sample-apps VS awesome-vector-search

See this blog post https://blog.vespa.ai/pretrained-transformer-language-models-for-search-part-1/ and the open source sample app it describes: https://github.com/vespa-engine/sample-apps/tree/master/msmarco-ranking

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Vespa.ai supports combining dense vector search with keyword search and ranking, see https://docs.google.com/presentation/d/1vWKhSvFH-4MFcs4aNa9C...

There is also a Vespa sample application (open source, Apache 2) demonstrating multiple different retrieval and ranking strategies over at https://github.com/vespa-engine/sample-apps/blob/master/msma...

Look up Vespa.ai. https://github.com/vespa-engine/sample-apps/tree/master/dense-passage-retrieval-with-ann

Probably. But there are a number of free open source ones. For example, I've got a document that I'm doing embedding-keys for that has about 8000 sentences. Here's a list of some [ https://github.com/currentslab/awesome-vector-search ]

note: search for vector databases not written in Go but with Go clients, in case there is anything more local/lightweight: https://github.com/currentslab/awesome-vector-search

https://github.com/currentslab/awesome-vector-search

I was surprised to see Elastic actually has ok support for some of this stuff, though it appears slower for most of the tasks.

Supporting sequence of vectors does seems like a fresh air to the vector search service. I have added marqo to the list of awesome vector search (disclosure: I am the maintainer of the list) to increase your exposure.

If you want a proper curated list of various libraries and standalone services of vector search engines, refer to this awesome GitHub repository by Currents API.