{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/6"}],"enrichment":{"capability":"Provides a configuration API for building synthetic data generation pipelines in the NeMo Data Designer framework, allowing you to define data sources, LLM models, and column generation rules.","skillfed_tags":["synthetic-data","configuration-framework","nvidia-nemo"],"use_cases":["Define synthetic data generation pipelines with multiple LLM models and custom inference parameters for experimentation.","Configure column samplers (UUID, categorical, numeric) and LLM-based text generation for structured dataset creation.","Build and serialize data generation configurations as reusable pipeline definitions.","Integrate configuration management into a larger NeMo Data Designer workflow for reproducible synthetic data generation."],"what_it_does":"data-designer-config is a configuration layer for NVIDIA's NeMo Data Designer synthetic data generation framework. It provides a builder-pattern API for constructing data generation pipelines declaratively, letting you define model configurations, inference parameters, and column generation rules (both sampled and LLM-based). The package is lightweight and can be used standalone for configuration management, though it is primarily intended as a dependency of the larger Data Designer framework.\n\nThe package depends on common data and ML libraries (pandas, numpy, pydantic, requests, httpx, jinja2, pillow, pyarrow, yaml, and others) to support configuration serialization, validation, and rendering. It targets Python 3.10 and later, is actively maintained, and carries no known security vulnerabilities.","worth_installing":"Yes, if you are building or using the NeMo Data Designer framework. The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it a safe dependency. If you need standalone configuration management for synthetic data pipelines, verify first that the package's feature set meets your needs independently of the full framework."},"id":"data-designer-config","links":{"html":"https://skillfed.io/packages/data-designer-config","md":"https://skillfed.io/packages/data-designer-config.md","pypi":"https://pypi.org/project/data-designer-config/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-11","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"data-designer-config","python_support":"supports_current","summary":"Configuration layer for DataDesigner synthetic data generation"},"popularity":{"monthly_downloads":312393,"position":7724,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.9.1"}