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Starting a Llama Stack Server

You can run a Llama Stack server in one of the following ways:

As a Library:​

This is the simplest way to get started. Using Llama Stack as a library means you do not need to start a server. This is especially useful when you are not running inference locally and relying on an external inference service (eg. fireworks, together, groq, etc.) See Using Llama Stack as a Library

Container:​

Another simple way to start interacting with Llama Stack is to just spin up a container (via Docker or Podman) which is pre-built with all the providers you need. We provide a number of pre-built images so you can start a Llama Stack server instantly. You can also build your own custom container. Which distribution to choose depends on the hardware you have. See Selection of a Distribution for more details.

Kubernetes:​

If you have built a container image and want to deploy it in a Kubernetes cluster instead of starting the Llama Stack server locally. See Kubernetes Deployment Guide for more details.

Configure logging​

Control log output via environment variables before starting the server.

  • LLAMA_STACK_LOGGING sets per-component levels, e.g. LLAMA_STACK_LOGGING=server=debug;core=info.
  • Supported categories: all, core, server, router, inference, agents, safety, eval, tools, client.
  • Levels: debug, info, warning, error, critical (default is info). Use all=<level> to apply globally.
  • LLAMA_STACK_LOG_FILE=/path/to/log mirrors logs to a file while still printing to stdout.

Export these variables prior to running llama stack run, launching a container, or starting the server through any other pathway.

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