API-Guides:

Guides and Example Code for FairNow API's.

Prerequisites

To use these guides, you will need a client_id and client_secret, which you can generate by logging into your account on https://app.fairnow.ai as an Admin or Model Owner, and going to the Admin menu.

The code examples in the notebooks require several libraries to be installed into your notebook environment. This can be done by running from the root directory:

pip install -r requirements.txt

Overview

Each of the notebooks found under the /notebooks directory is intended to be a working example on how to use the FairNow API's. The recommended order is:

1. Getting Started - demonstrates how to configure authorization and make a first API call.
2. Applications API - create and read an AI Application with the API. AI Applications are a core building block for the FairNow system.
3. Generating Synthetic User Bias Test Data - construct a synthetic test data file to be used to simulate ML model bias evaluation. Constructing synthetic data is optonal.
4. User Data Testing - how to perform ML model bias testing via the API.

Note to contributors:

Please use the following to prevent output/metadata from the notebook to be pushed to github:

pip install nbstripout
nbstripout --install