AI/ML on Landry Zetam - Tech Blog

The Full Architecture of My Kubernetes Agents

Mon, 10 Aug 2026 00:00:00 +0000

Five agents run against my K3s cluster. Three of them form a closed loop — one detects problems, one fixes them, one reviews the fix — and none of the three can do another’s job. This is everything about how they’re built: the framework, the prompt assembly, every tool, both safety gates, the memory layers, and a real pull request one of them opened.

Then I merged it and spent a day fixing what production found. Eight more bugs, none of them in the agent logic — §17 onward is that day, and it’s the more useful half.

From Transcripts to Summaries: Completing the Audio Pipeline

Sat, 20 Dec 2025 00:00:00 +0000

Remember that audio transcription pipeline I built? Raw recordings flow in, get compressed, transcribed by Whisper, and stored as JSON. Great for archival, but 204 transcript files sitting on NFS storage aren’t exactly useful. Today I’ll show you how I completed the loop—automatically summarizing transcripts with an LLM and publishing everything to my Obsidian vault.

Part 1: The Problem with Raw Transcripts

The original pipeline worked beautifully. Every morning, new transcripts appeared as JSON files:

Building an Automated Audio Transcription Pipeline on Kubernetes

Fri, 12 Dec 2025 00:00:00 +0000

Every day, raw audio recordings land on an SFTP server. By morning, they’re compressed, transcribed, and stored as searchable JSON - all without human intervention. Here’s how I built this pipeline on my homelab Kubernetes cluster.

The Problem

I had a growing collection of audio recordings that needed transcription. Manual processing wasn’t sustainable: download files, compress them, run through a transcription service, organize the output. This needed automation.

The requirements were straightforward:

ChatBuddy - Voice AI Companion for Children

Sun, 07 Dec 2025 00:00:00 +0000

Overview

ChatBuddy is an AI-powered voice companion designed specifically for children aged 3-8. When a child asks “Why is the sky blue?”, they get a fun, age-appropriate answer—not a Wikipedia article.

The system runs entirely on-device with 5 containerized services on hardware with just 8GB RAM, ensuring complete privacy while delivering natural voice interactions with educational content grounded in verified facts.

Why Build This?

Kids don’t want to type. They want to talk. And they need answers that:

Building a Local AI Cluster with Mac Hardware: From Vision to Reality

Fri, 08 Aug 2025 00:00:00 +0000

The Mission That Started It All

Note: This post combines the journeys documented in my Mac AI Cluster Project and GPUStack Mac Clustering Tutorial. For deep technical details, see those project pages.

When I first discovered EXO Labs, their mission resonated deeply with me.

Humanity is headed toward a world controlled by a handful of companies that will dictate the AI models everyone uses. The real threat isn’t AI destroying us — it’s losing sovereignty over our own minds.

Home Assistant Voice Pipeline with Ollama

Fri, 08 Aug 2025 00:00:00 +0000

Overview

This implementation demonstrates a complete voice assistant pipeline using Wyoming Satellite with Home Assistant and Ollama as the AI brain, achieving natural conversation and smart home control entirely on-premises. The system transforms spoken words into meaningful actions through a sophisticated pipeline of AI models, all running locally for complete privacy.

Why Ollama for Voice?

Voice assistants have unique requirements that Ollama handles beautifully:

Speed Requirements

Response Time: < 2 seconds for natural conversation
Model Loading: Pre-loaded models for instant responses
Streaming: Real-time token generation for faster perceived response

Privacy First

Local Processing: No cloud dependencies
Conversation History: Stored locally, never uploaded
Custom Wake Words: Combined with OpenWakeWord for complete privacy

Components Used

OpenWakeWord: Wake word detection (“Hey Jarvis”)
Whisper: Speech-to-text transcription
Ollama (Qwen2.5:3b & Llama 8B): Natural language understanding and response generation
Piper TTS: Text-to-speech synthesis
Home Assistant: Smart home orchestration and pipeline management
Wyoming Satellite: Voice satellite software on Raspberry Pi

Hardware Setup

Raspberry Pi 5 (2.4GHz, 4GB RAM) - Voice satellite device
ME6S USB Microphone - Audio input device
Bluetooth Speaker (88:92:CC:5D:CB:79) - Audio output via BlueALSA
Mini PC - Home Assistant server
Kubernetes Cluster - Container orchestration for AI services
NVIDIA GPU Node (yeezyai) - GPU acceleration for Ollama

The Voice Pipeline Architecture

The voice pipeline runs entirely on the K8s homelab, with Ollama at its heart:

Powering Open WebUI and Cline with GPUStack: My AI Infrastructure Journey

Fri, 08 Aug 2025 00:00:00 +0000

After building my Mac AI cluster, I needed a way to make it accessible to all my tools. The journey took me through several frameworks before landing on the perfect solution: GPUStack providing an OpenAI-compatible API that seamlessly integrates with everything.

The Evolution: Finding the Right Framework

The Journey

My path to the current setup wasn’t straightforward:

MLX Distributed Computing: Started here for model training and local inference on Apple Silicon
Exo Labs: Experimented with this promising framework, but pivoted when the community began a redesign
GPUStack: The solution that finally clicked - providing OpenAI-compatible endpoints that work with everything

The Current Architecture

Here’s how my AI infrastructure actually works:

Powering My Voice Assistant with Ollama: Local AI for Home Automation

Thu, 07 Aug 2025 00:00:00 +0000

Ollama has become the AI brain of my home automation infrastructure, powering my voice assistant pipeline and Home Assistant integrations. Running entirely on-premises on my NVIDIA GPU node, it enables natural language understanding and intelligent responses while maintaining complete privacy and control.

The Home Automation AI Hub

My Ollama deployment serves as the AI intelligence layer for home automation:

Ollama serves as the AI brain for voice pipeline and Home Assistant automations