airscholar / AlphaTeam

Complex Network Analysis Using Machine Learning
5 stars 7 forks source link
complex-networks deep-learning gnn graph-theory machine-learning

Alpha Team App

This is the repository for the Alpha Team App. The application is a web application that allows users to visualise and analyse complex networks. The application is built using Flask.

System Architecture

System Architecture

Scientific Paper

Read our scientific paper here.

Running the application locally

  1. Clone the repository
  2. Navigate to the backend directory and run
    • export FLASK_APP=app.py for Linux/Mac or set FLASK_APP=app.py for Windows
  3. Run flask run --host=0.0.0.0 --port=8000 to start the backend server
  4. Open another terminal and navigate to the application directory
  5. Run flask run --host=0.0.0.0 --port={chosen port} to start the frontend server
  6. Open your browser and go to http://127.0.0.1:{chosen port}

Docker Setup

Install Docker and Docker Compose on your machine. You can find the instructions here.

Running the application using Docker

  1. Clone the repository
  2. Run docker build -t alphateamapp . in the root directory of the project to build the Docker image
  3. Run docker run -d -p 8000:8000 -p 3000:3000 --name alphateam alphateamapp to start the application
  4. Open your browser and go to http://127.0.0.1:3000
  5. Enjoy!
  6. (Optional) Run docker logs -f alphateam to see the logs of the container

Alternatively

You can run docker pull airscholar/alphateamapp to pull already built image and then run the container using the command in step 3 above.

Documentation

You can view the documentation in the docs/ directory. The documentation is generated using Sphinx.

To regenerate the documentation

In the root directory of the project, run sh generate_docs.sh to regenerate the documentation.