#!/usr/bin/env python3
import argparse
import sys
from pathlib import Path
import vertexai
from vertexai import agent_engines

def deploy(project, region, display_name, staging_bucket):
    print(f"Initialiserer Vertex AI: project={project}, region={region}")
    vertexai.init(project=project, location=region, staging_bucket=staging_bucket)

    base_dir = Path(__file__).resolve().parent
    sys.path.insert(0, str(base_dir))

    import agent as _agent_module
    root_agent = _agent_module.root_agent

    print(f"Deployer agent '{display_name}'...")
    remote = agent_engines.create(
        root_agent,
        requirements=[
            "google-cloud-aiplatform[adk,agent_engines]>=1.157.0",
            "google-adk>=2.2.0",
            "httpx>=0.27.0",
            "google-auth>=2.29.0",
        ],
        extra_packages=[str(base_dir / "agent.py")],
        display_name=display_name,
    )
    print(f"\n✅ Agent deployet!\n   Resource name: {remote.resource_name}")

if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("--project", default="propane-will-491900-m5")
    parser.add_argument("--region", default="us-central1")
    parser.add_argument("--display-name", default="jason-vauger-v12")
    parser.add_argument("--staging-bucket", default="gs://propane-will-491900-m5-agent-staging")
    args = parser.parse_args()
    deploy(args.project, args.region, args.display_name, args.staging_bucket)