SearchPipeline.search() called self._embedder.embed() which doesn't exist
on BaseEmbedder/FastEmbedEmbedder — only embed_single() and embed_batch()
are defined. This was masked by MockEmbedder in tests. Changed to
embed_single() which is the correct API for single-query embedding.
Also added scripts/test_small_e2e.py for quick end-to-end validation of
indexing pipeline and all search features on a small file set.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Added BaseReranker abstract class for defining reranking interfaces.
- Implemented FastEmbedReranker using fastembed's TextCrossEncoder for scoring document-query pairs.
- Introduced FTSEngine for full-text search capabilities using SQLite FTS5.
- Developed SearchPipeline to integrate embedding, binary search, ANN indexing, FTS, and reranking.
- Added fusion methods for combining results from different search strategies using Reciprocal Rank Fusion.
- Created unit and integration tests for the new search and reranking components.
- Established configuration management for search parameters and models.
