L2-normalizes FastEmbed output vectors at the provider boundary so SQLite vector scoring keeps its unit-vector contract for custom FastEmbed models such as multilingual MiniLM variants.
Zero vectors are preserved as-is to avoid division errors, and the provider tests cover both non-unit vectors and zero-vector behavior.
Verification:
- uv run pytest tests/repository/test_fastembed_provider.py -q
- uv run ruff check src/basic_memory/repository/fastembed_provider.py tests/repository/test_fastembed_provider.py
- uv run ruff format --check src/basic_memory/repository/fastembed_provider.py tests/repository/test_fastembed_provider.py
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Signed-off-by: tk-pkm111 <133480534+tk-pkm111@users.noreply.github.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Add configurable cache_dir, threads, and parallel settings for FastEmbed
to support cloud deployments where defaults fail. Cache embedding providers
at the process level to avoid re-creating heavy ONNX model instances.
- Add semantic_embedding_cache_dir, semantic_embedding_threads, and
semantic_embedding_parallel config fields
- Thread-safe provider cache with double-checked locking in factory
- Forward runtime knobs through to TextEmbedding and embed() calls
- Fix if/elif chain in factory for correct error handling
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Paul Hernandez