Google ADK Agent Initialization and Multimodal Input

Initialize a Google ADK agent in Vertex AI. Define its capabilities to ingest multimodal input: text from news articles, sentiment scores, and numerical market data from a `Prediction Market API`. The agent should be able to receive a prompt like 'Analyze the market for the upcoming election' and respond with a basic summary of current data.

```python
from vertexai.preview.generative_models import GenerativeModel, Part
from google.cloud import aiplatform

aiplatform.init(project="your-gcp-project-id", location="us-central1")

model = GenerativeModel("gemini-1.5-pro-preview-0514") # Use an appropriate Gemini model for ADK

def create_prediction_market_agent():
    # This is a conceptual example, actual ADK setup involves defining specific flows and tools
    # You would define your agent's schema and actions through Vertex AI Console or SDK configuration.
    pass # Implement ADK agent setup here

# Example of multimodal input for a Gemini model call within ADK context
# You'll adapt this for specific ADK tools/actions
# response = model.generate_content([
#     Part.from_text("Recent news about candidate A:"),
#     Part.from_uri(uri="gs://your-bucket/news_image.jpg", mime_type="image/jpeg"),
#     Part.from_text("Market sentiment: bullish for A.")
# ])
```

Begin by structuring your ADK agent to define a tool for `fetch_market_data` from your simulated API and another for `analyze_news_sentiment` using Claude Opus 4.1.