chore: import upstream snapshot with attribution
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This commit is contained in:
wehub-resource-sync
2026-07-13 13:25:13 +08:00
commit ec2b666284
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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.
"""Agent definition for testing the Interactions API integration."""
from google.adk.agents.llm_agent import Agent
from google.adk.models.google_llm import Gemini
from google.adk.tools.google_search_tool import GoogleSearchTool
def get_current_weather(city: str) -> dict:
"""Get the current weather for a city.
This is a mock implementation for testing purposes.
Args:
city: The name of the city to get weather for.
Returns:
A dictionary containing weather information.
"""
# Mock weather data for testing
weather_data = {
"new york": {"temperature": 72, "condition": "Sunny", "humidity": 45},
"london": {"temperature": 59, "condition": "Cloudy", "humidity": 78},
"tokyo": {
"temperature": 68,
"condition": "Partly Cloudy",
"humidity": 60,
},
"paris": {"temperature": 64, "condition": "Rainy", "humidity": 85},
"sydney": {"temperature": 77, "condition": "Clear", "humidity": 55},
}
city_lower = city.lower()
if city_lower in weather_data:
data = weather_data[city_lower]
return {
"city": city,
"temperature_f": data["temperature"],
"condition": data["condition"],
"humidity": data["humidity"],
}
else:
return {
"city": city,
"temperature_f": 70,
"condition": "Unknown",
"humidity": 50,
"note": "Weather data not available, using defaults",
}
# Main agent with google_search built-in tool and custom function tools
#
# NOTE: code_executor is not compatible with function calling mode because the model
# tries to call a function (e.g., run_code) instead of outputting code in markdown.
root_agent = Agent(
model=Gemini(
model="gemini-3.1-flash-lite",
use_interactions_api=True,
),
name="interactions_test_agent",
description="An agent for testing the Interactions API integration",
instruction="""You are a helpful assistant that can:
1. Search the web for information using google_search
2. Get weather information using get_current_weather
When users ask for information that requires searching, use google_search.
When users ask about weather, use get_current_weather.
Be concise and helpful in your responses. Always confirm what you did.
""",
tools=[
GoogleSearchTool(),
get_current_weather,
],
)