Write MQL with Gemini assistance

This document describes how you can use Gemini Code Assist to get AI-powered assistance in 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. For more information about granting roles, see Manage access to projects, folders, and organizations .

You might also be able to get the required permissions through custom roles or other predefined roles .

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 Firestore with Gemini assistance, follow these steps:

1. In the Google Cloud console, go to the Firestore Databasespage.

   Go to Databases

2. Select an Firestore with MongoDB compatibility database from the list. The Firestore Studioopens.

3. In a new or empty query editor, click the Generate MQLbutton. 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 Runto run you query.
   • To edit your prompt, click Edit.

What's next

• Read Gemini for Google Cloud overview .
• Learn how Gemini uses your data .