On Architecture of LLM agents

Dmitry Namiot, Eugene Ilyushin

Abstract


The paper considers the architecture of agents for Artificial Intelligence systems. The word "agent" has become the topic of 2024 for such systems. Agent-based Artificial Intelligence is considered as the next step in the development of generative models. Accordingly, agents for large language models (base models) are one of the most rapidly developing research areas. An artificial intelligence agent is a program (software) that can collect data and, based on it, independently perform tasks to achieve predetermined goals. To perform tasks, agents use one or more language models. Agents can be considered as a logical step in helping developers create workflows (implement business models) using large language (base) models. In terms of collecting (analyzing) information, agents can be compared with long-known mashups (web mashups, for example), and in terms of performing any actions - with software robots. Large language models today can contain built-in support for some workflows. An alternative is various kinds of frameworks that are designed to simplify the process of creating agents

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References


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