Chris Christiansen
ee50f8318e
Adds the core logic for the OPAX agent, including the main agent file, a deployment script, and an MCP client. This provides the foundation for the new agent-based architecture.
40 lines
1.4 KiB
Python
40 lines
1.4 KiB
Python
#!/usr/bin/env python3
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import argparse
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import sys
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from pathlib import Path
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import vertexai
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from vertexai import agent_engines
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def deploy(project, region, display_name, staging_bucket):
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print(f"Initialiserer Vertex AI: project={project}, region={region}")
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vertexai.init(project=project, location=region, staging_bucket=staging_bucket)
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base_dir = Path(__file__).resolve().parent
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sys.path.insert(0, str(base_dir))
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import agent as _agent_module
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root_agent = _agent_module.root_agent
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print(f"Deployer agent '{display_name}'...")
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remote = agent_engines.create(
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root_agent,
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requirements=[
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"google-cloud-aiplatform[adk,agent_engines]>=1.157.0",
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"google-adk>=2.2.0",
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"httpx>=0.27.0",
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"google-auth>=2.29.0",
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],
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extra_packages=[str(base_dir / "agent.py")],
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display_name=display_name,
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)
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print(f"\n✅ Agent deployet!\n Resource name: {remote.resource_name}")
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--project", default="propane-will-491900-m5")
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parser.add_argument("--region", default="us-central1")
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parser.add_argument("--display-name", default="jason-vauger-v12")
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parser.add_argument("--staging-bucket", default="gs://propane-will-491900-m5-agent-staging")
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args = parser.parse_args()
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deploy(args.project, args.region, args.display_name, args.staging_bucket)
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