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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).

  • 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.

  • 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.

  • strategy string

    The chunking strategy: sentence or word.

• service string Required

  Value is alibabacloud-ai-search.

• service_settings object Required
  Hide service_settings attributes Show service_settings attributes object

  • api_key string Required

    A valid API key for the AlibabaCloud AI Search API.

  • host string Required

    The name of the host address used for the inference task. You can find the host address in the API keys section of the documentation.

    External documentation
  • 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
  • service_id string Required

    The name of the model service to use for the inference task. The following service IDs are available for the completion task:

    • ops-qwen-turbo
    • qwen-turbo
    • qwen-plus
    • qwen-max ÷ qwen-max-longcontext

    The following service ID is available for the rerank task:

    • ops-bge-reranker-larger

    The following service ID is available for the sparse_embedding task:

    • ops-text-sparse-embedding-001

    The following service IDs are available for the text_embedding task:

    ops-text-embedding-001 ops-text-embedding-zh-001 ops-text-embedding-en-001 ops-text-embedding-002

  • workspace string Required

    The name of the workspace used for the inference task.

• task_settings object
  Hide task_settings attributes Show task_settings attributes object

  • input_type string

    For a sparse_embedding or text_embedding task, specify the type of input passed to the model. Valid values are:

    • ingest for storing document embeddings in a vector database.
    • search for storing embeddings of search queries run against a vector database to find relevant documents.
  • return_token boolean

    For a sparse_embedding task, it affects whether the token name will be returned in the response. It defaults to false, which means only the token ID will be returned in the response.