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# What does this PR do? Clarifies that non-Llama models can be trained via the Post Training API ## Test Plan Build docs locally Signed-off-by: Nathan Weinberg <nweinber@redhat.com>
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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 model
- Synthetic Data Generation: generate synthetic data for model development