Get an inference endpoint Generally available; Added in 8.11.0

GET /_inference/{task_type}/{inference_id}
Api key auth Basic auth Bearer auth

All methods and paths for this operation:

GET /_inference

GET /_inference/{inference_id}
GET /_inference/{task_type}/{inference_id}

Path parameters

  • task_type string

    The task type

    Values are sparse_embedding, text_embedding, rerank, completion, or chat_completion.

  • inference_id string Required

    The inference Id

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • endpoints array[object] Required

      Represents an inference endpoint as returned by the GET API

      Hide endpoints attributes Show endpoints attributes object

      Represents an inference endpoint as returned by the GET API

      • 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

        The service type

      • service_settings object Required
      • task_settings object
      • inference_id string Required

        The inference Id

      • task_type string Required

        Values are sparse_embedding, text_embedding, rerank, completion, or chat_completion.
GET /_inference/{task_type}/{inference_id} 
GET _inference/sparse_embedding/my-elser-model

resp = client.inference.get(
    task_type="sparse_embedding",
    inference_id="my-elser-model",
)
const response = await client.inference.get({
  task_type: "sparse_embedding",
  inference_id: "my-elser-model",
});
response = client.inference.get(
  task_type: "sparse_embedding",
  inference_id: "my-elser-model"
)
$resp = $client->inference()->get([
    "task_type" => "sparse_embedding",
    "inference_id" => "my-elser-model",
]);
curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_inference/sparse_embedding/my-elser-model"
client.inference().get(g -> g
    .inferenceId("my-elser-model")
    .taskType(TaskType.SparseEmbedding)
);