A production-ready AI agent system built with Google Cloud's Vertex AI Agent Engine. This project demonstrates deploying and managing AI agents at scale using Google Cloud infrastructure.
- Fully managed AI agent deployment
- Scalable cloud infrastructure
- Session management and persistence
- Secure authentication via Google Cloud IAM
- Professional monitoring and logging
- REST API endpoints for agent interaction
- Python 3.9+
- Poetry for dependency management
- Google Cloud CLI
- Google Cloud project with Agent Engine API enabled
- Proper IAM permissions
# Clone the repository
git clone [your-repo-url]
cd agent-system
# Install dependencies
poetry install
# Configure Google Cloud
gcloud auth login
gcloud config set project agent-101-457716
Set up your environment variables:
GOOGLE_CLOUD_PROJECT=agent-101-457716
GOOGLE_CLOUD_LOCATION=us-central1
GOOGLE_CLOUD_STAGING_BUCKET=agent-101-staging
Deploy your agent to Agent Engine:
poetry run python deployment/remote.py --create
poetry run python deployment/remote.py --create_session --resource_id=687792901685510144
poetry run python deployment/remote.py --send \
--resource_id=687792901685510144 \
--session_id=YOUR_SESSION_ID \
--message="Your message here"
agent-system/
├── deployment/
│ ├── remote.py # Deployment management
│ └── utils.py # Utility functions
├── agent/
│ ├── core.py # Core agent logic
│ └── tools.py # Agent tools
├── tests/ # Test suite
├── poetry.lock # Lock file
└── pyproject.toml # Project configuration
Monitor your agent through Google Cloud Console:
- Cloud Monitoring for metrics
- Cloud Logging for logs
- Cloud Trace for performance analysis
- Authentication via Google Cloud IAM
- Encrypted communication
- Secure session management
- Rate limiting and quota management
[Your chosen license]
[Your contribution guidelines]