Creating an Endpoint

Warning

Azure AI Foundry has deprecated model deployments based on MLflow. New deployments, including that of Aurora 1.5, package the server-side code into a custom model and container image. Aurora remains available on Foundry for all previous checkpoints, while the new model Aurora-1.5 is available with a custom model. This repository contains the necessary client-side code to call and endpoint deployed with Foundry but does not currently support building your own endpoint, and as such this page is deprecated.

Likely you don’t need to create an endpoint yourself, because Aurora is already available in the Azure AI model catalog.

Nevertheless, should you want to create an endpoint, then you can follow these instructions. The model is served via MLflow. First, make sure that mlflow is installed:

pip install mlflow

Then build the MLflow model as follows:

python package_mlflow.py