Microsoft Azure cloud supports OpenAI models.
Translate5 OpenAI plugin proposes integration with the Microsoft Azure cloud as well. This documentation page contains configuration and implementation details important for plugin to be used.
Configs
Azure has its own specific configs:
All config values can be found in https://portal.azure.com/.
runtimeOptions.plugins.OpenAI.Azure.subscriptionId - is an id of the subscription used for the application - Home > Subscriptions
runtimeOptions.plugins.OpenAI.Azure.resourceGroupName - name of the resource group used for the application - Search > Resource groups
runtimeOptions.plugins.OpenAI.Azure.accountName - account name which is also used as a part of custom domain name - All resources > Create > AI + Machine learning > Azure OpenAI > Create
runtimeOptions.plugins.OpenAI.Azure.tenantId - Directory (tenant) id - Search > Microsoft Entra ID > Manage > App registrations > %YOUR APP% > Overview
runtimeOptions.plugins.OpenAI.Azure.clientId - Application (client) id - Search > Microsoft Entra ID > Manage > App registrations > %YOUR APP% > Overview
runtimeOptions.plugins.OpenAI.Azure.clientSecret - Client secret for accessing resource management - Search > Microsoft Entra ID > Manage > App registrations > %YOUR APP% > Manage > Certificates and secrets
Implementation details
After language resource is created - translate5 automatically creates a deployment of the selected model in Azure cloud. Deployment name will contain translate5 language resource id for ease identifying.
When finetuning a model - a new deployment is created after fine tuning is completed. Please note that Azure documentation says: After you deploy a customized model, if at any time the deployment remains inactive for greater than fifteen (15) days, the deployment is deleted. The deployment of a customized model is inactive if the model was deployed more than fifteen (15) days ago and no completions or chat completions calls were made to it during a continuous 15-day period. The deletion of an inactive deployment doesn't delete or affect the underlying customized model, and the customized model can be redeployed at any time.