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Getting Started

To integrate Google Vertex AI with your Rapida application, follow these steps:

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Supported Models

Google Vertex AI provides access to multiple advanced models: Note: Available models may vary by region. Check Vertex AI documentation for the complete list.

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Prerequisites

  • Have a Google Cloud account
  • Create a new Google Cloud Project or use an existing one
  • Enable the Vertex AI API in your Google Cloud Project
  • Create a service account with Vertex AI permissions
  • Download the service account key (JSON file)
  • Set up your Project ID and Region

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Setting Up Provider Credentials

1

Access the Integrations Page

Integrations PageNavigate to the “Integration > Models” page. Here you’ll see a grid of various AI model providers including Google Vertex AI, Azure OpenAI, Anthropic, and more.
2

Select Google Vertex AI

On the Integrations page, find the Google Vertex AI provider card.Click the “Setup Credential” button for Google Vertex AI.
3

Create Provider Credential

Create Provider CredentialA modal window will appear titled “Create provider credential”. Follow these steps:
  1. Select “Google Vertex AI” from the dropdown (if not already selected)
  2. Enter a Key Name: Assign a unique name to this provider key for easy identification
  3. Enter Project ID: Input your Google Cloud Project ID
  4. Enter Region: Specify the region where Vertex AI is available (e.g., us-central1)
  5. Enter Service Account Key: Paste the entire JSON content of your service account key
  6. Click “Configure” to save the credential
4

Verify Credential Setup

After setting up the credential, you can verify it’s been added:
  1. The Google Vertex AI provider card should now show “Connected”
  2. If you click on the provider, you’ll see a “View provider credential” modal
  3. This modal displays the credential name, when it was last updated, and options to delete or close
Your Google Vertex AI provider credential is now set up and ready to use with the integration system.

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Integration Features

  • Enterprise-Grade: Full enterprise features and compliance
  • Multi-Model Support: Access to Google’s latest models and third-party models
  • Model Garden: Fine-tune and deploy custom models
  • Monitoring: Built-in monitoring and logging for production deployments
  • Scalability: Automatic scaling for your AI workloads
For more information, visit the Google Vertex AI documentation.