harpa

Harpa implements a schema-based function orchestration mechanism that allows users to define and manage multiple function calls in a structured manner. This capability leverages the Model Context Protocol (MCP) to ensure that functions can be invoked with the correct context and parameters, enabling seamless integration with various AI models. The architecture supports dynamic function registration and invocation, making it adaptable to different use cases and model types.

Harpa provides context-aware API integration that allows users to call external APIs while maintaining the context of the conversation or task at hand. This is achieved through a middleware layer that captures context from user interactions and passes it along with API requests, ensuring that responses are relevant and tailored to the ongoing dialogue. The system uses a combination of state management and context tracking to enhance the user experience.

Harpa supports dynamic model switching, allowing users to change the AI model being used for a task without restarting the application. This is facilitated by a modular architecture that decouples model selection from execution, enabling real-time adjustments based on user needs or performance metrics. The system can automatically select the most appropriate model based on predefined criteria or user input.

Harpa enables multi-provider function calling, allowing users to invoke functions from different AI service providers within a single workflow. This capability is built on the MCP framework, which abstracts the underlying service calls and provides a unified interface for function invocation. Users can define functions that leverage capabilities from various AI models, facilitating complex workflows that span multiple providers.