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Large language models (LLMs) have revolutionized the way we interact with AI, but they come with inherent limitations. While they excel at predicting and generating text based on their training data, they struggle with performing meaningful real-world tasks independently. This fundamental limitation led to the development of tool-augmented LLMs, which can interact with external services through APIs, enabling capabilities like web searches and file operations.
However, tool-based approaches bring their own set of challenges. While they…
