> ## Documentation Index
> Fetch the complete documentation index at: https://doc.rapida.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Google Vertex AI

> Google Vertex AI is a fully-managed, unified AI development platform that provides access to Google's advanced models with enterprise features.

## Getting Started

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

## Supported Models

Google Vertex AI provides access to multiple advanced models:

| Model Name         | Type      | Description                                        |
| ------------------ | --------- | -------------------------------------------------- |
| gemini-2.5-pro     | Text      | Latest Gemini Pro model with advanced capabilities |
| gemini-2.5-flash   | Text      | Fast Gemini 2.5 model for efficient processing     |
| gemini-2.0-flash   | Text      | Gemini 2.0 Flash for optimized performance         |
| claude-3.5-sonnet  | Text      | Anthropic's Claude 3.5 Sonnet via Vertex AI        |
| llama-2-70b        | Text      | Meta's Llama 2 70B model for open-source users     |
| mistral-large      | Text      | Mistral's large language model                     |
| text-embedding-004 | Embedding | Latest Vertex AI embedding model                   |

Note: Available models may vary by region. Check Vertex AI documentation for the complete list.

## 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

# Setting Up Provider Credentials

<Steps>
  <Step title="Access the Integrations Page">
    <img src="https://mintcdn.com/rapidaai/iFtJHOhZE0HHFT_Q/images/integration/providers/providers-and-models.png?fit=max&auto=format&n=iFtJHOhZE0HHFT_Q&q=85&s=1aa112ebaf44541a92bcac925df62cf8" alt="Integrations Page" width="3600" height="2024" data-path="images/integration/providers/providers-and-models.png" />

    Navigate 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.
  </Step>

  <Step title="Select Google Vertex AI">
    On the Integrations page, find the Google Vertex AI provider card.

    Click the "Setup Credential" button for Google Vertex AI.
  </Step>

  <Step title="Create Provider Credential">
    <img src="https://mintlify.s3.us-west-1.amazonaws.com/rapidaai/images/integration/providers/vertexai_key.png" alt="Create Provider Credential" />

    A 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
  </Step>

  <Step title="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
  </Step>
</Steps>

Your Google Vertex AI provider credential is now set up and ready to use with the integration system.

## 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](https://cloud.google.com/vertex-ai/docs).