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# What does this PR do? Context: https://github.com/meta-llama/llama-stack/issues/2937 The API design is inspired by existing offerings, but not exactly the same: * `top_n` as the parameter to control number of results, instead of `top_k`, since `n` is conventional to control number * `truncation` bool instead of `max_token_per_doc`, since we should just handle the truncation automatically depending on model capability, instead of user setting the context length manually. * `data` field in the response, to be consistent with other OpenAI APIs (though they don't have a rerank API). Also, it is one less name to learn in the API. ## Test Plan Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com> |
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Llama Stack Documentation
Here's a collection of comprehensive guides, examples, and resources for building AI applications with Llama Stack. For the complete documentation, visit our ReadTheDocs page.
Render locally
From the llama-stack root directory, run the following command to render the docs locally:
uv run --group docs sphinx-autobuild docs/source docs/build/html --write-all
You can open up the docs in your browser at http://localhost:8000
Content
Try out Llama Stack's capabilities through our detailed Jupyter notebooks:
- Building AI Applications Notebook - A comprehensive guide to building production-ready AI applications using Llama Stack
- Benchmark Evaluations Notebook - Detailed performance evaluations and benchmarking results
- Zero-to-Hero Guide - Step-by-step guide for getting started with Llama Stack