forked from phoenix-oss/llama-stack-mirror
71ed47ea76
# What does this PR do? PR adds instructions to setup vLLM remote endpoint for vllm-remote llama stack distribution. ## Test Plan * Verified with manual tests of the configured vllm-remote against vllm endpoint running on the system with Intel GPU * Also verified with ci pytests (see cmdline below). Test passes in the same capacity as it does on the A10 Nvidia setup (some tests do fail which seems to be known issues with vllm remote llama stack distribution) ``` pytest -s -v tests/integration/inference/test_text_inference.py \ --stack-config=http://localhost:5001 \ --text-model=meta-llama/Llama-3.2-3B-Instruct ``` CC: @ashwinb Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.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 | ||
| license_header.txt | ||
| make.bat | ||
| Makefile | ||
| readme.md | ||
| requirements.txt | ||
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
pip install -r requirements.txt
cd docs
python -m sphinx_autobuild source _build
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