mirror of
https://github.com/meta-llama/llama-stack.git
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58 lines
2.2 KiB
Markdown
58 lines
2.2 KiB
Markdown
# Llama Stack Documentation
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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](https://llamastack.github.io/getting_started/quickstart).
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## Render locally
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From the llama-stack `docs/` directory, run the following commands to render the docs locally:
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```bash
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npm install
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npm run gen-api-docs all
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npm run build
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npm run serve
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```
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You can open up the docs in your browser at http://localhost:3000
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## File Import System
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This documentation uses `remark-code-import` to import files directly from the repository, eliminating copy-paste maintenance. Files are automatically embedded during build time.
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### Importing Code Files
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To import Python code (or any code files) with syntax highlighting, use this syntax in `.mdx` files:
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```markdown
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```python file=./demo_script.py title="demo_script.py"
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```
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```
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This automatically imports the file content and displays it as a formatted code block with Python syntax highlighting.
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**Note:** Paths are relative to the current `.mdx` file location, not the repository root.
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### Importing Markdown Files as Content
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For importing and rendering markdown files (like CONTRIBUTING.md), use the raw-loader approach:
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```jsx
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import Contributing from '!!raw-loader!../../../CONTRIBUTING.md';
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import ReactMarkdown from 'react-markdown';
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<ReactMarkdown>{Contributing}</ReactMarkdown>
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```
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**Requirements:**
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- Install dependencies: `npm install --save-dev raw-loader react-markdown`
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**Path Resolution:**
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- For `remark-code-import`: Paths are relative to the current `.mdx` file location
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- For `raw-loader`: Paths are relative to the current `.mdx` file location
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- Use `../` to navigate up directories as needed
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## Content
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Try out Llama Stack's capabilities through our detailed Jupyter notebooks:
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* [Building AI Applications Notebook](./getting_started.ipynb) - A comprehensive guide to building production-ready AI applications using Llama Stack
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* [Benchmark Evaluations Notebook](./notebooks/Llama_Stack_Benchmark_Evals.ipynb) - Detailed performance evaluations and benchmarking results
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* [Zero-to-Hero Guide](./zero_to_hero_guide) - Step-by-step guide for getting started with Llama Stack
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