## Why are these changes needed?

bug fix : add get_embedding() implementation

## Related issue number

"Closes #6240 " -->

## Checks

- [ ] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [X] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [X] I've made sure all auto checks have passed.

---------

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

# Azure AI Search Tool Implementation

This PR adds a new tool for Azure AI Search integration to autogen-ext,
enabling agents to search and retrieve information from Azure AI Search
indexes.

## Why Are These Changes Needed?
AutoGen currently lacks native integration with Azure AI Search, which
is a powerful enterprise search service that supports semantic, vector,
and hybrid search capabilities. This integration enables agents to:
1. Retrieve relevant information from large document collections
2. Perform semantic search with AI-powered ranking
3. Execute vector similarity search using embeddings
4. Combine text and vector approaches for optimal results

This tool complements existing retrieval capabilities and provides a
seamless way to integrate with Azure's search infrastructure.

## Features
- **Multiple Search Types**: Support for text, semantic, vector, and
hybrid search
- **Flexible Configuration**: Customizable search parameters and fields
- **Robust Error Handling**: User-friendly error messages with
actionable guidance
- **Performance Optimizations**: Configurable caching and retry
mechanisms
- **Vector Search Support**: Built-in embedding generation with
extensibility

## Usage Example
```python
from autogen_ext.tools.azure import AzureAISearchTool
from azure.core.credentials import AzureKeyCredential
from autogen import AssistantAgent, UserProxyAgent
# Create the search tool
search_tool = AzureAISearchTool.load_component({
   "provider": "autogen_ext.tools.azure.AzureAISearchTool",
   "config": {
       "name": "DocumentSearch",
       "description": "Search for information in the knowledge base",
       "endpoint": "https://your-service.search.windows.net",
       "index_name": "your-index",
       "credential": {"api_key": "your-api-key"},
       "query_type": "semantic",
       "semantic_config_name": "default"
   }
})
# Create an agent with the search tool
assistant = AssistantAgent(
   "assistant",
   llm_config={"tools": [search_tool]}
)
# Create a user proxy agent
user_proxy = UserProxyAgent(
   "user_proxy",
   human_input_mode="TERMINATE",
   max_consecutive_auto_reply=10,
   code_execution_config={"work_dir": "coding"}
)
# Start the conversation
user_proxy.initiate_chat(
   assistant,
   message="What information do we have about quantum computing in our knowledge base?"
)
```

## Testing
- Added unit tests for all search types (text, semantic, vector, hybrid)
- Added tests for error handling and cancellation
- All tests pass locally

## Documentation
- Added comprehensive docstrings with examples
- Included warnings about placeholder embedding implementation
- Added links to Azure AI Search documentation

## Related issue number

Closes #5419 

## Checks

- [x] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [x] I've made sure all auto checks have passed.

---------

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>