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* fix: auto-detect normalized embeddings and use cosine distance - Add automatic detection for normalized embedding models (OpenAI, Voyage AI, Cohere) - Automatically set distance_metric='cosine' for normalized embeddings - Add warnings when using non-optimal distance metrics - Implement manual L2 normalization in HNSW backend (custom Faiss build lacks normalize_L2) - Fix DiskANN zmq_port compatibility with lazy loading strategy - Add documentation for normalized embeddings feature This fixes the low accuracy issue when using OpenAI text-embedding-3-small model with default MIPS metric. * style: format * feat: add OpenAI embeddings support to google_history_reader_leann.py - Add --embedding-model and --embedding-mode arguments - Support automatic detection of normalized embeddings - Works correctly with cosine distance for OpenAI embeddings * feat: add --use-existing-index option to google_history_reader_leann.py - Allow using existing index without rebuilding - Useful for testing pre-built indices * fix: Improve OpenAI embeddings handling in HNSW backend * fix: improve macOS C++ compatibility and add CI tests * refactor: improve test structure and fix main_cli example - Move pytest configuration from pytest.ini to pyproject.toml - Remove unnecessary run_tests.py script (use test extras instead) - Fix main_cli_example.py to properly use command line arguments for LLM config - Add test_readme_examples.py to test code examples from README - Refactor tests to use pytest fixtures and parametrization - Update test documentation to reflect new structure - Set proper environment variables in CI for test execution * fix: add --distance-metric support to DiskANN embedding server and remove obsolete macOS ABI test markers - Add --distance-metric parameter to diskann_embedding_server.py for consistency with other backends - Remove pytest.skip and pytest.xfail markers for macOS C++ ABI issues as they have been fixed - Fix test assertions to handle SearchResult objects correctly - All tests now pass on macOS with the C++ ABI compatibility fixes * chore: update lock file with test dependencies * docs: remove obsolete C++ ABI compatibility warnings - Remove outdated macOS C++ compatibility warnings from README - Simplify CI workflow by removing macOS-specific failure handling - All tests now pass consistently on macOS after ABI fixes * fix: update macOS deployment target for DiskANN to 13.3 - DiskANN uses sgesdd_ LAPACK function which is only available on macOS 13.3+ - Update MACOSX_DEPLOYMENT_TARGET from 11.0 to 13.3 for DiskANN builds - This fixes the compilation error on GitHub Actions macOS runners * fix: align Python version requirements to 3.9 - Update root project to support Python 3.9, matching subpackages - Restore macOS Python 3.9 support in CI - This fixes the CI failure for Python 3.9 environments * fix: handle MPS memory issues in CI tests - Use smaller MiniLM-L6-v2 model (384 dimensions) for README tests in CI - Skip other memory-intensive tests in CI environment - Add minimal CI tests that don't require model loading - Set CI environment variable and disable MPS fallback - Ensure README examples always run correctly in CI * fix: remove Python 3.10+ dependencies for compatibility - Comment out llama-index-readers-docling and llama-index-node-parser-docling - These packages require Python >= 3.10 and were causing CI failures on Python 3.9 - Regenerate uv.lock file to resolve dependency conflicts * fix: use virtual environment in CI instead of system packages - uv-managed Python environments don't allow --system installs - Create and activate virtual environment before installing packages - Update all CI steps to use the virtual environment * add some env in ci * fix: use --find-links to install platform-specific wheels - Let uv automatically select the correct wheel for the current platform - Fixes error when trying to install macOS wheels on Linux - Simplifies the installation logic * fix: disable OpenMP parallelism in CI to avoid libomp crashes - Set OMP_NUM_THREADS=1 to avoid OpenMP thread synchronization issues - Set MKL_NUM_THREADS=1 for single-threaded MKL operations - This prevents segfaults in LayerNorm on macOS CI runners - Addresses the libomp compatibility issues with PyTorch on Apple Silicon * skip several macos test because strange issue on ci --------- Co-authored-by: yichuan520030910320 <yichuan_wang@berkeley.edu>
88 lines
2.1 KiB
Markdown
88 lines
2.1 KiB
Markdown
# LEANN Tests
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This directory contains automated tests for the LEANN project using pytest.
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## Test Files
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### `test_readme_examples.py`
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Tests the examples shown in README.md:
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- The basic example code that users see first
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- Import statements work correctly
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- Different backend options (HNSW, DiskANN)
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- Different LLM configuration options
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### `test_basic.py`
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Basic functionality tests that verify:
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- All packages can be imported correctly
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- C++ extensions (FAISS, DiskANN) load properly
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- Basic index building and searching works for both HNSW and DiskANN backends
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- Uses parametrized tests to test both backends
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### `test_main_cli.py`
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Tests the main CLI example functionality:
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- Tests with facebook/contriever embeddings
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- Tests with OpenAI embeddings (if API key is available)
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- Tests error handling with invalid parameters
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- Verifies that normalized embeddings are detected and cosine distance is used
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## Running Tests
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### Install test dependencies:
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```bash
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# Using extras
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uv pip install -e ".[test]"
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```
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### Run all tests:
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```bash
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pytest tests/
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# Or with coverage
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pytest tests/ --cov=leann --cov-report=html
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# Run in parallel (faster)
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pytest tests/ -n auto
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```
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### Run specific tests:
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```bash
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# Only basic tests
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pytest tests/test_basic.py
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# Only tests that don't require OpenAI
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pytest tests/ -m "not openai"
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# Skip slow tests
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pytest tests/ -m "not slow"
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```
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### Run with specific backend:
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```bash
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# Test only HNSW backend
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pytest tests/test_basic.py::test_backend_basic[hnsw]
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# Test only DiskANN backend
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pytest tests/test_basic.py::test_backend_basic[diskann]
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```
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## CI/CD Integration
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Tests are automatically run in GitHub Actions:
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1. After building wheel packages
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2. On multiple Python versions (3.9 - 3.13)
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3. On both Ubuntu and macOS
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4. Using pytest with appropriate markers and flags
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### pytest.ini Configuration
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The `pytest.ini` file configures:
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- Test discovery paths
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- Default timeout (600 seconds)
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- Environment variables (HF_HUB_DISABLE_SYMLINKS, TOKENIZERS_PARALLELISM)
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- Custom markers for slow and OpenAI tests
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- Verbose output with short tracebacks
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### Known Issues
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- OpenAI tests are automatically skipped if no API key is provided
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