Create an Azure OpenAI inference endpoint

Auth

Create an inference endpoint to perform an inference task with the azureopenai service.

The list of chat completion models that you can choose from in your Azure OpenAI deployment include:

The list of embeddings models that you can choose from in your deployment can be found in the Azure models documentation.

Required authorization

Cluster privileges manage_inference

Path parameters

task_type enum required

The type of the inference task that the model will perform. NOTE: The chat_completion task type only supports streaming and only through the _stream API.

Values: completion chat_completion text_embedding
azureopenai_inference_id string required

The unique identifier of the inference endpoint.

Query parameters

timeout string · default: 30s

Specifies the amount of time to wait for the inference endpoint to be created.

Request body

chunking_settings object

The chunking configuration object. Applies only to the text_embedding task type. Not applicable to the completion and chat_completion task types.

Reference
max_chunk_size number · default: 250

The maximum size of a chunk in words. This value cannot be lower than 20 (for sentence strategy) or 10 (for word strategy). This value should not exceed the window size for the associated model.

overlap number · default: 100

The number of overlapping words for chunks. It is applicable only to a word chunking strategy. This value cannot be higher than half the max_chunk_size value.

sentence_overlap number · default: 1

The number of overlapping sentences for chunks. It is applicable only for a sentence chunking strategy. It can be either 1 or 0.

separator_group string

Only applicable to the recursive strategy and required when using it.

Sets a predefined list of separators in the saved chunking settings based on the selected text type. Values can be markdown or plaintext.

Using this parameter is an alternative to manually specifying a custom separators list.

separators string[]

Only applicable to the recursive strategy and required when using it.

A list of strings used as possible split points when chunking text.

Each string can be a plain string or a regular expression (regex) pattern. The system tries each separator in order to split the text, starting from the first item in the list.

After splitting, it attempts to recombine smaller pieces into larger chunks that stay within the max_chunk_size limit, to reduce the total number of chunks generated.

strategy string · default: sentence

The chunking strategy: sentence, word, none or recursive.

  • If strategy is set to recursive, you must also specify:
  • max_chunk_size
  • either separators orseparator_group

Learn more about different chunking strategies in the linked documentation.

Reference
service enum required

The type of service supported for the specified task type. In this case, azureopenai.

Values: azureopenai
service_settings object required

Settings used to install the inference model. These settings are specific to the azureopenai service.

api_key string

A valid API key for your Azure OpenAI account.

Important

You must specify either api_key, entra_id, or client_secret. If you do not provide one or you provide more than one of them, you will receive an error when you try to create your endpoint.

External docs
api_version string required

The Azure API version ID to use. It is recommended to use the latest supported non-preview version.

client_id string

For OAuth 2.0 authorization using the client credentials grant flow. The application ID that's assigned to your app.

Important

To configure OAuth 2.0, you must specify client_id, scopes, tenant_id, and client_secret together. If one of the fields is missing, you will receive an error when you try to create your endpoint.

External docs
client_secret string

For OAuth 2.0 authorization using the client credentials grant flow. The application secret that you created in the Microsoft app registration portal for your app.

Important

You must specify either api_key, entra_id, or client_secret. If you do not provide one or you provide more than one of them, you will receive an error when you try to create your endpoint.

Important

To configure OAuth 2.0, you must specify client_id, scopes, tenant_id, and client_secret together. If one of the fields is missing, you will receive an error when you try to create your endpoint.

External docs
deployment_id string required

The deployment name of your deployed models. Your Azure OpenAI deployments can be found though the Azure OpenAI Studio portal that is linked to your subscription.

External docs
entra_id string

A valid Microsoft Entra token.

Important

You must specify either api_key, entra_id, or client_secret. If you do not provide one or you provide more than one of them, you will receive an error when you try to create your endpoint.

External docs
rate_limit object

This setting helps to minimize the number of rate limit errors returned from Azure. The azureopenai service sets a default number of requests allowed per minute depending on the task type. For text_embedding, it is set to 1440. For completion and chat_completion, it is set to 120.

External docs
requests_per_minute number

The number of requests allowed per minute. By default, the number of requests allowed per minute is set by each service as follows:

  • alibabacloud-ai-search service: 1000
  • amazonbedrock service: 240
  • anthropic service: 50
  • azureaistudio service: 240
  • azureopenai service and task type text_embedding: 1440
  • azureopenai service and task types completion or chat_completion: 120
  • cohere service: 10000
  • contextualai service: 1000
  • elastic service and task type chat_completion: 240
  • fireworksai service: 6000
  • googleaistudio service: 360
  • googlevertexai service: 30000
  • hugging_face service: 3000
  • jinaai service: 2000
  • llama service: 3000
  • mistral service: 240
  • openai service and task type text_embedding: 3000
  • openai service and task type completion: 500
  • openshift_ai service: 3000
  • voyageai service: 2000
  • watsonxai service: 120
resource_name string required

The name of your Azure OpenAI resource. You can find this from the list of resources in the Azure Portal for your subscription.

External docs
scopes string[]

For OAuth 2.0 authorization using the client credentials grant flow. The resource identifier (application ID URI) of the resource you want, suffixed with .default For example:

"scopes": [
  "https://cognitiveservices.azure.com/.default"
]
Important

To configure OAuth 2.0, you must specify client_id, scopes, tenant_id, and client_secret together. If one of the fields is missing, you will receive an error when you try to create your endpoint.

External docs
tenant_id string

For OAuth 2.0 authorization using the client credentials grant flow. The directory tenant the application plans to operate against.

Important

To configure OAuth 2.0, you must specify client_id, scopes, tenant_id, and client_secret together. If one of the fields is missing, you will receive an error when you try to create your endpoint.

External docs
task_settings object

Settings to configure the inference task. These settings are specific to the task type you specified.

user string

Specifies the user issuing the request. This information can be used for abuse detection.

headers map string to string

Specifies custom HTTP header parameters. For example:

"headers": {
  "Custom-Header": "Some-Value",
  "Another-Custom-Header": "Another-Value"
}

Response

application/json
chunking_settings object

The chunking configuration object. Applies only to the embedding, sparse_embedding and text_embedding task types. Not applicable to the rerank, completion, or chat_completion task types.

max_chunk_size number · default: 250

The maximum size of a chunk in words. This value cannot be lower than 20 (for sentence strategy) or 10 (for word strategy). This value should not exceed the window size for the associated model.

overlap number · default: 100

The number of overlapping words for chunks. It is applicable only to a word chunking strategy. This value cannot be higher than half the max_chunk_size value.

sentence_overlap number · default: 1

The number of overlapping sentences for chunks. It is applicable only for a sentence chunking strategy. It can be either 1 or 0.

separator_group string

Only applicable to the recursive strategy and required when using it.

Sets a predefined list of separators in the saved chunking settings based on the selected text type. Values can be markdown or plaintext.

Using this parameter is an alternative to manually specifying a custom separators list.

separators string[]

Only applicable to the recursive strategy and required when using it.

A list of strings used as possible split points when chunking text.

Each string can be a plain string or a regular expression (regex) pattern. The system tries each separator in order to split the text, starting from the first item in the list.

After splitting, it attempts to recombine smaller pieces into larger chunks that stay within the max_chunk_size limit, to reduce the total number of chunks generated.

strategy string · default: sentence

The chunking strategy: sentence, word, none or recursive.

  • If strategy is set to recursive, you must also specify:
  • max_chunk_size
  • either separators orseparator_group

Learn more about different chunking strategies in the linked documentation.

Reference
service string required

The service type

service_settings object required

Settings specific to the service

task_settings object

Task settings specific to the service and task type

inference_id string required

The inference Id

task_type enum required

The task type

Values: text_embedding completion chat_completion