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feat: Adding Demo script and allowing new Website to source files

Browse source 
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

# Conflicts:
#	docs/docs/getting_started/demo_script.py
#	docs/docs/getting_started/quickstart.mdx
This commit is contained in:
Francisco Javier Arceo 2025-10-20 21:28:09 -04:00
parent c582654d70
commit 7ab63068f8
7 changed files with 444 additions and 23 deletions
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13
docs/README.md
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@ -13,6 +13,19 @@ npm run serve
```
You can open up the docs in your browser at http://localhost:3000
## File Import System
This documentation uses a custom component to import files directly from the repository, eliminating copy-paste maintenance:
```jsx
import CodeFromFile from '@site/src/components/CodeFromFile';
<CodeFromFile src="path/to/file.py" />
<CodeFromFile src="README.md" startLine={1} endLine={20} />
```
Files are automatically synced from the repo root when building. See the `CodeFromFile` component for syntax highlighting, line ranges, and multi-language support.
## Content
Try out Llama Stack's capabilities through our detailed Jupyter notebooks:

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docs/docs/getting_started/quickstart.mdx
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@ -35,27 +35,9 @@ OLLAMA_URL=http://localhost:11434 uv run --with llama-stack llama stack run star
#### Step 3: Run the demo
Now open up a new terminal and copy the following script into a file named `demo_script.py`.
```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"],
)
import CodeFromFile from '@site/src/components/CodeFromFile';
<CodeFromFile src="demo_script.py" title="demo_script.py" />
We will use `uv` to run the script
```
uv run --with llama-stack-client,fire,requests demo_script.py

7
docs/package.json
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@ -4,8 +4,8 @@
"private": true,
"scripts": {
"docusaurus": "docusaurus",
"start": "docusaurus start",
"build": "docusaurus build",
"start": "npm run sync-files && docusaurus start",
"build": "npm run sync-files && docusaurus build",
"swizzle": "docusaurus swizzle",
"deploy": "docusaurus deploy",
"clear": "docusaurus clear",
@ -15,7 +15,8 @@
"gen-api-docs": "docusaurus gen-api-docs",
"clean-api-docs": "docusaurus clean-api-docs",
"gen-api-docs:version": "docusaurus gen-api-docs:version",
"clean-api-docs:version": "docusaurus clean-api-docs:version"
"clean-api-docs:version": "docusaurus clean-api-docs:version",
"sync-files": "node scripts/sync-files.js"
},
"dependencies": {
"@docusaurus/core": "3.8.1",

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docs/scripts/sync-files.js Executable file
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@ -0,0 +1,93 @@
#!/usr/bin/env node
const fs = require('fs');
const path = require('path');
// Repository root is always one level up from docs
const repoRoot = path.join(__dirname, '..', '..');
// Get all requested files from the usage tracking file
function getRequestedFiles() {
const usageFile = path.join(__dirname, '..', 'static', 'imported-files', 'usage.json');
if (!fs.existsSync(usageFile)) {
return [];
}
try {
const usage = JSON.parse(fs.readFileSync(usageFile, 'utf8'));
return usage.files || [];
} catch (error) {
console.warn('Could not read usage file:', error.message);
return [];
}
}
// Track file usage
function trackFileUsage(filePath) {
const usageFile = path.join(__dirname, '..', 'static', 'imported-files', 'usage.json');
const usageDir = path.dirname(usageFile);
// Ensure directory exists
if (!fs.existsSync(usageDir)) {
fs.mkdirSync(usageDir, { recursive: true });
}
let usage = { files: [] };
if (fs.existsSync(usageFile)) {
try {
usage = JSON.parse(fs.readFileSync(usageFile, 'utf8'));
} catch (error) {
console.warn('Could not read existing usage file, creating new one');
}
}
if (!usage.files.includes(filePath)) {
usage.files.push(filePath);
fs.writeFileSync(usageFile, JSON.stringify(usage, null, 2));
}
}
// Sync a file from repo root to static directory
function syncFile(filePath) {
const sourcePath = path.join(repoRoot, filePath);
const destPath = path.join(__dirname, '..', 'static', 'imported-files', filePath);
const destDir = path.dirname(destPath);
// Ensure destination directory exists
if (!fs.existsSync(destDir)) {
fs.mkdirSync(destDir, { recursive: true });
}
try {
if (fs.existsSync(sourcePath)) {
const content = fs.readFileSync(sourcePath, 'utf8');
fs.writeFileSync(destPath, content);
console.log(`✅ Synced ${filePath}`);
trackFileUsage(filePath);
return true;
} else {
console.warn(`⚠️ Source file not found: ${sourcePath}`);
return false;
}
} catch (error) {
console.error(`❌ Error syncing ${filePath}:`, error.message);
return false;
}
}
// Main execution
console.log(`📁 Repository root: ${path.resolve(repoRoot)}`);
// Get files that are being requested by the documentation
const requestedFiles = getRequestedFiles();
console.log(`📄 Syncing ${requestedFiles.length} requested files...`);
if (requestedFiles.length === 0) {
console.log('ℹ️ No files requested yet. Files will be synced when first referenced in documentation.');
} else {
requestedFiles.forEach(filePath => {
syncFile(filePath);
});
}
console.log('✅ File sync complete!');

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docs/src/components/CodeFromFile.jsx Normal file
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import React, { useState, useEffect } from 'react';
import CodeBlock from '@theme/CodeBlock';
export default function CodeFromFile({
src,
language = 'python',
title,
startLine,
endLine,
highlightLines
}) {
const [content, setContent] = useState('');
const [error, setError] = useState(null);
useEffect(() => {
async function loadFile() {
try {
// Register this file for syncing (build-time only)
if (typeof window === 'undefined') {
// This runs during build - register the file
const fs = require('fs');
const path = require('path');
const usageFile = path.join(process.cwd(), 'static', 'imported-files', 'usage.json');
const usageDir = path.dirname(usageFile);
if (!fs.existsSync(usageDir)) {
fs.mkdirSync(usageDir, { recursive: true });
}
let usage = { files: [] };
if (fs.existsSync(usageFile)) {
try {
usage = JSON.parse(fs.readFileSync(usageFile, 'utf8'));
} catch (error) {
console.warn('Could not read existing usage file');
}
}
if (!usage.files.includes(src)) {
usage.files.push(src);
fs.writeFileSync(usageFile, JSON.stringify(usage, null, 2));
}
}
// Load file from static/imported-files directory
const response = await fetch(`/imported-files/${src}`);
if (!response.ok) {
throw new Error(`Failed to fetch: ${response.status}`);
}
let text = await response.text();
// Handle line range if specified
if (startLine || endLine) {
const lines = text.split('\n');
const start = startLine ? Math.max(0, startLine - 1) : 0;
const end = endLine ? Math.min(lines.length, endLine) : lines.length;
text = lines.slice(start, end).join('\n');
}
setContent(text);
} catch (err) {
console.error('Failed to load file:', err);
setError(`Failed to load ${src}: ${err.message}`);
}
}
loadFile();
}, [src, startLine, endLine]);
if (error) {
return <div style={{ color: 'red', padding: '1rem', border: '1px solid red', borderRadius: '4px' }}>
Error: {error}
</div>;
}
if (!content) {
return <div>Loading {src}...</div>;
}
// Auto-detect language from file extension if not provided
const detectedLanguage = language || getLanguageFromExtension(src);
return (
<CodeBlock
language={detectedLanguage}
title={title || src}
metastring={highlightLines ? `{${highlightLines}}` : undefined}
>
{content}
</CodeBlock>
);
}
function getLanguageFromExtension(filename) {
const ext = filename.split('.').pop();
const languageMap = {
'py': 'python',
'js': 'javascript',
'jsx': 'jsx',
'ts': 'typescript',
'tsx': 'tsx',
'md': 'markdown',
'sh': 'bash',
'yaml': 'yaml',
'yml': 'yaml',
'json': 'json',
'css': 'css',
'html': 'html',
'cpp': 'cpp',
'c': 'c',
'java': 'java',
'go': 'go',
'rs': 'rust',
'php': 'php',
'rb': 'ruby',
};
return languageMap[ext] || 'text';
}

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# Llama Stack
[![PyPI version](https://img.shields.io/pypi/v/llama_stack.svg)](https://pypi.org/project/llama_stack/)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/llama-stack)](https://pypi.org/project/llama-stack/)
[![License](https://img.shields.io/pypi/l/llama_stack.svg)](https://github.com/meta-llama/llama-stack/blob/main/LICENSE)
[![Discord](https://img.shields.io/discord/1257833999603335178?color=6A7EC2&logo=discord&logoColor=ffffff)](https://discord.gg/llama-stack)
[![Unit Tests](https://github.com/meta-llama/llama-stack/actions/workflows/unit-tests.yml/badge.svg?branch=main)](https://github.com/meta-llama/llama-stack/actions/workflows/unit-tests.yml?query=branch%3Amain)
[![Integration Tests](https://github.com/meta-llama/llama-stack/actions/workflows/integration-tests.yml/badge.svg?branch=main)](https://github.com/meta-llama/llama-stack/actions/workflows/integration-tests.yml?query=branch%3Amain)
[**Quick Start**](https://llamastack.github.io/docs/getting_started/quickstart) | [**Documentation**](https://llamastack.github.io/docs) | [**Colab Notebook**](./docs/getting_started.ipynb) | [**Discord**](https://discord.gg/llama-stack)
### ✨🎉 Llama 4 Support 🎉✨
We released [Version 0.2.0](https://github.com/meta-llama/llama-stack/releases/tag/v0.2.0) with support for the Llama 4 herd of models released by Meta.
<details>
<summary>👋 Click here to see how to run Llama 4 models on Llama Stack </summary>
\
*Note you need 8xH100 GPU-host to run these models*
```bash
pip install -U llama_stack
MODEL="Llama-4-Scout-17B-16E-Instruct"
# get meta url from llama.com
huggingface-cli download meta-llama/$MODEL --local-dir ~/.llama/$MODEL
# start a llama stack server
INFERENCE_MODEL=meta-llama/$MODEL llama stack build --run --template meta-reference-gpu
# install client to interact with the server
pip install llama-stack-client
```
### CLI
```bash
# Run a chat completion
MODEL="Llama-4-Scout-17B-16E-Instruct"
llama-stack-client --endpoint http://localhost:8321 \
inference chat-completion \
--model-id meta-llama/$MODEL \
--message "write a haiku for meta's llama 4 models"
OpenAIChatCompletion(
...
choices=[
OpenAIChatCompletionChoice(
finish_reason='stop',
index=0,
message=OpenAIChatCompletionChoiceMessageOpenAIAssistantMessageParam(
role='assistant',
content='...**Silent minds awaken,** \n**Whispers of billions of words,** \n**Reasoning breaks the night.** \n\n— \n*This haiku blends the essence of LLaMA 4\'s capabilities with nature-inspired metaphor, evoking its vast training data and transformative potential.*',
...
),
...
)
],
...
)
```
### Python SDK
```python
from llama_stack_client import LlamaStackClient
client = LlamaStackClient(base_url=f"http://localhost:8321")
model_id = "meta-llama/Llama-4-Scout-17B-16E-Instruct"
prompt = "Write a haiku about coding"
print(f"User> {prompt}")
response = client.chat.completions.create(
model=model_id,
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": prompt},
],
)
print(f"Assistant> {response.choices[0].message.content}")
```
As more providers start supporting Llama 4, you can use them in Llama Stack as well. We are adding to the list. Stay tuned!
</details>
### 🚀 One-Line Installer 🚀
To try Llama Stack locally, run:
```bash
curl -LsSf https://github.com/meta-llama/llama-stack/raw/main/scripts/install.sh | bash
```
### Overview
Llama Stack standardizes the core building blocks that simplify AI application development. It codifies best practices across the Llama ecosystem. More specifically, it provides
- **Unified API layer** for Inference, RAG, Agents, Tools, Safety, Evals, and Telemetry.
- **Plugin architecture** to support the rich ecosystem of different API implementations in various environments, including local development, on-premises, cloud, and mobile.
- **Prepackaged verified distributions** which offer a one-stop solution for developers to get started quickly and reliably in any environment.
- **Multiple developer interfaces** like CLI and SDKs for Python, Typescript, iOS, and Android.
- **Standalone applications** as examples for how to build production-grade AI applications with Llama Stack.
<div style="text-align: center;">
<img
src="https://github.com/user-attachments/assets/33d9576d-95ea-468d-95e2-8fa233205a50"
width="480"
title="Llama Stack"
alt="Llama Stack"
/>
</div>
### Llama Stack Benefits
- **Flexible Options**: Developers can choose their preferred infrastructure without changing APIs and enjoy flexible deployment choices.
- **Consistent Experience**: With its unified APIs, Llama Stack makes it easier to build, test, and deploy AI applications with consistent application behavior.
- **Robust Ecosystem**: Llama Stack is already integrated with distribution partners (cloud providers, hardware vendors, and AI-focused companies) that offer tailored infrastructure, software, and services for deploying Llama models.
By reducing friction and complexity, Llama Stack empowers developers to focus on what they do best: building transformative generative AI applications.
### API Providers
Here is a list of the various API providers and available distributions that can help developers get started easily with Llama Stack.
Please checkout for [full list](https://llamastack.github.io/docs/providers)
| API Provider Builder | Environments | Agents | Inference | VectorIO | Safety | Telemetry | Post Training | Eval | DatasetIO |
|:--------------------:|:------------:|:------:|:---------:|:--------:|:------:|:---------:|:-------------:|:----:|:--------:|
| Meta Reference | Single Node | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| SambaNova | Hosted | | ✅ | | ✅ | | | | |
| Cerebras | Hosted | | ✅ | | | | | | |
| Fireworks | Hosted | ✅ | ✅ | ✅ | | | | | |
| AWS Bedrock | Hosted | | ✅ | | ✅ | | | | |
| Together | Hosted | ✅ | ✅ | | ✅ | | | | |
| Groq | Hosted | | ✅ | | | | | | |
| Ollama | Single Node | | ✅ | | | | | | |
| TGI | Hosted/Single Node | | ✅ | | | | | | |
| NVIDIA NIM | Hosted/Single Node | | ✅ | | ✅ | | | | |
| ChromaDB | Hosted/Single Node | | | ✅ | | | | | |
| Milvus | Hosted/Single Node | | | ✅ | | | | | |
| Qdrant | Hosted/Single Node | | | ✅ | | | | | |
| Weaviate | Hosted/Single Node | | | ✅ | | | | | |
| SQLite-vec | Single Node | | | ✅ | | | | | |
| PG Vector | Single Node | | | ✅ | | | | | |
| PyTorch ExecuTorch | On-device iOS | ✅ | ✅ | | | | | | |
| vLLM | Single Node | | ✅ | | | | | | |
| OpenAI | Hosted | | ✅ | | | | | | |
| Anthropic | Hosted | | ✅ | | | | | | |
| Gemini | Hosted | | ✅ | | | | | | |
| WatsonX | Hosted | | ✅ | | | | | | |
| HuggingFace | Single Node | | | | | | ✅ | | ✅ |
| TorchTune | Single Node | | | | | | ✅ | | |
| NVIDIA NEMO | Hosted | | ✅ | ✅ | | | ✅ | ✅ | ✅ |
| NVIDIA | Hosted | | | | | | ✅ | ✅ | ✅ |
> **Note**: Additional providers are available through external packages. See [External Providers](https://llamastack.github.io/docs/providers/external) documentation.
### Distributions
A Llama Stack Distribution (or "distro") is a pre-configured bundle of provider implementations for each API component. Distributions make it easy to get started with a specific deployment scenario - you can begin with a local development setup (eg. ollama) and seamlessly transition to production (eg. Fireworks) without changing your application code.
Here are some of the distributions we support:
| **Distribution** | **Llama Stack Docker** | Start This Distribution |
|:---------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------:|
| Starter Distribution | [llamastack/distribution-starter](https://hub.docker.com/repository/docker/llamastack/distribution-starter/general) | [Guide](https://llamastack.github.io/latest/distributions/self_hosted_distro/starter.html) |
| Meta Reference | [llamastack/distribution-meta-reference-gpu](https://hub.docker.com/repository/docker/llamastack/distribution-meta-reference-gpu/general) | [Guide](https://llamastack.github.io/latest/distributions/self_hosted_distro/meta-reference-gpu.html) |
| PostgreSQL | [llamastack/distribution-postgres-demo](https://hub.docker.com/repository/docker/llamastack/distribution-postgres-demo/general) | |
### Documentation
Please checkout our [Documentation](https://llamastack.github.io/latest/index.html) page for more details.
* CLI references
* [llama (server-side) CLI Reference](https://llamastack.github.io/latest/references/llama_cli_reference/index.html): Guide for using the `llama` CLI to work with Llama models (download, study prompts), and building/starting a Llama Stack distribution.
* [llama (client-side) CLI Reference](https://llamastack.github.io/latest/references/llama_stack_client_cli_reference.html): Guide for using the `llama-stack-client` CLI, which allows you to query information about the distribution.
* Getting Started
* [Quick guide to start a Llama Stack server](https://llamastack.github.io/latest/getting_started/index.html).
* [Jupyter notebook](./docs/getting_started.ipynb) to walk-through how to use simple text and vision inference llama_stack_client APIs
* The complete Llama Stack lesson [Colab notebook](https://colab.research.google.com/drive/1dtVmxotBsI4cGZQNsJRYPrLiDeT0Wnwt) of the new [Llama 3.2 course on Deeplearning.ai](https://learn.deeplearning.ai/courses/introducing-multimodal-llama-3-2/lesson/8/llama-stack).
* A [Zero-to-Hero Guide](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide) that guide you through all the key components of llama stack with code samples.
* [Contributing](CONTRIBUTING.md)
* [Adding a new API Provider](https://llamastack.github.io/latest/contributing/new_api_provider.html) to walk-through how to add a new API provider.
### Llama Stack Client SDKs
| **Language** | **Client SDK** | **Package** |
| :----: | :----: | :----: |
| Python | [llama-stack-client-python](https://github.com/meta-llama/llama-stack-client-python) | [![PyPI version](https://img.shields.io/pypi/v/llama_stack_client.svg)](https://pypi.org/project/llama_stack_client/)
| Swift | [llama-stack-client-swift](https://github.com/meta-llama/llama-stack-client-swift) | [![Swift Package Index](https://img.shields.io/endpoint?url=https%3A%2F%2Fswiftpackageindex.com%2Fapi%2Fpackages%2Fmeta-llama%2Fllama-stack-client-swift%2Fbadge%3Ftype%3Dswift-versions)](https://swiftpackageindex.com/meta-llama/llama-stack-client-swift)
| Typescript | [llama-stack-client-typescript](https://github.com/meta-llama/llama-stack-client-typescript) | [![NPM version](https://img.shields.io/npm/v/llama-stack-client.svg)](https://npmjs.org/package/llama-stack-client)
| Kotlin | [llama-stack-client-kotlin](https://github.com/meta-llama/llama-stack-client-kotlin) | [![Maven version](https://img.shields.io/maven-central/v/com.llama.llamastack/llama-stack-client-kotlin)](https://central.sonatype.com/artifact/com.llama.llamastack/llama-stack-client-kotlin)
Check out our client SDKs for connecting to a Llama Stack server in your preferred language, you can choose from [python](https://github.com/meta-llama/llama-stack-client-python), [typescript](https://github.com/meta-llama/llama-stack-client-typescript), [swift](https://github.com/meta-llama/llama-stack-client-swift), and [kotlin](https://github.com/meta-llama/llama-stack-client-kotlin) programming languages to quickly build your applications.
You can find more example scripts with client SDKs to talk with the Llama Stack server in our [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main/examples) repo.
## 🌟 GitHub Star History
## Star History
[![Star History Chart](https://api.star-history.com/svg?repos=meta-llama/llama-stack&type=Date)](https://www.star-history.com/#meta-llama/llama-stack&Date)
## ✨ Contributors
Thanks to all of our amazing contributors!
<a href="https://github.com/meta-llama/llama-stack/graphs/contributors">
<img src="https://contrib.rocks/image?repo=meta-llama/llama-stack" />
</a>

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{
"files": [
"docs/getting_started/demo_script.py",
"README.md"
]
}