Write MQL with Gemini assistance

This document describes how you can use Gemini Code Assist to get AI-powered assistance in Cloud Firestore to generate MQL queries using natural language prompts.

Learn how and when Gemini for Google Cloud uses your data.

Before you begin

  1. Optional: Set up Gemini Code Assist.

  2. To complete the tasks in this document, ensure that you have the necessary Identity and Access Management (IAM) permissions.

Required roles

To get the permissions that you need to complete the tasks in this document, ask your administrator to grant you the Gemini for Google Cloud User (roles/cloudaicompanion.user) IAM role on the project.

Generate MQL queries using natural language prompts

You can give Gemini natural language comments (or prompts) to generate queries that are based on your schema. For example, you can prompt Gemini to generate MQL in response to the following prompts:

  • "How many popular books with publication year 1960?"
  • "Create a sample collection of popular books."

To generate MQL in Cloud Firestore with Gemini assistance, follow these steps:

  1. In the Google Cloud console, go to the Cloud Firestore Databases page.

    Go to Databases

  2. Select an Cloud Firestore database from the list. The Firestore Studio opens.

  3. In a new or empty query editor, click the Generate MQL button. Otherwise, click Help me code.

  4. Enter a prompt to use to generate a query. To improve accuracy, select a collection for context in the drop-down.

  5. Review the generated MQL and take any of the following actions:

    • To accept MQL generated by Gemini, click Insert. You can continue to edit the MQL in the editor. Click Run to run you query.
    • To edit your prompt, click Edit.

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