Create an Google AI Studio inference endpoint | Elasticsearch API documentation (v8)

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.

Query parameters

timeout string

Specifies the amount of time to wait for the inference endpoint to be created.

Values are -1 or 0.

application/json

Body

chunking_settings object

The 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.
- strategy string
  
  The chunking strategy: sentence or word.
  
  Default value is sentence.
service string Required

The type of service supported for the specified task type. In this case, googleaistudio.

Value is googleaistudio.
service_settings object Required

Settings used to install the inference model. These settings are specific to the googleaistudio service.
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 Google AI Studio. By default, the googleaistudio service sets the number of requests allowed per minute to 360.
  Hide rate_limit attribute Show rate_limit attribute object
  
  requests_per_minute number
  
  The number of requests allowed per minute.

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).
  
  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.
  
  strategy string
  
  The chunking strategy: sentence or word.
  
  Default value is sentence.
- service string Required
  
  The service type
- service_settings object Required
  
  Settings specific to the service
- task_settings object
  
  Task settings specific to the service and task type
- inference_id string Required
  
  The inference Id
- task_type string Required
  
  The task type
  
  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"

client.inference().put(p -> p
    .inferenceId("google_ai_studio_completion")
    .taskType(TaskType.Completion)
    .inferenceConfig(i -> i
        .service("googleaistudio")
        .serviceSettings(JsonData.fromJson("{\"api_key\":\"api-key\",\"model_id\":\"model-id\"}"))
    )
);

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"
    }
}