What is Llama Stack?
Learn about Llama Stack, a modular, API-first framework that unifies the core infrastructure and workflows needed to build, run, and scale generative AI applications in real-world environments.
Llama Stack was created to address a growing pain in AI: while models have rapidly advanced, building actual applications with them remains frustratingly complex. Developers often must patch together multiple libraries, services, and configurations to make a simple chatbot reliable and safe. Llama Stack streamlines this by offering an architecture with sensible defaults that allows you to customize and extend components as needed.
Despite its name, Llama Stack isn’t limited to Meta’s Llama models; it’s a flexible framework that can support almost any model through its provider abstraction layer.
The purpose of this lesson is to lay the groundwork for everything to come. Before we explore APIs, build agents, or connect retrieval systems, we need to understand what Llama Stack is fundamentally solving, how it’s designed, and what kind of applications it enables. We won’t be revisiting the basics of LLMs here. You’re expected to already be familiar with core generative AI concepts. Here, we’re tackling how to turn that model knowledge into application-level development without reinventing the wheel at every layer.
AI development today
If you’ve tried to build anything more than a one-off demo with an LLM, you’ve probably encountered the same core frustrations: