Add Optional Agentic Retrieval Support to AI Search

We need AI Search to support agentic retrieval workflows (multi-step planning, iterative query refinement, and tool-driven retrieval). Today, AI Search assumes a single-shot or linear retrieval pattern, which limits more advanced agents that need to reason over multiple retrieval steps.

**Proposed feature**
Add **optional** “agentic retrieval” support aligned with the public preview described here:
https://learn.microsoft.com/en-us/azure/search/agentic-retrieval-overview?tabs=quickstarts

Key capabilities that would help:
- Multi-step retrieval orchestration (plan → retrieve → refine → retrieve)
- Built-in support for query rewrite and decomposition
- Native controls for tool selection, reranking strategy, and retrieval depth
- Traceability/telemetry for each retrieval step (for debugging and evaluation)

**Important constraint**
This should be opt-in and **must not impact deployments in other Azure clouds**, including **Azure Government, Azure China, and Azure Germany**. If agentic retrieval is unavailable in those clouds, the system should gracefully fall back to standard retrieval without behavior changes.

**Why this matters**
- Enables more accurate, context-aware responses for complex user questions
- Reduces application-side custom orchestration code
- Aligns AI Search with modern agent frameworks and best practices

No files, tests, or entry points are named. Start by locating the AI Search integration and Azure cloud configuration, then determine where opt-in agentic retrieval and cloud capability checks belong; done means supported clouds can use it while Azure Government, China, and Germany retain unchanged standard retrieval when unavailable.

Written by the indexing model from the issue text.