<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> Super-AutoStudy is a Spring Boot-based distributed platform automating course completion for learning systems like Xuexitong. It targets users seeking efficient online learning, offering multi-speed video playback and AI-powered automatic quiz answering using a large proprietary question bank. The project provides a high-success-rate, automated learning experience.

How It Works

Built on a Spring Boot, Dubbo, and RabbitMQ microservices architecture, it uses official APIs and intelligent time simulation for a 99.9% task success rate. Automated video playback includes anti-detection. Chapter quizzes leverage a million-level "Super题库" and large models for adaptive answering and retries. Redis accelerates caching.

Quick Start & Requirements

Clone the repository (git clone https://github.com/DuanInnovator/SuperAutoStudy.git) and deploy via Docker (docker-compose up -d). Full functionality necessitates installing and configuring multiple middleware components (e.g., RabbitMQ, Redis), which can be complex. Kubernetes deployment is supported. Detailed usage guides are available.

Highlighted Details

• Automated video playback with anti-detection.
• Chapter quizzes integrate "Super题库" (million-level) and LLMs for auto-answering.
• Supports breakpoint resuming.
• Microservices architecture (Dubbo, RabbitMQ, Redis) with K8s support.
• Claims 99.9% task success rate.

Maintenance & Community

Actively maintained, with v1.0.1 released May 17, 2025. Feedback via GitHub Issues, support@xxtmooc.com, and QQ group 1033757261. Contributions welcomed via PRs and Discussions.

Licensing & Compatibility

Licensed under Apache-2.0. Supports self-deployment and commercial operation, compatible with commercial use.

Limitations & Caveats

The exam system module is under development. Full features require complex middleware setup. A disclaimer warns against academic misconduct, with developers disclaiming liability for misuse.