Seba is an AI-powered educational platform designed to provide personalized, emotionally intelligent tutoring for students.
The system addresses major challenges in the Egyptian education system such as:
- Overcrowded classrooms
- Lack of personalized learning
- High cost of private tutoring
Seba transforms traditional LMS into an intelligent virtual teacher using advanced AI techniques like RAG and emotion detection.
- Emotion-aware AI Tutor (detects student feelings)
- Curriculum-based responses using RAG
- Bilingual support (Arabic / English)
- Learning analytics dashboard
- Dynamic quiz generation
- Microservices architecture with Docker
- Frontend: React (RTL support for Arabic)
- Backend: FastAPI (Python)
- AI Engine: RAG + NLP models
- Vector Database: FAISS
- Emotion Detection: RoBERTa (GoEmotions)
- Deployment: Docker & Microservices
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Student sends a question (Arabic or English)
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System analyzes emotion using NLP
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Query is processed using Hybrid RAG:
- Semantic Search (FAISS)
- Keyword Search (BM25)
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AI generates response based on curriculum
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System adapts explanation based on student emotion
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Dynamic quiz is generated based on performance
- Python (FastAPI, NLP libraries)
- Hugging Face Transformers
- FAISS (Vector Search)
- React + TypeScript
- Docker & Docker Compose
- SQLite / PostgreSQL
docker-compose up --buildcd backend
pip install -r requirements.txt
uvicorn app:app --reloadcd frontend
npm install
npm run dev- Build an emotion-aware AI tutor
- Implement Hybrid RAG system
- Support Arabic + English (RTL)
- Provide learning analytics dashboard
- Ensure scalable architecture
- Follow WCAG accessibility standards
- Students needing personalized explanations
- Teachers tracking student performance
- Reducing dependency on private tutoring
- Voice interaction (Speech-to-Text)
- Mobile application
- Advanced deep learning models
- Cloud deployment
- Nehal Kamal & teammates in graduation project
This project is developed as a Graduation Project for the Artificial Intelligence Engineering Program at Mansoura University.
It demonstrates the integration of:
- AI in Education
- Emotion-aware systems
- Retrieval-Augmented Generation (RAG)
- graduation project 2 Final.pdf