vertex_ai

Vertex AI

The same hello-world flow as hello_world, but pointed at Vertex AI instead of the Gemini Developer API. The only difference is configuration: both the worker's genai.Client and the workflow's TemporalAsyncClient set vertexai=True with a Google Cloud project and location. The vertexai setting must match on both sides.

Requires Google Cloud credentials, not a Gemini API key. Authenticate with Application Default Credentials (gcloud auth application-default login) or a service-account key (GOOGLE_APPLICATION_CREDENTIALS). This sample has no automated test.

Configuration

Variable	Description
GOOGLE_CLOUD_PROJECT	Your Google Cloud project ID (required)
GOOGLE_CLOUD_LOCATION	Region, e.g. us-central1 (defaults to us-central1)

What This Sample Demonstrates

• genai.Client(vertexai=True, project=..., location=...) on the worker
• TemporalAsyncClient(vertexai=True, project=..., location=...) in the workflow
• Passing project/location as workflow arguments to keep the workflow deterministic

Running the Sample

Prerequisites: install dependencies, configure GCP credentials, set GOOGLE_CLOUD_PROJECT, and start a Temporal dev server. See the suite README.

# Terminal 1
uv run google_genai/vertex_ai/run_worker.py

# Terminal 2
uv run google_genai/vertex_ai/run_workflow.py

Files

File	Description
workflow.py	VertexAIWorkflow — generate_content via Vertex AI
run_worker.py	Registers a Vertex-configured GoogleGenAIPlugin
run_workflow.py	Reads project/location from env and executes the workflow