We are [looking for contributors](https://honegumi.readthedocs.io/en/latest/contributing.html), so please let us know if you're interested! See [the high-level roadmap of Honegumi's development](https://github.com/sgbaird/honegumi/discussions/2). If you like this tool, please consider [starring it on GitHub](https://github.com/sgbaird/honegumi).
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Honegumi (骨組み), which means skeletal framework in Japanese, is a package for interactively creating API tutorials with a focus on optimization packages such as Meta's Ax Platform. You can interact with Honegumi "in the flesh" using the interactive grid below. Select one option per row and watch the template dynamically appear. Click the "Open in Colab" badge to open a self-contained Google Colab notebook corresponding to the selected template. Click "Open in GitHub" to view the notebook source directly.
:file: honegumi.html
Use Honegumi with ChatGPT to create non-halucinatory, custom Bayesian optimization scripts. See below for more info.
LLMs are good at recognizing patterns but really bad at suggesting Bayesian optimization scripts from scratch. Since Honegumi is really good at programatically giving valid Bayes opt scripts, you can use Honegumi to get a template and then ask an LLM to adapt it to your use case. The two-minute video below shows how a Honegumi template can be adapted using GPT-4 to a cookie taste optimization as a function of flour, sugar, and butter content.
<iframe width="560" height="315" src="https://www.youtube.com/embed/rnI2BvGgP9o?si=HGODRbP19MlkC662" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>:maxdepth: 2
Overview <readme>
Contributions & Help <contributing>
License <license>
Authors <authors>
Changelog <changelog>
Module Reference <api/modules>
GitHub Source <https://github.com/sgbaird/honegumi>
- {ref}
genindex - {ref}
modindex - {ref}
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