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Create a Google Vertex AI inference endpoint

Auth

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

Required privileges

Cluster privileges manage_inference

Path parameters

task_type enum required

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

Values: rerank text_embedding completion chat_completion
googlevertexai_inference_id string required

The unique identifier of the inference endpoint.

Query parameters

timeout union oneOf · default: 30s

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

Values: -1 0

Request body

service enum required

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

Values: googlevertexai
service_settings object required

Settings used to install the inference model. These settings are specific to the googlevertexai service.

provider enum

The name of the Google Model Garden Provider for completion and chat_completion tasks. In order for a Google Model Garden endpoint to be used provider must be defined and be other than google. Modes:

  • Google Model Garden (third-party models): set provider to a supported non-google value and provide url and/or streaming_url.
  • Google Vertex AI: omit provider or set it to google. In this mode, do not set url or streaming_url and Elastic will construct the endpoint url from location, model_id, and project_id parameters.
Values: google anthropic meta hugging_face mistral ai21
url string

The URL for non-streaming completion requests to a Google Model Garden provider endpoint. If both url and streaming_url are provided, each is used for its respective mode. If streaming_url is not provided, url is also used for streaming completion and chat_completion. If provider is not provided or set to google (Google Vertex AI), do not set url (or streaming_url). At least one of url or streaming_url must be provided for Google Model Garden endpoint usage. Certain providers require separate URLs for streaming and non-streaming operations (e.g., Anthropic, Mistral, AI21). Others support both operation types through a single URL (e.g., Meta, Hugging Face). Information on constructing the URL for various providers can be found in the Google Model Garden documentation for the model, or on the endpoint’s Sample request page. The request examples also illustrate the proper formatting for the url.

streaming_url string

The URL for streaming completion and chat_completion requests to a Google Model Garden provider endpoint. If both streaming_url and url are provided, each is used for its respective mode. If url is not provided, streaming_url is also used for non-streaming completion requests. If provider is not provided or set to google (Google Vertex AI), do not set streaming_url (or url). At least one of streaming_url or url must be provided for Google Model Garden endpoint usage. Certain providers require separate URLs for streaming and non-streaming operations (e.g., Anthropic, Mistral, AI21). Others support both operation types through a single URL (e.g., Meta, Hugging Face). Information on constructing the URL for various providers can be found in the Google Model Garden documentation for the model, or on the endpoint’s Sample request page. The request examples also illustrate the proper formatting for the streaming_url.

location string

The name of the location to use for the inference task for the Google Vertex AI inference task. For Google Vertex AI, when provider is omitted or google, location is optional. When location is omitted, the request targets the Google Vertex AI global endpoint (https://aiplatform.googleapis.com); when it is provided, the corresponding regional endpoint (https://<location>-aiplatform.googleapis.com) is used. The field must be omitted to select the global endpoint; an empty string is not a valid location. For Google Model Garden's completion and chat_completion tasks, when provider is a supported non-google value - location is ignored. Refer to the Google documentation for the list of supported locations.

External docs
model_id string

The name of the model to use for the inference task. For Google Vertex AI model_id is mandatory. For Google Model Garden's completion and chat_completion tasks, when provider is a supported non-google value - model_id will be used for some providers that require it, otherwise - ignored. Refer to the Google documentation for the list of supported models for Google Vertex AI.

External docs
project_id string

The name of the project to use for the Google Vertex AI inference task. For Google Vertex AI project_id is mandatory. For Google Model Garden's completion and chat_completion tasks, when provider is a supported non-google value - project_id is ignored.

service_account_json string required

A valid service account in JSON format for the Google Vertex AI API.

dimensions number

For a text_embedding task, the number of dimensions the resulting output embeddings should have. By default, the model's standard output dimension is used. Refer to the Google documentation for more information.

External docs
max_batch_size number · default: 250

Only applicable for the text_embedding task type. Controls the batch size of chunked inference requests sent to Google Vertex AI.

Setting this parameter lower reduces the risk of exceeding token limits but may result in more API calls. Setting it higher increases throughput but may risk hitting token limits.

To estimate a safe max_batch_size value, you can use it together with the max_chunk_size parameter using the following formula: max_batch_size ≈ max_chunk_size × 1.3 × 512 ÷ 20000

Where:

  • 1.3 is an approximate tokens-per-word ratio
  • 512 is the maximum number of chunks that can be generated per document
  • 20000 is the Google Vertex AI token limit per request

This estimate assumes the worst-case scenario with a document generating the maximum 512 chunks.

Response

application/json
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 enum required

The task type

Values: chat_completion completion text_embedding rerank