What is an agent?
The fundamental concept behind an agent in the context of generative AI applications is the use of a language model as a reasoning mechanism to select a sequence of actions to perform to achieve a goal.
The core distinction between these agent-based systems and traditional generative AI applications lies in their approach to task execution. Traditional generative AI applications usually rely on predefined chains of actions, executing them sequentially in a rigid manner. This limits their adaptability to user input or varying contexts.
Conversely, agent-based systems can dynamically interpret user intent and autonomously select the most appropriate actions and their order of execution. This flexibility allows them to handle complex tasks that require adaptability and decision-making capabilities.
Components of an agent
An agent consists of several essential components that collaborate to enable its intelligent behavior. The following diagram shows the components...
