chore: import upstream snapshot with attribution

contributing/samples/tools/parallel_functions/agent.py

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+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Sample agent for testing parallel function calling."""
+
+import asyncio
+import time
+from typing import List
+
+from google.adk import Agent
+from google.adk.tools.tool_context import ToolContext
+
+
+async def get_weather(city: str, tool_context: ToolContext) -> dict:
+  """Get the current weather for a city.
+
+  Args:
+    city: The name of the city to get weather for.
+
+  Returns:
+    A dictionary with weather information.
+  """
+  # Simulate some async processing time (non-blocking)
+  await asyncio.sleep(2)
+
+  # Mock weather data
+  weather_data = {
+      'New York': {'temp': 72, 'condition': 'sunny', 'humidity': 45},
+      'London': {'temp': 60, 'condition': 'cloudy', 'humidity': 80},
+      'Tokyo': {'temp': 68, 'condition': 'rainy', 'humidity': 90},
+      'San Francisco': {'temp': 65, 'condition': 'foggy', 'humidity': 85},
+      'Paris': {'temp': 58, 'condition': 'overcast', 'humidity': 70},
+      'Sydney': {'temp': 75, 'condition': 'sunny', 'humidity': 60},
+  }
+
+  result = weather_data.get(
+      city,
+      {
+          'temp': 70,
+          'condition': 'unknown',
+          'humidity': 50,
+          'note': (
+              f'Weather data not available for {city}, showing default values'
+          ),
+      },
+  )
+
+  # Store in context for testing thread safety
+  if 'weather_requests' not in tool_context.state:
+    tool_context.state['weather_requests'] = []
+  tool_context.state['weather_requests'].append(
+      {'city': city, 'result': result}
+  )
+
+  return {
+      'city': city,
+      'temperature': result['temp'],
+      'condition': result['condition'],
+      'humidity': result['humidity'],
+      **({'note': result['note']} if 'note' in result else {}),
+  }
+
+
+async def get_currency_rate(
+    from_currency: str, to_currency: str, tool_context: ToolContext
+) -> dict:
+  """Get the exchange rate between two currencies.
+
+  Args:
+    from_currency: The source currency code (e.g., 'USD').
+    to_currency: The target currency code (e.g., 'EUR').
+
+  Returns:
+    A dictionary with exchange rate information.
+  """
+  # Simulate async processing time
+  await asyncio.sleep(1.5)
+
+  # Mock exchange rates
+  rates = {
+      ('USD', 'EUR'): 0.85,
+      ('USD', 'GBP'): 0.75,
+      ('USD', 'JPY'): 110.0,
+      ('EUR', 'USD'): 1.18,
+      ('EUR', 'GBP'): 0.88,
+      ('GBP', 'USD'): 1.33,
+      ('GBP', 'EUR'): 1.14,
+      ('JPY', 'USD'): 0.009,
+  }
+
+  rate = rates.get((from_currency, to_currency), 1.0)
+
+  # Store in context for testing thread safety
+  if 'currency_requests' not in tool_context.state:
+    tool_context.state['currency_requests'] = []
+  tool_context.state['currency_requests'].append({
+      'from': from_currency,
+      'to': to_currency,
+      'rate': rate,
+  })
+
+  return {
+      'from_currency': from_currency,
+      'to_currency': to_currency,
+      'exchange_rate': rate,
+  }
+
+
+async def calculate_distance(
+    city1: str, city2: str, tool_context: ToolContext
+) -> dict:
+  """Calculate the distance between two cities.
+
+  Args:
+    city1: The first city.
+    city2: The second city.
+
+  Returns:
+    A dictionary with distance information.
+  """
+  # Simulate async processing time (non-blocking)
+  await asyncio.sleep(1)
+
+  # Mock distances (in kilometers)
+  city_coords = {
+      'New York': (40.7128, -74.0060),
+      'London': (51.5074, -0.1278),
+      'Tokyo': (35.6762, 139.6503),
+      'San Francisco': (37.7749, -122.4194),
+      'Paris': (48.8566, 2.3522),
+      'Sydney': (-33.8688, 151.2093),
+  }
+
+  # Simple distance calculation (mock)
+  if city1 in city_coords and city2 in city_coords:
+    coord1 = city_coords[city1]
+    coord2 = city_coords[city2]
+    # Simplified distance calculation
+    distance = int(
+        ((coord1[0] - coord2[0]) ** 2 + (coord1[1] - coord2[1]) ** 2) ** 0.5
+        * 111
+    )  # rough km conversion
+  else:
+    distance = 5000  # default distance
+
+  # Store in context for testing thread safety
+  if 'distance_requests' not in tool_context.state:
+    tool_context.state['distance_requests'] = []
+  tool_context.state['distance_requests'].append({
+      'city1': city1,
+      'city2': city2,
+      'distance': distance,
+  })
+
+  return {
+      'city1': city1,
+      'city2': city2,
+      'distance_km': distance,
+      'distance_miles': int(distance * 0.621371),
+  }
+
+
+async def get_population(cities: List[str], tool_context: ToolContext) -> dict:
+  """Get population information for multiple cities.
+
+  Args:
+    cities: A list of city names.
+
+  Returns:
+    A dictionary with population data for each city.
+  """
+  # Simulate async processing time proportional to number of cities (non-blocking)
+  await asyncio.sleep(len(cities) * 0.5)
+
+  # Mock population data
+  populations = {
+      'New York': 8336817,
+      'London': 9648110,
+      'Tokyo': 13960000,
+      'San Francisco': 873965,
+      'Paris': 2161000,
+      'Sydney': 5312163,
+  }
+
+  results = {}
+  for city in cities:
+    results[city] = populations.get(city, 1000000)  # default 1M if not found
+
+  # Store in context for testing thread safety
+  if 'population_requests' not in tool_context.state:
+    tool_context.state['population_requests'] = []
+  tool_context.state['population_requests'].append(
+      {'cities': cities, 'results': results}
+  )
+
+  return {
+      'populations': results,
+      'total_population': sum(results.values()),
+      'cities_count': len(cities),
+  }
+
+
+root_agent = Agent(
+    name='parallel_function_test_agent',
+    description=(
+        'Agent for testing parallel function calling performance and thread'
+        ' safety.'
+    ),
+    instruction="""
+    You are a helpful assistant that can provide information about weather, currency rates,
+    distances between cities, and population data. You have access to multiple tools and
+    should use them efficiently.
+
+    When users ask for information about multiple cities or multiple types of data,
+    you should call multiple functions in parallel to provide faster responses.
+
+    For example:
+    - If asked about weather in multiple cities, call get_weather for each city in parallel
+    - If asked about weather and currency rates, call both functions in parallel
+    - If asked to compare cities, you might need weather, population, and distance data in parallel
+
+    Always aim to be efficient and call multiple functions simultaneously when possible.
+    Be informative and provide clear, well-structured responses.
+  """,
+    tools=[
+        get_weather,
+        get_currency_rate,
+        calculate_distance,
+        get_population,
+    ],
+)