Python: Filter conversation_id when passing kwargs to agent as tool (#3266)

* Filter conversation_id when passing kwargs to agent as tool

* Small fix

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

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update python/samples/getting_started/agents/openai/openai_responses_client_with_agent_as_tool.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update python/samples/getting_started/agents/azure_ai/azure_ai_with_agent_as_tool.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

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

@@ -27,6 +27,7 @@ This folder contains examples demonstrating different ways to create and use age
 | [`openai_responses_client_image_generation.py`](openai_responses_client_image_generation.py) | Demonstrates how to use image generation capabilities with OpenAI agents to create images based on text descriptions. Requires PIL (Pillow) for image display. |
 | [`openai_responses_client_reasoning.py`](openai_responses_client_reasoning.py) | Demonstrates how to use reasoning capabilities with OpenAI agents, showing how the agent can provide detailed reasoning for its responses. |
 | [`openai_responses_client_streaming_image_generation.py`](openai_responses_client_streaming_image_generation.py) | Demonstrates streaming image generation with partial images for real-time image creation feedback and improved user experience. |
+| [`openai_responses_client_with_agent_as_tool.py`](openai_responses_client_with_agent_as_tool.py) | Shows how to use the agent-as-tool pattern with OpenAI Responses Client, where one agent delegates work to specialized sub-agents wrapped as tools using `as_tool()`. Demonstrates hierarchical agent architectures. |
 | [`openai_responses_client_with_code_interpreter.py`](openai_responses_client_with_code_interpreter.py) | Shows how to use the HostedCodeInterpreterTool with OpenAI agents to write and execute Python code. Includes helper methods for accessing code interpreter data from response chunks. |
 | [`openai_responses_client_with_explicit_settings.py`](openai_responses_client_with_explicit_settings.py) | Shows how to initialize an agent with a specific responses client, configuring settings explicitly including API key and model ID. |
 | [`openai_responses_client_with_file_search.py`](openai_responses_client_with_file_search.py) | Demonstrates how to use file search capabilities with OpenAI agents, allowing the agent to search through uploaded files to answer questions. |

python/samples/getting_started/agents/openai/openai_responses_client_with_agent_as_tool.py

@@ -0,0 +1,67 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from collections.abc import Awaitable, Callable
+
+from agent_framework import FunctionInvocationContext
+from agent_framework.openai import OpenAIResponsesClient
+
+"""
+OpenAI Responses Client Agent-as-Tool Example
+
+Demonstrates hierarchical agent architectures where one agent delegates
+work to specialized sub-agents wrapped as tools using as_tool().
+
+This pattern is useful when you want a coordinator agent to orchestrate
+multiple specialized agents, each focusing on specific tasks.
+"""
+
+
+async def logging_middleware(
+    context: FunctionInvocationContext,
+    next: Callable[[FunctionInvocationContext], Awaitable[None]],
+) -> None:
+    """Middleware that logs tool invocations to show the delegation flow."""
+    print(f"[Calling tool: {context.function.name}]")
+    print(f"[Request: {context.arguments}]")
+
+    await next(context)
+
+    print(f"[Response: {context.result}]")
+
+
+async def main() -> None:
+    print("=== OpenAI Responses Client Agent-as-Tool Pattern ===")
+
+    client = OpenAIResponsesClient()
+
+    # Create a specialized writer agent
+    writer = client.as_agent(
+        name="WriterAgent",
+        instructions="You are a creative writer. Write short, engaging content.",
+    )
+
+    # Convert writer agent to a tool using as_tool()
+    writer_tool = writer.as_tool(
+        name="creative_writer",
+        description="Generate creative content like taglines, slogans, or short copy",
+        arg_name="request",
+        arg_description="What to write",
+    )
+
+    # Create coordinator agent with writer as a tool
+    coordinator = client.as_agent(
+        name="CoordinatorAgent",
+        instructions="You coordinate with specialized agents. Delegate writing tasks to the creative_writer tool.",
+        tools=[writer_tool],
+        middleware=[logging_middleware],
+    )
+
+    query = "Create a tagline for a coffee shop"
+    print(f"User: {query}")
+    result = await coordinator.run(query)
+    print(f"Coordinator: {result}\n")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())