Try Gemini 1.5 models, the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window. Try Gemini 1.5 models, the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window.

Method: projects.locations.reasoningEngines.query

Queries using a reasoning engine.

Endpoint

post


                https://{service-endpoint}/v1beta1/{name}:query

Where {service-endpoint} is one of the supported service endpoints.

Path parameters

name string

Required. The name of the ReasoningEngine resource to use. Format: projects/{project}/locations/{location}/reasoningEngines/{reasoningEngine}

Request body

The request body contains data with the following structure:

Fields

input object (Struct format)

Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc.

Response body

Response message for [ReasoningEngineExecutionService.Query][]

If successful, the response body contains data with the following structure:

Fields

output value (Value format)

Response provided by users in JSON object format.

JSON representation
{ "output": value }