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lukaszraczylo
19514bdc55
Document the macOS ARM64 CGO linking issue with sqlite-vec-go-bindings that prevents hybrid package tests from compiling locally. Added: - .github/TESTING.md: Comprehensive testing guide with platform-specific issues, workarounds, and CI configuration details - internal/vector/hybrid/README.md: Package-specific documentation explaining the macOS limitation - .github/CI_FIX_SUMMARY.md: Technical details of the CI fix Key points: - 41 out of 42 packages test successfully on all platforms - hybrid package tests fail only on macOS ARM64 (local dev issue) - Linux CI tests pass with proper build-tags: "fts5" configuration - Production builds and runtime functionality unaffected This is a known limitation of sqlite-vec-go-bindings on macOS ARM64 and does not impact CI/CD or production deployments.
33 lines
1.2 KiB
Markdown
33 lines
1.2 KiB
Markdown
# Hybrid Vector Storage
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LEANN-inspired selective vector storage with hub detection and graph-based search.
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## Testing
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### macOS ARM64 Known Issue
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Tests in this package currently fail to link on macOS ARM64 due to a known issue with `sqlite-vec-go-bindings/cgo`. This is a linking-time issue specific to macOS ARM64 and does not affect:
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- Linux CI/CD (tests pass normally)
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- Windows builds
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- Runtime functionality (only affects test compilation)
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The issue is caused by how macOS ARM64 handles CGO linking with multiple SQLite implementations (mattn/go-sqlite3 and sqlite-vec's embedded SQLite).
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**Workaround for local development:**
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- Run tests for other packages: `go test ./internal/db/... ./internal/search/...`
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- The CI on Linux will test this package
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- Or use a Linux container for local testing
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**Status:** This does not affect production builds or CI/CD pipelines.
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## Architecture
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This package implements three storage strategies:
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1. **StorageAlways** - Store all embeddings (backwards compatible)
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2. **StorageHub** - Store only frequently-accessed "hub" embeddings
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3. **StorageOnDemand** - Recompute all embeddings during search
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See the main documentation for more details on the LEANN algorithm and hybrid storage approach.
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