How do LLM agents work? - explanation using graphs

The article delves into the application of language models as LLM agents, focusing on their internal structure represented as graphs. The author illustrates how computational agents interpret and process data by transforming information into functional graphs. This approach defines how language models can be employed for complex tasks such as data analysis and establishing relationships between different elements. A significant aspect highlighted is the importance of graphs as tools that allow for a better understanding and modeling of complex systems. Through this methodology, programmers and researchers can create more efficient solutions leveraging the power of LLM agents for automation and analysis of large datasets. The piece concludes with reflections on the future directions of LLM agents and their potential impact across various industries.