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49b729b30a
add RequestMetricsMiddleware which tracks key metrics related to each request the LLS server will recieve: 1. llama_stack_requests_total: tracks the total amount of requests the server has processed 2. llama_stack_request_duration_seconds: tracks the duration of each request 3. llama_stack_concurrent_requests: tracks concurrently processed requests by the server The usage of a middleware allows this to be done on the server level without having to add custom handling to each router like the inference router has today for its API specific metrics. Also, add some unit tests for this functionality resolves #2597 Signed-off-by: Charlie Doern <cdoern@redhat.com> |
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| .. | ||
| _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