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https://issues.apache.org/jira/browse/SOLR-18127?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18076545#comment-18076545
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Renato Haeberli commented on SOLR-18127:
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Hi [~prathyand] , it actually enough to extend
dev.langchain4j.model.embedding.DimensionAwareEmbeddingModel.
It is not decoupled from LangChain4j, but it is actually quite simple to do,
still waiting for feedback on my implementation:
https://github.com/apache/solr/pull/3476/
> Introduce pluggable solr native text-to-vector TextToVectorModel interface +
> LangChain4j compatibility adapter
> --------------------------------------------------------------------------------------------------------------
>
> Key: SOLR-18127
> URL: https://issues.apache.org/jira/browse/SOLR-18127
> Project: Solr
> Issue Type: Improvement
> Components: vector-search
> Reporter: Prathmesh Deshmukh
> Priority: Minor
> Labels: pull-requests-available
> Time Spent: 10m
> Remaining Estimate: 0h
>
> Introduce a Solr‑native {{TextToVectorModel}} interface to support pluggable
> embedding implementations without requiring LangChain4j.
> The current Text‑to‑Vector module {{SolrTextToVectorModel}} is tightly
> coupled to LangChain4j’s {{EmbeddingModel}} API. As a result, only the few
> LangChain4j‑bundled providers (OpenAI, HuggingFace, etc.) are supported out
> of the box. Anyone who wants to integrate a custom embedding endpoint must
> implement the full LangChain4j interface and builder pattern, even when they
> don’t use LangChain4j in their system.
> There’s no simple Solr‑native abstraction for “text → float vector” that
> custom implementations can plug into.
> This proposal introduces a small native interface that decouples Solr’s
> vector feature from LangChain4j, while keeping full backward compatibility.
> PR available: https://github.com/apache/solr/pull/4161
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