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ReDel: A Toolkit for LLM-Powered Recursive Multi-Agent Systems

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arxiv 2408.02248 v2 pith:7PO4QRYQ submitted 2024-08-05 cs.CL cs.MAcs.SE

classification cs.CLcs.MAcs.SE
keywords systemsmulti-agentredelrecursivedelegationmodelstaskstoolkit
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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  1. Adaptive Graph of Thoughts: Test-Time Adaptive Reasoning Unifying Chain, Tree, and Graph Structures

    cs.AI 2025-02 conditional novelty 5.0 of 10

    AGoT is a recursive graph-based prompting framework that decomposes LLM queries into nested subgraphs and reports large relative gains on some benchmarks, though headline GPQA gains rely on a shuffled subset.

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