Package co.elastic.clients.elasticsearch.inference

Class PutRequest

java.lang.Object
co.elastic.clients.elasticsearch._types.RequestBase
co.elastic.clients.elasticsearch.inference.PutRequest
All Implemented Interfaces:
JsonpSerializable
@JsonpDeserializable public class PutRequest extends RequestBase implements JsonpSerializable
Create an inference endpoint.

IMPORTANT: The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Mistral, Azure OpenAI, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.

The following integrations are available through the inference API. You can find the available task types next to the integration name:

  • AI21 (chat_completion, completion)
  • AlibabaCloud AI Search (completion, rerank, sparse_embedding, text_embedding)
  • Amazon Bedrock (chat_completion, completion, text_embedding)
  • Amazon SageMaker (chat_completion, completion, rerank, sparse_embedding, text_embedding)
  • Anthropic (chat_completion, completion)
  • Azure AI Studio (completion, rerank, text_embedding)
  • Azure OpenAI (chat_completion, completion, text_embedding)
  • Cohere (completion, rerank, text_embedding)
  • DeepSeek (chat_completion, completion)
  • Elasticsearch (rerank, sparse_embedding, text_embedding - this service is for built-in models and models uploaded through Eland)
  • ELSER (sparse_embedding)
  • Fireworks AI (chat_completion, completion, text_embedding)
  • Google AI Studio (completion, text_embedding)
  • Google Vertex AI (chat_completion, completion, rerank, text_embedding)
  • Groq (chat_completion)
  • Hugging Face (chat_completion, completion, rerank, text_embedding)
  • JinaAI (embedding, rerank, text_embedding)
  • Llama (chat_completion, completion, text_embedding)
  • Mistral (chat_completion, completion, text_embedding)
  • Nvidia (chat_completion, completion, text_embedding, rerank)
  • OpenAI (chat_completion, completion, text_embedding)
  • OpenShift AI (chat_completion, completion, rerank, text_embedding)
  • VoyageAI (rerank, text_embedding)
  • Watsonx (chat_completion, completion, rerank, text_embedding)
See Also:

  • Field Details

  • Method Details

    • of

      public static PutRequest of(Function<PutRequest.Builder,ObjectBuilder<PutRequest>> fn)

    • inferenceId

      public final String inferenceId()
      Required - The inference Id

      API name: inference_id

    • taskType

      @Nullable public final TaskType taskType()
      The task type. Refer to the integration list in the API description for the available task types.

      API name: task_type

    • timeout

      @Nullable public final Time timeout()
      Specifies the amount of time to wait for the inference endpoint to be created. The default depends on the task type: 120s for completion and chat_completion, and 30s for all other task types.

      API name: timeout

    • inferenceConfig

      public final InferenceEndpoint inferenceConfig()
      Required - Request body.

    • serialize

      public void serialize(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper)
      Serialize this value to JSON.
      Specified by:
      serialize in interface JsonpSerializable

    • rebuild

      public PutRequest.Builder rebuild()
      Returns:
      New PutRequest.Builder initialized with field values of this instance

    • createPutRequestDeserializer

      protected static JsonpDeserializer<PutRequest> createPutRequestDeserializer()