[Doc] ML_inference processor X RerankByField tutorial needed

[brianf-aws]

In Neural Search 2.18 it introduces rerank-by-field search response processor

We need to have a tutorial that shows how the ml-inference search response processor, can be used with the new rerank type in order to rank their documents according to an any external model! This is not to be confused with the current ml_opensearch rerank type that reranks using a cross encoder model only.

This action needs to be done in the OpenSearch/doc-website repo

• We may need to add a whole other page that shows a tutorial using these two processors

Here is a general workflow I can think of to describe this solution although I would like more discussion of how to bring it up.

<h1> Reranking search results using a remote model</h1>
    <p> You may want to rerank your documents according to an external model you may have that is not necessarily a rerank model. You can combine the ml inference search response processor along with the by field rerank processor to achieve this.
See below an example where .... </p>

I still have to think of an interesting scenario that a user may want to see.

[dhrubo-os]

Can I assign this issue to you?

[brianf-aws]

yep!