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Get action confirmation for ADK Tools

Some agent workflows require confirmation for decision making, verification, security, or general oversight. In these cases, you want to get a response from a human or supervising system before proceeding with a workflow. The Tool Confirmation feature in the Agent Development Kit (ADK) allows an ADK Tool to pause its execution and interact with a user or other system for confirmation or to gather structured data before proceeding. You can use Tool Confirmation with an ADK Tool in the following ways:

  • Boolean Confirmation: You can configure a FunctionTool with a require_confirmation parameter. This option pauses the tool for a yes or no confirmation response.
  • Advanced Confirmation: For scenarios requiring structured data responses, you can configure a FunctionTool with a text prompt to explain the confirmation and an expected response.

Experimental

The Tool Confirmation feature is experimental and has some known limitations. We welcome your feedback!

You can configure how a request is communicated to a user, and the system can also use remote responses sent via the ADK server's REST API. When using the confirmation feature with the ADK web user interface, the agent workflow displays a dialog box to the user to request input, as shown in Figure 1:

Screenshot of default user interface for tool confirmation

Figure 1. Example confirmation response request dialog box using an advanced, tool response implementation.

The following sections describe how to use this feature for the confirmation scenarios. For a complete code sample, see the human_tool_confirmation example. There are additional ways to incorporate human input into your agent workflow, for more details, see the Human-in-the-loop agent pattern.

Boolean confirmation

When your tool only requires a simple yes or no from the user, you can append a confirmation step using the FunctionTool class as a wrapper. For example, if you have a tool called reimburse, you can enable a confirmation step by wrapping it with the FunctionTool class and setting the require_confirmation parameter to True, as shown in the following example:

# From agent.py
root_agent = Agent(
   ...
   tools=[
        # Set require_confirmation to True to require user confirmation
        # for the tool call.
        FunctionTool(reimburse, require_confirmation=True),
    ],
...

This implementation method requires minimal code, but is limited to simple approvals from the user or confirming system. For a complete example of this approach, see the human_tool_confirmation code sample.

Require confirmation function

You can modify the behavior require_confirmation response by replacing its input value with a function that returns a boolean response. The following example shows a function for determining if a confirmation is required:

async def confirmation_threshold(
    amount: int, tool_context: ToolContext
) -> bool:
  """Returns true if the amount is greater than 1000."""
  return amount > 1000

This function than then be set as the parameter value for the require_confirmation parameter:

root_agent = Agent(
   ...
   tools=[
        # Set require_confirmation to True to require user confirmation
        FunctionTool(reimburse, require_confirmation=confirmation_threshold),
    ],
...

For a complete example of this implementation, see the human_tool_confirmation code sample.

Advanced confirmation

When a tool confirmation requires more details for the user or a more complex response, use a tool_confirmation implementation. This approach extends the ToolContext object to add a text description of the request for the user and allows for more complex response data. When implementing tool confirmation this way, you can pause a tool's execution, request specific information, and then resume the tool with the provided data.

This confirmation flow has a request stage where the system assembles and sends an input request human response, and a response stage where the system receives and processes the returned data.

Confirmation definition

When creating a Tool with an advanced confirmation, create a function that includes a ToolContext object. Then define the confirmation using a tool_confirmation object, the tool_context.request_confirmation() method with hint and payload parameters. These properties are used as follows:

  • hint: Descriptive message that explains what is needed from the user.
  • payload: The structure of the data you expect in return. This data type is Any and must be serializable into a JSON-formatted string, such as a dictionary or pydantic model.

The following code shows an example implementation for a tool that processes time off requests for an employee:

def request_time_off(days: int, tool_context: ToolContext):
  """Request day off for the employee."""
  ...
  tool_confirmation = tool_context.tool_confirmation
  if not tool_confirmation:
    tool_context.request_confirmation(
        hint=(
            'Please approve or reject the tool call request_time_off() by'
            ' responding with a FunctionResponse with an expected'
            ' ToolConfirmation payload.'
        ),
        payload={
            'approved_days': 0,
        },
    )
    # Return intermediate status indicating that the tool is waiting for
    # a confirmation response:
    return {'status': 'Manager approval is required.'}

  approved_days = tool_confirmation.payload['approved_days']
  approved_days = min(approved_days, days)
  if approved_days == 0:
    return {'status': 'The time off request is rejected.', 'approved_days': 0}
  return {
      'status': 'ok',
      'approved_days': approved_days,
  }

For a complete example of this approach, see the human_tool_confirmation code sample. Keep in mind that the agent workflow tool execution pauses while a confirmation is obtained. After confirmation is received, you can access the confirmation response in the tool_confirmation.payload object and then proceed with the execution of the workflow.

Remote confirmation with REST API

If there is no active user interface for a human confirmation of an agent workflow, you can handle the confirmation through a command-line interface or by routing it through another channel like email or a chat application. To confirm the tool call, the user or calling application needs to send a FunctionResponse event with the tool confirmation data.

You can send the request to the ADK API server's /run or /run_sse endpoint, or directly to the ADK runner. The following example uses a curl command to send the confirmation to the /run_sse endpoint:

 curl -X POST http://localhost:8000/run_sse \
 -H "Content-Type: application/json" \
 -d '{
    "app_name": "human_tool_confirmation",
    "user_id": "user",
    "session_id": "7828f575-2402-489f-8079-74ea95b6a300",
    "new_message": {
        "parts": [
            {
                "function_response": {
                    "id": "adk-13b84a8c-c95c-4d66-b006-d72b30447e35",
                    "name": "adk_request_confirmation",
                    "response": {
                        "confirmed": true
                    }
                }
            }
        ],
        "role": "user"
    }
}'

A REST-based response for a confirmation must meet the following requirements:

  • The id in the function_response should match the function_call_id from the RequestConfirmation FunctionCall event.
  • The name should be adk_request_confirmation.
  • The response object contains the confirmation status and any additional payload data required by the tool.

Known limitations

The tool confirmation feature has the following limitations:

Next steps

For more information on building ADK tools for agent workflows, see Function tools.