End-to-end user journeys for generative AI models (original) (raw)

This document describes the user journeys for BigQuery ML remote models, including the statements and functions that you can use to work with remote models. BigQuery ML offers the following types of remote models:

Remote model user journeys

The following table describes the statements and functions you can use to create, evaluate, and generate data from remote models:

Model category	Model type	Model creation	Evaluation	Inference	Tutorials
Generative AI remote models	Remote model over a Gemini text generation model1	CREATE MODEL	ML.EVALUATE	AI.GENERATE_TEXT AI.GENERATE_TABLE AI.GENERATE2 AI.GENERATE_BOOL2 AI.GENERATE_DOUBLE2 AI.GENERATE_INT2	Generate text using your data Generate structured data using your data Generate text with Gemini and public data Handle quota errors by calling ML.GENERATE_TEXT iteratively Analyze images with a Gemini model Try model tuning using public data Tune a model using your data
Remote model over a partner text generation model	CREATE MODEL	ML.EVALUATE	AI.GENERATE_TEXT	N/A
Remote model over an open text generation model3	CREATE MODEL	ML.EVALUATE	AI.GENERATE_TEXT	Generate text with Gemma and public data
Remote model over a Google embedding generation model	CREATE MODEL	N/A	AI.GENERATE_EMBEDDING	Generate text embeddings using your data Generate image embeddings using your data Generate video embeddings using your data Handle quota errors by calling ML.GENERATE_EMBEDDING iteratively Generate and search multimodal embeddings using public data
Remote model over an open embedding generation model3	CREATE MODEL	N/A	AI.GENERATE_EMBEDDING	Generate text embeddings by using an open model and the AI.GENERATE_EMBEDDING function
Cloud AI remote models	Remote model over the Cloud Vision API	CREATE MODEL	N/A	ML.ANNOTATE_IMAGE	Annotate images
Remote model over the Cloud Translation API	CREATE MODEL	N/A	ML.TRANSLATE	Translate text
Remote model over the Cloud Natural Language API	CREATE MODEL	N/A	ML.UNDERSTAND_TEXT	Understand text
Remote model over the Document AI API	CREATE MODEL	N/A	ML.PROCESS_DOCUMENT	Process documents Parse PDFs in a RAG pipeline
Remote model over the Speech-to-Text API	CREATE MODEL	N/A	ML.TRANSCRIBE	Transcribe audio files
Remote model over a custom model deployed to Gemini Enterprise Agent Platform	Remote model over a custom model deployed to Gemini Enterprise Agent Platform	CREATE MODEL	ML.EVALUATE	ML.PREDICT	Make predictions with a custom model

1 Some Gemini models supportsupervised tuning.

2 This function calls a hosted Gemini model, and doesn't require you to create a model separately using the CREATE MODELstatement.

3 You can automatically deploy an open model when you create the BigQuery ML remote model by specifying the model's Hugging Face or Agent Platform Model Garden ID. BigQuery manages the Agent Platform resources of open models deployed in this way, and lets you interact with those Agent Platform resources by using the BigQuery ML ALTER MODEL and DROP MODELstatements. It also lets you configure automatic undeployment of the model. For more information, seeAutomatically deployed models.