Dynamically annotating functions for agents and function calling for chats.

[igorcosta]

Summary

This pull request introduces a new article and a Jupyter notebook that explain how to dynamically annotate Python classes for function calling and agent utilization. The changes include a detailed walkthrough on how to create a decorator for function schema annotation, a function registry to map function names to the functions themselves, and how to use this registry to resolve function calls. The article and notebook are added to the registry for easy access.

New content:

• articles/dynamic_annotation_function_calling_and_agents.md: This new article explains how to dynamically annotate Python classes for function calling and agent utilization. It includes code examples and explanations for creating a FunctionRegistry class, a function_schema decorator, and how to use these tools.

• examples/Dynamically_annotating_functions_python.ipynb: This new Jupyter notebook contains the same content as the article but in an interactive format.

Updates to the registry:

• registry.yaml: Added the new article and Jupyter notebook to the registry. [1] [2]

Motivation

Why are these changes necessary? How do they improve the cookbook?

The examples only explore the capability, but nothing describe the capacity that can be achieved by scaling the function calling to the next level, this article and notebook explore these options where developers can just annotate and describe what they want.

This was part of my medium article.

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