llama-stack-mirror/docs
Ashwin Bharambe 0c49a53c97
chore(api)!: remove tool_runtime.rag_tool from the API surface (#4067)
RAG aka file search is implemented via the Responses API by specifying
the file-search tool. The backend implementation remains unchanged. This
PR merely removes the directly exposed API surface which allowed users
to directly perform searches from the client.

This facility is now available via the `client.vector_store.search()`
OpenAI compatible API.
2025-11-04 14:50:54 -08:00
..
docs fix: update tests for OpenAI-style models endpoint (#4053) 2025-11-03 17:30:08 -08:00
notebooks docs: A getting started notebook featuring simple agent examples. (#3955) 2025-10-29 14:13:34 -04:00
openapi_generator chore(api)!: remove tool_runtime.rag_tool from the API surface (#4067) 2025-11-04 14:50:54 -08:00
scripts feat: Add static file import system for docs (#3882) 2025-10-24 14:01:33 -04:00
src feat: Add static file import system for docs (#3882) 2025-10-24 14:01:33 -04:00
static chore(api)!: remove tool_runtime.rag_tool from the API surface (#4067) 2025-11-04 14:50:54 -08:00
supplementary docs: adding supplementary markdown content to API specs (#3632) 2025-10-01 10:15:30 -07:00
zero_to_hero_guide chore: update doc (#3857) 2025-10-20 10:33:21 -07:00
docusaurus.config.ts feat: Add static file import system for docs (#3882) 2025-10-24 14:01:33 -04:00
dog.jpg Support for Llama3.2 models and Swift SDK (#98) 2024-09-25 10:29:58 -07:00
getting_started.ipynb chore: update getting_started (#3875) 2025-10-21 11:09:45 -07:00
getting_started_llama4.ipynb chore: update doc (#3857) 2025-10-20 10:33:21 -07:00
getting_started_llama_api.ipynb chore: update doc (#3857) 2025-10-20 10:33:21 -07:00
license_header.txt Initial commit 2024-07-23 08:32:33 -07:00
original_rfc.md chore(rename): move llama_stack.distribution to llama_stack.core (#2975) 2025-07-30 23:30:53 -07:00
package-lock.json feat: Add static file import system for docs (#3882) 2025-10-24 14:01:33 -04:00
package.json feat: Add static file import system for docs (#3882) 2025-10-24 14:01:33 -04:00
quick_start.ipynb chore: update quick_start (#3878) 2025-10-21 11:33:23 -07:00
README.md feat: Add static file import system for docs (#3882) 2025-10-24 14:01:33 -04:00
sidebars.ts fix(docs): remove leftover telemetry sidebar section (#3961) 2025-10-29 11:20:13 -04:00
tsconfig.json docs: docusaurus setup (#3541) 2025-09-24 14:11:30 -07:00

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

File Import System

This documentation uses remark-code-import to import files directly from the repository, eliminating copy-paste maintenance. Files are automatically embedded during build time.

Importing Code Files

To import Python code (or any code files) with syntax highlighting, use this syntax in .mdx files:

```python file=./demo_script.py title="demo_script.py"

This automatically imports the file content and displays it as a formatted code block with Python syntax highlighting.

**Note:** Paths are relative to the current `.mdx` file location, not the repository root.

### Importing Markdown Files as Content

For importing and rendering markdown files (like CONTRIBUTING.md), use the raw-loader approach:

```jsx
import Contributing from '!!raw-loader!../../../CONTRIBUTING.md';
import ReactMarkdown from 'react-markdown';

<ReactMarkdown>{Contributing}</ReactMarkdown>

Requirements:

  • Install dependencies: npm install --save-dev raw-loader react-markdown

Path Resolution:

  • For remark-code-import: Paths are relative to the current .mdx file location
  • For raw-loader: Paths are relative to the current .mdx file location
  • Use ../ to navigate up directories as needed

Content

Try out Llama Stack's capabilities through our detailed Jupyter notebooks: