SQL Agent with Synthetic Data Generation

A Gradient AI-powered agent that generates realistic mock datasets and produces safe SQL INSERT scripts. Designed for developers and testers to bootstrap staging environments with synthetic data without touching production systems.

Based on: DigitalOcean Gradient Agent Templates - SQL Agent
Enhanced with: Synthetic data generation capabilities for safe testing and development

Features

• Natural Language Chat: Conversational interface for data generation requests
• Synthetic Data Generation: users, orders, payments, products, and custom schemas
• Multiple Output Formats: SQL INSERT statements, CSV, and JSON exports
• Safety First: Never touches production data; designed for staging/test bootstraps
• Real-time Generation: Instant data creation with live preview
• Dual Interface: Both chat and manual configuration options

Requirements

• Python 3.10+
• DigitalOcean account and Gradient AI credentials
• pip install -r requirements.txt

Quick Start

1. Install Dependencies

pip install -r requirements.txt

2. Set Up Gradient AI Credentials

cp env.example .env
# Edit .env and add your Gradient AI credentials:
# GRADIENT_ACCESS_TOKEN=your_token_here
# GRADIENT_WORKSPACE_ID=your_workspace_id_here

3. Launch the Web UI (Recommended)

python3 -m streamlit run app.py

Open http://localhost:8501 in your browser.

4. Generate Data

Use the Chat Interface tab to type natural language requests like:

• "Generate 10 mock users with random names and emails"
• "Create 20 orders with amounts between $10-$500 in 2024"
• "Give me 5 failed payment transactions"
• "Export 15 products as CSV"

Alternative: Command Line Interface

python3 main.py

Web UI Features

Chat Interface

The web UI features a conversational chat interface for data generation:

• Natural Language Processing: Type requests in plain English
• Smart Understanding: Interprets your data generation needs
• Instant Generation: Get SQL, CSV, or JSON output immediately
• Real-time Responses: Interactive conversation flow

Manual Configuration Interface

For precise control, use the manual configuration tab:

• One-Click Generation: Quick buttons for common scenarios
• Data Visualization: Interactive tables and previews
• Multiple Downloads: SQL, CSV, and JSON export options
• Easy Configuration: Sidebar controls for all parameters

Quick Actions

• 10 Users - Generate users with random names and emails
• 20 Orders ($10-$500) - Create orders with specified amount range
• 5 Failed Payments - Generate failed payment transactions
• 15 Products (CSV) - Export products in CSV format

Project Structure

• src/synthetic_data_generator.py - Core data generator
• src/sql_tools.py - SQL safety helpers and formatting
• src/agent.py - Interactive agent
• src/config.py - Environment settings
• main.py - Command-line entrypoint
• app.py - Streamlit web UI

Usage Examples

Generate Users

Generate 50 users with realistic addresses and phone numbers

Create Orders

Create 20 orders with amounts between $10-$500 in 2024

Failed Payments

Give me 5 failed payment transactions

Export Data

Export 15 products as CSV

Safety Features

• Never touches production data
• Generates realistic but fake data
• Safe for staging and development environments
• Multiple output formats available

Notes

• Use env.example as a guide; never commit real .env files
• Generated data is synthetic; do not treat as real user information
• The chat interface works with or without Gradient AI credentials