The AI-Native Tool Calling Framework addresses the challenges faced by modern AI agents in efficiently interacting with APIs. Current systems often result in overwhelmingly large tool responses that clutter the LLM context and limit developer control over which data is utilized. This results in difficulties for developers when mapping diverse APIs to AI agents. Toolflow provides a solution by acting as a middleware layer that connects APIs and tools to LLM agents. It enables minimal context payloads to filter necessary data, features a composable tool registry for modular definitions, and offers customizable modes (Light, Full, AI Filter, Custom) for data retrieval. Toolflow is designed to integrate seamlessly with existing frameworks like Langchain, Flowise, and AutoGen, providing plug-and-play TypeScript packages for runtime, registry, and types. This approach allows developers to create intelligent agents that efficiently manage API interactions while maintaining control over the data being processed.
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