Agent 配套工具

ChatDev 2.0(DevAll)|零代码多智能体编排平台

ChatDev 2.0(DevAll)

OpenBMB 推出的零代码多智能体编排平台,通过可视化画布与 YAML 配置定义智能体、工作流和任务,覆盖数据分析、3D 生成、深度研究等场景。

获取与使用

需要部署

按官方资料自行安装或部署

使用难度待核验
国内可用性待核验

2026-11-09 更新 · 本站尚未实测

项目介绍

Agent 配套工具 · 2026-11-09 更新 · 本站尚未实测

ChatDev 2.0(代号 DevAll)是 ChatDev 系列的迭代版本。按 README 描述,它已从面向软件开发的专用多智能体系统,演进为「A Zero-Code Multi-Agent Platform for Developing Everything」——即一个零代码多智能体编排平台。用户可通过简单配置定义智能体(agents)、工作流(workflows)与任务(tasks),编排数据可视化、3D 生成、深度研究等复杂场景。

早期的 ChatDev 1.0 作为「虚拟软件公司」,由 CEO、CTO、程序员等智能体参与研讨,自动化完成设计、编码、测试与文档等软件开发全流程。该版本现已移至 chatdev1.0 分支维护,主分支为 ChatDev 2.0。

需要说明的是,本文所述功能均以仓库 README 为据,未做实际部署验证。

核心能力

点击能力名称查看输入、输出和原文依据。

  • 零代码编排:README 称无需编码,通过 Web 控制台的可视化画布拖拽配置节点参数、定义上下文流转。
  • 工作流执行:在 Launch 页启动工作流、查看实时日志、检查中间产物,并支持人在环路(human-in-the-loop)反馈。
  • Python SDK:提供 runtime.sdk.run_workflow,可编程执行 YAML 工作流并取回结果;README 提到已发布 PyPI 包 chatdev(版本信息以 PyPI 页面为准)。
  • 官方工作流模板:仓库 yaml_instance/ 目录内置示例,据 README 表格包括数据分析(data_visualization_basic.yaml 等)、3D 生成(需 Blender 与 blender-mcp)、游戏开发(GameDev_v1.yaml、ChatDev_v1.yaml)、深度研究(deep_research_v1.yaml)、教学视频(teach_video.yaml,需先运行 uv add manim)。
  • OpenClaw 集成:README 说明 OpenClaw 可调用 ChatDev 中已有或动态创建的智能体团队。

实际应用场景

适用场景

  • 希望不写代码即可组合多个 LLM 智能体完成任务的用户;
  • 需要可复用工作流模板(数据分析图表、游戏原型、研究综述等)的团队;
  • 需要以 Python 脚本批量调用多智能体工作流的开发者;
  • 研究与学习多智能体协作编排的开发者。

3D 生成、教学视频等模板依赖外部组件,实际可用性需按对应说明自行核验。

安装与接入

README 给出的前置条件:OS 为 macOS / Linux / WSL / Windows;Python 3.12+;Node.js 18+;包管理器 uv。

安装步骤(摘自 README):

  1. 后端依赖:
uv sync
  1. 前端依赖:
cd frontend && npm install
  1. 配置环境变量:
cp .env.example .env

随后在 .env 中设置 API_KEY 与 BASE_URL(用于对接 LLM 服务商);YAML 配置可用 ${VAR} 形式引用变量。

启动方式(摘自 README):

  • 推荐使用 Makefile:
make dev

访问 Web 控制台 http://localhost:5173。

  • 手动启动后端:
uv run python server_main.py --port 6400 --reload
  • 手动启动前端:
cd frontend
VITE_API_BASE_URL=http://localhost:6400 npm run dev
  • Docker Compose 方式(需已安装 Docker 与 Compose,并准备好 .env):
docker compose up --build

其它工具命令:make help、make sync(同步 YAML 工作流到前端)、make validate-yamls(校验 YAML)。

OpenClaw 集成步骤:先启动后端,再安装技能:

clawdhub install chatdev

README 未提供 MCP 服务端配置或远端 MCP 地址,相关采集文件为 404,接入细节待核验。

使用条件与限制

是否需要部署
需自行准备运行环境,具体要求见正文
是否需要注册
账号和认证要求见正文;未明确说明的项目仍待核验
是否需要 API Key
待核验
费用与额度
费用边界见正文,项目许可不代表模型或托管服务免费
所需权限
待核验
许可证与服务条款
待核验

权限费用与限制

  • 模型与 API Key:需自备 LLM 服务商的 API_KEY 与 BASE_URL,费用由所选服务商决定,README 未列价格,费用待向官方核验。README 未逐一列明支持哪些具体模型,也未明确说明是否支持国内模型,均待核验。
  • 执行权限:工作流生成的产物位于 WareHouse/,本地运行会读写本机文件。
  • 外部依赖:3D 生成依赖 Blender 与 blender-mcp;教学视频依赖 manim;OpenClaw 集成依赖 clawdhub 工具,这些第三方组件的可用性、授权与费用均需单独核验。
  • 托管服务:README 旧闻提到 2023 年上线的 SaaS 平台(chatdev.modelbest.cn),其当前状态、费用与可用性待核验;域名不代表服务部署地域。

国内使用情况

网友核验 用户经验分享

与站长实测独立,不代表官方认证或本站已实测。

我要核验
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最近核验:暂无有效核验。参与人数按当前项目有效身份去重;不同核验项分别统计,不合并成用户总结果。仅统计审核通过且未过期的记录。

分项统计、有效期与样本量
核验项目有效人数成功 / 部分 / 失败 / 无法判断成功率最近核验 / 有效期
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成功率 = 成功 ÷(成功 + 部分成功 + 失败);无法判断不计入分母。至少 5 份可判断结果才显示成功率。账号、费用、海外依赖与语言等事实项,成功表示核查结论与资料吻合,具体观察另行统计;不表示免费或没有海外依赖。不同网络、客户端和版本的结果不能直接等同。

最近有效核验

暂无审核通过且未过期的网友核验。欢迎提交真实使用记录。

查看全部有效核验 →

国内实测状态:国内可用性待核验。协议兼容和官方资料说明不等于国内网络可用。

官方网站访问
尚未实测 待核验
GitHub 仓库访问
尚未实测 待核验
官方服务国内连接
尚未实测 待核验
国内网络情况
尚未实测 待核验
国内模型兼容性
尚未实测 待核验
自定义 API
尚未实测 待核验
海外服务依赖
尚未实测 待核验
海外账号要求
尚未实测 待核验
中文界面
尚未实测 待核验
国内最后核验时间
尚未实测

许可与国内使用

仓库根目录 LICENSE 为 Apache License 2.0(Copyright 2025 OpenBMB),适用于仓库代码。第三方组件(Blender、blender-mcp、manim、OpenClaw/clawdhub 等)、模型服务与托管 SaaS 各有独立条款,需分别核验;公开仓库不等于其依赖的模型或服务免费。国内使用方面,README 未声明国内镜像、备案或本地模型适配情况,实际可用性待核验。

项目资料与来源

官方网站 ↗

GitHub 仓库 ↗

官方文档 ↗

字段依据与待核验事项

access:来源确认 · uv sync

project_type:来源确认 · A Zero-Code Multi-Agent Platform for Developing Everything

原始 README(折叠技术参考)
# ChatDev 2.0 - DevAll

<p align="center">
  <img src="frontend/public/media/logo.png" alt="DevAll Logo" width="500"/>
</p>


<p align="center">
  <strong>A Zero-Code Multi-Agent Platform for Developing Everything</strong>
</p>

<p align="center">
  【<a href="./README.md">English</a> | <a href="./README-zh.md">简体中文</a>】
</p>
<p align="center">
    【📚 <a href="#developers">Developers</a> | 👥 <a href="#primary-contributors">Contributors</a>|⭐️ <a href="https://github.com/OpenBMB/ChatDev/tree/chatdev1.0">ChatDev 1.0 (Legacy)</a>】
</p>

## 📖 Overview
ChatDev has evolved from a specialized software development multi-agent system into a comprehensive multi-agent orchestration platform.

- <a href="https://github.com/OpenBMB/ChatDev/tree/main">**ChatDev 2.0 (DevAll)**</a> is a **Zero-Code Multi-Agent Platform** for "Developing Everything". It empowers users to rapidly build and execute customized multi-agent systems through simple configuration. No coding is required—users can define agents, workflows, and tasks to orchestrate complex scenarios such as data visualization, 3D generation, and deep research.
- <a href="https://github.com/OpenBMB/ChatDev/tree/chatdev1.0">**ChatDev 1.0 (Legacy)**</a> operates as a **Virtual Software Company**. It utilizes various intelligent agents (e.g., CEO, CTO, Programmer) participating in specialized functional seminars to automate the entire software development life cycle—including designing, coding, testing, and documenting. It serves as the foundational paradigm for communicative agent collaboration.

## 🎉 News
• **Jan 07, 2026: 🚀 We are excited to announce the official release of ChatDev 2.0 (DevAll)!** This version introduces a zero-code multi-agent orchestration platform. The classic ChatDev (v1.x) has been moved to the [`chatdev1.0`](https://github.com/OpenBMB/ChatDev/tree/chatdev1.0) branch for maintenance. More details about ChatDev 2.0 can be found on [our official post](https://x.com/OpenBMB/status/2008916790399701335).

<details>
<summary>Old News</summary>

•Sep 24, 2025: 🎉 Our paper [Multi-Agent Collaboration via Evolving Orchestration](https://arxiv.org/abs/2505.19591) has been accepted to NeurIPS 2025. The implementation is available in the `puppeteer` branch of this repository.

•May 26, 2025: 🎉 We propose a novel puppeteer-style paradigm for multi-agent collaboration among large language model based agents. By leveraging a learnable central orchestrator optimized with reinforcement learning, our method dynamically activates and sequences agents to construct efficient, context-aware reasoning paths. This approach not only improves reasoning quality but also reduces computational costs, enabling scalable and adaptable multi-agent cooperation in complex tasks.
See our paper in [Multi-Agent Collaboration via Evolving Orchestration](https://arxiv.org/abs/2505.19591).
  <p align="center">
  <img src='./assets/puppeteer.png' width=800>
  </p>

•June 25, 2024: 🎉To foster development in LLM-powered multi-agent collaboration🤖🤖 and related fields, the ChatDev team has curated a collection of seminal papers📄 presented in a [open-source](https://github.com/OpenBMB/ChatDev/tree/main/MultiAgentEbook) interactive e-book📚 format. Now you can explore the latest advancements on the [Ebook Website](https://thinkwee.top/multiagent_ebook) and download the [paper list](https://github.com/OpenBMB/ChatDev/blob/main/MultiAgentEbook/papers.csv).
  <p align="center">
  <img src='./assets/ebook.png' width=800>
  </p>
  
•June 12, 2024: We introduced Multi-Agent Collaboration Networks (MacNet) 🎉, which utilize directed acyclic graphs to facilitate effective task-oriented collaboration among agents through linguistic interactions 🤖🤖. MacNet supports co-operation across various topologies and among more than a thousand agents without exceeding context limits. More versatile and scalable, MacNet can be considered as a more advanced version of ChatDev's chain-shaped topology. Our preprint paper is available at [https://arxiv.org/abs/2406.07155](https://arxiv.org/abs/2406.07155). This technique has been incorporated into the [macnet](https://github.com/OpenBMB/ChatDev/tree/macnet) branch, enhancing support for diverse organizational structures and offering richer solutions beyond software development (e.g., logical reasoning, data analysis, story generation, and more).
  <p align="center">
  <img src='./assets/macnet.png' width=500>
  </p>

• May 07, 2024, we introduced "Iterative Experience Refinement" (IER), a novel method where instructor and assistant agents enhance shortcut-oriented experiences to efficiently adapt to new tasks. This approach encompasses experience acquisition, utilization, propagation and elimination across a series of tasks and making the pricess shorter and efficient. Our preprint paper is available at https://arxiv.org/abs/2405.04219, and this technique will soon be incorporated into ChatDev.
  <p align="center">
  <img src='./assets/ier.png' width=220>
  </p>

• January 25, 2024: We have integrated Experiential Co-Learning Module into ChatDev. Please see the [Experiential Co-Learning Guide](wiki.md#co-tracking).

• December 28, 2023: We present Experiential Co-Learning, an innovative approach where instructor and assistant agents accumulate shortcut-oriented experiences to effectively solve new tasks, reducing repetitive errors and enhancing efficiency.  Check out our preprint paper at https://arxiv.org/abs/2312.17025 and this technique will soon be integrated into ChatDev.
  <p align="center">
  <img src='./assets/ecl.png' width=860>
  </p>
• November 15, 2023: We launched ChatDev as a SaaS platform that enables software developers and innovative entrepreneurs to build software efficiently at a very low cost and remove the barrier to entry. Try it out at https://chatdev.modelbest.cn/.
  <p align="center">
  <img src='./assets/saas.png' width=560>
  </p>

• November 2, 2023: ChatDev is now supported with a new feature: incremental development, which allows agents to develop upon existing codes. Try ```--config "incremental" --path "[source_code_directory_path]"``` to start it.
  <p align="center">
  <img src='./assets/increment.png' width=700>
  </p>

• October 26, 2023: ChatDev is now supported with Docker for safe execution (thanks to contribution from [ManindraDeMel](https://github.com/ManindraDeMel)). Please see [Docker Start Guide](wiki.md#docker-start).
  <p align="center">
  <img src='./assets/docker.png' width=400>
  </p>
  
• September 25, 2023: The **Git** mode is now available, enabling the programmer <img src='visualizer/static/figures/programmer.png' height=20> to utilize Git for version control. To enable this feature, simply set ``"git_management"`` to ``"True"`` in ``ChatChainConfig.json``. See [guide](wiki.md#git-mode).
  <p align="center">
  <img src='./assets/github.png' width=600>
  </p>

• September 20, 2023: The **Human-Agent-Interaction** mode is now available! You can get involved with the ChatDev team by playing the role of reviewer <img src='visualizer/static/figures/reviewer.png' height=20> and making suggestions to the programmer <img src='visualizer/static/figures/programmer.png' height=20>;
  try ``python3 run.py --task [description_of_your_idea] --config "Human"``. See [guide](wiki.md#human-agent-interaction) and [example](WareHouse/Gomoku_HumanAgentInteraction_20230920135038).
  <p align="center">
  <img src='./assets/Human_intro.png' width=600>
  </p>

• September 1, 2023: The **Art** mode is available now! You can activate the designer agent <img src='visualizer/static/figures/designer.png' height=20> to generate images used in the software;
  try ``python3 run.py --task [description_of_your_idea] --config "Art"``. See [guide](wiki.md#art) and [example](WareHouse/gomokugameArtExample_THUNLP_20230831122822).
  
• August 28, 2023: The system is publicly available.

• August 17, 2023: The v1.0.0 version was ready for release.

• July 30, 2023: Users can customize ChatChain, Phasea and Role settings. Additionally, both online Log mode and replay
  mode are now supported.

• July 16, 2023: The [preprint paper](https://arxiv.org/abs/2307.07924) associated with this project was published.

• June 30, 2023: The initial version of the ChatDev repository was released.
</details>


## 🚀 Quick Start

### 📋 Prerequisites

*   **OS**: macOS / Linux / WSL / Windows
*   **Python**: 3.12+
*   **Node.js**: 18+
*   **Package Manager**: [uv](https://docs.astral.sh/uv/)

### 📦 Installation

1.  **Backend Dependencies** (Python managed by `uv`):
    ```bash
    uv sync
    ```

2.  **Frontend Dependencies** (Vite + Vue 3):
    ```bash
    cd frontend && npm install
    ```

### 🔑 Configuration

*   **Environment Variables**:
    ```bash
    cp .env.example .env
    ```
*   **Model Keys**: Set `API_KEY` and `BASE_URL` in `.env` for your LLM provider.
*   **YAML placeholders**: Use `${VAR}`(e.g., `${API_KEY}`)in configuration files to reference these variables.

### ⚡️ Run the Application

#### Using Makefile (Recommended)

**Start both Backend and Frontent**:
```bash
make dev
```

> Then access the Web Console at **[http://localhost:5173](http://localhost:5173)**.

#### Manual Commands

1.  **Start Backend**:
    ```bash
    # Run from the project root
    uv run python server_main.py --port 6400 --reload
    ```
    > `--reload` watches the server's Python source folders only; agent-generated files under `WareHouse/` no longer trigger restarts. Pass `--reload-dir` or `--reload-exclude` (repeatable) to customise.

2.  **Start Frontend**:
    ```bash
    cd frontend
    VITE_API_BASE_URL=http://localhost:6400 npm run dev
    ```
    > Then access the Web Console at **[http://localhost:5173](http://localhost:5173)**. 
    
    
    > **💡 Tip**: If the frontend fails to connect to the backend, the default port `6400` may already be occupied.
    > Please switch both services to an available port, for example:
    >
    > * **Backend**: start with `--port 6401`
    > * **Frontend**: set `VITE_API_BASE_URL=http://localhost:6401`

#### Utility Commands

*   **Help command**:
    ```bash
    make help
    ```

*   **Sync YAML workflows to frontend**:
    ```bash
    make sync
    ```
    Uploads all workflow files from `yaml_instance/` to the database.

*   **Validate all YAML workflows**:
    ```bash
    make validate-yamls
    ```
    Checks all YAML files for syntax and schema errors.

### 🦞 Run with OpenClaw
OpenClaw can integrate with ChatDev by invoking existing agent teams or dynamically creating new agent teams within ChatDev.
To get started:
1. Start the ChatDev 2.0 backend.
2. Install the required skills for your OpenClaw instance:
    ```bash
    clawdhub install chatdev
    ```

3. Ask your OpenClaw to create a ChatDev workflow. For example:

* **Automated information collection and content publishing**

  ```
  Create a ChatDev workflow to automatically collect trending information, generate a Xiaohongshu post, and publish it.
  ```

* **Multi-agent geopolitical simulation**
  ```
  Create a ChatDev workflow with multiple agents to simulate possible future developments of the Middle East situation.
  ```


### 🐳 Run with Docker
Alternatively, you can run the entire application using Docker Compose. This method simplifies dependency management and provides a consistent environment.

1.  **Prerequisites**:
    *   [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/) installed.
    *   Ensure you have a `.env` file in the project root for your API keys.

2.  **Build and Run**:
    ```bash
    # From the project root
    docker compose up --build
    ```

3.  **Access**:
    *   **Backend**: `http://localhost:6400`
    *   **Frontend**: `http://localhost:5173`

> The services will automatically restart if they crash, and local file changes will be reflected inside the containers for live development.

---

## 💡 How to Use

### 🖥️ Web Console

The DevAll interface provides a seamless experience for both construction and execution

*   **Tutorial**: Comprehensive step-by-step guides and documentation integrated directly into the platform to help you get started quickly.
<img src="assets/tutorial-en.png"/> 

*   **Workflow**: A visual canvas to design your multi-agent systems. Configure node parameters, define context flows, and orchestrate complex agent interactions with drag-and-drop ease.
<img src="assets/workflow.gif"/>

*   **Launch**: Initiate workflows, monitor real-time logs, inspect intermediate artifacts, and provide human-in-the-loop feedback.
<img src="assets/launch.gif"/>

### 🧰 Python SDK
For automation and batch processing, use our lightweight Python SDK to execute workflows programmatically and retrieve results directly.

```python
from runtime.sdk import run_workflow

# Execute a workflow and get the final node message
result = run_workflow(
    yaml_file="yaml_instance/demo.yaml",
    task_prompt="Summarize the attached document in one sentence.",
    attachments=["/path/to/document.pdf"],
    variables={"API_KEY": "sk-xxxx"} # Override .env variables if needed
)

if result.final_message:
    print(f"Output: {result.final_message.text_content()}")
```

**We have released the ChatDev Python SDK (PyPI package `chatdev`)**, so you can also run YAML workflow and multi-agent tasks directly in Python. For installation and version details, see [PyPI: chatdev 0.1.0](https://pypi.org/project/chatdev/0.1.0/).

---

<a id="developers"></a>
## ⚙️ For Developers

**For secondary development and extensions, please proceed with this section.**

Extend DevAll with new nodes, providers, and tools.
The project is organized into a modular structure:
*   **Core Systems**: `server/` hosts the FastAPI backend, while `runtime/` manages agent abstraction and tool execution.
*   **Orchestration**: `workflow/` handles the multi-agent logic, driven by configurations in `entity/`.
*   **Frontend**: `frontend/` contains the Vue 3 Web Console.
*   **Extensibility**: `functions/` is the place for custom Python tools.

Relevant reference documentation:
*   **Getting Started**: [Start Guide](./docs/user_guide/en/index.md)
*   **Core Modules**: [Workflow Authoring](./docs/user_guide/en/workflow_authoring.md), [Memory](./docs/user_guide/en/modules/memory.md), and [Tooling](./docs/user_guide/en/modules/tooling/index.md)

---

## 🌟 Featured Workflows
We provide robust, out-of-the-box templates for common scenarios. All runnable workflow configs are located in `yaml_instance/`.
*   **Demos**: Files named `demo_*.yaml` showcase specific features or modules.
*   **Implementations**: Files named directly (e.g., `ChatDev_v1.yaml`) are full in-house or recreated workflows. As follows:

### 📋 Workflow Collection

| Category | Workflow                                                                                                    | Case | 
| :--- |:------------------------------------------------------------------------------------------------------------| :--- | 
| **📈 Data Visualization** | `data_visualization_basic.yaml`<br>`data_visualization_enhanced.yaml`                                       | <img src="assets/cases/data_analysis/data_analysis.gif" width="100%"><br>Prompt: *"Create 4–6 high-quality PNG charts for my large real-estate transactions dataset."* |
| **🛠️ 3D Generation**<br>*(Requires [Blender](https://www.blender.org/) & [blender-mcp](https://github.com/ahujasid/blender-mcp))* | `blender_3d_builder_simple.yaml`<br>`blender_3d_builder_hub.yaml`<br>`blender_scientific_illustration.yaml` | <img src="assets/cases/3d_generation/3d.gif" width="100%"><br>Prompt: *"Please build a Christmas tree."* |
| **🎮 Game Dev** | `GameDev_v1.yaml`<br>`ChatDev_v1.yaml`                                                                      | <img src="assets/cases/game_development/game.gif" width="100%"><br>Prompt: *"Please help me design and develop a Tank Battle game."* |
| **📚 Deep Research** | `deep_research_v1.yaml`                                                                                     | <img src="assets/cases/deep_research/deep_research.gif" width="85%"><br>Prompt: *"Research about recent advances in the field of LLM-based agent RL"* |
| **🎓 Teach Video** | `teach_video.yaml` (Please run command `uv add manim` before running this workflow)                         | <img src="assets/cases/video_generation/video.gif" width="140%"><br>Prompt: *"讲一下什么是凸优化"* |

---

### 💡 Usage Guide
For those implementations, you can use the **Launch** tab to execute them.
1.  **Select**: Choose a workflow in the **Launch** tab.
2.  **Upload**: Upload necessary files (e.g., `.csv` for data analysis) if required.
3.  **Prompt**: Enter your request (e.g., *"Visualize the sales trends"* or *"Design a snake game"*).

---

## 🤝 Contributing

We welcome contributions from the community! Whether you're fixing bugs, adding new workflow templates, or sharing high-quality cases/artifacts produced by DevAll, your help is much appreciated. Feel free to contribute by submitting **Issues** or **Pull Requests**.

By contributing to DevAll, you'll be recognized in our **Contributors** list below. Check out our [Developer Guide](#developers) to get started!

### 👥 Contributors

#### Primary Contributors

<table>
  <tr>
    <td align="center"><a href="https://github.com/NA-Wen"><img src="https://github.com/NA-Wen.png?size=100" width="64px;" alt=""/><br /><sub><b>NA-Wen</b></sub></a></td>
    <td align="center"><a href="https://github.com/zxrys"><img src="https://github.com/zxrys.png?size=100" width="64px;" alt=""/><br /><sub><b>zxrys</b></sub></a></td>
    <td align="center"><a href="https://github.com/swugi"><img src="https://github.com/swugi.png?size=100" width="64px;" alt=""/><br /><sub><b>swugi</b></sub></a></td>
    <td align="center"><a href="https://github.com/huatl98"><img src="https://github.com/huatl98.png?size=100" width="64px;" alt=""/><br /><sub><b>huatl98</b></sub></a></td>
  </tr>
</table>

#### Contributors
<table>
  <tr>
    <td align="center"><a href="https://github.com/LaansDole"><img src="https://github.com/LaansDole.png?size=100" width="64px;"/><br /><sub><b>LaansDole</b></sub></a></td>
    <td align="center"><a href="https://github.com/zivkovicp"><img src="https://github.com/zivkovicp.png?size=100" width="64px;"/><br /><sub><b>zivkovicp</b></sub></a></td>
    <td align="center"><a href="https://github.com/ACE-Prism"><img src="https://github.com/ACE-Prism.png?size=100" width="64px;"/><br /><sub><b>ACE-Prism</b></sub></a></td>
    <td align="center"><a href="https://github.com/shiowen"><img src="https://github.com/shiowen.png?size=100" width="64px;"/><br /><sub><b>shiowen</b></sub></a></td>
    <td align="center"><a href="https://github.com/kilo2127"><img src="https://github.com/kilo2127.png?size=100" width="64px;"/><br /><sub><b>kilo2127</b></sub></a></td>
    <td align="center"><a href="https://github.com/AckerlyLau"><img src="https://github.com/AckerlyLau.png?size=100" width="64px;"/><br /><sub><b>AckerlyLau</b></sub></a></td>
    <td align="center"><a href="https://github.com/rainoeelmae"><img src="https://github.com/rainoeelmae.png?size=100" width="64px;"/><br /><sub><b>rainoeelmae</b></sub></a></td>
    <td align="center"><a href="https://github.com/conprour"><img src="https://github.com/conprour.png?size=100" width="64px;"/><br /><sub><b>conprour</b></sub></a></td>
  </tr>
  <tr>
    <td align="center"><a href="https://github.com/Br1an67"><img src="https://github.com/Br1an67.png?size=100" width="64px;"/><br /><sub><b>Br1an67</b></sub></a></td>
    <td align="center"><a href="https://github.com/NINE-J"><img src="https://github.com/NINE-J.png?size=100" width="64px;"/><br /><sub><b>NINE-J</b></sub></a></td>
    <td align="center"><a href="https://github.com/Yanghuabei-design"><img src="https://github.com/Yanghuabei-design.png?size=100" width="64px;"/><br /><sub><b>Yanghuabei</b></sub></a></td>
    <td align="center"><a href="https://github.com/nregret"><img src="https://github.com/nregret.png?size=100" width="64px;"/><br /><sub><b>nregret</b></sub></a></td>
    <td align="center"><a href="https://github.com/kartik-mem0"><img src="https://github.com/kartik-mem0.png?size=100" width="64px;"/><br /><sub><b>kartik-mem0</b></sub></a></td>
    <td align="center"><a href="https://github.com/Yanghuabei-design"><img src="https://github.com/Yanghuabei-design.png?size=100" width="64px;"/><br /><sub><b>Yanghuabei-design</b></sub></a></td>
    <td align="center"><a href="https://github.com/benjamin7007"><img src="https://github.com/benjamin7007.png?size=100" width="64px;"/><br /><sub><b>benjamin7007</b></sub></a></td>
    <td align="center"><a href="https://github.com/gouziman"><img src="https://github.com/gouziman.png?size=100" width="64px;"/><br /><sub><b>gouziman</b></sub></a></td>
  </tr>
  <tr>
    <td align="center"><a href="https://github.com/hobostay"><img src="https://github.com/hobostay.png?size=100" width="64px;"/><br /><sub><b>hobostay</b></sub></a></td>
    <td align="center"><a href="https://github.com/token2everything"><img src="https://github.com/token2everything.png?size=100" width="64px;"/><br /><sub><b>token2everything</b></sub></a></td>
  </tr>
</table>

## 🤝 Acknowledgments

<a href="http://nlp.csai.tsinghua.edu.cn/"><img src="assets/thunlp.png" height=50pt></a>&nbsp;&nbsp;
<a href="https://modelbest.cn/"><img src="assets/modelbest.png" height=50pt></a>&nbsp;&nbsp;
<a href="https://github.com/OpenBMB/AgentVerse/"><img src="assets/agentverse.png" height=50pt></a>&nbsp;&nbsp;
<a href="https://github.com/OpenBMB/RepoAgent"><img src="assets/repoagent.png"  height=50pt></a>
<a href="https://app.commanddash.io/agent?github=https://github.com/OpenBMB/ChatDev"><img src="assets/CommandDash.png" height=50pt></a>
<a href="www.teachmaster.cn"><img src="assets/teachmaster.png" height=50pt></a>
<a href="https://github.com/OpenBMB/AppCopilot"><img src="assets/appcopilot.png" height=50pt></a>

## 🔎 Citation

```
@article{chatdev,
    title = {ChatDev: Communicative Agents for Software Development},
    author = {Chen Qian and Wei Liu and Hongzhang Liu and Nuo Chen and Yufan Dang and Jiahao Li and Cheng Yang and Weize Chen and Yusheng Su and Xin Cong and Juyuan Xu and Dahai Li and Zhiyuan Liu and Maosong Sun},
    journal = {arXiv preprint arXiv:2307.07924},
    url = {https://arxiv.org/abs/2307.07924},
    year = {2023}
}

@article{colearning,
    title = {Experiential Co-Learning of Software-Developing Agents},
    author = {Chen Qian and Yufan Dang and Jiahao Li and Wei Liu and Zihao Xie and Yifei Wang and Weize Chen and Cheng Yang and Xin Cong and Xiaoyin Che and Zhiyuan Liu and Maosong Sun},
    journal = {arXiv preprint arXiv:2312.17025},
    url = {https://arxiv.org/abs/2312.17025},
    year = {2023}
}

@article{macnet,
    title={Scaling Large-Language-Model-based Multi-Agent Collaboration},
    author={Chen Qian and Zihao Xie and Yifei Wang and Wei Liu and Yufan Dang and Zhuoyun Du and Weize Chen and Cheng Yang and Zhiyuan Liu and Maosong Sun}
    journal={arXiv preprint arXiv:2406.07155},
    url = {https://arxiv.org/abs/2406.07155},
    year={2024}
}

@article{iagents,
    title={Autonomous Agents for Collaborative Task under Information Asymmetry},
    author={Wei Liu and Chenxi Wang and Yifei Wang and Zihao Xie and Rennai Qiu and Yufan Dnag and Zhuoyun Du and Weize Chen and Cheng Yang and Chen Qian},
    journal={arXiv preprint arXiv:2406.14928},
    url = {https://arxiv.org/abs/2406.14928},
    year={2024}
}

@article{puppeteer,
      title={Multi-Agent Collaboration via Evolving Orchestration}, 
      author={Yufan Dang and Chen Qian and Xueheng Luo and Jingru Fan and Zihao Xie and Ruijie Shi and Weize Chen and Cheng Yang and Xiaoyin Che and Ye Tian and Xuantang Xiong and Lei Han and Zhiyuan Liu and Maosong Sun},
      journal={arXiv preprint arXiv:2505.19591},
      url={https://arxiv.org/abs/2505.19591},
      year={2025}
}
```

## 📬 Contact

If you have any questions, feedback, or would like to get in touch, please feel free to reach out to us via email at [qianc62@gmail.com](mailto:qianc62@gmail.com)
历史前置条件说明(补充参考)

Python 3.12+、Node.js 18+、uv 包管理器;OS 支持 macOS/Linux/WSL/Windows(README 声明);需自备 LLM 服务商 API_KEY 与 BASE_URL;Docker 方式需 Docker 与 Docker Compose;3D 生成需 Blender 与 blender-mcp,教学视频需先安装 manim;模型费用、具体支持的模型清单、国内可用性均待核验。

项目来源与清单版权许可

https://github.com/OpenBMB/ChatDev

https://github.com/OpenBMB

整理来源:https://github.com/slavakurilyak/awesome-ai-agents

清单版权与许可:

MIT License

Copyright (c) 2024 Slava Kurilyak

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.