Circuit-Agent: A Large Language Model Based Circuit Agent Framework for Analog/Mixed-signal Circuit Design Automation

Large Language Models (LLMs) have demonstrated remarkable capabilities across various domain tasks. Following this trend, this paper is dedicated to a new LLM-based design methodology for analog/mixed-signal (AMS) circuit design automation. The proposed LLM-based multi-agent circuit framework is capable of generating circuits based on given requirements. The framework leverages circuit-oriented retrieval-augmented generation (RAG) technology to retrieve specific circuit design knowledge and employs multi-agent collaboration. The proposed framework has been validated by designing fundamental AMS circuits, such as operational amplifiers (OPAMPs) and analog-to-digital converters (ADCs), which enhances the efficiency of AMS circuit design and promotes the development of AI-driven circuit design methodologies.