What I Did with Hermes Agent, Ollama & Local Models

I wanted an AI agent that could actually help me plan a trip, research a destination, suggest where to stay, and find a real flight — without a subscription, without sending every question to a cloud provider, and without a monthly bill creeping up the more I used it. That search led me to two tools worth knowing: Hermes Agent and Ollama. This article is the real project that came out of pairing them: a working, tested, multi-agent travel research team running entirely on my own hardware.

Before the build, though, it's worth actually understanding the two tools doing the work, since most of what makes this project possible traces back to what each one is specifically good at.

Introducing Hermes Agent

Hermes Agent is an open-source AI agent built by Nous Research, released under the permissive MIT license and currently at version 0.21.1 as of this writing. It ships in two ways: a native desktop app for macOS, Windows, and Linux, and a terminal-first CLI. Both give you the same underlying agent, not a stripped-down version.

What separates Hermes from an ordinary chatbot is genuine agentic capability. It can read and edit real files on your machine, run terminal commands, and browse the live web, which is the exact combination this travel project depends on: an agent that can search for current destination information and act on what it finds, not just describe what it would do.

Understanding Ollama and Local Models

Hermes needs a language model to actually think with, and that's Ollama's job. Ollama is an open-source tool that downloads, manages, and serves large language models directly on your own computer, exposing them through a local API that behaves exactly like a cloud provider's, just pointed at localhost instead of the internet. That detail is what makes the whole pairing work: because Ollama's API is OpenAI-compatible, Hermes can talk to a model running entirely on your machine using the same integration path it would use for any cloud model.