In this article, you will learn how to build a local, privacy-first tool-calling agent using the Gemma 4 model family and Ollama.

Topics we will cover include:

An overview of the Gemma 4 model family and its capabilities.

How tool calling enables language models to interact with external functions.

How to implement a local tool calling system using Python and Ollama.

How to Implement Tool Calling with Gemma 4 and Python

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Introducing the Gemma 4 Family

The open-weights model ecosystem shifted recently with the release of the Gemma 4 model family . Built by Google, the Gemma 4 variants were created with the intention of providing frontier-level capabilities under a permissive Apache 2.0 license, enabling machine learning practitioners complete control over their infrastructure and data privacy.

The Gemma 4 release features models ranging from the parameter-dense 31B and structurally complex 26B Mixture of Experts (MoE) to lightweight, edge-focused variants.…