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# What does this PR do? First step towards cleaning up the API reference section of the docs. - Separates API reference into 3 sections: stable (`v1`), experimental (`v1alpha` and `v1beta`), and deprecated (`deprecated=True`) - Each section is accessible via the dropdown menu and `docs/api-overview` <img width="1237" height="321" alt="Screenshot 2025-09-30 at 5 47 30 PM" src="https://github.com/user-attachments/assets/fe0e498c-b066-46ed-a48e-4739d3b6724c" /> <img width="860" height="510" alt="Screenshot 2025-09-30 at 5 47 49 PM" src="https://github.com/user-attachments/assets/a92a8d8c-94bf-42d5-9f5b-b47bb2b14f9c" /> - Deprecated APIs: Added styling to the sidebar, and a notice on the endpoint pages <img width="867" height="428" alt="Screenshot 2025-09-30 at 5 47 43 PM" src="https://github.com/user-attachments/assets/9e6e050d-c782-461b-8084-5ff6496d7bd9" /> Closes #3628 TODO in follow-up PRs: - Add the ability to annotate API groups with supplementary content (so we can have longer descriptions of complex APIs like Responses) - Clean up docstrings to show API endpoints (or short semantic titles) in the sidebar ## Test Plan - Local testing - Made sure API conformance test still passes |
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docs | ||
notebooks | ||
openapi_generator | ||
src | ||
static | ||
zero_to_hero_guide | ||
docusaurus.config.ts | ||
dog.jpg | ||
getting_started.ipynb | ||
getting_started_llama4.ipynb | ||
getting_started_llama_api.ipynb | ||
license_header.txt | ||
original_rfc.md | ||
package-lock.json | ||
package.json | ||
quick_start.ipynb | ||
README.md | ||
sidebars.ts | ||
tsconfig.json |
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 Github page.
Render locally
From the llama-stack docs/
directory, run the following commands to render the docs locally:
npm install
npm run gen-api-docs all
npm run build
npm run serve
You can open up the docs in your browser at http://localhost:3000
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