Update wiki Home page for google-vertexai-sink
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# Deploy the Project on CamelX Platform
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# Google Vertex AI Sink
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Deploy on CamelX Platform in three steps
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Send data to Google Vertex AI for generating content with generative AI models.
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## Step 1: Create a release
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From the project space, click on **"Create a release"**
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## Metadata
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The new version is automatically available in the list
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| Property | Value |
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|----------|-------|
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| Type | sink |
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| Group | Google Vertex AI |
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| Namespace | GCP |
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| Support Level | Preview |
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| Provider | Apache Software Foundation |
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## Step 2: Deploy
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Click on **"Deploy"**
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## Properties
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- **Version:** Select the desired release
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- **Environment:** Choose `Development`, `Staging`, or `Production`
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- **Configuration:** Select the configuration source
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- **Resources:** Set CPU and Memory
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| Name | Type | Required | Default | Description |
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|------|------|----------|---------|-------------|
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| `projectId` | string | ✓ | | The Google Cloud Project ID. |
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| `location` | string | ✓ | | The Google Cloud region (e.g., us-central1). |
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| `modelId` | string | ✓ | | The Model ID to use for predictions (e.g., gemini-2.5-pro). |
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| `serviceAccountKey` | binary | | | The service account key to use as credentials for the Vertex AI client. You must encode this value in base64. |
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| `operation` | string | | `generateText` | The operation to perform. |
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| `temperature` | string | | | Controls randomness in generation. Lower values make output more deterministic. Range 0.0 to 1.0. |
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| `maxOutputTokens` | string | | | Maximum number of tokens to generate in the response. |
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| `topP` | string | | | Nucleus sampling parameter. Considers tokens with top_p probability mass. Range 0.0 to 1.0. |
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| `topK` | string | | | Only sample from the top K options for each subsequent token. |
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## Step 3: Expose
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Enable **"Expose"**
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## Dependencies
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Choose an **API Gateway** (Internal, Public, etc.)
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- `camel:core`
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- `camel:kamelet`
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- `camel:google-vertexai`
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