How to Improve the accuracy of vector search in weaviate

General
1

I am using hybrid search of the Weaviate where I have kept value of alpha = 1 means it will do vector search.

But I am not getting accurate results for that.

I am using openai’s ada model to generate an embeddings.

I am using structure data in which there are two languages that is English and Danish.

example response:
query: I want results with value less than 10mm.
response will give values with less than 10mm also more than 10mm

example2:
query: I want results with value not less than 10mm.
here it gives values less than 10mm, it is not able to understand the meaning of not.

What can be the solution to improve the results of vector search.

Thank you in advance.

2

hi @Rohini_vaidya !

Is 10mm a property value?

Doing a hybrid query to filter a data set will not properly work, as Weaviate will get the closer vector for the semantic search, and then all objects that has the provided keywords, then fuse the distance and keyword.

It will not filter all results with less than 10mm

We have developer a Query Agent, that could help here, as it will generate a Weaviate query based on your initial query:

3

Thank you @DudaNogueira

Here, 10mm is not my property value, I just given a example.

I just want to know how we can improve the vector search results in weaviate.

currently, I am using openai’s ada model for embeddings but still I am not getting good accuracy for vector search.

I went through Vector indexes | Weaviate this but for this I need to recreate my schema which is not feasible.

Are there any other ways to improve the results ?

Thank you in advance.