llama-stack
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Testing - Memory provider fakes
Summary: Implementing Memory provider fakes as discussed in this draft https://github.com/meta-llama/llama-stack/pull/490#issuecomment-2492877393.
High level changes:
- Fake provider is specified via the "fake" mark
- Test config will setup a fake fixture for the run of the test
- Test resolver checks fixtures and upon finding a fake provider it injects InlineProviderSpec for fake provider
- Fake provider gets resolved through path/naming convention
- Fake provider implementaion is contained to the tests/ directory and implements stubs and method fakes with minimal functionality to simulate real provider
Instructins to creating a fake
- Create the "fakes" module inside the provider test directory
- Inside the module implement
get_provider_implthat will return fake implementation object - Name the fake implementation class to match the fake provider id (e.g. memory_fake -> MemoryFakeImpl)
- Same rule for the config (e.g. memory_fake -> MemoryFakeConfig)
- Add fake fixture (in the fixtures.py) and setup methods stubs there
Test Plan: Run memory tests
pytest llama_stack/providers/tests/memory/test_memory.py -m "fake" -v -s --tb=short
====================================================================================================== test session starts ======================================================================================================
platform darwin -- Python 3.11.10, pytest-8.3.3, pluggy-1.5.0 -- /opt/homebrew/Caskroom/miniconda/base/envs/llama-stack/bin/python
cachedir: .pytest_cache
rootdir: /Users/vivic/Code/llama-stack
configfile: pyproject.toml
plugins: asyncio-0.24.0, anyio-4.6.2.post1
asyncio: mode=Mode.STRICT, default_loop_scope=None
collected 18 items / 15 deselected / 3 selected
llama_stack/providers/tests/memory/test_memory.py::TestMemory::test_banks_list[fake] PASSED
llama_stack/providers/tests/memory/test_memory.py::TestMemory::test_banks_register[fake] PASSED
llama_stack/providers/tests/memory/test_memory.py::TestMemory::test_query_documents[fake] The scores are: [0.5]
PASSED
========================================================================================= 3 passed, 15 deselected, 10 warnings in 0.46s =========================================================================================