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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>
18 lines
1,019 B
Markdown
18 lines
1,019 B
Markdown
## APIs
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A Llama Stack API is described as a collection of REST endpoints. We currently support the following APIs:
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- **Inference**: run inference with a LLM
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- **Safety**: apply safety policies to the output at a Systems (not only model) level
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- **Agents**: run multi-step agentic workflows with LLMs with tool usage, memory (RAG), etc.
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- **DatasetIO**: interface with datasets and data loaders
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- **Scoring**: evaluate outputs of the system
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- **Eval**: generate outputs (via Inference or Agents) and perform scoring
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- **VectorIO**: perform operations on vector stores, such as adding documents, searching, and deleting documents
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- **Telemetry**: collect telemetry data from the system
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We are working on adding a few more APIs to complete the application lifecycle. These will include:
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- **Batch Inference**: run inference on a dataset of inputs
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- **Batch Agents**: run agents on a dataset of inputs
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- **Post Training**: fine-tune a model
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- **Synthetic Data Generation**: generate synthetic data for model development
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