This project provides a full-stack WeChat mini-program, H5, and web application for AI-powered chat, leveraging models like DeepSeek and ChatGPT. It targets users and developers looking for a customizable AI chatbot solution with features like streaming output, usage limits, and social sharing for bonus credits.

How It Works

The application uses a Java Spring Boot backend with a Vue2 and Uniapp frontend. It supports multiple AI model integrations, including DeepSeek, ChatGPT, Baidu Wenxin, and Alibaba Tongyi Qianwen. Key features include a tiered access system, user credit management via sharing or daily claims, and a robust set of login options.

Quick Start & Requirements

• Backend: Requires JDK 8, Spring Boot, and MySQL. Deploy by creating the aezo-chat-gpt database, executing the SQL script, modifying application.yml with API keys and credentials, and running the compiled JAR or startup scripts (start.bat/start.sh).
• Frontend: Requires HBuilder for the Uniapp project. Modify common/config.js with the backend API address.
• Documentation: One能聊天】开发指南

Highlighted Details

• Supports streaming output for a natural chat experience.
• Offers extensive user management features like chat limits, sharing incentives, and membership tiers.
• Includes a prompt function with nearly 300 built-in prompts for various use cases.
• Provides multiple login methods: mini-program, WeChat official account, phone number, and email.

Maintenance & Community

The project is actively developed, with a community forum accessible via a small donation for contact information.

Licensing & Compatibility

The open-source version is strictly for learning and exchange, prohibiting commercial use or resale. A "Professional Edition" with expanded features is available.

Limitations & Caveats

The open-source version lacks features like DeepSeek, Baidu, and Alibaba model integration, H5/Web adaptation, a backend management system, and multi-API key pooling. Commercial use is explicitly forbidden.