Add cuvs-bench-elastic: HTTP backend for Elasticsearch GPU vector search

[afourniernv]

Introduce cuvs-bench-elastic as an optional plugin for cuvs-bench that provides an Elasticsearch backend. The backend communicates with Elasticsearch via HTTP and supports HNSW indexing with optional GPU acceleration when using the Elasticsearch GPU image (cuVS-accelerated vector search).

• Add cuvs_bench_elastic package with backend and config loader entry points
• Extend cuvs_bench registry and search spaces for pluggable backends
• Add elastic and integration optional dependencies to cuvs-bench
• Add modularization tests and integration test scaffolding (disabled until CI has ES GPU image, cuVS libs, and GPU runner)

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[jnke2016]

Nice. This is what I discussed with @cjnolet pertaining to lazy import and used Milvus as an example

class MilvusBackend(BenchmarkBackend):
    def __init__(self, config: Dict[str, Any]):
        super().__init__(config)
        try:
            from pymilvus import connections, Collection
        except ImportError:
            raise ImportError(
                "pymilvus is required for MilvusBackend. "
                "Install with: pip install pymilvus"
            )
        connections.connect(host=config["host"], port=config["port"])