Local AI Assistant powered by Gemma 4

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Gemma 4 Challenge: Build With Gemma 4 Submission

This is a submission for the Gemma 4 Challenge: Build with Gemma 4

What I Built

Reiseki (霊石)　is a local AI assistant. It uses Gemma 4 via Ollama to handle real tasks: reading and writing files, generating Word and PDF documents, lightweight data analysis, managing reminders, and remembering context across sessions.

The goal was to build something usable by people who have never touched a terminal. Reiseki ships as a Windows installer — after installing Ollama and a model, you pick a workspace folder, and the agent is ready. No Python environment, no config files, no command line.

Under the hood it runs a ReAct loop (Reason → Act → Observe) with 15+ tools, persistent conversation history in SQLite, a live tool trace in the UI, and a LAN access toggle for smartphone use via QR code.

Code & Demo

The full source code and a video are available on GitHub:
github.com/Flo1632/reiseki

The Windows installer (ReisekiSetup.exe) is available on the Releases page.

How I Used Gemma 4

Reiseki uses Gemma 4:e2b (the 2B edge model) as its default model via Ollama.

The choice was deliberate: Reiseki is built specifically for laptops and low-RAM devices. Most capable local models require significantly more resources or a dedicated GPU. Gemma 4:e2b is the first model I tested that handles multi-step tool calling reliably at this hardware tier — it follows the ReAct loop, uses tools correctly, and produces coherent responses.