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Python: Introducing UserInputRequest and Response types and HostedMcpTool (#405)
* initial work on User Approval (and hosted mcp to validate) * small update to the comments in the sample * enable local MCP tools in chatClient get methods * working streaming and improved setup * fix for pyright * updated create_approval -> create_response method * added tests * updated HostedMcpTool and addressed feedback * update type name * naming updates * small docstring update * mypy fix * fixes and updates * fixes for responses * fix int tests * removed broken tests * updated test running * removed specific content check on websearch * increased timeout * split slow foundry test * don't parallel run samples * add dist load to unit tests --------- Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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Eduard van Valkenburg
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from typing import TYPE_CHECKING, Any
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from agent_framework import ChatAgent, HostedMCPTool
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from agent_framework.openai import OpenAIResponsesClient
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if TYPE_CHECKING:
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from agent_framework import AgentProtocol, AgentThread
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async def handle_approvals_without_thread(query: str, agent: "AgentProtocol"):
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"""When we don't have a thread, we need to ensure we return with the input, approval request and approval."""
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from agent_framework import ChatMessage
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result = await agent.run(query)
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while len(result.user_input_requests) > 0:
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new_inputs: list[Any] = [query]
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for user_input_needed in result.user_input_requests:
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print(
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f"User Input Request for function from {agent.name}: {user_input_needed.function_call.name}"
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f" with arguments: {user_input_needed.function_call.arguments}"
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)
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new_inputs.append(ChatMessage(role="assistant", contents=[user_input_needed]))
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user_approval = input("Approve function call? (y/n): ")
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new_inputs.append(
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ChatMessage(role="user", contents=[user_input_needed.create_response(user_approval.lower() == "y")])
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)
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result = await agent.run(new_inputs)
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return result
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async def handle_approvals_with_thread(query: str, agent: "AgentProtocol", thread: "AgentThread"):
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"""Here we let the thread deal with the previous responses, and we just rerun with the approval."""
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from agent_framework import ChatMessage
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result = await agent.run(query, thread=thread, store=True)
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while len(result.user_input_requests) > 0:
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new_input: list[Any] = []
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for user_input_needed in result.user_input_requests:
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print(
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f"User Input Request for function from {agent.name}: {user_input_needed.function_call.name}"
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f" with arguments: {user_input_needed.function_call.arguments}"
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)
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user_approval = input("Approve function call? (y/n): ")
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new_input.append(
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ChatMessage(
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role="user",
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contents=[user_input_needed.create_response(user_approval.lower() == "y")],
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)
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)
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result = await agent.run(new_input, thread=thread, store=True)
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return result
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async def handle_approvals_with_thread_streaming(query: str, agent: "AgentProtocol", thread: "AgentThread"):
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"""Here we let the thread deal with the previous responses, and we just rerun with the approval."""
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from agent_framework import ChatMessage
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new_input: list[ChatMessage] = []
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new_input_added = True
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while new_input_added:
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new_input_added = False
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new_input.append(ChatMessage(role="user", text=query))
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async for update in agent.run_stream(new_input, thread=thread, store=True):
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if update.user_input_requests:
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for user_input_needed in update.user_input_requests:
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print(
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f"User Input Request for function from {agent.name}: {user_input_needed.function_call.name}"
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f" with arguments: {user_input_needed.function_call.arguments}"
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)
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user_approval = input("Approve function call? (y/n): ")
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new_input.append(
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ChatMessage(
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role="user", contents=[user_input_needed.create_response(user_approval.lower() == "y")]
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)
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)
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new_input_added = True
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else:
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yield update
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async def run_hosted_mcp_without_thread_and_specific_approval() -> None:
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"""Example showing Mcp Tools with approvals without using a thread."""
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print("=== Mcp with approvals and without thread ===")
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# Tools are provided when creating the agent
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# The agent can use these tools for any query during its lifetime
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async with ChatAgent(
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chat_client=OpenAIResponsesClient(),
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name="DocsAgent",
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instructions="You are a helpful assistant that can help with microsoft documentation questions.",
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tools=HostedMCPTool(
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name="Microsoft Learn MCP",
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url="https://learn.microsoft.com/api/mcp",
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# we don't require approval for microsoft_docs_search tool calls
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# but we do for any other tool
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approval_mode={"never_require_approval": ["microsoft_docs_search"]},
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),
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) as agent:
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# First query
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query1 = "How to create an Azure storage account using az cli?"
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print(f"User: {query1}")
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result1 = await handle_approvals_without_thread(query1, agent)
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print(f"{agent.name}: {result1}\n")
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print("\n=======================================\n")
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# Second query
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query2 = "What is Microsoft Semantic Kernel?"
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print(f"User: {query2}")
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result2 = await handle_approvals_without_thread(query2, agent)
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print(f"{agent.name}: {result2}\n")
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async def run_hosted_mcp_without_approval() -> None:
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"""Example showing Mcp Tools without approvals."""
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print("=== Mcp without approvals ===")
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# Tools are provided when creating the agent
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# The agent can use these tools for any query during its lifetime
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async with ChatAgent(
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chat_client=OpenAIResponsesClient(),
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name="DocsAgent",
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instructions="You are a helpful assistant that can help with microsoft documentation questions.",
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tools=HostedMCPTool(
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name="Microsoft Learn MCP",
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url="https://learn.microsoft.com/api/mcp",
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# we don't require approval for any function calls
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# this means we will not see the approval messages,
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# it is fully handled by the service and a final response is returned.
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approval_mode="never_require",
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),
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) as agent:
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# First query
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query1 = "How to create an Azure storage account using az cli?"
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print(f"User: {query1}")
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result1 = await handle_approvals_without_thread(query1, agent)
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print(f"{agent.name}: {result1}\n")
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print("\n=======================================\n")
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# Second query
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query2 = "What is Microsoft Semantic Kernel?"
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print(f"User: {query2}")
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result2 = await handle_approvals_without_thread(query2, agent)
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print(f"{agent.name}: {result2}\n")
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async def run_hosted_mcp_with_thread() -> None:
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"""Example showing Mcp Tools with approvals using a thread."""
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print("=== Mcp with approvals and with thread ===")
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# Tools are provided when creating the agent
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# The agent can use these tools for any query during its lifetime
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async with ChatAgent(
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chat_client=OpenAIResponsesClient(),
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name="DocsAgent",
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instructions="You are a helpful assistant that can help with microsoft documentation questions.",
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tools=HostedMCPTool(
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name="Microsoft Learn MCP",
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url="https://learn.microsoft.com/api/mcp",
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# we require approval for all function calls
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approval_mode="always_require",
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),
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) as agent:
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# First query
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thread = agent.get_new_thread()
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query1 = "How to create an Azure storage account using az cli?"
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print(f"User: {query1}")
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result1 = await handle_approvals_with_thread(query1, agent, thread)
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print(f"{agent.name}: {result1}\n")
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print("\n=======================================\n")
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# Second query
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query2 = "What is Microsoft Semantic Kernel?"
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print(f"User: {query2}")
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result2 = await handle_approvals_with_thread(query2, agent, thread)
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print(f"{agent.name}: {result2}\n")
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async def run_hosted_mcp_with_thread_streaming() -> None:
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"""Example showing Mcp Tools with approvals using a thread."""
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print("=== Mcp with approvals and with thread ===")
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# Tools are provided when creating the agent
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# The agent can use these tools for any query during its lifetime
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async with ChatAgent(
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chat_client=OpenAIResponsesClient(),
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name="DocsAgent",
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instructions="You are a helpful assistant that can help with microsoft documentation questions.",
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tools=HostedMCPTool(
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name="Microsoft Learn MCP",
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url="https://learn.microsoft.com/api/mcp",
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# we require approval for all function calls
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approval_mode="always_require",
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),
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) as agent:
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# First query
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thread = agent.get_new_thread()
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query1 = "How to create an Azure storage account using az cli?"
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print(f"User: {query1}")
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print(f"{agent.name}: ", end="")
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async for update in handle_approvals_with_thread_streaming(query1, agent, thread):
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print(update, end="")
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print("\n")
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print("\n=======================================\n")
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# Second query
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query2 = "What is Microsoft Semantic Kernel?"
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print(f"User: {query2}")
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print(f"{agent.name}: ", end="")
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async for update in handle_approvals_with_thread_streaming(query2, agent, thread):
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print(update, end="")
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print("\n")
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async def main() -> None:
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print("=== OpenAI Responses Client Agent with Hosted Mcp Tools Examples ===\n")
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await run_hosted_mcp_without_approval()
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await run_hosted_mcp_without_thread_and_specific_approval()
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await run_hosted_mcp_with_thread()
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await run_hosted_mcp_with_thread_streaming()
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if __name__ == "__main__":
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asyncio.run(main())
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