This project is a knowledge base plugin and RAG context manager that uses a local vector database interface to enable semantic search and relationship mapping. It transforms text into numerical vectors to find semantically related notes and excerpts based on conceptual meaning rather than keyword matches. The system differentiates itself through a semantic graph visualizer that maps notes into clusters to reveal conceptual connections. It also features a context manager capable of bundling local notes and excerpts into reusable packs to provide grounded factual bases for large language model
Code for Paper Sentence-aware Contrastive Learning for Open-Domain Passage Retrieval. ACL2022 Main Conference, Long Paper. DCSR aims to elliminate the occurence of Contrastive Conflicts, in order to provide a more general dense retriever model for pratical use.
