Prompt to DBML

Prompt to DBML enables you to generate Database Markup Language (DBML) from natural language.

Instead of writing DBML manually, describe your database requirements in plain language, and Qubase AI generates a structured DBML representation that can be reviewed, edited, and synchronized with your database model.

This feature helps database engineers quickly create maintainable database definitions.

Before you begin

Before generating DBML, ensure that you have:

Created a Workspace
Created a Project
Opened a Database Schema

[!NOTE] AI-generated DBML should always be reviewed before importing or sharing.

What can AI generate?

Depending on your prompt, Qubase AI can generate:

Tables
Columns
Data types
Primary Keys
Foreign Keys
Relationships
Constraints
DBML references

Generated DBML follows standard DBML syntax whenever possible.

Example prompt


Create a library management system.

Books belong to categories.

Members can borrow multiple books.

Each borrowing record stores the borrow date and return date.

A librarian manages borrowing transactions.

AI workflow


Write Prompt
      │
      ▼
AI Understands Requirements
      │
      ▼
Generate DBML
      │
      ▼
Review Output
      │
      ▼
Copy or Save

Generate DBML

To generate DBML:

Open AI Engineering.
Select Prompt to DBML.
Enter your database requirements.
Submit the prompt.
Review the generated DBML.
Edit the output if necessary.
Save or copy the result.

Example output


Table users {
  id uuid [pk]
  full_name varchar
  email varchar [unique]
}

Table orders {
  id uuid [pk]
  user_id uuid [ref: > users.id]
  order_date timestamp
}

The generated output can be modified before importing or exporting.

Writing better prompts

To improve generation quality:

Describe the business domain.
Mention the main entities.
Explain relationships.
Include important business rules.
Specify special requirements if needed.

Example:


Create a university database.

Students enroll in many courses.

Teachers teach multiple courses.

Each department manages several courses.

Store enrollment dates and grades.

Benefits

Prompt to DBML helps you:

Generate DBML quickly
Reduce manual coding
Share database models easily
Improve consistency
Accelerate database documentation

Limitations

Generated DBML may require manual adjustments.

Examples include:

Naming conventions
Database-specific rules
Complex constraints
Advanced indexing strategies

Always review the generated output before using it.

Best practices

Write clear prompts.
Include relationships explicitly.
Review generated references.
Validate the generated structure.
Keep DBML synchronized with your database model.

[!TIP] The quality of the generated DBML depends on the clarity and completeness of your prompt.