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function_tool_with_approval.py
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# Copyright (c) Microsoft. All rights reserved.
import asyncio
from random import randrange
from typing import TYPE_CHECKING, Annotated, Any
from agent_framework import AgentResponse, ChatAgent, ChatMessage, tool
from agent_framework.openai import OpenAIResponsesClient
if TYPE_CHECKING:
from agent_framework import AgentProtocol
"""
Demonstration of a tool with approvals.
This sample demonstrates using AI functions with user approval workflows.
It shows how to handle function call approvals without using threads.
"""
conditions = ["sunny", "cloudy", "raining", "snowing", "clear"]
# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py.
@tool(approval_mode="never_require")
def get_weather(location: Annotated[str, "The city and state, e.g. San Francisco, CA"]) -> str:
"""Get the current weather for a given location."""
# Simulate weather data
return f"The weather in {location} is {conditions[randrange(0, len(conditions))]} and {randrange(-10, 30)}°C."
# Define a simple weather tool that requires approval
@tool(approval_mode="always_require")
def get_weather_detail(location: Annotated[str, "The city and state, e.g. San Francisco, CA"]) -> str:
"""Get the current weather for a given location."""
# Simulate weather data
return (
f"The weather in {location} is {conditions[randrange(0, len(conditions))]} and {randrange(-10, 30)}°C, "
"with a humidity of 88%. "
f"Tomorrow will be {conditions[randrange(0, len(conditions))]} with a high of {randrange(-10, 30)}°C."
)
async def handle_approvals(query: str, agent: "AgentProtocol") -> AgentResponse:
"""Handle function call approvals.
When we don't have a thread, we need to ensure we include the original query,
the approval request, and the approval response in each iteration.
"""
result = await agent.run(query)
while len(result.user_input_requests) > 0:
# Start with the original query
new_inputs: list[Any] = [query]
for user_input_needed in result.user_input_requests:
print(
f"\nUser Input Request for function from {agent.name}:"
f"\n Function: {user_input_needed.function_call.name}"
f"\n Arguments: {user_input_needed.function_call.arguments}"
)
# Add the assistant message with the approval request
new_inputs.append(ChatMessage(role="assistant", contents=[user_input_needed]))
# Get user approval
user_approval = await asyncio.to_thread(input, "\nApprove function call? (y/n): ")
# Add the user's approval response
new_inputs.append(
ChatMessage(role="user", contents=[user_input_needed.to_function_approval_response(user_approval.lower() == "y")])
)
# Run again with all the context
result = await agent.run(new_inputs)
return result
async def handle_approvals_streaming(query: str, agent: "AgentProtocol") -> None:
"""Handle function call approvals with streaming responses.
When we don't have a thread, we need to ensure we include the original query,
the approval request, and the approval response in each iteration.
"""
current_input: str | list[Any] = query
has_user_input_requests = True
while has_user_input_requests:
has_user_input_requests = False
user_input_requests: list[Any] = []
# Stream the response
async for chunk in agent.run_stream(current_input):
if chunk.text:
print(chunk.text, end="", flush=True)
# Collect user input requests from the stream
if chunk.user_input_requests:
user_input_requests.extend(chunk.user_input_requests)
if user_input_requests:
has_user_input_requests = True
# Start with the original query
new_inputs: list[Any] = [query]
for user_input_needed in user_input_requests:
print(
f"\n\nUser Input Request for function from {agent.name}:"
f"\n Function: {user_input_needed.function_call.name}"
f"\n Arguments: {user_input_needed.function_call.arguments}"
)
# Add the assistant message with the approval request
new_inputs.append(ChatMessage(role="assistant", contents=[user_input_needed]))
# Get user approval
user_approval = await asyncio.to_thread(input, "\nApprove function call? (y/n): ")
# Add the user's approval response
new_inputs.append(
ChatMessage(role="user", contents=[user_input_needed.to_function_approval_response(user_approval.lower() == "y")])
)
# Update input with all the context for next iteration
current_input = new_inputs
async def run_weather_agent_with_approval(is_streaming: bool) -> None:
"""Example showing AI function with approval requirement."""
print(f"\n=== Weather Agent with Approval Required ({'Streaming' if is_streaming else 'Non-Streaming'}) ===\n")
async with ChatAgent(
chat_client=OpenAIResponsesClient(),
name="WeatherAgent",
instructions=("You are a helpful weather assistant. Use the get_weather tool to provide weather information."),
tools=[get_weather, get_weather_detail],
) as agent:
query = "Can you give me an update of the weather in LA and Portland and detailed weather for Seattle?"
print(f"User: {query}")
if is_streaming:
print(f"\n{agent.name}: ", end="", flush=True)
await handle_approvals_streaming(query, agent)
print()
else:
result = await handle_approvals(query, agent)
print(f"\n{agent.name}: {result}\n")
async def main() -> None:
print("=== Demonstration of a tool with approvals ===\n")
await run_weather_agent_with_approval(is_streaming=False)
await run_weather_agent_with_approval(is_streaming=True)
if __name__ == "__main__":
asyncio.run(main())