forked from phoenix-oss/llama-stack-mirror
dd62a2388c
# What does this PR do? - Adds a note about unexpected Brave Search output appearing even when Tavily Search is called. This behavior is expected for now and is a work in progress https://github.com/meta-llama/llama-stack/issues/1229. The note aims to clear any confusion for new users. - Adds two example scripts demonstrating how to build an agent using: 1. WebSearch tool 2. WolframAlpha tool These examples provide new users with an instant understanding of how to integrate these tools. [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan Tested these example scripts using following steps: step 1. `ollama run llama3.2:3b-instruct-fp16 --keepalive 60m` step 2. ``` export INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" export LLAMA_STACK_PORT=8321 ``` step 3: `llama stack run --image-type conda ~/llama-stack/llama_stack/templates/ollama/run.yaml` step 4: run the example script with your api keys. expected output:   [//]: # (## Documentation) |
||
|---|---|---|
| .. | ||
| _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