Create an Azure AI studio inference endpoint

Auth

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

Required authorization

Cluster privileges manage_inference

Path parameters

task_type enum required

The type of the inference task that the model will perform.

Values: completion rerank text_embedding
azureaistudio_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 rerank or 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, azureaistudio.

Values: azureaistudio
service_settings object required

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

api_key string required

A valid API key of your Azure AI Studio model deployment. This key can be found on the overview page for your deployment in the management section of your Azure AI Studio account.

Important

You need to provide the API key only once, during the inference model creation. The get inference endpoint API does not retrieve your API key.

External docs
endpoint_type string required

The type of endpoint that is available for deployment through Azure AI Studio: token or realtime. The token endpoint type is for "pay as you go" endpoints that are billed per token. The realtime endpoint type is for "real-time" endpoints that are billed per hour of usage.

External docs
target string required

The target URL of your Azure AI Studio model deployment. This can be found on the overview page for your deployment in the management section of your Azure AI Studio account.

provider string required

The model provider for your deployment. Note that some providers may support only certain task types. Supported providers include:

  • cohere - available for text_embedding, rerank and completion task types
  • databricks - available for completion task type only
  • meta - available for completion task type only
  • microsoft_phi - available for completion task type only
  • mistral - available for completion task type only
  • openai - available for text_embedding and completion task types
rate_limit object

This setting helps to minimize the number of rate limit errors returned from Azure AI Studio. By default, the azureaistudio service sets the number of requests allowed per minute to 240.

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
task_settings object

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

do_sample number

For a completion task, instruct the inference process to perform sampling. It has no effect unless temperature or top_p is specified.

max_new_tokens number

For a completion task, provide a hint for the maximum number of output tokens to be generated.

temperature number

For a completion task, control the apparent creativity of generated completions with a sampling temperature. It must be a number in the range of 0.0 to 2.0. It should not be used if top_p is specified.

top_p number

For a completion task, make the model consider the results of the tokens with nucleus sampling probability. It is an alternative value to temperature and must be a number in the range of 0.0 to 2.0. It should not be used if temperature is specified.

user string

For a text_embedding task, specify the user issuing the request. This information can be used for abuse detection.

return_documents boolean

For a rerank task, return doc text within the results.

top_n number

For a rerank task, the number of most relevant documents to return. It defaults to the number of the documents.

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 rerank