How to Set Up a Self-Hosted AI Stack in Your Homelab

Running AI models locally is no longer reserved for researchers with GPU clusters. With the right setup, you can run powerful open-source models on commodity hardware — and keep your data completely private.

In this post, I will walk through how I built a self-hosted AI stack using Ollama, Open WebUI, and a local Notion-to-WordPress publishing pipeline powered by Notipo.

Why Self-Host?

Privacy is the obvious answer. When you run models locally, your prompts never leave your network. But there is another reason: cost. Running GPT-4 for every task adds up fast. A local Llama 3 or Mistral model handles 90% of tasks at zero marginal cost.

The Stack

The core components are simple. Ollama runs the models — it handles downloading, running, and serving any open-source model via a local API. Open WebUI gives you a ChatGPT-style interface on top of Ollama. And Notipo handles the publishing side, syncing content from Notion to WordPress automatically.

Setting Up Ollama

Install Ollama and pull a model. Llama 3.2 is a good starting point — it runs well on 16GB of RAM and handles writing tasks comfortably.

Once Ollama is running, you have a local API at localhost:11434 that any agent or script can call.

Connecting to Notipo

With Notipo installed and configured, an AI agent running locally can write a post, call notipo posts create, and have it live on WordPress in under 10 seconds. The agent never needs internet access except for the final publish step.

This is the self-hosted agentic publishing stack — local model, local orchestration, cloud publishing only when you choose it.