Expand description
Embedding engine for semantic code search.
Provides dense vector embeddings for code chunks using a local ONNX model
(all-MiniLM-L6-v2). Feature-gated under embeddings — falls back gracefully
to BM25-only search when the feature or model is not available.
Architecture:
WordPieceTokenizer → ONNX Model (rten) → Mean Pooling → L2 Normalize → Vec
Modules§
- download
- Automatic model download from HuggingFace Hub.
- pooling
- Pooling strategies for transformer hidden states.
- tokenizer
- Minimal WordPiece tokenizer for BERT-style embedding models.
Structs§
Functions§
- cosine_
similarity - Compute cosine similarity between two L2-normalized vectors. Both vectors must be pre-normalized for correct results.
- cosine_
similarity_ raw - Compute cosine similarity without requiring pre-normalization.