vital-agent-container-sdk 0.1.15

Vital Agent Container SDK

Vital Agent Container Python SDK

A Python SDK that provides infrastructure components for building AI agent applications with WebSocket-based communication and asynchronous message processing.

Features

• 🚀 FastAPI-based WebSocket server with real-time communication
• 🔄 Asynchronous message processing with task management
• 🛡️ Production-ready with structured logging and health checks
• 🔌 Plugin architecture for custom message handlers
• ☁️ Cloud-ready with flexible deployment options
• 📊 Streaming support for real-time data flows
• ⚡ Task cancellation and interruption handling

Installation

Install from PyPI (when published)

pip install vital-agent-container-sdk

Install from Source

Using Conda (Recommended for Development)

# Clone the repository
git clone https://github.com/vital-ai/vital-agent-container-python.git
cd vital-agent-container-python

# Create environment from environment.yml
conda env create -f environment.yml
conda activate vital-agent-container

# Install in development mode
pip install -e .

Using pip

# Clone the repository
git clone https://github.com/vital-ai/vital-agent-container-python.git
cd vital-agent-container-python

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode
pip install -e .

Configuration

1. Copy the configuration template:

   cp agent_config.yaml.template agent_config.yaml
   

2. Copy the environment template:

   cp .env.example .env
   

3. Update both files with your specific configuration.

Usage

Basic Implementation

Create a custom message handler by implementing the AIMPMessageHandlerInf interface:

from vital_agent_container.handler.aimp_message_handler_inf import AIMPMessageHandlerInf
from vital_agent_container.agent_container_app import AgentContainerApp

class MyMessageHandler(AIMPMessageHandlerInf):
    async def process_message(self, config, client, websocket, data, started_event):
        # Your custom message processing logic here
        # Process the incoming message data
        message = json.loads(data)
        
        # Perform your agent logic
        response = await self.handle_agent_request(message)
        
        # Send response back through websocket
        await websocket.send_text(json.dumps(response))
        
        # Signal that processing has started
        started_event.set()
    
    async def handle_agent_request(self, message):
        # Implement your specific agent logic here
        return {"status": "processed", "result": "Agent response"}

# In your application's main module:
def create_agent_app():
    handler = MyMessageHandler()
    return AgentContainerApp(handler, app_home=".")

# Your application can then run the agent container
if __name__ == "__main__":
    import uvicorn
    app = create_agent_app()
    uvicorn.run(app, host="0.0.0.0", port=8000)

Message Format

Applications using this library will receive messages in the following format through the WebSocket connection:

[{
  "type": "message",
  "http://vital.ai/ontology/vital-aimp#hasIntent": "process",
  "content": "Your message content"
}]

Your message handler implementation should parse and respond to these messages according to your agent's logic.

Development

Setup Development Environment

# Install with development dependencies
make install-dev

# Or manually
pip install -e ".[dev]"
pre-commit install

Available Make Commands

make help           # Show available commands
make test           # Run tests
make test-cov       # Run tests with coverage
make lint           # Run linting
make format         # Format code
make build          # Build package

Code Quality

This project uses:

• Black for code formatting
• isort for import sorting
• flake8 for linting
• mypy for type checking
• pre-commit hooks for automated checks

API Endpoints

• GET /health - Health check endpoint
• WebSocket /ws - Main WebSocket endpoint for message processing

Architecture

├── vital_agent_container/
│   ├── agent_container_app.py      # Main FastAPI application
│   ├── handler/                    # Message handler interfaces
│   ├── processor/                  # Message processing logic
│   ├── tasks/                      # Task management
│   ├── streaming/                  # Streaming response handling
│   └── utils/                      # Utility functions
├── agent_config.yaml               # Agent configuration
├── environment.yml                 # Conda environment
└── pyproject.toml                  # Modern Python project config

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Make your changes and add tests
4. Run the test suite: make test
5. Format your code: make format
6. Submit a pull request

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Support

For questions and support, please open an issue on the GitHub repository.