ChatDev 2.0 (DevAll) is a zero-code multi-agent orchestration platform from OpenBMB that enables users to build and execute customized multi-agent systems through visual configuration, requiring no programming expertise. Officially released on January 7, 2026, it represents a major evolution from the original ChatDev, which simulated a virtual software company with role-playing AI agents. With 31,200 GitHub stars and 3,900 forks, ChatDev 2.0 has become one of the most popular multi-agent frameworks in the open-source ecosystem. ## Zero-Code Visual Workflow Canvas The centerpiece of ChatDev 2.0 is a drag-and-drop visual workflow canvas where users design multi-agent systems by connecting agent nodes, defining communication channels, and specifying task flows. This removes the programming barrier entirely -- users who cannot write Python can still orchestrate complex multi-agent scenarios for data analysis, content generation, research, and more. ## Beyond Software Development While ChatDev 1.0 focused specifically on automating software development with role-playing agents (CEO, CTO, Programmer), ChatDev 2.0 generalizes to arbitrary domains. The platform supports data visualization, 3D generation, game development, deep research, and any workflow that benefits from coordinated multi-agent collaboration. This expansion is captured in the tagline 'Dev All.' ## Python SDK for Programmatic Control Alongside the visual interface, ChatDev 2.0 provides a Python SDK for developers who prefer programmatic automation. The SDK supports batch processing, workflow templating, and integration with existing codebases, making it suitable for both interactive exploration and production deployment. ## Real-Time Execution Monitoring The web console provides real-time logging and artifact inspection during workflow execution. Users can observe each agent's reasoning, inter-agent messages, and intermediate outputs as they are produced. Human-in-the-loop feedback allows users to intervene and redirect agent behavior mid-execution. ## NeurIPS 2025 Research Foundation The platform's orchestration approach is informed by the research paper 'Multi-Agent Collaboration via Evolving Orchestration,' accepted to NeurIPS 2025. This work introduced a puppeteer-style paradigm where a learnable central orchestrator, optimized with reinforcement learning, dynamically activates and sequences agents to construct efficient, context-aware reasoning paths. ## Architecture: Web Console and Vue 3 Frontend The frontend is built with Vue 3, providing a modern reactive interface for the workflow canvas. The backend orchestration engine is implemented in Python, with WebSocket communication enabling real-time updates between the execution engine and the browser-based UI.