For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
  • Getting Started
    • Welcome
    • Contributing
  • Concepts
    • Columns
    • Seed Datasets
    • Agent Rollout Ingestion
    • Custom Columns
    • Validators
    • Processors
    • Person Sampling
    • Traces
    • Architecture & Performance
    • Deployment Options
    • Security
  • Tutorials
    • Overview
    • The Basics
    • Structured Outputs, Jinja Expressions, and Conditional Generation
    • Seeding with an External Dataset
    • Providing Images as Context
    • Generating Images
    • Image-to-Image Editing
  • Recipes
    • Recipe Cards
  • Plugins
    • Overview
    • Example Plugin
    • FileSystemSeedReader Plugins
    • Discover
  • Code Reference
    • Overview
  • Dev Notes
    • Overview
    • Prompt Sensitivity
    • Retriever SDG Toolkit
    • Have It Your Way
    • VLM Long Document Understanding
    • Push Datasets to Hugging Face Hub
    • Text-to-SQL for Nemotron Super
    • Async All the Way Down
    • Owning the Model Stack
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Tutorials

Tutorials Overview

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These tutorials walk through Data Designer end-to-end with executable Jupyter notebooks. Each one runs in Google Colab — no local setup required.

NotebookWhat you learn
The BasicsDeclare columns, generate your first dataset
Structured Outputs, Jinja Expressions, and Conditional GenerationSchema-constrained outputs and dynamic prompts
Seeding with an External DatasetUse existing data as input for generation
Providing Images as ContextMultimodal prompts with image inputs
Generating ImagesCreate image columns from text prompts
Image-to-Image EditingEdit images using image context
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