LLM-Driven Intelligent Agent Architecture Diagram

This diagram illustrates the architecture of an intelligent agent driven by a large language model (LLM), covering the full workflow from user input to final output. It includes key processes such as intent understanding, task decomposition, planning, memory interaction, tool usage, verification, and feedback optimization. The framework highlights how short-term and long-term memory, tool execution, and evaluation mechanisms work together to support iterative reasoning and decision-making. It provides a clear view of how complex tasks are broken down, processed, and refined through multiple stages. It is suitable for AI engineers, product managers, and researchers working on agent systems, LLM applications, or intelligent automation. For more flexible diagram design or customization, it can also be enhanced using EdrawMax.