Adds new parameters to the elasticsearch inference API for the rerank task type

[kosabogi]

This PR adds the new long_document_strategy and max_chunks_per_doc parameters to the service_settings object of the Create an Elasticsearch inference endpoint documentation.

It also updates the description of the chunking_settings object to clarify that this setting is only applicable for the sparse_embeddings and text_embeddings task types.

Related issue: #5451

[github-actions]

Following you can find the validation changes against the target branch for the APIs.

API	Status	Request	Response
index	🟢	1445/1445 → 1443/1443	1447/1447 → 1445/1445
indices.create	🔴	1378/1402 → 1385/1409	1402/1402 → 1409/1409
indices.refresh	🟢	329/329 → 327/327	329/329 → 327/327
ml.get_job_stats	🟢	30/30 → 29/29	30/30 → 29/29
ml.put_job	🟢	65/65 → 64/64	65/65 → 64/64

You can validate these APIs yourself by using the make validate target.

[dan-rubinstein]

A quick clarification. For 9.2, these two values are only configurable for rerank endpoints using the elastic reranker model.

[dan-rubinstein]

I'm not sure if we need to be more specific about this anywhere but for this new method of chunking the user can not set chunking_settings the way that they would for embeddings. We handle building the chunking settings for them. If we want to clarify how we build the chunking settings somewhere we can.

[dan-rubinstein]

I'm not sure where it's best to clarify this but with chunking enabled we will return to the user a single score per document (same as we do for truncating) with the score correlating to the highest score of any chunk. I just want to make it clear that the structure of the response to the user will not change, only the rerank relevance scores.

[davidkyle]

LGTM