Sounds great! See https://github.com/apache/solr/pull/3476 where @renatoh is faced with this conundrum
On Thu, Feb 19, 2026 at 6:32 AM Prathmesh Deshmukh <[email protected]> wrote: > Hi everyone, > > > I’d like to propose an enhancement to the Text to Vector(language-models) > module to support pluggable/custom embedding model implementations. > > At the moment, SolrTextToVectorModel is tightly coupled to LangChain4j’s > EmbeddingModel interface. This effectively limits support to the bundled > LangChain4j providers (HuggingFace, OpenAI, etc.). If someone wants to > integrate a custom embedding endpoint, they currently need to implement the > full LangChain4j EmbeddingModel interface, including its builder > conventions — even if they don’t otherwise use LangChain4j. > > There’s also no Solr-native abstraction for text-to-vector conversion > today. > > My proposal is to introduce a Solr-native TextToVectorModel interface and > decouple the module from LangChain4j. For backward compatibility, we could > add a Langchain4jModelAdapter that implements TextToVectorModel by wrapping > a LangChain4j EmbeddingModel. That way, existing configurations would > continue to work unchanged. > > With this approach, users could implement TextToVectorModel in their own > JAR, drop it into Solr’s classpath, and register it via the existing REST > API without taking on a LangChain4j dependency. > > The change would involve: > > - adding TextToVectorModel > - adding Langchain4jModelAdapter > - updating SolrTextToVectorModel factory logic to support both paths > > I’d appreciate feedback on whether this direction makes sense. I’m happy to > open a JIRA and put together a draft PR for discussion. I have a working > implementation locally that demonstrates the approach. > > > Thanks, > > Prathmesh Deshmukh >
