a6dad47280
Fixed the actual root cause instead of just masking it in tests: 1. Root Problem: - C++ side's ZmqDistanceComputer creates ZMQ connections but doesn't clean them - Python 3.9/3.13 are more sensitive to cleanup timing during shutdown 2. Core Fixes in SearcherBase and LeannSearcher: - Added cleanup() method to BaseSearcher that cleans ZMQ and embedding server - LeannSearcher.cleanup() now also handles ZMQ context cleanup - Both HNSW and DiskANN searchers now properly delete C++ index objects 3. Backend-Specific Cleanup: - HNSWSearcher.cleanup(): Deletes self.index to trigger C++ destructors - DiskannSearcher.cleanup(): Deletes self._index and resets state - Both force garbage collection after deletion 4. Test Infrastructure: - Added auto_cleanup_searcher fixture for explicit resource management - Global cleanup now more aggressive with ZMQ context destruction This is the proper fix - cleaning up resources at the source, not just working around the issue in tests. The hanging was caused by C++ side ZMQ connections not being properly terminated when is_recompute=True.
LEANN Tests
This directory contains automated tests for the LEANN project using pytest.
Test Files
test_readme_examples.py
Tests the examples shown in README.md:
- The basic example code that users see first (parametrized for both HNSW and DiskANN backends)
- Import statements work correctly
- Different backend options (HNSW, DiskANN)
- Different LLM configuration options (parametrized for both backends)
- All main README examples are tested with both HNSW and DiskANN backends using pytest parametrization
test_basic.py
Basic functionality tests that verify:
- All packages can be imported correctly
- C++ extensions (FAISS, DiskANN) load properly
- Basic index building and searching works for both HNSW and DiskANN backends
- Uses parametrized tests to test both backends
test_document_rag.py
Tests the document RAG example functionality:
- Tests with facebook/contriever embeddings
- Tests with OpenAI embeddings (if API key is available)
- Tests error handling with invalid parameters
- Verifies that normalized embeddings are detected and cosine distance is used
test_diskann_partition.py
Tests DiskANN graph partitioning functionality:
- Tests DiskANN index building without partitioning (baseline)
- Tests automatic graph partitioning with
is_recompute=True - Verifies that partition files are created and large files are cleaned up for storage saving
- Tests search functionality with partitioned indices
- Validates medoid and max_base_norm file generation and usage
- Includes performance comparison between DiskANN (with partition) and HNSW
- Note: These tests are skipped in CI due to hardware requirements and computation time
Running Tests
Install test dependencies:
# Using extras
uv pip install -e ".[test]"
Run all tests:
pytest tests/
# Or with coverage
pytest tests/ --cov=leann --cov-report=html
# Run in parallel (faster)
pytest tests/ -n auto
Run specific tests:
# Only basic tests
pytest tests/test_basic.py
# Only tests that don't require OpenAI
pytest tests/ -m "not openai"
# Skip slow tests
pytest tests/ -m "not slow"
# Run DiskANN partition tests (requires local machine, not CI)
pytest tests/test_diskann_partition.py
Run with specific backend:
# Test only HNSW backend
pytest tests/test_basic.py::test_backend_basic[hnsw]
pytest tests/test_readme_examples.py::test_readme_basic_example[hnsw]
# Test only DiskANN backend
pytest tests/test_basic.py::test_backend_basic[diskann]
pytest tests/test_readme_examples.py::test_readme_basic_example[diskann]
# All DiskANN tests (parametrized + specialized partition tests)
pytest tests/ -k diskann
CI/CD Integration
Tests are automatically run in GitHub Actions:
- After building wheel packages
- On multiple Python versions (3.9 - 3.13)
- On both Ubuntu and macOS
- Using pytest with appropriate markers and flags
pytest.ini Configuration
The pytest.ini file configures:
- Test discovery paths
- Default timeout (600 seconds)
- Environment variables (HF_HUB_DISABLE_SYMLINKS, TOKENIZERS_PARALLELISM)
- Custom markers for slow and OpenAI tests
- Verbose output with short tracebacks
Known Issues
- OpenAI tests are automatically skipped if no API key is provided