OctoTools: An Agentic Framework with Extensible Tools for Complex
  Reasoning
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.
67b4322c217ec18a40587bec
Pan Lu
claimed_verified
2025-02-19T09:04:43.677Z
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Pan Lu
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lupantech
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Bowen Chen
claimed_verified
2025-02-20T09:37:37.912Z
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Bowen Chen
user
bowen118
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Sheng Liu
claimed_verified
2025-02-20T09:37:35.169Z
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Sheng Liu
user
shengliu66
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Rahul Thapa
67b4322c217ec18a40587bf0
Joseph Boen
admin_assigned
2025-02-19T14:39:08.417Z
66846f30f53c83742c117277
/avatars/31a2434297a6c194d57f2a0234f1ca2c.svg
Joseph Boen
user
tboen1
67b4322c217ec18a40587bf1
James Zou
OctoTools: An Agentic Framework with Extensible Tools for Complex
  Reasoning
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.
OctoTools, an open-source agentic framework, enhances complex reasoning across diverse tasks by utilizing tool cards, planning, and execution without additional training.
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