Generate vector embeddings with model endpoint management

This page describes how to register an AI model endpoint and generate vector embeddings with model endpoint management. To use AI models in production environments, see Generate and manage vector embeddings.

After the model endpoints are added and registered in model endpoint management, you can reference them using the model ID to generate embeddings.

Before you begin

Make sure that you complete the following actions:

• Register your model endpoint with model endpoint management. For more information, see Register and call remote AI models using model endpoint management.
• Create or update your Cloud SQL instance so that the instance can integrate with Vertex AI. For more information, see Enable database integration with Vertex AI.

Generate embeddings

Use the mysql.ml_embedding() SQL function to call the registered model endpoint with the text embedding model type to generate embeddings.

To call the model and generate embeddings, use the following SQL query:

SELECT
  mysql.ml_embedding(
    'MODEL_ID',
    'CONTENT');

Replace the following:

• MODEL_ID: the model ID you defined when registering the model endpoint
• CONTENT: the text to translate into a vector embedding

Examples

Some examples for generating embeddings using registered model endpoints are listed in this section.

Text embedding models with built-in support

Vertex AI embedding models are supported by default. You don't need to register them. To generate embeddings for a registered gemini-embedding-001 model endpoint, run the following statement:

    SELECT
      mysql.ml_embedding(
        'gemini-embedding-001',
        'Cloud SQL is a managed, cloud-hosted SQL database service');