Implementation principles and performance advantages of hybrid search technology
LightRAG realizes multi-dimensional information retrieval through a dual-engine architecture of vector + graph. Vector search handles literal similarity (local matching), while knowledge graph mines conceptual relevance (global reasoning). The system provides five query modes: the basic naive mode, the detail-focused local mode, the macro-focused global mode, the hybrid optimized hybrid mode, and the full-featured integrated mix mode.
Practical tests show that when dealing with a query such as "the history of Apple's founders and related products", which needs to connect fragmented information, the hybrid mode improves the accuracy by 37% and the coherence of the answer by 52% compared with the pure vector retrieval, which is a feature that makes it valuable in enterprise knowledge management and academic research scenarios, academic research scenarios.
This answer comes from the articleLightRAG: A Lightweight Framework for Building Retrieval Augmented Generation (RAG) ApplicationsThe
