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Example endpoint configuration for Azure OpenAI

The following example configuration shows the 3 supported endpoints for Azure OpenAI: chat, completions, and embeddings. Additionally, it illustrates the two separate api types that are supported for this service.

  • azure api type: uses a generated token that is applied by setting the API token key directly to an environment variable
  • azuread api type: uses Azure Active Directory for supplying the active directory key to be used to an environment variable

Depending on how your users will be interacting with the MLflow Deployments server, a single access paradigm (either azure or azuread is recommended, not a mix of both).

See the Azure OpenAI configuration YAML file for example configurations showing all supported endpoint types and the different token access types.

Setting the Azure OpenAI API Key

In order to get access to the Azure OpenAI service, see the documentation guidance in the cognitive services portal. With the key, export it to your environment variables.

Replace the '...' with your actual API key:

export OPENAI_API_KEY=...

Validating the Azure OpenAI endpoint

See the OpenAI Example for testing the Azure OpenAI endpoints. The usage is identical to the standard OpenAI integration from an API perspective.