Update Azure AI Search Vector Store

[ZachHandley]

Description

• Updated Metadata so you can use either a metadata string (LlamaIndex) or a dict/JSON object where it will extract the default fields, and then assume the remainder is metadata and match your fields
• Added new SearchField option configs for the _metadata_filterable_keys
• Added new semantic_config (SemanticConfiguration | str | None) and semantic_config_name (I added semantic_config_name for backwards compatibility but)
• Added new vector_search_profile (VectorSearchProfile | None) and kept the existing vector_search_profile_name for backwards compatiblity
• Changed key_fields to doc_id_field (from doc_id_field_str) to support new str | SearchField
• All changes should be backwards compatible in keeping in-line with LlamaIndex's docs
• Added more helper methods to try to make it a bit easier to use, I may have gone a bit overboard, but feel free to scale back

All Tests Pass, but need to test with an actual Azure Vector Store I would imagine

Fixes # (issue)

New Package?

Did I fill in the tool.llamahub section in the pyproject.toml and provide a detailed README.md for my new integration or package?

• Yes
• No (I can!)

Version Bump?

Did I bump the version in the pyproject.toml file of the package I am updating? (Except for the llama-index-core package)

• Yes
• No (I can!)

Type of Change

Please delete options that are not relevant.

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

How Has This Been Tested?

Your pull-request will likely not be merged unless it is covered by some form of impactful unit testing.

• I added new unit tests to cover this change
• I believe this change is already covered by existing unit tests

Suggested Checklist:

• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• I have added Google Colab support for the newly added notebooks.
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes
• I ran make format; make lint to appease the lint gods

[ZachHandley]

So I guess Azure was returning metadata without ending brackets, so I took this on for not a ton of reason, but after checking my work I would remove the following:

• The semantic config and Vector Search don't need to be given as parameters, they can be given in the SearchIndex (should I do this? It would be less user friendly) --and the client can hook that for the name and configuration. I'm just gonna swap it to an optional VectorSearch/SemanticSearch instead, as those contain all of the data, allowing for drop-in replacement, which is what I was going for anyways
• The spread object I added I think was unnecessary

I still stand by the metadata improvements in terms of the filterable_metadata_field_keys being SearchField bases optionally as those are a 1:1, as well as the other QOL stuff like using the custom semantic config, but I can reduce the code (and I will be doing that)

[logan-markewich]

Not sure if you are still updating this, but in the sake of keeping PRs smaller, going to go ahead and merge this #17683