title	DataGen
emoji	🧬
colorFrom	indigo
colorTo	pink
sdk	docker
short_description	AI-powered synthetic data generator

🧬 DataGen: AI-Powered Synthetic Data Generator

Generate realistic synthetic datasets by simply describing what you need.

🚀 Try the Live Demo

✨ What DataGen Does

DataGen transforms simple descriptions into structured datasets using AI. Perfect for researchers, data scientists, and developers who need realistic test data fast.

Key Features:

• Type what you want → Get real data
• Multiple formats: CSV, JSON, Parquet, Markdown
• Dataset types: Tables, time-series, text data
• AI-powered: Uses GPT and Claude models
• Instant download with clean, ready-to-use datasets

To understand the full workflow from user input to file output, see the architecture section.

🚀 Quick Start

Prerequisites

• Python 3.11+
• Docker Desktop
• uv package manager

Installation

git clone https://github.com/lisekarimi/datagen.git
cd datagen
uv sync
source .venv/bin/activate  # Unix/macOS
# or .\.venv\Scripts\activate on Windows

Configuration

1. Copy .env.example to .env
2. Populate it with the required secrets

Run DataGen

# Local development
make run

# With hot reload
make ui

For complete setup instructions, commands, and development guidelines, see the Docs Page.

🧑‍💻 How to Use

1. Describe your data: "Customer purchase history with demographics"
2. Choose format: CSV, JSON, Parquet, or Markdown
3. Select AI model: GPT or Claude
4. Set sample size: Number of records to generate
5. Generate & download your dataset

🛡️ Quality & Security

DataGen maintains high standards with comprehensive test coverage, automated security scanning, and code quality enforcement.

For CI/CD setup and technical details, see the docs Page.

📝 Notes

• Generated files are automatically cleaned up after 5 minutes
• Supports 10-1000 samples per dataset
• JSON output includes proper indentation for readability
• Cross-platform compatibility (Windows, macOS, Linux)

📄 License

MIT