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Meilisearch – search engine API bringing AI-powered hybrid search

(github.com)
151 points modinfo | 1 comments | 14 Apr 25 12:46 UTC | HN request time: 0.57s | source
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adeptima ◴[14 Apr 25 14:56 UTC] No.43682013[source]▶
Meilisearch is great, used it for a quick demo

However if you need a full-text search similar to Apache Lucene, my go-to options are based on Tantivy

Tantivy https://github.com/quickwit-oss/tantivy

Asian language, BM25 scoring, Natural query language, JSON fields indexing support are all must-have features for me

Quickwit - https://github.com/quickwit-oss/quickwit - https://quickwit.io/docs/get-started/quickstart

ParadeDB - https://github.com/paradedb/paradedb

I'm still looking for a systematic approach to make a hybrid search (combined full-text with embedding vectors).

Any thoughts on up-to-date hybrid search experience are greatly appreciated

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1. inertiatic ◴[14 Apr 25 15:42 UTC] No.43682566[source]▶
>I'm still looking for a systematic approach to make a hybrid search (combined full-text with embedding vectors).

Start off with ES or Vespa, probably. ES is not hard at all to get started with, IMO.

Try RRF - see how far that gets you for your use case. If it's not where you want to be, time to get thinking about what you're trying to do. Maybe a score multiplication gets you where you want to be - you can do it in Vespa I think, but you have to hack around the inability to express exactly that in ES.

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