llama-stack-mirror/docs/source/index.md

Llama Stack

Llama Stack defines and standardizes the building blocks needed to bring generative AI applications to market. It empowers developers building agentic applications by giving them options to operate in various environments (on-prem, cloud, single-node, on-device) while relying on a standard API interface and developer experience that's certified by Meta.

The Stack APIs are rapidly improving but still a work-in-progress. We invite feedback as well as direct contributions.

:alt: Llama Stack
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APIs

The set of APIs in Llama Stack can be roughly split into two broad categories:

• APIs focused on Application development

  • Inference
  • Safety
  • Memory
  • Agentic System
  • Evaluation

• APIs focused on Model development

  • Evaluation
  • Post Training
  • Synthetic Data Generation
  • Reward Scoring

Each API is a collection of REST endpoints.

API Providers

A Provider is what makes the API real – they provide the actual implementation backing the API.

As an example, for Inference, we could have the implementation be backed by open source libraries like [ torch | vLLM | TensorRT ] as possible options.

A provider can also be a relay to a remote REST service – ex. cloud providers or dedicated inference providers that serve these APIs.

Distribution

A Distribution is where APIs and Providers are assembled together to provide a consistent whole to the end application developer. You can mix-and-match providers – some could be backed by local code and some could be remote. As a hobbyist, you can serve a small model locally, but can choose a cloud provider for a large model. Regardless, the higher level APIs your app needs to work with don't need to change at all. You can even imagine moving across the server / mobile-device boundary as well always using the same uniform set of APIs for developing Generative AI applications.

Supported Llama Stack Implementations

API Providers

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

Distributions

Distribution	Llama Stack Docker	Start This Distribution	Inference	Agents	Memory	Safety	Telemetry
Meta Reference	llamastack/distribution-meta-reference-gpu	Guide	meta-reference	meta-reference	meta-reference; remote::pgvector; remote::chromadb	meta-reference	meta-reference
Meta Reference Quantized	llamastack/distribution-meta-reference-quantized-gpu	Guide	meta-reference-quantized	meta-reference	meta-reference; remote::pgvector; remote::chromadb	meta-reference	meta-reference
Ollama	llamastack/distribution-ollama	Guide	remote::ollama	meta-reference	remote::pgvector; remote::chromadb	meta-reference	meta-reference
TGI	llamastack/distribution-tgi	Guide	remote::tgi	meta-reference	meta-reference; remote::pgvector; remote::chromadb	meta-reference	meta-reference
Together	llamastack/distribution-together	Guide	remote::together	meta-reference	remote::weaviate	meta-reference	meta-reference
Fireworks	llamastack/distribution-fireworks	Guide	remote::fireworks	meta-reference	remote::weaviate	meta-reference	meta-reference

Llama Stack Client SDK

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.

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:maxdepth: 3

getting_started/index
cli_reference/index
cli_reference/download_models
api_providers/index
distribution_dev/index