This project extends ChatGPT-Next-Web by adding user management, quota limits, payment integration, and support for multiple Chinese AI models, targeting users who want to build a self-hosted AI chat service with monetization and customization features. It offers a one-click Docker deployment and a comprehensive admin panel for easy configuration.

How It Works

The project provides a frontend chat interface and a separate backend service, both deployable via Docker. It leverages a Vue-based admin panel for extensive customization of site titles, welcome messages, user packages, registration methods, and sensitive word filters. The architecture supports integration with various payment gateways and multiple AI models, including domestic Chinese LLMs.

Quick Start & Requirements

• Install: Execute bash <(curl -s https://raw.githubusercontent.com/Nanjiren01/AIChatWeb/main/scripts/setup.sh) on a CentOS 7.9 server.
• Prerequisites: A server with CentOS 7.9, ports 80 and 8080 open in the security group.
• Setup Time: Under 3 minutes for deployment.
• Demo: User Frontend: https://chat.nanjiren.online, Admin Backend: https://admin.nanjiren.online

Highlighted Details

• Supports domestic AI platforms: Baidu Wenxin Yiyan, Alibaba Tongyi Qianwen, Tsinghua Zhipu (GLM-4, GLM-4v), Moonshot AI, Lingyi Wanwu, Juejie Xingchen.
• Offers extensive customization via an admin panel, including package management (time/quota based) and user registration options.
• Professional version includes payment system integration (Hupijiao, Lantu), invitation mechanisms, and WeChat login.
• Includes AI drawing functionalities (Upscale, Variation, ZoomOut, Pan, Square, Vary).

Maintenance & Community

• Active development with frequent updates (e.g., v0.11.3 as of README).
• Community support via QQ group (437863036) and Telegram.
• Offers a paid "AI Cape of Good Hope" community for early access and advanced tutorials.

Licensing & Compatibility

• Distributed under the MIT license, based on Yidadaa's ChatGPT-Next-Web (which itself has a 996 license).
• The project explicitly states it's for learning and communication, advising caution for commercial use due to potential legal compliance.

Limitations & Caveats

• The project is not designed for Vercel deployment.
• Requires a separate backend service deployment.
• The README mentions a 996 license basis, which may have implications for commercial use depending on interpretation and jurisdiction.