AutoGLMUI

A modern web interface for interacting with the AutoGLM API (z1 AutoGLM ). This project provides both a web-based UI and a command-line interface for sending tasks to AutoGLM and receiving real-time responses.

Quick Start / 快速开始

1. Set API Token / 设置API Token

Before running, please set your AutoGLM API Token first:

Windows:

set AUTOGLM_AUTOGLM_API_TOKEN=your_token

Linux/Mac:

export AUTOGLM_AUTOGLM_API_TOKEN=your_token

2. Run the Application / 运行应用

Method 1: Using the launcher (recommended) / 方式一：使用启动器（推荐）

python run.py

Method 2: Run web server directly / 方式二：直接运行Web服务器

python main.py

Then open your browser and visit: http://localhost:8000

Method 3: Use CLI client / 方式三：使用命令行客户端

python auto.py

3. Usage Instructions / 使用说明

Web Interface / Web界面

1. Open http://localhost:8000 in your browser
2. Enter your task in the input box
3. Click the "Send" button
4. View the returned results

Command Line Interface / 命令行界面

1. Enter your task directly after running
2. Press Enter to send
3. Type quit to exit

Common Issues / 常见问题

1. Connection Failed / 连接失败

   • Check if API Token is set correctly
   • Check network connection
   • View error messages in console output

2. Port Already in Use / 端口被占用

   • Change port number: set AUTOGLM_PORT=8001

3. Need Debug Information / 需要调试信息

   • Enable debug mode: set AUTOGLM_DEBUG=true

Features

• Web Interface: Clean, responsive web UI for interacting with AutoGLM
• CLI Client: Command-line interface for direct WebSocket communication
• WebSocket Support: Real-time bidirectional communication with AutoGLM API
• Configuration Management: Environment-based configuration with .env support
• Logging: Structured logging for debugging and monitoring
• Auto-Reconnection: Automatic reconnection with exponential backoff
• Error Handling: Comprehensive error handling and graceful degradation

Installation

Prerequisites

• Python 3.8 or higher
• An AutoGLM API token from Zhipu AI

Install from source

git clone https://github.com/yourusername/AutoGLMUI.git
cd AutoGLMUI
pip install -e .

Install development dependencies

pip install -e ".[dev]"

Configuration

Create a .env file in the project root:

cp .env.example .env

Edit .env with your configuration:

# AutoGLM API Configuration
AUTOGLM_AUTOGLM_API_TOKEN=your_autoglm_api_token_here

# Server Configuration
AUTOGLM_HOST=127.0.0.1
AUTOGLM_PORT=8000
AUTOGLM_DEBUG=false

# WebSocket Configuration
AUTOGLM_WEBSOCKET_TIMEOUT=30
AUTOGLM_MAX_RECONNECT_ATTEMPTS=5

# Logging Configuration
AUTOGLM_LOG_LEVEL=INFO

Usage

Web Interface

Start the web server:

python main.py

Or using the development server with hot reload:

AUTOGLM_DEBUG=true python main.py

Open your browser and navigate to http://localhost:8000

Command Line Interface

Run the CLI client:

python auto.py

Or with a custom token:

python auto.py --token your_api_token

Environment Variables

You can also configure the application using environment variables:

export AUTOGLM_AUTOGLM_API_TOKEN=your_token
export AUTOGLM_HOST=0.0.0.0
export AUTOGLM_PORT=8080
python main.py

API Endpoints

Web API

• GET / - Main web interface
• POST /api/send-task - Send a task to AutoGLM
• GET /api/status - Get WebSocket connection status
• GET /api/responses - Get recent responses
• GET /health - Health check endpoint

Development

Code Formatting

The project uses Black for code formatting and isort for import sorting:

black .
isort .

Type Checking

mypy src/

Linting

flake8 src/

Running Tests

pytest

Pre-commit Hooks

Install pre-commit hooks:

pre-commit install

Project Structure

AutoGLMUI/
├── src/
│   ├── __init__.py
│   ├── app.py              # FastAPI application
│   ├── config.py           # Configuration management
│   ├── logging_config.py   # Logging setup
│   ├── websocket_client.py # WebSocket client
│   └── dependencies.py     # Dependency injection
├── static/
│   └── style.css           # CSS styles
├── templates/
│   └── index.html          # Web interface template
├── main.py                 # Web server entry point
├── auto.py                 # CLI client
├── pyproject.toml          # Project configuration
├── .env.example            # Environment template
└── README.md               # This file

Security Notes

• Never commit your API token to version control
• Use environment variables or a .env file for sensitive configuration
• The web interface is intended for local development use only
• Consider adding authentication for production deployment

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Make your changes and ensure they pass tests
4. Format your code: black . && isort .
5. Commit your changes: git commit -am 'Add some feature'
6. Push to the branch: git push origin feature-name
7. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For issues and questions:

• Create an issue on GitHub
• Check the documentation
• Join our community discussions

Acknowledgments

• Zhipu AI for the AutoGLM API
• FastAPI for the web framework
• WebSocket-Client for WebSocket support