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https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15252089#comment-15252089
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Alessandro Benedetti commented on SOLR-8542:
--------------------------------------------

Hi gents,
I am going to start using the plugin in a closer way.
I think it is likely that I will find small bugs ( like the cache for EFI 
features ect) or improvements.
What is the last version of the code available ?
How can I contribute back improvements/bug-fix ?

Is this the last version : 
https://github.com/bloomberg/lucene-solr/commits/master-ltr-plugin-rfc-cpoerschke-comments
 ?

Could make sense to create a separate repo, containing only the plugin, self 
contained without the entire Solr.
In that way I could branch from there, and then time by time ask pull-requests 
to include bug-fix if approved.

What do you think? [~diegoceccarelli]  [~mnilsson] ?

Cheers

> Integrate Learning to Rank into Solr
> ------------------------------------
>
>                 Key: SOLR-8542
>                 URL: https://issues.apache.org/jira/browse/SOLR-8542
>             Project: Solr
>          Issue Type: New Feature
>            Reporter: Joshua Pantony
>            Assignee: Christine Poerschke
>            Priority: Minor
>         Attachments: README.md, README.md, SOLR-8542-branch_5x.patch, 
> SOLR-8542-trunk.patch
>
>
> This is a ticket to integrate learning to rank machine learning models into 
> Solr. Solr Learning to Rank (LTR) provides a way for you to extract features 
> directly inside Solr for use in training a machine learned model. You can 
> then deploy that model to Solr and use it to rerank your top X search 
> results. This concept was previously presented by the authors at Lucene/Solr 
> Revolution 2015 ( 
> http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp
>  ).
> The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, 
> David Grohmann and Diego Ceccarelli.
> Any chance this could make it into a 5x release? We've also attached 
> documentation as a github MD file, but are happy to convert to a desired 
> format.
> h3. Test the plugin with solr/example/techproducts in 6 steps
> Solr provides some simple example of indices. In order to test the plugin 
> with 
> the techproducts example please follow these steps
> h4. 1. compile solr and the examples 
> cd solr
> ant dist
> ant example
> h4. 2. run the example
> ./bin/solr -e techproducts 
> h4. 3. stop it and install the plugin:
>    
> ./bin/solr stop
> mkdir example/techproducts/solr/techproducts/lib
> cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar 
> example/techproducts/solr/techproducts/lib/
> cp contrib/ltr/example/solrconfig.xml 
> example/techproducts/solr/techproducts/conf/
> h4. 4. run the example again
>     
> ./bin/solr -e techproducts
> h4. 5. index some features and a model
> curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore'  
> --data-binary "@./contrib/ltr/example/techproducts-features.json"  -H 
> 'Content-type:application/json'
> curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore'  
> --data-binary "@./contrib/ltr/example/techproducts-model.json"  -H 
> 'Content-type:application/json'
> h4. 6. have fun !
> *access to the default feature store*
> http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ 
> *access to the model store*
> http://localhost:8983/solr/techproducts/schema/mstore
> *perform a query using the model, and retrieve the features*
> http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true



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