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This page describes how to invoke predictions using functions from the public and google_ml namespaces. The google_ml_integration extension includes prediction functions for these namespaces.
You can use the ml_predict_row() function in the public schema with any generic model hosted in Vertex AI without registering the endpoint. The google_ml.predict_row() function in the google_ml schema can be used with any model that has been registered with Model endpoint management.
To invoke predictions, select one of the following schemas.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-05-23 UTC."],[[["AlloyDB allows online predictions within SQL code using the `google_ml.predict_row()` function."],["Before invoking predictions, you must integrate your database with Vertex AI and grant users permission to execute `google_ml.predict_row()`."],["The `google_ml.predict_row()` function requires you to specify a Vertex AI Model Garden model or a Vertex AI model endpoint with accessible IAM permissions."],["The format of the initial argument in `google_ml.predict_row()` varies depending on whether you are using a Vertex AI Model Garden model or a Vertex AI endpoint."],["You can utilize the `json_build_object()` function with `google_ml.predict_row()` to format function parameters, including using database content as input."]]],[]]
