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https://issues.apache.org/jira/browse/SOLR-17525?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17896035#comment-17896035
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Alessandro Benedetti commented on SOLR-17525:
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Thanks guys for your input!
[~epugh] I am in favour of having multiple people contributing, I would love to
first close a first version that works and then create other tasks to improve
it/solidify it.
I think this ticket should handle the first iteration + documentation.
Other tasks I see coming:
- UpdateRequestProcessor to add the indexing time support
- performance testing
- support for additional embedding models (including potentially an In-Process
one)
My plan is to create the Jiras and work at least on the UpdateRequestProcessor.
Happy for anyone who joins the train!
[~ichattopadhyaya] I don't know what a SIP is
(https://www.acronymfinder.com/SIP.html didn't help).
If it's anything that can help in finalising the contribution quickly, great, I
am open to it, but I have limited time allocated to the task and I hope we can
get feedback and improve the pull request in a decent time frame to avoid
losing the momentum
> 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: 4h 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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