Python: Add sample to show how to retrieve existing azure ai agent definition. (microsoft#10801)

### Motivation and Context

Some users may want to re-use an existing Azure AI Agent definition
inside of SK. We don't have an example showing this.

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### Description

Add a sample showing how to retrieve an Azure AI Agent definition and
use it within SK.
- Update `AzureAIAgent` README
- Closes microsoft#10800 

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### Contribution Checklist

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- [X] The code builds clean without any errors or warnings
- [X] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
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script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [X] I didn't break anyone 😄

Author: moonbox3

python/samples/getting_started_with_agents/azure_ai_agent/README.md

@@ -93,6 +93,12 @@ agent = AzureAIAgent(
 
 Now, you can create a thread, add chat messages to the agent, and invoke it with given inputs and optional parameters.
 
+### Reusing an Agent Definition
+
+In certain scenarios, you may prefer to reuse an existing agent definition rather than creating a new one. This can be done by calling `await client.agents.get_agent(...)` instead of `await client.agents.create_agent(...)`. 
+
+For a practical example, refer to the [`step7_azure_ai_agent_retrieval`](./step7_azure_ai_agent_retrieval.py) sample.
+
 ## Requests and Rate Limits
 
 ### Managing API Request Frequency

python/samples/getting_started_with_agents/azure_ai_agent/step7_azure_ai_agent_retrieval.py

@@ -0,0 +1,66 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from azure.identity.aio import DefaultAzureCredential
+
+from semantic_kernel.agents.azure_ai import AzureAIAgent
+
+"""
+The following sample demonstrates how to use an already existing
+Azure AI Agent within Semantic Kernel. This sample requires that you
+have an existing agent created either previously in code or via the
+Azure Portal (or CLI).
+"""
+
+
+# Simulate a conversation with the agent
+USER_INPUTS = [
+    "Why is the sky blue?",
+]
+
+
+async def main() -> None:
+    async with (
+        DefaultAzureCredential() as creds,
+        AzureAIAgent.create_client(credential=creds) as client,
+    ):
+        # 1. Retrieve the agent definition based on the `assistant_id`
+        # Replace the "your-assistant-id" with the actual assistant ID
+        # you want to use.
+        agent_definition = await client.agents.get_agent(
+            assistant_id="your-assistant-id",
+        )
+
+        # 2. Create a Semantic Kernel agent for the Azure AI agent
+        agent = AzureAIAgent(
+            client=client,
+            definition=agent_definition,
+        )
+
+        # 3. Create a new thread on the Azure AI agent service
+        thread = await client.agents.create_thread()
+
+        try:
+            for user_input in USER_INPUTS:
+                # 4. Add the user input as a chat message
+                await agent.add_chat_message(thread_id=thread.id, message=user_input)
+                print(f"# User: '{user_input}'")
+                # 5. Invoke the agent for the specified thread for response
+                response = await agent.get_response(thread_id=thread.id)
+                print(f"# {response.name}: {response}")
+        finally:
+            # 6. Cleanup: Delete the thread and agent
+            await client.agents.delete_thread(thread.id)
+            # Do not clean up the assistant so it can be used again
+
+        """
+        Sample Output:
+        # User: 'Why is the sky blue?'
+        # Agent: The sky appears blue because molecules in the Earth's atmosphere scatter sunlight, 
+        and blue light is scattered more than other colors due to its shorter wavelength.
+        """
+
+
+if __name__ == "__main__":
+    asyncio.run(main())