# 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, ], )