AgentScope: A Flexible yet Robust Multi-Agent Platform
With the rapid advancement of Large Language Models (LLMs), significant
progress has been made in multi-agent applications. However, the complexities
in coordinating agents' cooperation and LLMs' erratic performance pose notable
challenges in developing robust and efficient multi-agent applications. To
tackle these challenges, we propose AgentScope, a developer-centric multi-agent
platform with message exchange as its core communication mechanism. Together
with abundant syntactic tools, built-in resources, and user-friendly
interactions, our communication mechanism significantly reduces the barriers to
both development and understanding. Towards robust and flexible multi-agent
application, AgentScope provides both built-in and customizable fault tolerance
mechanisms while it is also armed with system-level supports for multi-modal
data generation, storage and transmission. Additionally, we design an
actor-based distribution framework, enabling easy conversion between local and
distributed deployments and automatic parallel optimization without extra
effort. With these features, AgentScope empowers developers to build
applications that fully realize the potential of intelligent agents. We have
released AgentScope at https://github.com/modelscope/agentscope, and hope
AgentScope invites wider participation and innovation in this fast-moving
field.
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Dawei Gao
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2024-02-23T12:44:36.304Z
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dawei gao
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DavdGao
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Zitao Li
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Weirui Kuang
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weirui kuang
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rayrayray
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Xuchen Pan
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2024-02-23T12:45:04.869Z
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Xuchen Pan
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panxuchen
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Daoyuan Chen
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2024-02-23T12:45:13.031Z
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Daoyuan Chen
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yxdyc
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Zhijian Ma
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Bingchen Qian
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Liuyi Yao
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Liuyi Yao
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Briayao
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Lin Zhu
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Chen Cheng
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Hongzhu Shi
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2024-02-23T12:46:23.764Z
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Hongzhu Shi
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vivianvolvo
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Yaliang Li
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Bolin Ding
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Jingren Zhou
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2024-02-23T12:46:49.429Z
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Zhou
user
Jingren
AgentScope: A Flexible yet Robust Multi-Agent Platform
With the rapid advancement of Large Language Models (LLMs), significant
progress has been made in multi-agent applications. However, the complexities
in coordinating agents' cooperation and LLMs' erratic performance pose notable
challenges in developing robust and efficient multi-agent applications. To
tackle these challenges, we propose AgentScope, a developer-centric multi-agent
platform with message exchange as its core communication mechanism. Together
with abundant syntactic tools, built-in resources, and user-friendly
interactions, our communication mechanism significantly reduces the barriers to
both development and understanding. Towards robust and flexible multi-agent
application, AgentScope provides both built-in and customizable fault tolerance
mechanisms while it is also armed with system-level supports for multi-modal
data generation, storage and transmission. Additionally, we design an
actor-based distribution framework, enabling easy conversion between local and
distributed deployments and automatic parallel optimization without extra
effort. With these features, AgentScope empowers developers to build
applications that fully realize the potential of intelligent agents. We have
released AgentScope at https://github.com/modelscope/agentscope, and hope
AgentScope invites wider participation and innovation in this fast-moving
field.
AgentScope is a developer-centric platform for multi-agent applications, facilitating message exchange, fault tolerance, and multi-modal data handling with an actor-based framework.
Large Language Models (LLMs) multi-agent platform message exchange fault tolerance multi-modal data actor-based framework