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This capability allows users to define functions using a schema that can be called across multiple AI model providers. It employs a registry pattern to manage function definitions and their corresponding API calls, enabling seamless integration with various model endpoints. The architecture is designed to facilitate easy switching between providers without altering the core application logic, making it highly flexible and adaptable for developers.

This capability enables the server to switch between different AI models based on the context of the request. It analyzes incoming requests and determines the most suitable model to handle the task, leveraging a context-aware routing mechanism. This design allows for optimized performance by utilizing the strengths of each model for specific tasks, enhancing the overall user experience.

This capability orchestrates multiple API calls in real-time, allowing for complex workflows that involve interactions with various AI services. It uses an event-driven architecture to manage asynchronous API requests, ensuring that responses are handled efficiently and in the correct order. This design pattern enables developers to create sophisticated applications that require multiple data sources and processing steps.