Path parameters

  • task_typestring Required

    The type of the inference task that the model will perform.

    Values are text_embedding or rerank.

  • voyageai_inference_idstring Required

    The unique identifier of the inference endpoint.

application/json

Body

  • chunking_settingsobject

    Chunking configuration object

    Hide chunking_settings attributes Show chunking_settings attributes object
    • max_chunk_sizenumber

      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).

    • overlapnumber

      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_overlapnumber

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

    • strategystring

      The chunking strategy: sentence or word.

  • servicestring Required

    Value is voyageai.

  • service_settingsobject Required
    Hide service_settings attributes Show service_settings attributes object
    • dimensionsnumber

      The number of dimensions for resulting output embeddings. This setting maps to output_dimension in the VoyageAI documentation. Only for the text_embedding task type.

      External documentation
    • model_idstring Required

      The name of the model to use for the inference task. Refer to the VoyageAI documentation for the list of available text embedding and rerank models.

      External documentation
    • rate_limitobject

      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_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-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
    • embedding_typenumber

      The data type for the embeddings to be returned. This setting maps to output_dtype in the VoyageAI documentation. Permitted values: float, int8, bit. int8 is a synonym of byte in the VoyageAI documentation. bit is a synonym of binary in the VoyageAI documentation. Only for the text_embedding task type.

      External documentation
  • task_settingsobject
    Hide task_settings attributes Show task_settings attributes object
    • input_typestring

      Type of the input text. Permitted values: ingest (maps to document in the VoyageAI documentation), search (maps to query in the VoyageAI documentation). Only for the text_embedding task type.

    • return_documentsboolean

      Whether to return the source documents in the response. Only for the rerank task type.

    • top_knumber

      The number of most relevant documents to return. If not specified, the reranking results of all documents will be returned. Only for the rerank task type.

    • truncationboolean

      Whether to truncate the input texts to fit within the context length.

Responses

  • 200 application/json
    Hide response attributes Show response attributes object
    • chunking_settingsobject

      Chunking configuration object

      Hide chunking_settings attributes Show chunking_settings attributes object
      • max_chunk_sizenumber

        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).

      • overlapnumber

        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_overlapnumber

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

      • strategystring

        The chunking strategy: sentence or word.

    • servicestring Required

      The service type

    • service_settingsobject Required
    • task_settingsobject
    • inference_idstring Required

      The inference Id

    • task_typestring Required

      Values are text_embedding or rerank.

PUT /_inference/{task_type}/{voyageai_inference_id}
PUT _inference/text_embedding/openai-embeddings
{
    "service": "voyageai",
    "service_settings": {
        "model_id": "voyage-3-large",
        "dimensions": 512
    }
}
resp = client.inference.put(
    task_type="text_embedding",
    inference_id="openai-embeddings",
    inference_config={
        "service": "voyageai",
        "service_settings": {
            "model_id": "voyage-3-large",
            "dimensions": 512
        }
    },
)
const response = await client.inference.put({
  task_type: "text_embedding",
  inference_id: "openai-embeddings",
  inference_config: {
    service: "voyageai",
    service_settings: {
      model_id: "voyage-3-large",
      dimensions: 512,
    },
  },
});
response = client.inference.put(
  task_type: "text_embedding",
  inference_id: "openai-embeddings",
  body: {
    "service": "voyageai",
    "service_settings": {
      "model_id": "voyage-3-large",
      "dimensions": 512
    }
  }
)
$resp = $client->inference()->put([
    "task_type" => "text_embedding",
    "inference_id" => "openai-embeddings",
    "body" => [
        "service" => "voyageai",
        "service_settings" => [
            "model_id" => "voyage-3-large",
            "dimensions" => 512,
        ],
    ],
]);
curl -X PUT -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d '{"service":"voyageai","service_settings":{"model_id":"voyage-3-large","dimensions":512}}' "$ELASTICSEARCH_URL/_inference/text_embedding/openai-embeddings"
Request examples
Run `PUT _inference/text_embedding/voyageai-embeddings` to create an inference endpoint that performs a `text_embedding` task. The embeddings created by requests to this endpoint will have 512 dimensions.
{
    "service": "voyageai",
    "service_settings": {
        "model_id": "voyage-3-large",
        "dimensions": 512
    }
}
Run `PUT _inference/rerank/voyageai-rerank` to create an inference endpoint that performs a `rerank` task.
{
    "service": "voyageai",
    "service_settings": {
        "model_id": "rerank-2"
    }
}