Llama Stack

Quick Start | Documentation | Colab Notebook

Llama Stack defines and standardizes the core building blocks needed to bring generative AI applications to market. It provides a unified set of APIs with implementations from leading service providers, enabling seamless transitions between development and production environments.

We focus on making it easy to build production applications with the Llama model family - from the latest Llama 3.3 to specialized models like Llama Guard for safety.

Key Features

• Unified API Layer for:

  • Inference: Run LLM models efficiently
  • Safety: Apply content filtering and safety policies
  • DatasetIO: Store and retrieve knowledge for RAG
  • Agents: Build multi-step agentic workflows
  • Evaluation: Test and improve model and agent quality
  • Telemetry: Collect and analyze usage data and complex agentic traces
  • Post Training ( Coming Soon ): Fine tune models for specific use cases

• Rich Provider Ecosystem

  • Local Development: Meta's Reference,Ollama, vLLM, TGI
  • Self-hosted: Chroma, pgvector, Nvidia NIM
  • Cloud: Fireworks, Together, Nvidia, AWS Bedrock, Groq, Cerebras
  • On-device: iOS and Android support

• Built for Production

  • Pre-packaged distributions for common deployment scenarios
  • Comprehensive evaluation capabilities
  • Full observability and monitoring
  • Provider federation and fallback

Supported Llama Stack Implementations

API Providers

API Provider Builder	Environments	Agents	Inference	Memory	Safety	Telemetry
Meta Reference	Single Node	✔️	✔️	✔️	✔️	✔️
Cerebras	Hosted		✔️
Fireworks	Hosted	✔️	✔️	✔️
AWS Bedrock	Hosted		✔️		✔️
Together	Hosted	✔️	✔️		✔️
Groq	Hosted		✔️
Ollama	Single Node		✔️
TGI	Hosted and Single Node		✔️
NVIDIA NIM	Hosted and Single Node		✔️
Chroma	Single Node			✔️
PG Vector	Single Node			✔️
PyTorch ExecuTorch	On-device iOS	✔️	✔️
vLLM	Hosted and Single Node		✔️

Distributions

A Llama Stack Distribution (or "distro") is a pre-configured bundle of provider implementations for each API component. Distributions make it easy to get started with a specific deployment scenario - you can begin with a local development setup (eg. ollama) and seamlessly transition to production (eg. Fireworks) without changing your application code. Here are some of the distributions we support:

Distribution	Llama Stack Docker	Start This Distribution
Meta Reference	llamastack/distribution-meta-reference-gpu	Guide
Meta Reference Quantized	llamastack/distribution-meta-reference-quantized-gpu	Guide
Cerebras	llamastack/distribution-cerebras	Guide
Ollama	llamastack/distribution-ollama	Guide
TGI	llamastack/distribution-tgi	Guide
Together	llamastack/distribution-together	Guide
Fireworks	llamastack/distribution-fireworks	Guide
vLLM	llamastack/distribution-remote-vllm	Guide

Installation

You have two ways to install this repository:

1. Install as a package: You can install the repository directly from PyPI by running the following command:

   pip install llama-stack
   

2. Install from source: If you prefer to install from the source code, make sure you have conda installed. Then, follow these steps:

    mkdir -p ~/local
    cd ~/local
    git clone git@github.com:meta-llama/llama-stack.git
   
    conda create -n stack python=3.10
    conda activate stack
   
    cd llama-stack
    pip install -e .
   

Documentation

Please checkout our Documentation page for more details.

• CLI reference
  • Guide using llama CLI to work with Llama models (download, study prompts), and building/starting a Llama Stack distribution.
• Getting Started
  • Quick guide to start a Llama Stack server.
  • Jupyter notebook to walk-through how to use simple text and vision inference llama_stack_client APIs
  • The complete Llama Stack lesson Colab notebook of the new Llama 3.2 course on Deeplearning.ai.
  • A Zero-to-Hero Guide that guide you through all the key components of llama stack with code samples.
• Contributing
  • Adding a new API Provider to walk-through how to add a new API provider.

Llama Stack Client SDKs

Language	Client SDK	Package
Python	llama-stack-client-python
Swift	llama-stack-client-swift
Node	llama-stack-client-node
Kotlin	llama-stack-client-kotlin

Check out our client SDKs for connecting to Llama Stack server in your preferred language, you can choose from python, node, swift, and kotlin programming languages to quickly build your applications.

You can find more example scripts with client SDKs to talk with the Llama Stack server in our llama-stack-apps repo.