Create a AI21 inference endpoint
- PUT /_inference/{task_type}/{ai21_inference_id}
Create an inference endpoint to perform an inference task with the ai21 service.
Required authorization
- Cluster privileges manage_inference
Request body
-
servicerequired -
The type of service supported for the specified task type. In this case,
ai21. -
Values:
ai21 -
service_settingsobjectrequired -
Settings used to install the inference model. These settings are specific to the
ai21service. -
model_idstringrequired -
The name of the model to use for the inference task. Refer to the AI21 models documentation for the list of supported models and versions. Service has been tested and confirmed to be working for
completionandchat_completiontasks with the following models:jamba-minijamba-large
- External docs
-
api_keystring -
A valid API key for accessing AI21 API.
ImportantYou need to provide the API key only once, during the inference model creation. The get inference endpoint API does not retrieve your API key.
-
rate_limitobject -
This setting helps to minimize the number of rate limit errors returned from the AI21 API. By default, the
ai21service sets the number of requests allowed per minute to 200. Please refer to AI21 documentation for more details. - External docs
-
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
Response
-
chunking_settingsobject -
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. -
strategystring · default: sentence -
The chunking strategy:
sentence,word,noneorrecursive.- If
strategyis set torecursive, you must also specify:
max_chunk_size- either
separatorsorseparator_group
Learn more about different chunking strategies in the linked documentation.
- If
- Reference