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docs: establish doc templating, building, and strategy (#31)
* initial updates with jupyter tutorials and styling * filling out some docs * add blank index * update docs workflow * clean up style sheet
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.github/workflows/build_docs.yml renamed to .github/workflows/build-docs.yml

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name: build_docs
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# Disable for now while the repo is private
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# on:
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# push:
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# branches:
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# - main
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on:
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push:
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branches:
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- main
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jobs:
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deploy:
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runs-on: ubuntu-latest

‎.gitignore‎

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docs/examples/artifacts/

‎docs/assets/palette-favicon.png‎

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‎docs/code_reference/column_configs.md‎

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# Column Configurations
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The `column_configs` module defines configuration objects for all Data Designer column types. Each configuration inherits from [SingleColumnConfig](#data_designer.config.column_configs.SingleColumnConfig), which provides shared arguments like the column `name`, whether to `drop` the column after generation, and the `column_type`.
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!!! info "`column_type` is a discriminator field"
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The `column_type` argument is used to identify column types when deserializing the [Data Designer Config](data_designer_config.md) from JSON/YAML. It acts as the discriminator in a [discriminated union](https://docs.pydantic.dev/latest/concepts/unions/#discriminated-unions), allowing Pydantic to automatically determine which column configuration class to instantiate.
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::: data_designer.config.column_configs

‎docs/code_reference/config_builder.md‎

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# Data Designer's Config Builder
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The `config_builder` module provides a high-level interface for constructing Data Designer configurations through the [DataDesignerConfigBuilder](#data_designer.config.config_builder.DataDesignerConfigBuilder) class, enabling programmatic creation of [DataDesignerConfig](data_designer_config.md#data_designer.config.data_designer_config.DataDesignerConfig) objects by incrementally adding column configurations, constraints, processors, and profilers.
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You can use the builder to create Data Designer configurations from scratch or from existing configurations stored in YAML/JSON files via [`from_config()`](#data_designer.config.config_builder.DataDesignerConfigBuilder.from_config). The builder includes validation capabilities to catch configuration errors early and can work with seed datasets from local sources or external datastores. Once configured, use [`build()`](#data_designer.config.config_builder.DataDesignerConfigBuilder.build) to generate the final configuration object or [`write_config()`](#data_designer.config.config_builder.DataDesignerConfigBuilder.write_config) to serialize it to disk.
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!!! info "Model configs are required"
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[DataDesignerConfigBuilder](#data_designer.config.config_builder.DataDesignerConfigBuilder) requires a list of model configurations at initialization. This tells the builder which model aliases can be referenced by LLM-generated columns (such as [`LLMTextColumnConfig`](column_configs.md#data_designer.config.column_configs.LLMTextColumnConfig), [`LLMCodeColumnConfig`](column_configs.md#data_designer.config.column_configs.LLMCodeColumnConfig), [`LLMStructuredColumnConfig`](column_configs.md#data_designer.config.column_configs.LLMStructuredColumnConfig), and [`LLMJudgeColumnConfig`](column_configs.md#data_designer.config.column_configs.LLMJudgeColumnConfig)). Each model configuration specifies the model alias, model provider, model ID, and inference parameters that will be used during data generation.
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::: data_designer.config.config_builder

‎docs/code_reference/data_designer_config.md‎

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# Data Designer Configuration
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[DataDesignerConfig](#data_designer.config.data_designer_config.DataDesignerConfig) is the main configuration object for builder datasets with Data Designer. It is a declarative configuration for defining the dataset you want to generate column-by-column, including options for dataset post-processing, validation, and profiling.
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Generally, you should use the [DataDesignerConfigBuilder](config_builder.md#data_designer.config.config_builder.DataDesignerConfigBuilder) to build your configuration, but you can also build it manually by instantiating the [DataDesignerConfig](#data_designer.config.data_designer_config.DataDesignerConfig) class directly.
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::: data_designer.config.data_designer_config

‎docs/css/code_select.css‎

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‎docs/css/mkdocstrings.css‎

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/* https://primer.style/octicons/arrow-up-right-24 */
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‎docs/css/style.css‎

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.nvidia-green {
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color: #76B900; /* NVIDIA green */
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/* Style "NeMo" in the site name with pure CSS */
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.md-header__topic:first-child .md-ellipsis {
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/* Make "NeMo" green using a gradient background trick */
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.md-header__topic:first-child .md-ellipsis::after {
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content: "NeMo Data Designer";
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visibility: visible;
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position: absolute;
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left: 0;
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background: linear-gradient(90deg, #76B900 0%, #76B900 4.8ch, currentColor 4.8ch, currentColor 100%);
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background-clip: text;
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/* Prevent selection of prompt and output markers */
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‎docs/index.md‎

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# Data Designer
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Welcome to the Data Designer documentation.

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