Anvia

Appearance

Vertex AI ​

Use Vertex mode when Gemini is provisioned through a Google Cloud project. GeminiClient still returns the same Anvia model contracts; only client construction and authentication change.

Configure Application Default Credentials ​

Set the project, location, and local credential source in the server environment:

sh
export GOOGLE_CLOUD_PROJECT="my-gcp-project"
export GOOGLE_VERTEX_LOCATION="us-central1"
export GOOGLE_APPLICATION_CREDENTIALS="/absolute/path/service-account.json"

Create the client with explicit project and location values:

ts
import { GeminiClient } from '@anvia/gemini'

export const vertexGemini = new GeminiClient({
  vertexai: true,
  project: process.env.GOOGLE_CLOUD_PROJECT,
  location: process.env.GOOGLE_VERTEX_LOCATION ?? 'us-central1',
})

export const model = vertexGemini.completionModel(
  'gemini-2.5-flash',
)

When googleAuthOptions is omitted, the official Google SDK uses Application Default Credentials. In Google-hosted environments, prefer the workload's attached service identity over a long-lived JSON key.

The constructor requires non-empty project and location values. Validate both at startup instead of relying on implicit environment discovery inside the adapter.

Use explicit Google authentication ​

Pass the Google SDK's googleAuthOptions when the application owns a trusted credential object or preconfigured authentication behavior:

ts
const vertexGemini = new GeminiClient({
  vertexai: true,
  project: 'my-gcp-project',
  location: 'us-central1',
  googleAuthOptions: {
    credentials: serviceAccountJson,
  },
})

Validate externally supplied credential configuration and never commit service-account JSON or private keys. Use short-lived credentials or workload identity where possible.

Keep Vertex concerns at the model boundary ​

ts
import type { CompletionModel } from '@anvia/core'

export function createSupportModel(): CompletionModel {
  return vertexGemini.completionModel('gemini-2.5-flash')
}

Agent and pipeline code can now depend on CompletionModel rather than project IDs, IAM details, or Google SDK types.

Vertex-specific checks ​

  • Verify that the model is available in the configured project and location.
  • Grant the workload only the IAM permissions required for the enabled model operations.
  • Test completion, streaming, embeddings, media, and model listing separately when the product uses them.
  • Record the Google Cloud project, region, provider, and model as safe operational metadata.
  • Treat quota, safety policy, and model availability as deployment-specific behavior.

Local ADC success does not prove that the production workload identity can use the selected model. Run an authenticated smoke test in every deployed environment.

Built for Anvia.