Before you begin
You need Python 3.11+, Git, and uv. Choose one inference route:
Hosted inference does not require a local GPU. Node.js and a headset are optional until you add spatial presence.
1
Get the runtime
2
Create and configure your Entity
- Hosted API
- Local Ollama
.env and Entity YAML.Memory also needs embeddings. Use the wizard’s provider defaults where available; if your chat provider does not serve embeddings, configure the separate embedding route it offers.3
Start a conversation
Run the exact command the wizard prints. If you named your Entity Ask a concrete question. A successful first run reaches the terminal conversation and returns a reply without provider or embedding errors.
rook:What you just created
The Entity’s YAML defines its identity and behavior. Its runtime stores memory and state separately from the source code. The default local state lives under~/.ngram/entities/; an explicit execution workspace or portable container can change those paths.
Inspect the configured Entity:
configs/entities/rook.yaml, use rook, even if the display name inside the file differs.
Keep it running
talk is a terminal conversation. run starts the daemon and configured surfaces:
--ollama. Background work can call your inference provider while you are not chatting. Read usage and stop controls before leaving a hosted Entity running.
Stop a foreground run with Ctrl+C. Exit the terminal conversation when you finish. State persists; stopping the process does not wipe the Entity.
Give it a body
Connect the same Entity to a browser or headset.
Make it yours
Edit identity, voice, tools, and platforms.