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commit db0e82756a2ae066f1a24ff627994b5808c3d72c Author: Stefan Krawczyk <[email protected]> AuthorDate: Tue Feb 24 15:45:24 2026 -0800 Update contrib/NOTICE with third-party attributions Added proper attribution for Apache 2.0-compatible code that was adapted or referenced in the contrib package: 1. OpenAI Cookbook (MIT License) - hamilton.contrib.user.skrawcz.customize_embeddings - Based on: Customizing_embeddings.ipynb - Copyright (c) 2025 OpenAI 2. NumPy Tutorials (BSD 3-Clause License) - hamilton.contrib.user.skrawcz.air_quality_analysis - Based on: tutorial-air-quality-analysis.md - Copyright (c) 2005-2025, NumPy Developers 3. Optuna Examples (MIT License) - hamilton.contrib.user.zilto.xgboost_optuna - References: xgboost_integration.py - Copyright (c) 2018 Preferred Networks, Inc. All these licenses are Category A (MIT and BSD-3-Clause) and are Apache 2.0 compatible. The code has been adapted/used in compliance with their respective licenses. Related: Apache legal policy on including third-party content https://www.apache.org/legal/resolved.html#category-a --- contrib/NOTICE | 30 ++++++++++++++++++++++++++++++ 1 file changed, 30 insertions(+) diff --git a/contrib/NOTICE b/contrib/NOTICE index eddfea68..b9b9a9e4 100644 --- a/contrib/NOTICE +++ b/contrib/NOTICE @@ -3,3 +3,33 @@ Copyright 2025-2026 The Apache Software Foundation This product includes software developed at The Apache Software Foundation (http://www.apache.org/). + +================================================================================ + +This product includes code adapted from the OpenAI Cookbook +(https://github.com/openai/openai-cookbook), which is licensed under the MIT License. +Specifically, the hamilton.contrib.user.skrawcz.customize_embeddings module is based on: +https://github.com/openai/openai-cookbook/blob/6d89e11fed344237f07910a98ba98303ece7dd18/examples/Customizing_embeddings.ipynb + + MIT License + Copyright (c) 2025 OpenAI + +================================================================================ + +This product includes code adapted from NumPy Tutorials +(https://github.com/numpy/numpy-tutorials), which is licensed under the BSD 3-Clause License. +Specifically, the hamilton.contrib.user.skrawcz.air_quality_analysis module is based on: +https://github.com/numpy/numpy-tutorials/blob/main/content/tutorial-air-quality-analysis.md + + BSD 3-Clause License + Copyright (c) 2005-2025, NumPy Developers + +================================================================================ + +This product references code patterns from Optuna Examples +(https://github.com/optuna/optuna-examples), which is licensed under the MIT License. +Specifically, the hamilton.contrib.user.zilto.xgboost_optuna module references: +https://github.com/optuna/optuna-examples/blob/main/xgboost/xgboost_integration.py + + MIT License + Copyright (c) 2018 Preferred Networks, Inc.
