Semantic search and text expansion query with self-deployed model

I'm trying to use the text expansion query to implement semantic search on a rank features field. I've read the ELSER documentation and understand the process. I'm using a local/downloaded elasticsearch on docker (not connected to elastic cloud).

In this example they reference the ELSER model ID to query a rank features field:

I'm curious if there's a way to use this query but use a self deployed model (not on elastic cloud) rather than the ELSER model.


I'd start with Import the trained model and vocabulary | Machine Learning in the Elastic Stack [8.9] | Elastic on how to import custom NLP models (with --url instead of --cloud-id).

PS: Out of interest, which model do you have in mind?

Hey Camoneme,

You can import your own text embedding model into elasticsearch with eland and use query_vector_builder to embed your query.

This notebook is also an end to end example of how you would do this with a hugging face model

Hope this helps!

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