 import os
import re
from abilities import llm_prompt

# Define the schema pattern for SQL
SCHEMA_PATTERN = r'CREATE\sTABLE|SELECT\s.*\sFROM\s.*|INSERT\sINTO\s.*|UPDATE\s.*\sSET\s.*|DELETE\sFROM\s.*'

def interpret_schema(schema):
    # Use AI to interpret the schema and identify tables and columns
    try:
        # Call the AI with the schema, asking it to identify tables and columns
        interpretation = llm_prompt(
            prompt=f"Identify tables, columns, and relationships from this SQL schema: '{schema}'",
            model="gpt-4-1106-preview"
        )
        return interpretation
    except Exception as e:
        logger.error(f"Error interpreting schema: {e}")
        raise

def generate_sql_query(user_request, schema):
    # Interpret the schema to find tables and columns
    try:
        tables_and_columns = interpret_schema(schema)

About this template

This AI-powered application generates SQL queries code based on user retrieval requests. It helps generating SQL queries using natural language messages from users. This app allows for easier database management and helps to fulful data analytics requests.

Introduction to the AI-Based Online SQL Query Code Generator Template

Welcome to the AI-Based Online SQL Query Code Generator template! This powerful tool is designed to assist builders in creating SQL queries using natural language. It leverages AI to interpret database schemas and generate SQL queries based on user requests, simplifying database management and data analytics tasks. This step-by-step guide will walk you through using this template on the Lazy platform.

Getting Started

To begin using this template, click on "Start with this Template" on the Lazy platform. This will pre-populate the code in the Lazy Builder interface, so you won't need to copy, paste, or delete any code manually.

Test: Deploying the App

Once you have the template ready, press the "Test" button to start the deployment of your app. The Lazy CLI will handle the deployment process, and you will not need to worry about installing libraries or setting up your environment.

Entering Input

After pressing the "Test" button and initiating the deployment, the Lazy App's CLI interface will appear. You will be prompted to provide the necessary user input there. The app will ask you to enter the SQL code for your database schema and then to describe in everyday language what you want to retrieve from the database.

Example User Input

For the SQL schema, you might input something like:


CREATE TABLE customers (
    id INT PRIMARY KEY,
    name VARCHAR(100),
    email VARCHAR(100)
);

For the user request, you could say:

"Show me all customer names and emails."

Using the App

After providing the necessary input, the app will generate the SQL query for you. If you requested an explanation of the code, it would also provide that. There is no frontend experience or dashboard rendered by this app; all interactions occur through the Lazy CLI.

Integrating the App

If you need to integrate the generated SQL query into another service or frontend, you can simply take the output from the Lazy CLI and use it in your database management tool or application code.

Remember, this template is designed to run entirely on the Lazy platform, so there's no need to worry about external integrations for the template itself. However, if you're using the generated SQL code in another tool, you may need to follow that tool's specific integration steps.

By following these steps, you can efficiently use the AI-Based Online SQL Query Code Generator template to create SQL queries from natural language requests, streamlining your database interactions and analytics processes.

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