# Copyright 2025 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. import asyncio from google.adk.agents import Agent from google.adk.tools import FunctionTool from google.adk.runners import Runner from google.adk.sessions import InMemorySessionService from google.genai import types APP_NAME="weather_sentiment_agent" USER_ID="user1234" SESSION_ID="1234" MODEL_ID="gemini-2.0-flash" # Tool 1 def get_weather_report(city: str) -> dict: """Retrieves the current weather report for a specified city. Returns: dict: A dictionary containing the weather information with a 'status' key ('success' or 'error') and a 'report' key with the weather details if successful, or an 'error_message' if an error occurred. """ if city.lower() == "london": return {"status": "success", "report": "The current weather in London is cloudy with a temperature of 18 degrees Celsius and a chance of rain."} elif city.lower() == "paris": return {"status": "success", "report": "The weather in Paris is sunny with a temperature of 25 degrees Celsius."} else: return {"status": "error", "error_message": f"Weather information for '{city}' is not available."} weather_tool = FunctionTool(func=get_weather_report) # Tool 2 def analyze_sentiment(text: str) -> dict: """Analyzes the sentiment of the given text. Returns: dict: A dictionary with 'sentiment' ('positive', 'negative', or 'neutral') and a 'confidence' score. """ if "good" in text.lower() or "sunny" in text.lower(): return {"sentiment": "positive", "confidence": 0.8} elif "rain" in text.lower() or "bad" in text.lower(): return {"sentiment": "negative", "confidence": 0.7} else: return {"sentiment": "neutral", "confidence": 0.6} sentiment_tool = FunctionTool(func=analyze_sentiment) # Agent weather_sentiment_agent = Agent( model=MODEL_ID, name='weather_sentiment_agent', instruction="""You are a helpful assistant that provides weather information and analyzes the sentiment of user feedback. **If the user asks about the weather in a specific city, use the 'get_weather_report' tool to retrieve the weather details.** **If the 'get_weather_report' tool returns a 'success' status, provide the weather report to the user.** **If the 'get_weather_report' tool returns an 'error' status, inform the user that the weather information for the specified city is not available and ask if they have another city in mind.** **After providing a weather report, if the user gives feedback on the weather (e.g., 'That's good' or 'I don't like rain'), use the 'analyze_sentiment' tool to understand their sentiment.** Then, briefly acknowledge their sentiment. You can handle these tasks sequentially if needed.""", tools=[weather_tool, sentiment_tool] ) async def main(): """Main function to run the agent asynchronously.""" # Session and Runner Setup session_service = InMemorySessionService() # Use 'await' to correctly create the session await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID) runner = Runner(agent=weather_sentiment_agent, app_name=APP_NAME, session_service=session_service) # Agent Interaction query = "weather in london?" print(f"User Query: {query}") content = types.Content(role='user', parts=[types.Part(text=query)]) # The runner's run method handles the async loop internally events = runner.run(user_id=USER_ID, session_id=SESSION_ID, new_message=content) for event in events: if event.is_final_response(): final_response = event.content.parts[0].text print("Agent Response:", final_response) # Standard way to run the main async function if __name__ == "__main__": asyncio.run(main())