chore: import upstream snapshot with attribution
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# Copyright 2026 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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"""Sample agent demonstrating DebugLoggingPlugin usage.
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This sample shows how to use the DebugLoggingPlugin to capture complete
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debug information (LLM requests/responses, tool calls, events, session state)
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to a YAML file for debugging purposes.
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Usage:
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adk run contributing/samples/plugin_debug_logging
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After running, check the generated `adk_debug.yaml` file for detailed logs.
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"""
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from typing import Any
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from google.adk.agents import LlmAgent
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from google.adk.apps import App
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from google.adk.plugins import DebugLoggingPlugin
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def get_weather(city: str) -> dict[str, Any]:
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"""Get the current weather for a city.
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Args:
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city: The name of the city to get weather for.
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Returns:
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A dictionary containing weather information.
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"""
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# Simulated weather data
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weather_data = {
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"new york": {"temperature": 22, "condition": "sunny", "humidity": 45},
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"london": {"temperature": 15, "condition": "cloudy", "humidity": 70},
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"tokyo": {"temperature": 28, "condition": "humid", "humidity": 85},
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"paris": {"temperature": 18, "condition": "rainy", "humidity": 80},
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}
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city_lower = city.lower()
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if city_lower in weather_data:
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data = weather_data[city_lower]
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return {
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"city": city,
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"temperature_celsius": data["temperature"],
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"condition": data["condition"],
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"humidity_percent": data["humidity"],
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}
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else:
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return {
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"city": city,
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"error": f"Weather data not available for {city}",
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}
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def calculate(expression: str) -> dict[str, Any]:
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"""Evaluate a simple mathematical expression.
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Args:
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expression: A mathematical expression to evaluate (e.g., "2 + 2").
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Returns:
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A dictionary containing the result or error.
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"""
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try:
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# Only allow safe mathematical operations
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allowed_chars = set("0123456789+-*/.() ")
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if not all(c in allowed_chars for c in expression):
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return {"error": "Invalid characters in expression"}
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result = eval(expression) # Safe due to character restriction
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return {"expression": expression, "result": result}
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except Exception as e:
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return {"expression": expression, "error": str(e)}
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# Sample queries to try:
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# - "What's the weather in Tokyo?"
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# - "Calculate 15 * 7 + 3"
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# - "What's the weather in London and calculate 100 / 4"
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root_agent = LlmAgent(
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name="debug_demo_agent",
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description="A demo agent that shows DebugLoggingPlugin capabilities",
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instruction="""You are a helpful assistant that can:
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1. Get weather information for cities (New York, London, Tokyo, Paris)
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2. Perform simple calculations
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When asked about weather, use the get_weather tool.
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When asked to calculate, use the calculate tool.
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Be concise in your responses.""",
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tools=[get_weather, calculate],
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)
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# Create the app with DebugLoggingPlugin
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# The plugin will write detailed debug information to adk_debug.yaml
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app = App(
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name="plugin_debug_logging",
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root_agent=root_agent,
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plugins=[
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# DebugLoggingPlugin captures complete interaction data to a YAML file
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# Options:
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# output_path: Path to output file (default: "adk_debug.yaml")
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# include_session_state: Include session state snapshot (default: True)
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# include_system_instruction: Include full system instruction (default: True)
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DebugLoggingPlugin(
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output_path="adk_debug.yaml",
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include_session_state=True,
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include_system_instruction=True,
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),
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],
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)
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