AI GoogleVertexAI
CertifiedUse Google Vertex AI models
AI GoogleVertexAI
Use Google Vertex AI models
Calls Vertex AI Gemini chat, embeddings, or images using project, location, and endpoint settings. Authenticates like the GCP plugin: serviceAccount when set, otherwise Application Default Credentials, optionally impersonating impersonatedServiceAccount; ensure response formats are supported by the selected model/region. Tool calls work on Gemini 3 models: the thought_signature returned with each function call is sent back automatically on the following turns. Thinking is left to the model default unless thinkingEnabled or thinkingBudgetTokens is set.
type: io.kestra.plugin.ai.provider.GoogleVertexAIExamples
Chat completion with Google Vertex AI
id: chat_completion
namespace: company.ai
inputs:
- id: prompt
type: STRING
tasks:
- id: chat_completion
type: io.kestra.plugin.ai.completion.ChatCompletion
provider:
type: io.kestra.plugin.ai.provider.GoogleVertexAI
modelName: gemini-3.5-flash-lite
location: your-google-cloud-region
projectId: your-google-cloud-project-id
messages:
- type: SYSTEM
content: You are a helpful assistant, answer concisely, avoid overly casual language or unnecessary verbosity.
- type: USER
content: "{{ inputs.prompt }}"
Chat completion with Google Vertex AI using a service account
id: chat_completion_service_account
namespace: company.ai
tasks:
- id: chat_completion
type: io.kestra.plugin.ai.completion.ChatCompletion
provider:
type: io.kestra.plugin.ai.provider.GoogleVertexAI
modelName: gemini-3.5-flash-lite
location: your-google-cloud-region
projectId: your-google-cloud-project-id
serviceAccount: "{{ secret('GCP_SERVICE_ACCOUNT_JSON') }}"
messages:
- type: USER
content: What is the capital of France?
Properties
location *string
Project location
Google Cloud region hosting the Vertex AI model, or global to use the global endpoint aiplatform.googleapis.com. No default: this property is required for chat models.
baseUrl string
Base URL
Custom base URL overriding the provider's default endpoint. Useful for enterprise gateways, proxies, self-hosted deployments, or test doubles such as WireMock. Defaults to the provider's public endpoint.
caPem string
CA PEM certificate content
PEM-encoded certificate authority chain, as text, used to verify the TLS certificate presented by a custom endpoint. Not set by default, in which case the JVM's default trust store is used.
clientPem string
Client PEM certificate content
PEM-encoded client certificate and private key, as text, used for mutual-TLS authentication against enterprise AI endpoints. Not set by default, in which case the default HTTP client is used.
endpoint string
Endpoint URL
Vertex AI API endpoint for image and embedding models, as host: port or a full https:// URL. Not set by default, in which case the endpoint is derived from location (aiplatform.googleapis.com for global). Must not be set for chat models, which always use Gemini.
impersonatedServiceAccount string
Service account to impersonate
Email of the service account to impersonate. Not supported for image models.
modelName string
Model name
projectId string
Project ID
Google Cloud project ID that owns the Vertex AI resources. When not set, it is taken from the service account credentials.
scopes array
["https://www.googleapis.com/auth/cloud-platform"]OAuth scopes
OAuth scopes requested for the credentials. Defaults to https://www.googleapis.com/auth/cloud-platform. Not supported for image models, which always use Application Default Credentials with their default scopes.
serviceAccount string
Service account JSON key
Content of a Google Cloud service account JSON key. When not set, Application Default Credentials are used. Not supported for image models, which always use Application Default Credentials.
