Model Container

The Model Container is a core component of the Four-Sided Triangle framework that manages the lifecycle and interactions of various specialized models.

Overview

The model container provides a centralized system for:

• Model registration and initialization
• Dependency injection for model components
• Resource management and cleanup
• Model state persistence
• Inter-model communication

Components

Container Class

The main ModelContainer class provides:

• Model registration and retrieval
• Dependency resolution
• Configuration management
• Resource allocation and deallocation
• State management

Model Interfaces

The container works with models that implement standard interfaces:

• BaseModel: Common functionality for all models
• QueryProcessor: Interface for query processing models
• DomainExpert: Interface for specialized domain models
• ResponseGenerator: Interface for response generation models

Configuration

Models are configured through:

• YAML configuration files
• Environment variables
• Runtime parameters
• Dynamic configuration updates

Usage

Model Registration

container = ModelContainer()
container.register(QueryProcessorModel)
container.register(DomainExpertModel)
container.register(ResponseGeneratorModel)

Model Retrieval

query_processor = container.get(QueryProcessorModel)
domain_expert = container.get(DomainExpertModel)

Resource Management

with container.get_context():
    # Models are automatically initialized and cleaned up
    model = container.get(SomeModel)
    result = model.process()

Best Practices

1. Always use dependency injection through the container
2. Implement proper cleanup in model destructors
3. Use context managers for resource management
4. Keep model configurations separate from code
5. Follow the interface contracts strictly

Error Handling

The container provides robust error handling for:

• Missing dependencies
• Configuration errors
• Resource allocation failures
• Model initialization errors
• Runtime exceptions

Performance Considerations

• Models are lazy-loaded by default
• Resources are shared when possible
• Memory usage is optimized
• Thread safety is ensured for concurrent access