Create an Anthropic inference endpoint
- PUT /_inference/{task_type}/{anthropic_inference_id}
Create an inference endpoint to perform an inference task with the anthropic service.
- Cluster privileges:
manage_inference
Path Parameters
-
task_typeAnthropicTaskTyperequired -
The task type. The valid task types for the model to perform are
completionandchat_completion. NOTE: Thechat_completiontask type only supports streaming and only through the _stream API. -
Values:
completionchat_completion -
anthropic_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
-
serviceAnthropicServiceTyperequired -
The type of service supported for the specified task type. In this case,
anthropic. -
Values:
anthropic -
service_settingsAnthropicServiceSettingsrequired -
Settings used to install the inference model. These settings are specific to the
anthropicservice. -
api_keystringrequired -
A valid API key for the Anthropic API.
-
model_idstringrequired -
The name of the model to use for the inference task. Refer to the Anthropic documentation for the list of supported models.
-
rate_limitRateLimitSetting -
This setting helps to minimize the number of rate limit errors returned from Anthropic. By default, the
anthropicservice sets the number of requests allowed per minute to 50. -
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_settingsAnthropicTaskSettings -
Settings to configure the inference task. These settings are specific to the task type you specified.
-
max_tokensnumberrequired -
For a
completionorchat_completiontask, it is the maximum number of tokens to generate before stopping. -
temperaturenumber -
For a
completionorchat_completiontask, it is the amount of randomness injected into the response. For more details about the supported range, refer to Anthropic documentation. - External docs
-
top_knumber -
For a
completionorchat_completiontask, it specifies to only sample from the top K options for each subsequent token. It is recommended for advanced use cases only. You usually only need to usetemperature. -
top_pnumber -
For a
completionorchat_completiontask, it specifies to use Anthropic's nucleus sampling. In nucleus sampling, Anthropic computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches the specified probability. You should either altertemperatureortop_p, but not both. It is recommended for advanced use cases only. You usually only need to usetemperature.
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