title: OctoTools: An Agentic Framework with Extensible Tools for Complex
    Reasoning
summary: 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.
paper_authors._id: 67b4322c217ec18a40587bec
paper_authors.name: Pan Lu
paper_authors.status: claimed_verified
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paper_authors.fullname: Pan Lu
paper_authors.type: user
paper_authors.user: lupantech
paper_authors._id: 67b4322c217ec18a40587bed
paper_authors.name: Bowen Chen
paper_authors.status: claimed_verified
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paper_authors.fullname: Bowen Chen
paper_authors.type: user
paper_authors.user: bowen118
paper_authors._id: 67b4322c217ec18a40587bee
paper_authors.name: Sheng Liu
paper_authors.status: claimed_verified
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paper_authors.fullname: Sheng Liu
paper_authors.type: user
paper_authors.user: shengliu66
paper_authors._id: 67b4322c217ec18a40587bef
paper_authors.name: Rahul Thapa
paper_authors._id: 67b4322c217ec18a40587bf0
paper_authors.name: Joseph Boen
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-02-19T14:39:08.417Z
paper_authors._id: 66846f30f53c83742c117277
paper_authors.avatarUrl: /avatars/31a2434297a6c194d57f2a0234f1ca2c.svg
paper_authors.fullname: Joseph Boen
paper_authors.type: user
paper_authors.user: tboen1
paper_authors._id: 67b4322c217ec18a40587bf1
paper_authors.name: James Zou
paper_title: OctoTools: An Agentic Framework with Extensible Tools for Complex
    Reasoning
paper_summary: 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.
paper_ai_summary: OctoTools, an open-source agentic framework, enhances complex reasoning across diverse tasks by utilizing tool cards, planning, and execution without additional training.
paper_ai_keywords: large language models LLMS OctoTools tool cards planner executor MathVista MMLU-Pro MedQA GAIA-Text GPT-4o AutoGen GPT-Functions LangChain task planning tool usage multi-step problem solving