diff --git a/README.md b/README.md
index 94e7fc2..f62bcc9 100755
--- a/README.md
+++ b/README.md
@@ -1,85 +1,104 @@
-Ubuntu20.04 + python3.11.9 + django
-#1、安装python3.11.9
-sudo apt install build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev libsqlite3-dev wget
-wget https://www.python.org/ftp/python/3.11.9/Python-3.11.9.tgz
-tar zxvf Python-3.11.9.tgz
-cd Python-3.11.9
-./configure --enable-optimizations
-make -j$(nproc)
-sudo make altinstall
-python3.11 -m ensurepip --upgrade
-wget https://bootstrap.pypa.io/get-pip.py
-python3.11 get-pip.py
-#2、安装python虚拟环境和依赖
-cd /opt/matagent
-python3.11 -m venv pyautogen
-source pyautogen/bin/activate
-#安装pyautogen
-pip install pyautogen==0.2.34
-pip install flaml[automl]
-pip install chromadb
-pip install Image
-#安装django
-pip install django
-pip install djangorestframework
-pip install requests
-#安装 websocket支持  channels+asgi
-pip install channels
-pip install asgiref  # Django Channels 依赖的包
-#运行服务，支持http+websocket  websocket接口：  ws://192.168.42.130:8000/matagent/chat
-DJANGO_SETTINGS_MODULE=matagent.settings uvicorn matagent.asgi:application --host 0.0.0.0 --port 8000
-#安装nginx
-sudo apt-get update
-sudo apt-get install nginx
---查看状态
-sudo systemctl status nginx
---修改配置
-/etc/nginx/default
-nginx配置在default
+# Multi-Agent Material Science Research Platform
 
+This project is a comprehensive platform for material science research, consisting of a backend API server, a frontend web application, and a middleware desktop application. The platform integrates various AI agents for planning, scientific analysis, engineering tasks, and data analysis to assist in material science research.
 
+## Project Structure
 
+The project is divided into three main components:
 
-#pip install autogen-agentchat[websockets]~=0.2 fastapi uvicorn
+1. Backend (Python/FastAPI)
+2. Frontend (Vue.js)
+3. Middleware (C#/WPF)
 
+## Backend
 
-# 完整agent的console版本
-matagent_main.py是入口点。
-安装requirements.txt里面的pyautogen，然后运行即可。
-.coding目录不要删除，里面包含的是一个配置好的，AGENT执行python代码的环境，否则会报错。
-如果存在问题，检查.coding/pyvenv.cfg文件配置
-data目录记录了实验数据，PL和UV数据，不要删除，否则会报错。
+The backend is built with Python using the FastAPI framework. It manages the core logic of the multi-agent system, handles WebSocket connections for real-time communication, and provides API endpoints for the frontend.
 
-代码中，agent之间的状态流转逻辑通常为每个group的state_transition函数中，其中return 'auto'表示自动选择合适的agent。
+### Setup and Running
 
-# 简单agent的ui版本
-cd ui-simple
-chainlit run --port 8989 appUI.py
+1. Navigate to the backend directory:
+   ```
+   cd backend
+   ```
 
-chainlit继承了pyautogen的AssistantAgent，在这个基础上实现了chainlit的接口。
-class ChainlitAssistantAgent(AssistantAgent):
-class ChainlitUserProxyAgent(UserProxyAgent):
-同时重载了两个方法以发送数据到前端。
+2. Install dependencies (it's recommended to use a virtual environment):
+   ```
+   pip install -r requirements.txt
+   ```
 
-    """
-    Wrapper for AutoGens Assistant Agent
-    """
-    def send(
-        self,
-        message: Union[Dict, str],
-        recipient: Agent,
-        request_reply: Optional[bool] = None,
-        silent: Optional[bool] = False,
-    ) -> bool:
-        cl.run_sync(
-            cl.Message(
-                content=f'**{self.name}** Sending message to "{recipient.name}":\n\n{message}',
-                author=self.name,
-            ).send()
-        )
-        super(ChainlitAssistantAgent, self).send(
-            message=message,
-            recipient=recipient,
-            request_reply=request_reply,
-            silent=silent,
-        )
\ No newline at end of file
+3. Set up environment variables:
+   - Copy `.env.example` to `.env`
+   - Fill in the required API keys and configuration settings
+
+4. Run the backend server:
+   ```
+   uvicorn api:app --host 0.0.0.0 --port 8000
+   ```
+
+The backend will be available at `http://localhost:8000`.
+
+## Frontend
+
+The frontend is a Vue.js application that provides the user interface for interacting with the multi-agent system.
+
+### Setup and Running
+
+1. Navigate to the frontend directory:
+   ```
+   cd frontend
+   ```
+
+2. Install dependencies:
+   ```
+   npm install
+   ```
+
+3. Run the development server:
+   ```
+   npm run dev
+   ```
+
+4. For production build:
+   ```
+   npm run build
+   ```
+
+Before building for production, ensure that the following environment variables in the `.env` file are correctly set:
+- `VITE_API_URL`: The backend API URL
+- `VITE_API_URL_PREFIX`: The API prefix
+- `VITE_WB_BASE_URL`: The WebSocket base URL for real-time communication
+
+## Middleware
+
+The middleware is a C# WPF desktop application that provides additional functionality and integration with local systems.
+
+### Setup and Running
+
+1. Open the solution file `middleware/zdhsys.sln` in Visual Studio.
+
+2. Build the solution in Visual Studio.
+
+3. Run the application from Visual Studio or navigate to the build output directory and run the executable.
+
+## Usage
+
+1. Start the backend server.
+2. Launch the frontend application (either in development mode or by serving the production build).
+3. If required, run the middleware desktop application.
+4. Access the web interface through your browser and begin interacting with the multi-agent material science research platform.
+
+## Features
+
+- Real-time communication using WebSockets
+- Multi-agent system for complex task planning and execution
+- Integration of scientific, engineering, and data analysis teams
+- Video streaming capabilities for remote monitoring
+- Customizable UI for different aspects of material science research
+
+## Contributing
+
+Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.
+
+## License
+
+This project is licensed under the MIT License - see the LICENSE.md file for details.