mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-10-04 12:07:34 +00:00
cb7354a9ce
This PR focuses on improving the developer experience by adding comprehensive docstrings to the API data models across the Llama Stack. These docstrings provide detailed explanations for each model and its fields, making the API easier to understand and use. **Key changes:** - **Added Docstrings:** Added reST formatted docstrings to Pydantic models in the `llama_stack/apis/` directory. This includes models for: - Agents (`agents.py`) - Benchmarks (`benchmarks.py`) - Datasets (`datasets.py`) - Inference (`inference.py`) - And many other API modules. - **OpenAPI Spec Update:** Regenerated the OpenAPI specification (`docs/_static/llama-stack-spec.yaml` and `docs/_static/llama-stack-spec.html`) to include the new docstrings. This will be reflected in the API documentation, providing richer information to users. **Impact:** - Developers using the Llama Stack API will have a better understanding of the data structures. - The auto-generated API documentation is now more informative. --------- Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com> |
||
|---|---|---|
| .. | ||
| _static | ||
| notebooks | ||
| openapi_generator | ||
| resources | ||
| source | ||
| zero_to_hero_guide | ||
| conftest.py | ||
| contbuild.sh | ||
| dog.jpg | ||
| getting_started.ipynb | ||
| getting_started_llama4.ipynb | ||
| getting_started_llama_api.ipynb | ||
| license_header.txt | ||
| make.bat | ||
| Makefile | ||
| original_rfc.md | ||
| quick_start.ipynb | ||
| README.md | ||
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