Providers Overview — llama-stack documentation (original) (raw)

The goal of Llama Stack is to build an ecosystem where users can easily swap out different implementations for the same API. Examples for these include:

Providers come in two flavors:

Importantly, Llama Stack always strives to provide at least one fully inline provider for each API so you can iterate on a fully featured environment locally.

External Providers

Llama Stack supports external providers that live outside of the main codebase. This allows you to create and maintain your own providers independently. See the External Providers Guide for details.

Agents

Run multi-step agentic workflows with LLMs with tool usage, memory (RAG), etc.

DatasetIO

Interfaces with datasets and data loaders.

Eval

Generates outputs (via Inference or Agents) and perform scoring.

Inference

Runs inference with an LLM.

Post Training

Fine-tunes a model.

Safety

Applies safety policies to the output at a Systems (not only model) level.

Scoring

Evaluates the outputs of the system.

Telemetry

Collects telemetry data from the system.

Tool Runtime

Is associated with the ToolGroup resouces.

Vector IO

Vector IO refers to operations on vector databases, such as adding documents, searching, and deleting documents. Vector IO plays a crucial role in Retreival Augmented Generation (RAG), where the vector io and database are used to store and retrieve documents for retrieval.

Vector IO Providers

The following providers (i.e., databases) are available for Vector IO: