Python: [BREAKING] cleanup of thread API and serialization (#893)

* cleanup of threads and serialization

* fix for sliding window

* fix redis test

* updated from comments

* updated context provider and threads

* updated lock

* add asyncio default

* fix redis tests

* fix tests

* fix tests

* renamed to invoking

* fixed tests

* fix for instructions

python/samples/getting_started/agents/azure_ai/README.md

@@ -9,6 +9,7 @@ This folder contains examples demonstrating different ways to create and use age
 | [`azure_ai_basic.py`](azure_ai_basic.py) | The simplest way to create an agent using `ChatAgent` with `AzureAIAgentClient`. It automatically handles all configuration using environment variables. |
 | [`azure_ai_with_explicit_settings.py`](azure_ai_with_explicit_settings.py) | Shows how to create an agent with explicitly configured `AzureAIAgentClient` settings, including project endpoint, model deployment, credentials, and agent name. |
 | [`azure_ai_with_existing_agent.py`](azure_ai_with_existing_agent.py) | Shows how to work with a pre-existing agent by providing the agent ID to the Azure AI chat client. This example also demonstrates proper cleanup of manually created agents. |
+| [`azure_ai_with_existing_thread.py`](azure_ai_with_existing_thread.py) | Shows how to work with a pre-existing thread by providing the thread ID to the Azure AI chat client. This example also demonstrates proper cleanup of manually created threads. |
 | [`azure_ai_with_function_tools.py`](azure_ai_with_function_tools.py) | Demonstrates how to use function tools with agents. Shows both agent-level tools (defined when creating the agent) and query-level tools (provided with specific queries). |
 | [`azure_ai_with_code_interpreter.py`](azure_ai_with_code_interpreter.py) | Shows how to use the HostedCodeInterpreterTool with Azure AI agents to write and execute Python code. Includes helper methods for accessing code interpreter data from response chunks. |
 | [`azure_ai_with_local_mcp.py`](azure_ai_with_local_mcp.py) | Shows how to integrate Azure AI agents with Model Context Protocol (MCP) servers for enhanced functionality and tool integration. Demonstrates both agent-level and run-level tool configuration. |

python/samples/getting_started/agents/azure_ai/azure_ai_with_existing_thread.py

@@ -0,0 +1,52 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+import os
+from random import randint
+from typing import Annotated
+
+from agent_framework import ChatAgent
+from agent_framework.azure import AzureAIAgentClient
+from azure.ai.projects.aio import AIProjectClient
+from azure.identity.aio import AzureCliCredential
+from pydantic import Field
+
+
+def get_weather(
+    location: Annotated[str, Field(description="The location to get the weather for.")],
+) -> str:
+    """Get the weather for a given location."""
+    conditions = ["sunny", "cloudy", "rainy", "stormy"]
+    return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
+
+
+async def main() -> None:
+    print("=== Azure AI Chat Client with Existing Thread ===")
+
+    # Create the client
+    async with (
+        AzureCliCredential() as credential,
+        AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as client,
+    ):
+        # Create an thread that will persist
+        created_thread = await client.agents.threads.create()
+
+        try:
+            async with ChatAgent(
+                # passing in the client is optional here, so if you take the agent_id from the portal
+                # you can use it directly without the two lines above.
+                chat_client=AzureAIAgentClient(project_client=client),
+                instructions="You are a helpful weather agent.",
+                tools=get_weather,
+            ) as agent:
+                thread = agent.get_new_thread(service_thread_id=created_thread.id)
+                assert thread.is_initialized
+                result = await agent.run("What's the weather like in Tokyo?", thread=thread)
+                print(f"Result: {result}\n")
+        finally:
+            # Clean up the thread manually
+            await client.agents.threads.delete(created_thread.id)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())