Fewshot or few-shot learning refers to a machine learning paradigm where a model is trained to make accurate predictions with only a small number of examples per class. This approach enables the model to generalize well to new, unseen data despite having limited training data.

The information in the Description / Fewshot field in "Agent" will be used by the system to determine which function (tool) will be utilized based on the provided input.

You can modify the Description / Fewshot and save if you'd like to customize your logic.