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Foundation models, such as large language models (LLMs), have been widelyrecognised as transformative AI technologies due to their capabilities tounderstand and generate content, including plans with reasoning capabilities.Foundation model based agents derive their autonomy from the capabilities offoundation models, which enable them to autonomously break down a given goalinto a set of manageable tasks and orchestrate task execution to meet the goal.Despite the huge efforts put into building foundation model based agents, thearchitecture design of the agents has not yet been systematically explored.Also, while there are significant benefits of using agents for planning andexecution, there are serious considerations regarding responsible AI relatedsoftware quality attributes, such as security and accountability. Therefore,this paper presents a pattern-oriented reference architecture that serves asguidance when designing foundation model based agents. We evaluate thecompleteness and utility of the proposed reference architecture by mapping itto the architecture of two real-world agents.

Towards Responsible Generative AI: A Reference Architecture for Designing Foundation Model based Agents