bot-sense

Twitter bot detection project for KSU SWE7903

Project Structure

The project utilizes docker images to separate the services

• bot-ui (front-end)
• bot-int-services (integration services)
• bot-ml (machine learning)

Local Deployment with Docker

1. CD to bot-build

2. Edit the docker-compose.yml file to reflect your local directories

   • For Windows, make sure to include the full path and escape backslashes (e.g. C:\\Workspace\\bot-sense\\...)

3. Run the below to build the docker containers

   docker-compose build

4. Run the below to run the containers...

   docker-compose up

5. Open browser and navigate to:

   http://localhost:5001 (ML test screen)

   http://localhost:3000 (Web landing screen)

Local Deployment of Services

To test services individually and outside of Docker, you can simply install the requirements and run each service in its own terminal session as shown below:

1. For bot-ml and bot-int-services, install the requirements and launch the Flask app.

   cd bot-ml/int-services
   python3 -m pip install -r requirements.txt
   python3 app.py
   

   Check the corresponding server in http://localhost:5000/5001

2. For the UI portion, ensure you jave NodeJS installed and npm package manager

   cd bot-ui
   npm install
   npm start
   

   Check the front-end in http://localhost:3000

Having all three services running you can now use the app locally.