The issue was that tmate was placed before pytest step, but the hang
occurs during pytest execution. Now tmate starts inside the test step
and provides connection info before running tests.
1. Tmate SSH Debugging:
- Added manual workflow_dispatch trigger with debug_enabled option
- Integrated mxschmitt/action-tmate@v3 for SSH access to CI runner
- Can be triggered manually or by adding [debug] to commit message
- Detached mode with 30min timeout, limited to actor only
- Also triggers on test failure when debug is enabled
2. Enhanced Pytest Output:
- Added --capture=no to see real-time output
- Added --log-cli-level=DEBUG for maximum verbosity
- Added --tb=short for cleaner tracebacks
- Pipe output to tee for both display and logging
- Show last 20 lines of output on completion
3. Environment Diagnostics:
- Export PYTHONUNBUFFERED=1 for immediate output
- Show Python/Pytest versions at start
- Display relevant environment variables
- Check network ports before/after tests
4. Diagnostic Script:
- Created scripts/diagnose_hang.sh for comprehensive system checks
- Shows processes, network, file descriptors, memory, ZMQ status
- Automatically runs on timeout for detailed debugging info
This allows debugging CI hangs via SSH when needed while providing extensive logging by default.
- Remove --no-index so numpy/scipy/etc can be resolved on Python 3.13
- Keep --find-links to force our packages from local dist
Fixes: dependency resolution failure on Ubuntu Python 3.13 (numpy missing)
- Build leann-core and leann on macOS too
- Install all packages via --find-links and --no-index across platforms
- Lower macOS MACOSX_DEPLOYMENT_TARGET to 12.0 for wider compatibility
This ensures consistency and avoids PyPI drift while improving macOS compatibility.
- Ubuntu: Install all packages from local builds with --no-index
- macOS: Install core packages from PyPI, backends from local builds
- Remove --no-index for macOS backend installation to allow dependency resolution
- Pin versions when installing from PyPI to ensure consistency
Fixes error: 'leann-core was not found in the provided package locations'
- Explicitly specify Python version when creating venv with uv
- Prevents mismatch between build Python (e.g., 3.10) and test Python
- Fixes: _diskannpy.cpython-310-x86_64-linux-gnu.so in Python 3.11 error
The issue: uv venv was defaulting to Python 3.11 regardless of matrix version
- Use --find-links with --no-index to let uv select correct wheel
- Prevents installing wrong Python version wheel (e.g., cp310 for Python 3.11)
- Fixes ImportError: _diskannpy.cpython-310-x86_64-linux-gnu.so in Python 3.11
The issue was that *.whl glob matched all Python versions, causing
uv to potentially install a cp310 wheel in a Python 3.11 environment.
- Remove '--plat linux_x86_64' which is not a valid platform tag
- Let auditwheel automatically determine the correct platform
- Based on CI output, it will use manylinux_2_35_x86_64
This was causing auditwheel repair to fail, preventing proper wheel repair
- Check wheel contents before and after auditwheel repair
- Verify _diskannpy module installation after pip install
- List installed package directory structure
- Add explicit platform tag for auditwheel repair
This helps diagnose why ImportError: cannot import name '_diskannpy' occurs
- Change from --find-links to direct wheel installation with --force-reinstall
- This ensures CI uses locally built packages with latest source code
- Prevents uv from using PyPI packages with same version number but old code
- Fixes CI test failures where old code (without metadata_file_path) was used
Root cause: CI was installing leann-backend-diskann v0.2.1 from PyPI
instead of the locally built wheel with same version number.
- Pin ruff==0.12.7 in pyproject.toml dev dependencies
- Update CI to use exact ruff version instead of latest
- Add comments explaining version pinning rationale
- Ensures consistent formatting across local, CI, and pre-commit
* 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>
- Add pre-commit configuration with ruff and black
- Fix lint CI job to use uv tool install instead of sync
- Add essential LlamaIndex dependencies to leann-core
Co-Authored-By: Yichuan Wang <73766326+yichuan-w@users.noreply.github.com>
- Fix ambiguous fullwidth characters (commas, parentheses) in strings and comments
- Replace Chinese comments with English equivalents
- Fix unused imports with proper noqa annotations for intentional imports
- Fix bare except clauses with specific exception types
- Fix redefined variables and undefined names
- Add ruff noqa annotations for generated protobuf files
- Add lint and format check to GitHub Actions CI pipeline
The build workflow was checking for matrix.os == 'ubuntu-latest',
but we changed the matrix to use 'ubuntu-22.04', causing the
pure Python packages (leann-core and leann) to never be built.
Changed to use pattern matching [[ == ubuntu-* ]] to match any
Ubuntu version.
This explains why v0.1.9 only published the C++ backend packages
but not the pure Python packages.
- Explicitly use ubuntu-22.04 instead of ubuntu-latest
- Add Python 3.13 to the build matrix
- This ensures we build on the same OS version as Google Colab
- Revert to simple Ubuntu 22.04 builds that should work with Colab
- Remove all manylinux container complexity
- Colab runs on Ubuntu 22.04, so direct builds should be compatible
- Restore build-reusable.yml to v0.1.5 version
- Remove cibuildwheel option from release workflow
This should fix the overcomplicated build issues while maintaining
Colab compatibility through direct Ubuntu 22.04 builds.
- Add gcc-c++ and cmake to dependencies
- Create libzmq.pc file if missing (CentOS 7 issue)
- Set PKG_CONFIG_PATH through CIBW_ENVIRONMENT_LINUX
- Add protobuf-devel to ensure all headers are available
- Fix shell variable escaping in heredoc
- Add yum cache cleaning and updating
- Make package installations more resilient with fallbacks
- Use pkgconfig instead of pkg-config (CentOS 7 naming)
- Handle optional packages that might not be available
- Add error handling for package installation failures
- Add multiple safe.directory configurations to cover different possible paths
- This fixes 'detected dubious ownership in repository' error
- Ensures git works properly in manylinux2014 containers
- Upgrade all GitHub Actions to v4 (v3 is deprecated)
- Use manual git checkout in manylinux2014 containers to avoid Node.js issues
- Update artifact naming to ensure uniqueness (required by v4)
- Add fail-fast: false to build strategies
- This maintains manylinux2014 compatibility while using latest actions
- Use actions/checkout@v3 instead of v4 (Node.js 16 vs 20)
- Use actions/setup-python@v4 instead of v5
- Use actions/upload-artifact@v3 and download-artifact@v3
- This fixes GLIBC version errors in manylinux2014 containers
- manylinux2014 (CentOS 7) has glibc 2.17 but Node.js 20 needs 2.25+
- Add manylinux2014 Docker containers for Linux builds
- This will generate wheels compatible with older Linux systems (CentOS 7+, Ubuntu 16.04+)
- Separate build logic for container vs regular environments
- Install appropriate system dependencies for yum-based manylinux environment
- Use pip instead of uv in containers for better compatibility
- Fix Python version format for manylinux container paths
- Remove --plat manylinux2014_x86_64 flag that was causing build failures
- Let auditwheel automatically determine the appropriate manylinux tag
- Add auditwheel show command to display compatibility info
- This fixes the 'too-recent versioned symbols' error
- Change auditwheel --plat to manylinux2014_x86_64
- This ensures wheels work on Ubuntu 16.04+ instead of requiring 24.04+
- Fixes compatibility issues for users on Ubuntu 22.04 and similar systems
