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This capability enables the server to execute functions based on a defined schema that integrates with multiple model providers. It uses a modular architecture that allows easy addition of new providers, ensuring that developers can switch between models seamlessly. The schema acts as a contract, ensuring that inputs and outputs are consistent across different integrations, which simplifies the development process and enhances interoperability.

This capability manages contextual information across multiple interactions with AI models, ensuring that each request retains relevant state from previous interactions. It employs a lightweight context storage mechanism that can be easily queried and updated, allowing for a more coherent conversation flow and improved user experience. This approach minimizes the need for repeated context inputs, streamlining the interaction process.

This capability orchestrates API calls to various AI models based on user-defined workflows, allowing for complex interactions that can involve multiple models in a single request. It utilizes a pipeline architecture that enables the chaining of API calls, where the output of one model can be fed directly into another, facilitating advanced use cases like multi-step reasoning or data transformation.