Method: projects.locations.endpoints.rawPredict

Perform an online prediction with an arbitrary HTTP payload.

The response includes the following HTTP headers:

• X-Vertex-AI-Endpoint-id: id of the Endpoint that served this prediction.

• X-Vertex-AI-Deployed-Model-id: id of the Endpoint's DeployedModel that served this prediction.

Endpoint

post https://{endpoint}/v1beta1/{endpoint}:rawPredict

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

Path parameters

endpoint string

Required. The name of the Endpoint requested to serve the prediction. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

Request body

The request body contains data with the following structure:

Fields

httpBody object (HttpBody)

The prediction input. Supports HTTP headers and arbitrary data payload.

A DeployedModel may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the endpoints.rawPredict method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model.

You can specify the schema for each instance in the predictSchemata.instance_schema_uri field when you create a Model. This schema applies when you deploy the Model as a DeployedModel to an Endpoint and use the endpoints.rawPredict method.

Response body

If successful, the response is a generic HTTP response whose format is defined by the method.