For the complete documentation index, see llms.txt. Markdown versions of all docs pages are available by appending .md to any docs URL.

Configure kagent to use Google Gemini models through the Google AI Studio API.

The Gemini provider reaches Google’s Gemini models through the Google AI Studio API, authenticating with a single API key. To reach Gemini through Google Cloud instead, see Google Vertex AI.

Before you begin

Make sure that your Google Cloud account has a project with the Gemini API enabled.

Create the ModelConfig

1. Get an API key from Google AI Studio, and save it as an environment variable.

   export GOOGLE_API_KEY=<your_api_key>

2. Create a Kubernetes Secret that stores the API key. Create it in the same namespace as the AgentTemplates that use it, such as kagent.

   kubectl create secret generic kagent-gemini -n kagent --from-literal GOOGLE_API_KEY=$GOOGLE_API_KEY

3. Create a ModelConfig that references the Secret.

   kubectl apply -f - <<EOF
   apiVersion: kagent.dev/v1alpha3
   kind: ModelConfig
   metadata:
     name: gemini-model-config
     namespace: kagent
   spec:
     apiKeySecret: kagent-gemini
     apiKeySecretKey: GOOGLE_API_KEY
     model: gemini-2.5-flash
     provider: Gemini
     gemini: {}
   EOF

   Field	Description
   apiKeySecret	The name of the Kubernetes Secret that stores the API key, in the same namespace as this ModelConfig.
   apiKeySecretKey	The key within that Secret that holds the API key.
   model	The model to use. For the available models, see the Gemini API docs.
   provider	The provider to use, Gemini.
   gemini	Settings that only the Gemini provider takes. An empty block is valid.

Gemini provider settings

The gemini block takes one optional setting. For its type, default, and validation rules, see the API reference.

Use the ModelConfig

Reference the ModelConfig by name from an AgentTemplate in the same namespace.

spec:
  modelConfig:
    name: gemini-model-config

Next steps