Self-Hosted AI Agent Orchestration: A Full Tour
Clone the repo, bring the stack up, install a model, then build, run, and trace an agent — the full tour.
Walkthrough · 7:01
One agent, two models. A small local model triages every request, and a router sends each one where it belongs: greetings and short factual questions to a local model, coding and multi-step reasoning to a hosted model registered as an OpenAI-compatible API. The reasons are the ones you'd expect — keep sensitive requests on your machine, and stop paying API prices for easy work.
It is built from the Hybrid Reasoner sample. The triage model answers with a minified JSON route, a transform node combines that route with the original question, and the router follows it to the local or the remote branch. Two test runs show both paths, and the trace shows which model answered each time.
Clone the repo, bring the stack up, install a model, then build, run, and trace an agent — the full tour.
Upload a PDF, crawl a docs site, and wire both into an agent as retrieval tools — no code.
Speech-to-text, a model, and text-to-speech wired on the canvas — a spoken conversation with an agent you built.
Build the images, load them into a cluster, apply the manifests, and sign in — the same stack, on Kubernetes.