Vertex AI
Configure Google Cloud Vertex AI to access Google's foundation models through Braintrust.
Authentication
Choose between two authentication methods:
- Access token: Use a Vertex AI access token for authentication
- Service account key: Use a service account key JSON file for authentication
Configuration
| Field | Description |
|---|---|
| Project String | Required. Your Google Cloud Project ID where Vertex AI is enabled. |
Authentication typeaccess_token | service_account_key | Required. Choose between access token or service account key authentication. Documentation |
| Secret JSON String | Required if using service_account_key auth type. The service account key JSON content. Documentation |
| API base URL String | Optional. Custom API endpoint URL if using a different Vertex AI endpoint. Documentation. Default is https://{location}-aiplatform.googleapis.com. |
Models
Popular Vertex AI models include:
- Gemini 1.5 Pro (
gemini-1.5-pro) - Gemini 1.5 Flash (
gemini-1.5-flash) - PaLM 2 (
text-bison) - Codey (
code-bison)
Setup requirements
- Enable Vertex AI API: Ensure the Vertex AI API is enabled in your Google Cloud project
- Service account permissions: If using service account authentication, ensure the service account has the
AI Platform Developerrole - Quotas: Check your project's Vertex AI quotas and limits