ChatDev 2.0: A No-Code Multi-Agent Platform for Developing Everything

2026-09-01

AI Summary

为解决多智能体系统开发中代码框架复杂与无代码构建限制交互的问题，提出ChatDev 2.0: DevAll平台，通过声明式执行图和可视化界面提供易用性和表达力。

Abstract

Large language model (LLM)-based multi-agent systems (MAS) have shown strong potential for solving complex tasks, yet their development forces a tradeoff: code frameworks are expressive but engineering-intensive, while no-code builders simplify authoring but constrain agent interactions to author-defined workflows. We present ChatDev 2.0: DevAll (hereafter DevAll), a no-code platform for building, executing, and inspecting heterogeneous MAS that delivers both high expressiveness and ease of use. In terms of expressiveness, DevAll pairs a declarative executable graph abstraction with a cycle-aware execution engine, so that heterogeneous agents and dynamic and cyclic interactions can be represented and executed within a single framework. For ease of use, an integrated visual interface lets users author, run, monitor, and inspect MAS, including human-in-the-loop steps, entirely without writing code. Experiments demonstrate that DevAll reproduces state-of-the-art MAS across three representative tasks at competitive performance and without task-specific orchestration code, highlighting its effectiveness as a general-purpose platform for LLM-based MAS. DevAll is available at https://github.com/OpenBMB/ChatDev.

Problem

• large language model
• multi-agent systems
• no-code

Innovation

• no-code platform
• multi-agent systems
• declarative executable graph
• cycle-aware execution engine
• visual interface