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• chunking_settings object

  Chunking configuration object

  Hide chunking_settings attributes Show chunking_settings attributes object

  • max_chunk_size number

    The maximum size of a chunk in words. This value cannot be higher than 300 or lower than 20 (for sentence strategy) or 10 (for word strategy).

    Default value is 250.

  • overlap number

    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.

    Default value is 100.

  • sentence_overlap number

    The number of overlapping sentences for chunks. It is applicable only for a sentence chunking strategy. It can be either 1 or 0.

    Default value is 1.

  • separator_group string Required

    This parameter is only applicable when using the recursive chunking strategy.

    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 array[string] Required

    A list of strings used as possible split points when chunking text with the recursive strategy.

    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

    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.

    Default value is sentence.

    External documentation
• service string Required

  Value is anthropic.

• service_settings object Required
  Hide service_settings attributes Show service_settings attributes object

  • 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 the service.

    Hide rate_limit attribute Show rate_limit attribute object

    • 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
      • anthropic service: 50
      • azureaistudio service: 240
      • azureopenai service and task type text_embedding: 1440
      • azureopenai service and task type completion: 120
      • cohere service: 10000
      • elastic service and task type chat_completion: 240
      • googleaistudio service: 360
      • googlevertexai service: 30000
      • hugging_face service: 3000
      • jinaai service: 2000
      • mistral service: 240
      • openai service and task type text_embedding: 3000
      • openai service and task type completion: 500
      • voyageai service: 2000
      • watsonxai service: 120
• task_settings object
  Hide task_settings attributes Show task_settings attributes object

  • max_tokens number Required

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

  • temperature number

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

    External documentation
  • top_k number

    For a 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 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.