1. Project Overview

AI tutor system

AI tutor - Intelligent education support system

Based on RuoYi-Vue + Ollama + Dify's AI Education Support System

AI Tutor is a smart education support system that integrates multi-modal data analysis and knowledge graph technology to build a highly matched smart question engine with classroom teaching content, achieving high-precision responses to individual student questions. The system deeply integrates discipline knowledge systems and cognitive laws, breaking through traditional passive learning bottlenecks, and promoting the "teacher-led + AI-assisted" collaborative teaching mode.

2. Open Source License

Licensed under MIT

3. Screenshots

System Demonstration

4. Feature Overview

 Core Features

• Agent Work Link
  : Teachers can generate practice questions and examination questions with one click, reducing the burden of lesson preparation
• Multi-Tenant Architecture
  : Data isolation is achieved from the college perspective, ensuring data security and privacy
• AI Precise Companion
  : Based on large model intelligent question-answering, reducing learning barriers
• Real-time Student Tracking
  : Dynamically analyzing student inquiry situations, learning progress, and creating student portraits
• Course Fine-Grained Management
  : Teachers can create new courses and add students, achieving precise teaching
• Knowledge Base Customization
  : Supporting domain knowledge customization, improving answer accuracy

Teacher End

Student End

Future Planning

Smart Classroom Interactive Module

Real-time analysis of student classroom discussion data, dynamically generating guiding questions, stimulating in-depth thinking and cross-disciplinary thinking. Suitable for "Science and Ethics" and other general courses, promoting critical thinking cultivation through structured guidance.

Assistant Teacher Generation of Teaching Content

Using generative AI technology, assisting teachers in quickly generating courseware, lecture notes, and cross-disciplinary teaching cases, based on knowledge graphs generating comprehensive content from multiple disciplines, enhancing classroom appeal.

Automated Question Generation and Grading

Through NLP and automatic evaluation algorithms, generating diverse questions and supporting open-ended assignments automatic grading, reducing teacher burden, and providing personalized feedback mechanisms.

AI-Generated Cross-Disciplinary Teaching Resource Library

Using generative AI and knowledge graphs, building multi-modal cross-disciplinary resource libraries, supporting resource dynamic updates and regular crawling, ensuring content timeliness.

Automatic Academic Writing Guidance Tool

Providing students with paper structure optimization, literature recommendation, and language polishing support, through knowledge graphs recommending cross-disciplinary reference literature, enhancing academic writing ability.

Project Advantages

Self-developed management system, precise matching of education scenarios

Based on large model technology framework, building core engine, self-developed intelligent interactive system, and knowledge management platform, ensuring efficient teacher-student interaction and problem response.

Layered Level Customized Development, Adapting to Multiple Education Demands

Supporting discipline knowledge system modular configuration, flexible adjustment of learning paths and recommendation strategies, providing personalized layered teaching services.

Dynamic Evolution of System Architecture, Ensuring Continuous Service Capability

Using incremental knowledge update architecture and large model fine-tuning framework, supporting real-time updates and dynamic optimization, maintaining knowledge forefront.

5. Tech Stack

Technical Architecture

Front-end Technology

• Vue 2.x (Backend Management System)
• Vue 3.x (User End)
• Element UI/Element Plus
• Axios Request Library
• ECharts Data Visualization

Back-end Technology

• Spring Boot 2.7.x
• Spring Security Security Framework
• MyBatis ORM Framework
• Redis Cache
• JWT Authentication
• MySQL Database

AI Technology

• Ollama Local Large Language Model Deployment
• Dify AI Application Development Platform
• Knowledge Graph and RAG Search Enhancement
• Multi-modal Data Processing

  Deployment Method

Localized Deployment (Hardware Not Included)

Provide localized deployment services, customers can deploy to local servers or cloud environments according to their needs, ensuring data security and system stability.

git clone AI Tutor System

# Backend Environment Requirements
JDK >= 1.8
MySQL >= 5.7
Redis >= 5.0

# Frontend Environment Requirements
Node.js >= 12.0

# Backend Start

cd ruoyi-admin
mvn spring-boot:run

# Frontend Start
cd ruoyi-ui
npm install
npm run dev