Body Required

• chunking_settings object

  The chunking configuration object.

  External documentation
  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 lower than 20 (for sentence strategy) or 10 (for word strategy). This value should not exceed the window size for the associated model.

    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

    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 array[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

    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

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

  Value is hugging_face.

• service_settings object Required

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

  Hide service_settings attributes Show service_settings attributes object

  • api_key string Required

    A valid access token for your HuggingFace account. You can create or find your access tokens on the HuggingFace settings page.

    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. After creating the inference model, you cannot change the associated API key. If you want to use a different API key, delete the inference model and recreate it with the same name and the updated API key.

    External documentation
  • rate_limit object

    This setting helps to minimize the number of rate limit errors returned from Hugging Face. By default, the hugging_face service sets the number of requests allowed per minute to 3000 for all supported tasks. Hugging Face does not publish a universal rate limit — actual limits may vary. It is recommended to adjust this value based on the capacity and limits of your specific deployment environment.

    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
      • contextualai service: 1000
      • elastic service and task type chat_completion: 240
      • 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
      • voyageai service: 2000
      • watsonxai service: 120
  • url string Required

    The URL endpoint to use for the requests. For completion and chat_completion tasks, the deployed model must be compatible with the Hugging Face Chat Completion interface (see the linked external documentation for details). The endpoint URL for the request must include /v1/chat/completions. If the model supports the OpenAI Chat Completion schema, a toggle should appear in the interface. Enabling this toggle doesn't change any model behavior, it reveals the full endpoint URL needed (which should include /v1/chat/completions) when configuring the inference endpoint in Elasticsearch. If the model doesn't support this schema, the toggle may not be shown.

    External documentation
  • model_id string

    The name of the HuggingFace model to use for the inference task. For completion and chat_completion tasks, this field is optional but may be required for certain models — particularly when using serverless inference endpoints. For the text_embedding task, this field should not be included. Otherwise, the request will fail.

• task_settings object

  Settings to configure the inference task. These settings are specific to the task type you specified.

  Hide task_settings attributes Show task_settings attributes object

  • return_documents boolean

    For a rerank task, return doc text within the results.

  • top_n number

    For a rerank task, the number of most relevant documents to return. It defaults to the number of the documents.