llama-stack-mirror/docs/source/concepts/apis.md

APIs

A Llama Stack API is described as a collection of REST endpoints. We currently support the following APIs:

• Inference: run inference with a LLM
• Safety: apply safety policies to the output at a Systems (not only model) level
• Agents: run multi-step agentic workflows with LLMs with tool usage, memory (RAG), etc.
• DatasetIO: interface with datasets and data loaders
• Scoring: evaluate outputs of the system
• Eval: generate outputs (via Inference or Agents) and perform scoring
• VectorIO: perform operations on vector stores, such as adding documents, searching, and deleting documents
• Telemetry: collect telemetry data from the system

We are working on adding a few more APIs to complete the application lifecycle. These will include:

• Batch Inference: run inference on a dataset of inputs
• Batch Agents: run agents on a dataset of inputs
• Post Training: fine-tune a Llama model
• Synthetic Data Generation: generate synthetic data for model development