ChatbotEdu – An Intelligent RAG-Powered Educational Assistant for ENSET 📚
🔗 GitHub Repository: ChatbotEdu on GitHub
👨💻 Authors:
- TANGARA YOUSSOUF – Lead Developer
- TSEH KOKOU BENOIT – Lead Developer
🔍 An Intelligent Learning Assistant for Personalized Education
ChatbotEdu isn’t just another chatbot—it’s a revolution in digital learning! By combining artificial intelligence, multimodal capabilities, and advanced document retrieval, ChatbotEdu delivers an unparalleled interactive learning experience for students.
Built on RAG (Retrieval-Augmented Generation) architecture, it goes beyond conventional chatbots by integrating a cutting-edge LLM (Large Language Model) with a rich database of educational resources. The result? Context-aware, precise, and well-referenced answers tailored to students’ academic needs.
💡 What Makes ChatbotEdu Stand Out?
📖 Advanced Contextual Understanding
ChatbotEdu doesn’t just generate random answers—it interprets student questions, explores its knowledge base, and provides well-structured, relevant explanations aligned with academic requirements.
🔎 Intelligent Search & Knowledge Synthesis
- FAISS-powered search engine: Rapidly retrieves the most relevant educational documents.
- LLM-enhanced responses: Generates insightful answers based on validated academic sources.
- Source referencing: Ensures transparency and reliability by displaying cited materials.
🖼️ Multimodal Intelligence – Visual & Text-Based Learning
Education isn’t just about text! ChatbotEdu analyzes and understands images, diagrams, and documents using two cutting-edge technologies:
🔹 CLIP / Gemini Vision: Extracts key concepts and insights from images.
🔹 OCR (Optical Character Recognition): Reads and processes PDFs, scanned documents, handwritten notes, and complex diagrams for enhanced accuracy.
By combining CLIP + OCR, ChatbotEdu achieves unmatched document comprehension, allowing it to extract formulas, analyze charts, and decode handwritten academic content with precision.
👩🎓 User-Friendly Interface & Optimized Experience
- JavaFX-based frontend: Modern and intuitive UI for seamless interactions.
- Conversation history tracking: Enhances progressive learning.
- Multilingual support (coming soon!): Making AI education accessible to all.
⚙️ Architecture & Technology Stack
ChatbotEdu is built on a robust and scalable architecture, integrating cutting-edge technologies for maximum performance:
📌 Frontend: JavaFX – Intuitive user interface.
📌 Backend: FastAPI / Flask – Fast and secure API framework.
📌 AI Engine: **Gemini API ** for advanced text generation.
📌 Database: MySQL – Structured data storage.
📌 Search Engine: FAISS – High-speed document retrieval.
📌 Multimodal Capabilities: CLIP + OCR – Advanced image analysis and text extraction.
🚀 Impact & Vision
🔹 Revolutionizing education by offering an intelligent learning assistant.
🔹 Providing seamless access to academic resources through AI-powered search.
🔹 Developing a high-performance, reliable AI to support students throughout their studies.
🔹 Evolving into a comprehensive educational platform with multiple learning modes.
🖥️ Screenshots – ChatbotEdu Interface
Below are some screenshots showcasing ChatbotEdu’s powerful and intuitive interface:
1️⃣ Chatbot Main Interface and Document Search in Action
2️⃣ Multimodal Image Analysis and Conversation History & User Interaction
🏆 Why ChatbotEdu Deserves to Win?
✅ A groundbreaking AI-powered solution that combines RAG, multimodality, and search intelligence.
✅ A real-world application with a direct impact on education.
✅ A highly optimized technical implementation for speed and accuracy.
✅ A seamless, intuitive user experience designed specifically for students.
🚀🔥 ChatbotEdu isn’t just an AI assistant—it’s the future of smart education. 🌟
🔗 GitHub Repository: ChatbotEdu on GitHub
👨💻 Authors:
- TANGARA YOUSSOUF – Lead Developer
- TSEH KOKOU BENOIT – Lead Developer