Create an Azure AI studio inference endpoint
- PUT /_inference/{task_type}/{azureaistudio_inference_id}
Create an inference endpoint to perform an inference task with the azureaistudio service.
- Cluster privileges:
manage_inference
Path Parameters
-
task_typeAzureAiStudioTaskTyperequired -
The type of the inference task that the model will perform.
-
Values:
completionreranktext_embedding -
azureaistudio_inference_idstring Idrequired -
The unique identifier of the inference endpoint.
Query Parameters
-
timeoutstring Duration · default: 30s Specifies the amount of time to wait for the inference endpoint to be created.
Request
-
chunking_settingsInferenceChunkingSettings -
The chunking configuration object. Applies only to the
text_embeddingtask type. Not applicable to thererankorcompletiontask types. - Reference
-
max_chunk_sizenumber · default: 250 -
The maximum size of a chunk in words. This value cannot be lower than
20(forsentencestrategy) or10(forwordstrategy). This value should not exceed the window size for the associated model. -
overlapnumber · default: 100 -
The number of overlapping words for chunks. It is applicable only to a
wordchunking strategy. This value cannot be higher than half themax_chunk_sizevalue. -
sentence_overlapnumber · default: 1 -
The number of overlapping sentences for chunks. It is applicable only for a
sentencechunking strategy. It can be either1or0. -
separator_groupstring -
Only applicable to the
recursivestrategy 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
markdownorplaintext.Using this parameter is an alternative to manually specifying a custom
separatorslist. -
separatorsstring -
Only applicable to the
recursivestrategy 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_sizelimit, to reduce the total number of chunks generated. -
serviceAzureAiStudioServiceTyperequired -
The type of service supported for the specified task type. In this case,
azureaistudio. -
Values:
azureaistudio -
service_settingsAzureAiStudioServiceSettingsrequired -
Settings used to install the inference model. These settings are specific to the
azureaistudioservice. -
api_keystringrequired -
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_typestringrequired -
The type of endpoint that is available for deployment through Azure AI Studio:
tokenorrealtime. Thetokenendpoint type is for "pay as you go" endpoints that are billed per token. Therealtimeendpoint type is for "real-time" endpoints that are billed per hour of usage. - External docs
-
targetstringrequired -
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.
-
providerstringrequired -
The model provider for your deployment. Note that some providers may support only certain task types. Supported providers include:
cohere- available fortext_embedding,rerankandcompletiontask typesdatabricks- available forcompletiontask type onlymeta- available forcompletiontask type onlymicrosoft_phi- available forcompletiontask type onlymistral- available forcompletiontask type onlyopenai- available fortext_embeddingandcompletiontask types
-
rate_limitRateLimitSetting -
This setting helps to minimize the number of rate limit errors returned from Azure AI Studio. By default, the
azureaistudioservice sets the number of requests allowed per minute to 240. -
requests_per_minutenumber -
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-searchservice:1000amazonbedrockservice:240anthropicservice:50azureaistudioservice:240azureopenaiservice and task typetext_embedding:1440azureopenaiservice and task typescompletionorchat_completion:120cohereservice:10000contextualaiservice:1000elasticservice and task typechat_completion:240fireworksaiservice:6000googleaistudioservice:360googlevertexaiservice:30000hugging_faceservice:3000jinaaiservice:2000llamaservice:3000mistralservice:240openaiservice and task typetext_embedding:3000openaiservice and task typecompletion:500openshift_aiservice:3000voyageaiservice:2000watsonxaiservice:120
-
task_settingsAzureAiStudioTaskSettings -
Settings to configure the inference task. These settings are specific to the task type you specified.
-
do_samplenumber -
For a
completiontask, instruct the inference process to perform sampling. It has no effect unlesstemperatureortop_pis specified. -
max_new_tokensnumber -
For a
completiontask, provide a hint for the maximum number of output tokens to be generated. -
temperaturenumber -
For a
completiontask, 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 iftop_pis specified. -
top_pnumber -
For a
completiontask, make the model consider the results of the tokens with nucleus sampling probability. It is an alternative value totemperatureand must be a number in the range of 0.0 to 2.0. It should not be used iftemperatureis specified. -
userstring -
For a
text_embeddingtask, specify the user issuing the request. This information can be used for abuse detection. -
return_documentsboolean -
For a
reranktask, return doc text within the results. -
top_nnumber -
For a
reranktask, the number of most relevant documents to return. It defaults to the number of the documents.
Response
-
chunking_settingsInferenceChunkingSettings -
The chunking configuration object. Applies only to the
embedding,sparse_embeddingandtext_embeddingtask types. Not applicable to thererank,completion, orchat_completiontask types. -
max_chunk_sizenumber · default: 250 -
The maximum size of a chunk in words. This value cannot be lower than
20(forsentencestrategy) or10(forwordstrategy). This value should not exceed the window size for the associated model. -
overlapnumber · default: 100 -
The number of overlapping words for chunks. It is applicable only to a
wordchunking strategy. This value cannot be higher than half themax_chunk_sizevalue. -
sentence_overlapnumber · default: 1 -
The number of overlapping sentences for chunks. It is applicable only for a
sentencechunking strategy. It can be either1or0. -
separator_groupstring -
Only applicable to the
recursivestrategy 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
markdownorplaintext.Using this parameter is an alternative to manually specifying a custom
separatorslist. -
separatorsstring -
Only applicable to the
recursivestrategy 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_sizelimit, to reduce the total number of chunks generated. -
servicestringrequired -
The service type
-
service_settingsServiceSettingsrequired -
Settings specific to the service
-
task_settingsTaskSettings -
Task settings specific to the service and task type
-
inference_idstringrequired -
The inference Id