Configuring Google Vertex AI#

Google Vertex AI is supported for Gemini and Anthropic models.

1. Create the Google Application Default Credentials file and store it in a Kubernetes Secret. If your credentials are in a different location, update the filepath.

kubectl create secret generic kagent-google-creds -n kagent --from-file=~/.config/gcloud/application_default_credentials.json

2. For Gemini models: create a ModelConfig resource using the GeminiVertexAI provider that references the secret and key name, and specify the Gemini model you want to use. Note the projectID and location are required:

apiVersion: kagent.dev/v1alpha2
kind: ModelConfig
metadata:
  name: gemini-model-config-vertexai
  namespace: kagent
spec:
  apiKeySecret: kagent-google-creds
  apiKeySecretKey: google_creds.json
  model: gemini-2.0-flash-lite
  provider: GeminiVertexAI
  geminiVertexAI:
    projectID: kagent-dev
    location: us-west1
    maxOutputTokens: 1000

3. For Anthropic models: create a ModelConfig resource using the AnthropicVertexAI provider that references the secret and key name, and specify the Anthropic model you want to use. Note the projectID and location are required:

apiVersion: kagent.dev/v1alpha2
kind: ModelConfig
metadata:
  name: anthropic-model-config-vertexai
  namespace: kagent
spec:
  apiKeySecret: kagent-google-creds
  apiKeySecretKey: google_creds.json
  model: claude-sonnet-4@20250514
  provider: AnthropicVertexAI
  anthropicVertexAI:
    projectID: kagent-dev
    location: us-east5