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# What does this PR do? - Removed Optional return types for GET methods - Raised ValueError when requested resource is not found - Ensures proper 4xx response for missing resources - Updated the API generator to check for wrong signatures ``` $ uv run --with ".[dev]" ./docs/openapi_generator/run_openapi_generator.sh Validating API method return types... API Method Return Type Validation Errors: Method ScoringFunctions.get_scoring_function returns Optional type ``` Closes: https://github.com/meta-llama/llama-stack/issues/1630 ## Test Plan Run the server then: ``` curl http://127.0.0.1:8321/v1/models/foo {"detail":"Invalid value: Model 'foo' not found"}% ``` Server log: ``` INFO: 127.0.0.1:52307 - "GET /v1/models/foo HTTP/1.1" 400 Bad Request 09:51:42.654 [END] /v1/models/foo [StatusCode.OK] (134.65ms) 09:51:42.651 [ERROR] Error executing endpoint route='/v1/models/{model_id:path}' method='get' Traceback (most recent call last): File "/Users/leseb/Documents/AI/llama-stack/llama_stack/distribution/server/server.py", line 193, in endpoint return await maybe_await(value) File "/Users/leseb/Documents/AI/llama-stack/llama_stack/distribution/server/server.py", line 156, in maybe_await return await value File "/Users/leseb/Documents/AI/llama-stack/llama_stack/providers/utils/telemetry/trace_protocol.py", line 102, in async_wrapper result = await method(self, *args, **kwargs) File "/Users/leseb/Documents/AI/llama-stack/llama_stack/distribution/routers/routing_tables.py", line 217, in get_model raise ValueError(f"Model '{model_id}' not found") ValueError: Model 'foo' not found ``` Signed-off-by: Sébastien Han <seb@redhat.com> |
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| zero_to_hero_guide | ||
| conftest.py | ||
| contbuild.sh | ||
| dog.jpg | ||
| getting_started.ipynb | ||
| license_header.txt | ||
| make.bat | ||
| Makefile | ||
| readme.md | ||
| requirements.txt | ||
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 ReadTheDocs page.
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