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Azure OpenAI vectorizer

The Azure OpenAI vectorizer connects to an embedding model deployed to your Azure OpenAI resource or Azure AI Foundry project to generate embeddings at query time. Your data is processed in the Geo where your model is deployed.

Although vectorizers are used at query time, you specify them in index definitions and reference them on vector fields through a vector profile. For more information, see Configure a vectorizer in a search index.

The Azure OpenAI vectorizer is called AzureOpenAIVectorizer in the REST API. Use the latest stable version of Indexes - Create (REST API) or an Azure SDK package that provides the feature.

Note

This vectorizer is bound to Azure OpenAI and is charged at the existing Azure OpenAI Standard price.

Prerequisites

  • An Azure OpenAI in Azure AI Foundry Models resource or Azure AI Foundry project.

    • Your Azure OpenAI resource must have a custom subdomain, such as https://<resourcename>.openai.azure.com. If you created the resource in the Azure portal, this subdomain was automatically generated during resource setup.

    • Your Azure AI Foundry project should have an Azure AI services endpoint with the cognitiveservices.azure.com domain. After you deploy an Azure OpenAI embedding model to the project, you must change the endpoint to use the openai.azure.com domain. For example, change the endpoint from https://<resourcename>.cognitiveservices.azure.com to https://<resourcename>.openai.azure.com. You can then use this updated endpoint for the resourceUri property in this vectorizer.

  • An Azure OpenAI embedding model deployed to your resource or project. For supported models, see the next section.

Vectorizer parameters

Parameters are case-sensitive.

Parameter name Description
resourceUri The URI of the model provider. This parameter only supports URLs with the openai.azure.com domain, such as https://<resourcename>.openai.azure.com. Azure API Management endpoints are supported with URL https://<resourcename>.azure-api.net. Shared private links aren't supported for API Management endpoints.
apiKey The secret key used to access the model. If you provide a key, leave authIdentity empty. If you set both the apiKey and authIdentity, the apiKey is used on the connection.
deploymentId The name of the deployed Azure OpenAI embedding model. The model should be an embedding model, such as text-embedding-ada-002. See the List of Azure OpenAI models for supported models.
authIdentity A user-managed identity used by the search service for connecting to Azure OpenAI. You can use either a system or user managed identity. To use a system managed identity, leave apiKey and authIdentity blank. The system-managed identity is used automatically. A managed identity must have Cognitive Services OpenAI User permissions to send text to Azure OpenAI.
modelName (Required in API version 2024-05-01-Preview and later). The name of the Azure OpenAI embedding model that is deployed at the provided resourceUri and deploymentId. Currently, supported values are text-embedding-ada-002, text-embedding-3-large, and text-embedding-3-small.

Supported vector query types

The Azure OpenAI vectorizer only supports text vector queries.

Expected field dimensions

The expected field dimensions for a field configured with an Azure OpenAI vectorizer depend on the modelName that is configured.

modelName Minimum dimensions Maximum dimensions
text-embedding-ada-002 1536 1536
text-embedding-3-large 1 3072
text-embedding-3-small 1 1536

Sample definition

"vectorizers": [
    {
        "name": "my-openai-vectorizer",
        "kind": "azureOpenAI",
        "azureOpenAIParameters": {
            "resourceUri": "https://my-fake-azure-openai-resource.openai.azure.com",
            "apiKey": "0000000000000000000000000000000000000",
            "deploymentId": "my-ada-002-deployment",
            "authIdentity": null,
            "modelName": "text-embedding-ada-002",
        },
    }
]

See also