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# What does this PR do? <!-- Provide a short summary of what this PR does and why. Link to relevant issues if applicable. --> The purpose of this PR is to replace the Llama Stack's default embedding model by nomic-embed-text-v1.5. These are the key reasons why Llama Stack community decided to switch from all-MiniLM-L6-v2 to nomic-embed-text-v1.5: 1. The training data for [all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2#training-data) includes a lot of data sets with various licensing terms, so it is tricky to know when/whether it is appropriate to use this model for commercial applications. 2. The model is not particularly competitive on major benchmarks. For example, if you look at the [MTEB Leaderboard](https://huggingface.co/spaces/mteb/leaderboard) and click on Miscellaneous/BEIR to see English information retrieval accuracy, you see that the top of the leaderboard is dominated by enormous models but also that there are many, many models of relatively modest size whith much higher Retrieval scores. If you want to look closely at the data, I recommend clicking "Download Table" because it is easier to browse that way. More discussion info can be founded [here](https://github.com/llamastack/llama-stack/issues/2418) <!-- If resolving an issue, uncomment and update the line below --> <!-- Closes #[issue-number] --> Closes #2418 ## 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.* --> 1. Run `./scripts/unit-tests.sh` 2. Integration tests via CI wokrflow --------- Signed-off-by: Sébastien Han <seb@redhat.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Francisco Arceo <arceofrancisco@gmail.com> Co-authored-by: Sébastien Han <seb@redhat.com> |
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| .. | ||
| cli | ||
| conversations | ||
| core/routers | ||
| distribution | ||
| files | ||
| models | ||
| prompts/prompts | ||
| providers | ||
| rag | ||
| registry | ||
| server | ||
| tools | ||
| utils | ||
| __init__.py | ||
| conftest.py | ||
| fixtures.py | ||
| README.md | ||
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
- Python Environment: Ensure you have Python 3.12+ installed
- uv Package Manager: Install
uvif 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=autofor 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_VERSIONenvironment 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