== Google Vertex AI Sink Kamelet Description

=== Authentication

This Kamelet uses Google Cloud service account authentication. The service account key is optional - if not provided, the Kamelet will use Application Default Credentials (ADC).

If you provide a service account key, it must be base64-encoded. Ensure that the service account has the `aiplatform.endpoints.predict` permission (typically granted through the `Vertex AI User` role).

=== Required Configuration

- **Project ID**: The Google Cloud Project ID
- **Location**: The Google Cloud region where Vertex AI models are available (e.g., `us-central1`)
- **Model ID**: The model identifier to use for predictions (e.g., `gemini-2.5-pro`)

=== Optional Configuration

- **Service Account Key**: Base64-encoded service account credentials
- **Operation**: The operation to perform (default: `generateText`). Supported operations are `generateText`, `generateChat`, `generateImage`, `generateEmbeddings`, `generateCode`, `generateMultimodal`, and `rawPredict`
- **Temperature**: Controls randomness in generation (0.0 to 1.0)
- **Max Output Tokens**: Maximum number of tokens to generate in the response
- **Top P**: Nucleus sampling parameter (0.0 to 1.0)
- **Top K**: Only sample from the top K options for each subsequent token

=== Content Generation

The Kamelet sends the message body as a prompt to the specified Google Vertex AI model and returns the generated content. It supports Google native models (Gemini, Imagen) as well as partner models (Claude, Llama, Mistral) through the `rawPredict` operation.
