mirror of
https://github.com/meta-llama/llama-stack.git
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e3cb8ed74a
Removes the need for the strong_typing and pyopenapi packages and purely
use Pydantic for schema generation.
Our generator now purely relies on Pydantic and FastAPI, it is available
at `scripts/fastapi_generator.py`, you can run it like so:
```
uv run ./scripts/run_openapi_generator.sh
```
The generator will:
* Generate the deprecated, experimental, stable and combined specs
* Validate all the spec it generates against OpenAPI standards
A few changes in the schema required for oasdiff some updates so I've
made the following ignore rules. The new Pydantic-based generator is
likely more correct and follows OpenAPI standards better than the old
pyopenapi generator. Instead of trying to make the new generator match
the old one's quirks, we should focus on what's actually correct
according to OpenAPI standards.
These are non-critical changes:
* response-property-became-nullable: Backward compatible:
existing non-null values still work, now also accepts null
* response-required-property-removed: oasdiff reports a false
positive because it doesn't resolve $refs inside anyOf; we could use
tool like 'redocly' to flatten the schema to a single file.
* response-property-type-changed: properties are still object
types, but oasdiff doesn't resolve $refs, so it flags the missing
inline type: object even though the referenced schemas define type:
object
* request-property-one-of-removed: These are false positives
caused by schema restructuring (wrapping in anyOf for nullability,
using -Input variants, or simplifying nested oneOf structures)
that don't change the actual API contract - the same data types are
still accepted, just represented differently in the schema.
* request-parameter-enum-value-removed: These are false
positives caused by oasdiff not resolving $refs - the enum values
(asc, desc, assistants, batch) are still present in the referenced
schemas (Order and OpenAIFilePurpose), just represented via schema
references instead of inline enums.
* request-property-enum-value-removed: this is a false positive caused
by oasdiff not resolving $refs - the enum values (llm, embedding,
rerank) are still present in the referenced ModelType schema,
just represented via schema reference instead of inline enums.
* request-property-type-changed: These are schema quality issues
where type information is missing (due to Any fallback in dynamic
model creation), but the API contract remains unchanged -
properties still exist with correct names and defaults, so the same
requests will work.
* response-body-type-changed: These are false positives caused
by schema representation changes (from inferred/empty types to
explicit $ref schemas, or vice versa) - the actual response types
an API contract remain unchanged, just how they're represented in the
OpenAPI spec.
* response-media-type-removed: This is a false positive caused
by FastAPI's OpenAPI generator not documenting union return types with
AsyncIterator - the streaming functionality with text/event-stream
media type still works when stream=True is passed, it's just not
reflected in the generated OpenAPI spec.
* request-body-type-changed: This is a schema correction - the
old spec incorrectly represented the request body as an object, but
the function signature shows chunks: list[Chunk], so the new spec
correctly shows it as an array, matching the actual API
implementation.
Signed-off-by: Sébastien Han <seb@redhat.com>
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| .. | ||
| docs | ||
| notebooks | ||
| scripts | ||
| src | ||
| static | ||
| supplementary | ||
| 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
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.mdxfile location - For
raw-loader: Paths are relative to the current.mdxfile location - Use
../to navigate up directories as needed
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