machine, you can just follow these steps:

Build your own container

1.) Build the image:

// Pull python:3.11 image
docker pull python:3.11

// Build title_classer image
docker build -t title_classer .

2.) Run:

docker run -it -e "PORT=8000" -p 8000:8000 title_classer:latest

b.) Outside of Docker:

0.) Create Conda environment

// Create venv
conda create -n title-classer

// Activate
conda activate title-classer

1.) Get packages:

Get packages that had issues being in requirements.txt:

pip install -U pip setuptools wheel
pip install -U spacy
python -m spacy download en_core_web_sm 
python -m pip install tensorflow
pip install seaborn

Rest of the requirements:

pip install --no-cache-dir -r requirements.txt

Run the application:

python manage.py runserver

Deployment on Heroku:

Deployment:

Address: See the address on top of the document

Login to Heroku:

heroku login

Login to Heroku's Container Registry:

heroku container:login

Create app:

We already took this name and the name won't work for anyone else if they try running this command verbatim. This is only to demonstrate how the application was created in Heroku

heroku apps:create title-classer

Build, push and deploy Docker container:

// Build and push the container
heroku container:push -a title-classer web

// Deploy the container
heroku container:release -a title-classer web

When the container is deployed the app will restart will take about 60 seconds to be running again.

Using the Shell Script

There is a shell script located in the root of the repository named deploy.sh. This shell script was added to streamline building and running the docker image and deploying the docker image to Heroku. To run the script use these commands:

// Make the script executable:
chmod +x deploy.sh

// Run the script:
./deploy.sh [ ARGUMENT_1 ]

The arguments are necessary to run the script so it would know which set of commands it should run. Here are the accepted arguments:

NOTE: some arguments must be followed by another to work

• --deploy

  • Push a docker containter to Heroku and release it on the title-classer app on heroku
  • This should and can only be by the group

• --deploy-new [ APP_NAME ]

  • Create your own app on Heroku and deploy a container there

• --build [IMAGE_NAME]

  • Build a Docker image on your machine

• --run [ IMAGE_NAME ] [ PORT ]

  • Run the Docker image

NOTE: This is an UNX shell script, while it may work on Linux or Mac, it may not work on Windows' native command line*

Tools and Technologies:

• Website:

  • Django
  • SQLite

• Preprocessing:

  • spaCy
  • en_core_web_sm

• AI Model:

  • Pandas
  • SQLite
  • scikit-learn
  • Tensorflow
  • Numpy

Contributors:

• Aditya Nair
• Daniel Dovhun