Create an Anthropic inference endpoint

Auth

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

Required authorization

Cluster privileges manage_inference

Path parameters

task_type enum required

The task type. The valid task types for the model to perform are completion and chat_completion. NOTE: The chat_completion task type only supports streaming and only through the _stream API.

Values: completion chat_completion
anthropic_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

service enum required

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

Values: anthropic
service_settings object required

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

api_key string required

A valid API key for the Anthropic API.

model_id string required

The name of the model to use for the inference task. Refer to the Anthropic documentation for the list of supported models.

rate_limit object

This setting helps to minimize the number of rate limit errors returned from Anthropic. By default, the anthropic service sets the number of requests allowed per minute to 50.

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.

max_tokens number required

For a completion or chat_completion task, it is the maximum number of tokens to generate before stopping.

temperature number

For a completion or chat_completion task, it is the amount of randomness injected into the response. For more details about the supported range, refer to Anthropic documentation.

External docs
top_k number

For a completion or chat_completion task, 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 use temperature.

top_p number

For a completion or chat_completion task, 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 alter temperature or top_p, but not both. It is recommended for advanced use cases only. You usually only need to use temperature.

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: completion chat_completion