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Rank Fusion for improved code context in RAG

by wsxiaoys on 6/11/24, 3:30 PM with 1 comments

• by wsxiaoys on 6/11/24, 3:36 PM

  Fun fact: We've implemented binary embedding search [1] without the need for a specialized vector database. Instead, dimensional tokens like 'embedding_0_0', 'embedding_1_0' are created and being built into the tantivy index [2].

  We're satisfied with the quality and performance this approach yields, while still keep Tabby embed everything into a single binary.

  [1] My binary vector search is better than your FP32 vectors: https://blog.pgvecto.rs/my-binary-vector-search-is-better-th...

  [2] Tantivy: https://github.com/quickwit-oss/tantivy