Create an Google AI Studio inference endpoint Generally available; Added in 8.15.0

PUT /_inference/{task_type}/{googleaistudio_inference_id}
Api key auth Basic auth Bearer auth

Create an inference endpoint to perform an inference task with the googleaistudio service.

Required authorization

  • Cluster privileges: manage_inference

Path parameters

  • task_type string

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

    Values are completion or text_embedding.

  • googleaistudio_inference_id string Required

    The unique identifier of the inference endpoint.

application/json

Body

  • 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 googleaistudio.

  • service_settings object Required
    Hide service_settings attributes Show service_settings attributes object
    • api_key string Required

      A valid API key of your Google Gemini account.

    • model_id string Required

      The name of the model to use for the inference task. Refer to the Google documentation for the list of supported models.

      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

Responses

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

      The service type

    • service_settings object Required
    • task_settings object
    • inference_id string Required

      The inference Id

    • task_type string Required

      Values are text_embedding or completion.
PUT /_inference/{task_type}/{googleaistudio_inference_id} 
PUT _inference/completion/google_ai_studio_completion { "service": "googleaistudio", "service_settings": { "api_key": "api-key", "model_id": "model-id" } }
resp = client.inference.put( task_type="completion", inference_id="google_ai_studio_completion", inference_config={ "service": "googleaistudio", "service_settings": { "api_key": "api-key", "model_id": "model-id" } }, )
const response = await client.inference.put({ task_type: "completion", inference_id: "google_ai_studio_completion", inference_config: { service: "googleaistudio", service_settings: { api_key: "api-key", model_id: "model-id", }, }, });
response = client.inference.put( task_type: "completion", inference_id: "google_ai_studio_completion", body: { "service": "googleaistudio", "service_settings": { "api_key": "api-key", "model_id": "model-id" } } )
$resp = $client->inference()->put([ "task_type" => "completion", "inference_id" => "google_ai_studio_completion", "body" => [ "service" => "googleaistudio", "service_settings" => [ "api_key" => "api-key", "model_id" => "model-id", ], ], ]);
curl -X PUT -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d '{"service":"googleaistudio","service_settings":{"api_key":"api-key","model_id":"model-id"}}' "$ELASTICSEARCH_URL/_inference/completion/google_ai_studio_completion"
Request example
Run `PUT _inference/completion/google_ai_studio_completion` to create an inference endpoint to perform a `completion` task type. 
{ "service": "googleaistudio", "service_settings": { "api_key": "api-key", "model_id": "model-id" } }