Welcome to the Llama Stack Tutorial - your comprehensive guide to learning and using Llama Stack.

Llama Stack is an open-source framework that makes it easier to build, run, and experiment with large language models on your own infrastructure. It provides:

• Unified interface for different model providers (Ollama, vLLM, etc.)
• Tools and agents for complex AI workflows
• Safety and telemetry built-in
• CLI, Python SDK, and web playground for development

This repository contains hands-on tutorials covering:

• Getting started with CLI and Python SDK
• Using the web playground
• Basic model interactions

• Model Context Protocol (MCP) integration
• Retrieval Augmented Generation (RAG)
• Building interactive agents

• Safety and content filtering
• Telemetry and observability
• Production deployments

• Custom providers and extensions
• Advanced agent workflows

• Web Playground: http://localhost:8502
• Llama Stack API: http://localhost:8321
• Jaeger Telemetry: http://localhost:16686
• Tutorial Site: Run ./utilities/lab-serve then http://localhost:8080

This tutorial is designed to help developers learn Llama Stack through practical examples. The content is built with Antora and can be edited in the content/modules/ROOT/pages/ directory.