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# What does this PR do? Updated quickstart `demo_script.py` to use OpenAI APIs, which is simply: ```python import io, requests from openai import OpenAI url="https://www.paulgraham.com/greatwork.html" client = OpenAI(base_url="http://localhost:8321/v1/", api_key="none") vs = client.vector_stores.create() response = requests.get(url) pseudo_file = io.BytesIO(str(response.content).encode('utf-8')) uploaded_file = client.files.create(file=(url, pseudo_file, "text/html"), purpose="assistants") client.vector_stores.files.create(vector_store_id=vs.id, file_id=uploaded_file.id) resp = client.responses.create( model="openai/gpt-4o", input="How do you do great work? Use the existing knowledge_search tool.", tools=[{"type": "file_search", "vector_store_ids": [vs.id]}], include=["file_search_call.results"], ) print(resp) ``` <!-- If resolving an issue, uncomment and update the line below --> <!-- Closes #[issue-number] --> ## Test Plan <!-- Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.* --> --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com> |
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zero_to_hero_guide | ||
docusaurus.config.ts | ||
dog.jpg | ||
getting_started.ipynb | ||
getting_started_llama4.ipynb | ||
getting_started_llama_api.ipynb | ||
license_header.txt | ||
original_rfc.md | ||
package-lock.json | ||
package.json | ||
quick_start.ipynb | ||
README.md | ||
sidebars.ts | ||
tsconfig.json |
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 Github page.
Render locally
From the llama-stack docs/
directory, run the following commands to render the docs locally:
npm install
npm run gen-api-docs all
npm run build
npm run serve
You can open up the docs in your browser at http://localhost:3000
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