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1. Does anyone know a postgres reranking extension, to go beyond RRF through ML models or at least custom code?

2. If anyone is observing significant gains from incorporating knowledge graphs into the retrieval step, what kind of a knowledge graph are you working with, what is your retrieval algorithm, and what technology are you using to store it?




Re 1) pgvector has an example in the repo that uses a model for re-ranking: https://github.com/pgvector/pgvector-python/blob/master/exam...

I'm not using that in my own experiments since I don't want to worry about the performance of running a model on production, but seems worth a try.


That's outside the database, though. This is closer to what I had in mind: https://postgresml.org/blog/how-to-improve-search-results-wi...




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