🎨 NeMo Data Designer

Generate high-quality synthetic datasets from scratch or using your own seed data.

📄 Read the technical report — Architecture, programming model, and case studies for multimodal synthetic data generation.

Welcome!

Data Designer helps you create synthetic datasets that go beyond simple LLM prompting. Whether you need diverse statistical distributions, meaningful correlations between fields, or validated high-quality outputs, Data Designer provides a flexible framework for building production-grade synthetic data.

What can you do with Data Designer?

• Generate diverse text, structured data, and images using samplers, LLMs, image models, or existing seed datasets
• Build multimodal workflows with image, audio, and video context
• Connect generation to external tools through local or remote MCP servers and capture interaction traces
• Control relationships between fields with dependency-aware generation
• Validate and score outputs with Python, SQL, custom validators, and LLM judges
• Extend Data Designer with plugins for specialized data sources, generation capabilities, and processing steps
• Preview, resume, and monitor generation from small experiments to large runs

Quick Start

1. Install

pip install data-designer

[!NOTE] This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.

Or install from source:

git clone https://github.com/NVIDIA-NeMo/DataDesigner.git
cd DataDesigner
make install

2. Set your API key

Start with one of our default model providers:

• NVIDIA Build API
• OpenAI
• OpenRouter

Grab your API key(s) using the above links and set one or more of the following environment variables:

export NVIDIA_API_KEY="your-api-key-here"

export OPENAI_API_KEY="your-openai-api-key-here"

export OPENROUTER_API_KEY="your-openrouter-api-key-here"

3. Start generating data!

import data_designer.config as dd
from data_designer.interface import DataDesigner

# Initialize with default settings
data_designer = DataDesigner()
config_builder = dd.DataDesignerConfigBuilder()

# Add a product category
config_builder.add_column(
    dd.SamplerColumnConfig(
        name="product_category",
        sampler_type=dd.SamplerType.CATEGORY,
        params=dd.CategorySamplerParams(
            values=["Electronics", "Clothing", "Home & Kitchen", "Books"],
        ),
    )
)

# Generate personalized customer reviews
config_builder.add_column(
    dd.LLMTextColumnConfig(
        name="review",
        model_alias="nvidia-text",
        prompt="Write a brief product review for a {{ product_category }} item you recently purchased.",
    )
)

# Preview your dataset
preview = data_designer.preview(config_builder=config_builder)
preview.display_sample_record()

Do more with Data Designer plugins

Plugins extend the data sources, generation capabilities, and processing steps available in your Data Designer workflows. The DataDesignerPlugins repository contains optional NVIDIA-maintained packages that add these capabilities.