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https://issues.apache.org/jira/browse/SOLR-17525?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17907395#comment-17907395
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Eric Pugh edited comment on SOLR-17525 at 12/20/24 2:55 PM:
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I know this is a bit late, but I wonder if we could mark this new module as 
"experimental" in any way?   I suspect that as we start using it, we find lots 
of ways to improve it/evolve it, and it would be nice to not have to worry 
about back compat issues....  

 

I really like the list of improvements that you are already thinking about ;).

 

I am looking forward to updating the Chorus reference implmentation to use this 
instead of the homegrown python API's....!

 

 


was (Author: epugh):
I know this is a bit late, but I wonder if we could mark this new module as 
"experimental" in any way?   I suspect that as we start using it, we find lots 
of ways to improve it/evolve it, and it would be nice to not have to worry 
about back compat issues....  

 

I really like the list of improvements that you are already thinking about ;).

 

 

> Text to Vector Query Parser
> ---------------------------
>
>                 Key: SOLR-17525
>                 URL: https://issues.apache.org/jira/browse/SOLR-17525
>             Project: Solr
>          Issue Type: New Feature
>      Security Level: Public(Default Security Level. Issues are Public) 
>          Components: query parsers
>            Reporter: Alessandro Benedetti
>            Priority: Major
>              Labels: pull-request-available
>          Time Spent: 21h 20m
>  Remaining Estimate: 0h
>
> Scope of this issue is to introduce support for automatic text vectorisation 
> in Apache Solr, directly in a query parser.
> A LLM fine-tuned for sentence similarity will be accessed to embed the text.
> Apache Solr will host the configuration parameters to access embedding 
> services and the query parser will use such services to directly encode the 
> query to a vector and then run vector search on a DenseVectorField.



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