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https://github.com/encounter/adk-python.git
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Shangjie ChenandCopybara-Service
a17bcbb2aa
The existing `LongRunningTool` does not define a programmatic way to provide & validate structured input, also it relies on LLM to reason and parse the user's response. For a quick start, annotate the function with `FunctionTool(my_function, require_confirmation=True)`. A more advanced flow is shown in the `human_tool_confirmation` sample. The new flow is similar to the existing Auth flow: - User request a tool confirmation by calling `tool_context.request_confirmation()` in the tool or `before_tool_callback`, or just using the `require_confirmation` shortcut in FunctionTool. - User can provide custom validation logic before tool call proceeds. - ADK creates corresponding RequestConfirmation FunctionCall Event to ask user for confirmation - User needs to provide the expected tool confirmation to a RequestConfirmation FunctionResponse Event. - ADK then checks the response and continues the tool call. PiperOrigin-RevId: 801019917
81 lines
2.7 KiB
Python
81 lines
2.7 KiB
Python
# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from google.adk import Agent
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from google.adk.tools.function_tool import FunctionTool
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from google.adk.tools.tool_confirmation import ToolConfirmation
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from google.adk.tools.tool_context import ToolContext
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from google.genai import types
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def reimburse(amount: int, tool_context: ToolContext) -> str:
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"""Reimburse the employee for the given amount."""
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return {'status': 'ok'}
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def request_time_off(days: int, tool_context: ToolContext):
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"""Request day off for the employee."""
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if days <= 0:
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return {'status': 'Invalid days to request.'}
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if days <= 2:
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return {
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'status': 'ok',
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'approved_days': days,
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}
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tool_confirmation = tool_context.tool_confirmation
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if not tool_confirmation:
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tool_context.request_confirmation(
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hint=(
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'Please approve or reject the tool call request_time_off() by'
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' responding with a FunctionResponse with an expected'
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' ToolConfirmation payload.'
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),
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payload={
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'approved_days': 0,
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},
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)
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return {'status': 'Manager approval is required.'}
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approved_days = tool_confirmation.payload['approved_days']
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approved_days = min(approved_days, days)
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if approved_days == 0:
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return {'status': 'The time off request is rejected.', 'approved_days': 0}
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return {
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'status': 'ok',
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'approved_days': approved_days,
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}
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root_agent = Agent(
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model='gemini-2.5-flash',
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name='time_off_agent',
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instruction="""
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You are a helpful assistant that can help employees with reimbursement and time off requests.
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- Use the `reimburse` tool for reimbursement requests.
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- Use the `request_time_off` tool for time off requests.
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- Prioritize using tools to fulfill the user's request.
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- Always respond to the user with the tool results.
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""",
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tools=[
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# Set require_confirmation to True to require user confirmation for the
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# tool call. This is an easier way to get user confirmation if the tool
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# just need a boolean confirmation.
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FunctionTool(reimburse, require_confirmation=True),
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request_time_off,
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],
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generate_content_config=types.GenerateContentConfig(temperature=0.1),
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)
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