Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-id: id of theEndpointthat served this prediction.X-Vertex-AI-Deployed-Model-id: id of the Endpoint'sDeployedModelthat served this prediction.
Endpoint
post
https://{service-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:
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 models.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 models.rawPredict method.
Response body
If successful, the response is a generic HTTP response whose format is defined by the method.