raudaschl / rag-fusion Goto Github PK

I think this could make a very good python package which can be deployed to pypi and a lot of people could use it.

Hi, thank for rag-fusion but i want compare this with RAG, how can i do it? Have you tried doing that yet? if you have tried, can you public me the results?

Hi, I noticed that you are using some random mock up and I wonder how practically one has to think of reranking in real usecases. Is it intended to generate a regression algo that takes a query and bunch of responses and score them accordingly (I mean based some supervised data)?

👋

Interesting work!
However I do not fully understand the need of generating multiple queries doing a vector search.
Once the query is transformed into a vector the search is latent space centric so it will retrieve documents close to our vector. The rewritten queries will be semantically similar and I would not expect much benefit from this. The downside is the cost effectiveness having to multiply the number of queries and vector calculation for each query.

However, a completely different scenario would be generating the different queries in solely text based search DBs where having the same query reformulated with even different words that could retrieve semantically similar documents improving the results.

Have you made some comparison tests?

WDYT?

what does k stand for? how do we decide it?