With the rapid development of large model technology, agent technology is increasingly applied in various fields, profoundly changing people’s work and lifestyle. In complex and dynamic system environments, multiple agents complete complex tasks that a single agent cannot accomplish through division of labor and collaboration. This article explores the comprehensive application of LangGraph and CrewAI. LangGraph improves the efficiency of information transmission through a graphical architecture, while CrewAI enhances team collaboration capabilities and system performance through intelligent task allocation and resource management. The main research contents of this study include: (1) designing an agent architecture based on LangGraph for precise control; (2) enhancing the ability of agents based on CrewAI to complete diversified tasks. This research aims to explore the applications of LangGraph and CrewAI in multi-agent systems, providing new perspectives for the future development of agent technology and promoting technological progress and application innovation in the field of intelligent agents with large models.
Paper link: http://arxiv.org/abs/2411.18241v1Recommended Long Reads (written bit by bit by myself, including practical code and videos)
RAG Sharing – Q&A (includes practical video at the end)
RAG Sharing – Q&A (includes practical video at the end)
RAG Sharing – Q&A (includes practical video at the end)