Google Agent Development Kit integrated with ZenML
Google ADK lets you build Gemini-powered agents with a simple callable interface and built-in tools; connecting ADK to ZenML wraps those agents in reproducible pipelines with artifact tracking, observability, and an easy path from local experiments to production.
Features with ZenML
- Pipeline orchestration. Run Google ADK agents as ZenML steps inside reproducible pipelines.
- Artifact management. Capture agent inputs and outputs for lineage, versioning, and auditability.
- Evaluation ready. Add post-run checks or eval steps to monitor quality over time.
- Infrastructure agnostic. Scale from local runs to Kubernetes, Airflow, and other ZenML stacks.
- Composable workflows. Combine agents with retrieval, evals, and deployment steps in one DAG.
Main Features
- Gemini-powered agents. Build on Google’s latest models through ADK.
- Simple callable interface. Invoke agents directly or through common
run and execute methods. - Built-in tools. Integrate calculations and custom tools inside agent workflows.
How to use ZenML with
Google ADK Agent
from zenml import ExternalArtifact, pipeline, step
from adk_agent import root_agent
@step
def run_adk(query: str) -> str:
return str(root_agent.run(query))
@pipeline
def google_adk_pipeline() -> str:
q = ExternalArtifact(value="What's the weather like in Tokyo?")
return run_adk(q.value)
if __name__ == "__main__":
print(google_adk_pipeline())
Additional Resources
ZenML Agent Framework Integrations (GitHub)
ZenML Documentation
Google ADK Documentation
