Python: Rebase durable task feature branch with main (#2806)

python/samples/getting_started/tools/README.md

@@ -11,6 +11,8 @@ This folder contains examples demonstrating how to use AI functions (tools) with
 | [`ai_function_recover_from_failures.py`](ai_function_recover_from_failures.py) | Demonstrates graceful error handling when tools raise exceptions. Shows how agents receive error information and can recover from failures, deciding whether to retry or respond differently based on the exception. |
 | [`ai_function_with_approval.py`](ai_function_with_approval.py) | Shows how to implement user approval workflows for function calls without using threads. Demonstrates both streaming and non-streaming approval patterns where users can approve or reject function executions before they run. |
 | [`ai_function_with_approval_and_threads.py`](ai_function_with_approval_and_threads.py) | Demonstrates tool approval workflows using threads for automatic conversation history management. Shows how threads simplify approval workflows by automatically storing and retrieving conversation context. Includes both approval and rejection examples. |
+| [`ai_function_with_kwargs.py`](ai_function_with_kwargs.py) | Demonstrates how to inject custom arguments (context) into an AI function from the agent's run method. Useful for passing runtime information like access tokens or user IDs that the tool needs but the model shouldn't see. |
+| [`ai_function_with_thread_injection.py`](ai_function_with_thread_injection.py) | Shows how to access the current `thread` object inside an AI function via `**kwargs`. |
 | [`ai_function_with_max_exceptions.py`](ai_function_with_max_exceptions.py) | Shows how to limit the number of times a tool can fail with exceptions using `max_invocation_exceptions`. Useful for preventing expensive tools from being called repeatedly when they keep failing. |
 | [`ai_function_with_max_invocations.py`](ai_function_with_max_invocations.py) | Demonstrates limiting the total number of times a tool can be invoked using `max_invocations`. Useful for rate-limiting expensive operations or ensuring tools are only called a specific number of times per conversation. |
 | [`ai_functions_in_class.py`](ai_functions_in_class.py) | Shows how to use `ai_function` decorator with class methods to create stateful tools. Demonstrates how class state can control tool behavior dynamically, allowing you to adjust tool functionality at runtime by modifying class properties. |