llama-stack-mirror/tests/unit
Akram Ben Aissi 1970b4aa4b
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fix: improve model availability checks: Allows use of unavailable models on startup (#3717)
- Allows use of unavailable models on startup
- Add has_model method to ModelsRoutingTable for checking pre-registered
models
- Update check_model_availability to check model_store before provider
APIs

# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

## Test Plan
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->


Start llama stack and point unavailable vLLM

```
VLLM_URL=https://my-unavailable-vllm/v1 MILVUS_DB_PATH=./milvus.db INFERENCE_MODEL=vllm uv run --with llama-stack llama stack build --distro starter --image-type venv --run
```

llama stack will start without crashing but only notifying error. 

```


         - provider_id: rag-runtime
           toolgroup_id: builtin::rag
         vector_dbs: []
         version: 2

INFO     2025-10-07 06:40:41,804 llama_stack.providers.utils.inference.inference_store:74 inference: Write queue disabled for SQLite to avoid concurrency issues
INFO     2025-10-07 06:40:42,066 llama_stack.providers.utils.responses.responses_store:96 openai_responses: Write queue disabled for SQLite to avoid concurrency issues
ERROR    2025-10-07 06:40:58,882 llama_stack.providers.utils.inference.openai_mixin:436 providers::utils: VLLMInferenceAdapter.list_provider_model_ids() failed with: Request timed out.
WARNING  2025-10-07 06:40:58,883 llama_stack.core.routing_tables.models:36 core::routing_tables: Model refresh failed for provider vllm: Request timed out.
[...]
INFO     2025-10-07 06:40:59,036 uvicorn.error:216 uncategorized: Uvicorn running on http://['::', '0.0.0.0']:8321 (Press CTRL+C to quit)
INFO     2025-10-07 06:41:04,064 openai._base_client:1618 uncategorized: Retrying request to /models in 0.398814 seconds
INFO     2025-10-07 06:41:09,497 openai._base_client:1618 uncategorized: Retrying request to /models in 0.781908 seconds
ERROR    2025-10-07 06:41:15,282 llama_stack.providers.utils.inference.openai_mixin:436 providers::utils: VLLMInferenceAdapter.list_provider_model_ids() failed with: Request timed out.
WARNING  2025-10-07 06:41:15,283 llama_stack.core.routing_tables.models:36 core::routing_tables: Model refresh failed for provider vllm: Request timed out.
```
2025-10-07 14:27:24 -04:00
..
cli chore(rename): move llama_stack.distribution to llama_stack.core (#2975) 2025-07-30 23:30:53 -07:00
conversations feat: Add OpenAI Conversations API (#3429) 2025-10-03 08:47:18 -07:00
distribution fix: improve model availability checks: Allows use of unavailable models on startup (#3717) 2025-10-07 14:27:24 -04:00
files chore(files tests): update files integration tests and fix inline::localfs (#3195) 2025-08-20 14:22:40 -04:00
models feat(tools)!: substantial clean up of "Tool" related datatypes (#3627) 2025-10-02 15:12:03 -07:00
prompts/prompts feat: Adding OpenAI Prompts API (#3319) 2025-09-08 11:05:13 -04:00
providers fix: improve model availability checks: Allows use of unavailable models on startup (#3717) 2025-10-07 14:27:24 -04:00
rag fix: pre-commit issues: non executable shebang file and removal of @pytest.mark.asyncio decorator (#3397) 2025-09-10 15:27:35 +02:00
registry fix: Revert "fix: Added a bug fix when registering new models" (#3473) 2025-09-26 16:19:21 -04:00
server feat: Add Kubernetes auth provider to use SelfSubjectReview and kubernetes api server (#2559) 2025-09-08 11:25:10 +02:00
tools feat(tools)!: substantial clean up of "Tool" related datatypes (#3627) 2025-10-02 15:12:03 -07:00
utils feat: Add OpenAI Conversations API (#3429) 2025-10-03 08:47:18 -07:00
__init__.py chore: Add fixtures to conftest.py (#2067) 2025-05-06 13:57:48 +02:00
conftest.py chore: block network access from unit tests (#2732) 2025-07-12 16:53:54 -07:00
fixtures.py chore(rename): move llama_stack.distribution to llama_stack.core (#2975) 2025-07-30 23:30:53 -07:00
README.md test: Measure and track code coverage (#2636) 2025-07-18 18:08:36 +02:00

Llama Stack Unit Tests

Unit Tests

Unit tests verify individual components and functions in isolation. They are fast, reliable, and don't require external services.

Prerequisites

  1. Python Environment: Ensure you have Python 3.12+ installed
  2. uv Package Manager: Install uv if not already installed

You can run the unit tests by running:

./scripts/unit-tests.sh [PYTEST_ARGS]

Any additional arguments are passed to pytest. For example, you can specify a test directory, a specific test file, or any pytest flags (e.g., -vvv for verbosity). If no test directory is specified, it defaults to "tests/unit", e.g:

./scripts/unit-tests.sh tests/unit/registry/test_registry.py -vvv

If you'd like to run for a non-default version of Python (currently 3.12), pass PYTHON_VERSION variable as follows:

source .venv/bin/activate
PYTHON_VERSION=3.13 ./scripts/unit-tests.sh

Test Configuration

  • Test Discovery: Tests are automatically discovered in the tests/unit/ directory
  • Async Support: Tests use --asyncio-mode=auto for automatic async test handling
  • Coverage: Tests generate coverage reports in htmlcov/ directory
  • Python Version: Defaults to Python 3.12, but can be overridden with PYTHON_VERSION environment variable

Coverage Reports

After running tests, you can view coverage reports:

# Open HTML coverage report in browser
open htmlcov/index.html  # macOS
xdg-open htmlcov/index.html  # Linux
start htmlcov/index.html  # Windows