ML-Server

Installation

Setting up the ML-Server if you follow the instructions laid out below:

• Create a virtual-environment for the application, ensure it is a python3 environment
• Install the project's dependencies with the command pip install -r requirements.txt via your terminal
• You can make a copy of the .env.sample file and name it .env and in this file you set the PORT to your choice.
• After this is done, you can start the application with the command python main.py via your terminal

Endpoints

The following Endpoints are available:

Emulate ML Model

POST HTTP Request

• POST /ml INPUT: As defined in input_data.json

  HTTP Response

• HTTP Status: 200: OK
• JSON data

{
  "data": [
    {
      "Predict": 1,
      "Userid": 1
    },
    {
      "Predict": 0,
      "Userid": 2
    }
  ]
}

POST HTTP Request

• POST /login INPUT: As defined in input_data.json

  HTTP Response

• HTTP Status: 200: OK
• JSON data

{
  "openid": "<open-id>"
}