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ChatDev 2.0 - A zero-code multi-agent tool open-sourced by Tsinghua University and Mianbi Intelligence.

ChatDev 2.0 is a no-code multi-agent tool open-sourced by a joint team from Tsinghua University, Shanghai Jiao Tong University, OpenBMB, and Wallfacer Intelligence. The tool uses a visual interface, allowing users to quickly build multi-agent systems through drag-and-drop configuration...

What is ChatDev 2.0?

ChatDev 2.0 is a product of Tsinghua University, Shanghai Jiao Tong University,OpenBMBChatDev 2.0 is a no-code multi-agent tool open-sourced by the Wallfacer AI team. Through a visual interface, users can quickly build multi-agent systems by dragging and dropping and configuring, without writing any code. ChatDev 2.0 supports multiple node types, including Agent, Human, Python, and Logic nodes, enabling automated collaboration for complex tasks. The tool uses a highly robust graph structure at its core, supporting unlimited nesting and free topology to meet diverse needs from simple to complex.

Main features of ChatDev 2.0

  • No-code development and visual interactionThrough a visual approach of "drag and drop + configuration," users can build multi-agent systems without writing code, greatly reducing the development threshold.
  • Multi-agent collaborationIt provides a variety of computing nodes (such as Agent, Human, Python, and Logic) to support flexible collaboration between intelligent agents and meet different task requirements.
  • Powerful low-level orchestration capabilitiesIt decouples control flow from data flow, supports unlimited nesting and free topology, and can build complex and efficient multi-agent systems.
  • Standardized templates and code-level extensionsIt has multiple built-in templates to help beginners get started quickly, and it is also completely open source to support in-depth customization by geeks.
  • Diverse application scenariosIt supports a variety of complex tasks such as 3D modeling, data analysis, video generation, deep research, and game development, meeting the needs of different fields.

How to use ChatDev 2.0

  • Installation EnvironmentEnsure your computer has an operating system (macOS / Linux / WSL / Windows), Python (3.12 or later), Node.js (18 or later), and UV package manager installed.
  • Download ProjectVisit the ChatDev 2.0 GitHub page, click the "Code" button to download the ZIP file and extract it to your local directory.
  • Install dependenciesEnter the unzipped project directory and run the command to install the backend (uv sync) and frontend (cd frontend && npm install) dependencies.
  • Start serviceStart the backend service in the project root directory (uv run python server_main.py –port 6400 –reload), and start the frontend service in the frontend directory (cd frontend && VITE_API_BASE_URL=http://localhost:6400 npm run dev). Then access the web console via your browser at http://localhost:5173.
  • Configure environment variablesCreate a .env file in the project root directory and set the API key and base URL of the LLM provider.
  • Use a visual interfaceIn the Web console, select a preset workflow template in the "Launch" tab, upload the required files (such as data files or documents), enter task prompts (such as "Analyze data trends" or "Generate a 3D model"), and click the "Start" button to start the workflow. You can view the logs and monitor the progress in real time.

ChatDev 2.0 project address

  • GitHub repositoryhttps://github.com/OpenBMB/ChatDev

Application scenarios of ChatDev 2.0

  • Software developmentThrough multi-agent collaboration, the entire software development lifecycle is automated, including requirements analysis, design, coding, testing, and documentation generation.
  • Data AnalysisThe tool allows users to quickly build data processing workflows, enabling data cleaning, analysis, and visualization, and helping them extract valuable information from complex data.
  • 3D Modeling and DesignThe tool can be combined with professional tools (such as Blender) to generate 3D models through intelligent agent collaboration, and can be applied to fields such as game development, architectural design and scientific visualization.
  • Creative Video ProductionUse multi-agent systems to generate creative scripts and design storyboards to assist in video editing and special effects production.
  • academic researchIt supports an integrated workflow from literature retrieval and research design to experimental data analysis and paper writing, thereby improving research efficiency.
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