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adk-python/contributing/samples/interactions_api/agent.py
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George Weale 2367901ec5 chore: Upgrade to headers to 2026
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 858763407
2026-01-20 14:50:09 -08:00

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Python

# 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.
NOTE: The Interactions API does NOT support mixing custom function calling tools
with built-in tools in the same agent. To work around this limitation, we use
bypass_multi_tools_limit=True on GoogleSearchTool, which converts the built-in
google_search to a function calling tool (via GoogleSearchAgentTool).
The bypass is only triggered when len(agent.tools) > 1, so we include multiple
tools in the agent (GoogleSearchTool + get_current_weather).
With bypass_multi_tools_limit=True and multiple tools, all tools become function
calling tools, which allows mixing google_search with custom function tools.
"""
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 (via bypass) and custom function tools
# Using bypass_multi_tools_limit=True converts google_search to a function calling tool.
# We need len(tools) > 1 to trigger the bypass, so we include get_current_weather directly.
# This allows mixing google_search with custom function tools via the Interactions API.
#
# 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-2.5-flash",
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(bypass_multi_tools_limit=True),
get_current_weather,
],
)