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Paper · arXiv 2502.11271

OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning

Pan Lu, Bowen Chen, Sheng Liu, Rahul Thapa, Joseph Boen, James Zou

19 upvotesFebruary 16, 2025arXiv 预印本
AI 摘要

OctoTools, an open-source agentic framework, enhances complex reasoning across diverse tasks by utilizing tool cards, planning, and execution without additional training.

large language modelsLLMSOctoToolstool cardsplannerexecutorMathVistaMMLU-ProMedQAGAIA-TextGPT-4oAutoGenGPT-FunctionsLangChaintask planningtool usagemulti-step problem solving

Abstract

Solving complex reasoning tasks may involve visual understanding, domain knowledge retrieval, numerical calculation, and multi-step reasoning. Existing methods augment large language models (LLMs) with external tools but are restricted to specialized domains, limited tool types, or require additional training data. In this paper, we introduce OctoTools, a training-free, user-friendly, and easily extensible open-source agentic framework designed to tackle complex reasoning across diverse domains. OctoTools introduces standardized tool cards to encapsulate tool functionality, a planner for both high-level and low-level planning, and an executor to carry out tool usage. We validate OctoTools' generality across 16 diverse tasks (including MathVista, MMLU-Pro, MedQA, and GAIA-Text), achieving substantial average accuracy gains of 9.3% over GPT-4o. Furthermore, OctoTools outperforms AutoGen, GPT-Functions and LangChain by up to 10.6% when given the same set of tools. Through comprehensive analysis and ablations, OctoTools demonstrates advantages in task planning, effective tool usage, and multi-step problem solving.

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