mirror of
https://github.com/meta-llama/llama-stack.git
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cb2a9784ab
Fixes multiple issues 1. llama stack build of dependencies was breaking with incompatible numpy / pandas when importing datasets Moved the notebook to start a local server instead of using library as a client. This way the setup is cleaner since its all contained and by using `uv run --with` we can test both the server setup process too in CI and release time. 2. The change to [1] surfaced some other issues - running `llama stack run` was defaulting to conda env name - provider data was not being managed properly - Some notebook cells (telemetry for evals) were not updated with latest changes Fixed all the issues and update the notebook. ### Test 1. Manually run it all in local env 2. `pytest -v -s --nbval-lax docs/getting_started.ipynb` |
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| notebooks | ||
| openapi_generator | ||
| resources | ||
| source | ||
| zero_to_hero_guide | ||
| conftest.py | ||
| contbuild.sh | ||
| dog.jpg | ||
| getting_started.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.
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