--- title: APIs description: Available REST APIs and planned capabilities in Llama Stack sidebar_label: APIs sidebar_position: 1 --- # APIs A Llama Stack API is described as a collection of REST endpoints following OpenAI API standards. 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 - **Files**: manage file uploads, storage, and retrieval - **Telemetry**: collect telemetry data from the system - **Post Training**: fine-tune a model - **Tool Runtime**: interact with various tools and protocols - **Responses**: generate responses from an LLM 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 - **Batches**: OpenAI-compatible batch management for inference ## OpenAI API Compatibility We are working on adding OpenAI API compatibility to Llama Stack. This will allow you to use Llama Stack with OpenAI API clients and tools. ### File Operations and Vector Store Integration The Files API and Vector Store APIs work together through file operations, enabling automatic document processing and search. This integration implements the [OpenAI Vector Store Files API specification](https://platform.openai.com/docs/api-reference/vector-stores-files) and allows you to: - Upload documents through the Files API - Automatically process and chunk documents into searchable vectors - Store processed content in vector databases based on the availability of [our providers](../../providers/index.mdx) - Search through documents using natural language queries For detailed information about this integration, see [File Operations and Vector Store Integration](../file_operations_vector_stores.md).