Deploy to Vertex AI and Simulate Interaction

Outline the steps to prepare and deploy your Google ADK agent to Vertex AI. This includes creating a model, versioning, and deploying an endpoint. Once deployed, provide a simple Python script using the Vertex AI client libraries to interact with your agent, simulating user queries and demonstrating its personalized responses. Explain how multimodal input (text + simulated image data) would be sent to the deployed agent. 

```python
# from google.cloud import aiplatform
# from google.cloud.aiplatform_v1.services import endpoint_service
# from google.cloud.aiplatform_v1.types import PredictRequest

# # Example for deployment (conceptual)
# # client_options = {"api_endpoint": "YOUR_REGION-aiplatform.googleapis.com"}
# # client = aiplatform.gapic.ModelServiceClient(client_options=client_options)
# # model = client.upload_model(...)

# # Example for interaction
# # endpoint = aiplatform.Endpoint(endpoint_name="your_endpoint_id")
# # response = endpoint.predict(instances=[{"user_id": "test_user", "query": "Hello"}])
# # print(response.predictions)
```