Tags give the ability to mark specific points in history as being important
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v0.1.0
19694d31 · ·v0.1.0: Initial release Local-first vector search for structure-aware plain text documents. Extracted from a production second-brain knowledge base where it replaced a 1200-line monolith, validated through real consumption as a library dependency before tagging. Features: - Structure-aware chunking that respects meeting-date section boundaries - Hybrid search (vector + FTS) with RRF reranking via LanceDB - Automatic date extraction from natural language queries - Section expansion: retrieves sibling chunks for full meeting context - Library API with custom LanceModel schemas and filtered queries - CLI for index, query, and status operations Tested: 58 tests across chunking, date parsing, query integration, and custom schema library usage patterns. Built on: LanceDB, sentence-transformers (BGE), tantivy FTS.