mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-12-28 01:41:59 +00:00
4df8caab41
Testing with Codex locally, I found another issue in how we were plumbing through tool calls in multi-turn scenarios and the way tool call inputs and outputs from previous turns were passed back into future turns. This led me to realize we were missing the function tool call output type in the Responses API, so this adds that and plumbs handling of it through the responses API to chat completion conversion code. Signed-off-by: Ben Browning <bbrownin@redhat.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 | ||
| 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