ReDel: A Toolkit for LLM-Powered Recursive Multi-Agent Systems
원문 초록
Recently, there has been increasing interest in using Large Language Models (LLMs) to construct complex multi-agent systems to perform tasks such as compiling literature reviews, drafting consumer reports, and planning vacations. Many tools and libraries exist for helping create such systems, however none support recursive multi-agent systems -- where the models themselves flexibly decide when to delegate tasks and how to organize their delegation structure. In this work, we introduce ReDel: a toolkit for recursive multi-agent systems that supports custom tool-use, delegation schemes, event-based logging, and interactive replay in an easy-to-use web interface. We show that, using ReDel, we are able to easily identify potential areas of improvements through the visualization and debugging tools. Our code, documentation, and PyPI package are open-source and free to use under the MIT license at https://github.com/zhudotexe/redel.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
$τ^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment
Comparative Analysis of AI Agent Architectures for Entity Relationship Classification
ThinkTank: A Framework for Generalizing Domain-Specific AI Agent Systems into Universal Collaborative Intelligence Platforms
AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-Tuning
Will Agents Replace Us? Perceptions of Autonomous Multi-Agent AI
From Knowledge to Noise: CTIM-Rover and the Pitfalls of Episodic Memory in Software Engineering Agents
토론
이 논문과 연결된 포럼 글이 아직 없습니다.