🚀 ENTC AI Assistant

A production-style AI-powered academic assistant built for ENTC (Electronics & Telecommunication) students, using a decoupled frontend–backend architecture.
This project demonstrates real-world usage of automation workflows, AI services, and cloud deployment.

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📌 Project Overview

ENTC AI Assistant allows students to ask subject-related technical questions and receive structured, exam-oriented responses.

The system is designed with clear separation between:

• Frontend (UI)
• Automation & workflow logic
• AI processing layer

⚠️ Note: AI responses depend on backend services (n8n + OpenAI). The frontend remains functional even if the AI service is unavailable.

📂 Project Structure

entc-ai-assistant/ │ ├── index.html # Main user interface ├── style.css # Styling and layout ├── script.js # Frontend logic & API calls ├── netlify.toml # Netlify configuration └── README.md # Project documentation

🧠 Features

• Clean, responsive user interface
• Asynchronous AI query handling
• Decoupled frontend and backend design
• Automation-driven request processing using webhooks
• Scalable architecture for future expansion

🧩 System Architecture

User (Browser) ↓ Frontend (HTML + CSS + JS) ↓ Netlify Hosted Site ↓ Webhook Request ↓ n8n Workflow Engine ↓ OpenAI API ↓ AI Response ↓ Frontend UI

🛠️ Tech Stack

Frontend

• HTML5 – semantic markup
• CSS3 – modern UI and responsive layout
• JavaScript (ES6+) – Fetch API and async logic

Backend & Automation

• n8n – workflow automation engine
• OpenAI API – AI-based answer generation

Deployment & DevOps

• GitHub – version control and project hosting
• Netlify – frontend deployment
• Webhooks – frontend–backend communication

⚙️ How It Works

1. User enters a technical question in the UI
2. Frontend sends a POST request via Fetch API
3. Request reaches an n8n webhook
4. n8n processes the request and calls OpenAI
5. AI-generated response is returned
6. Answer is displayed on the frontend

🚧 Project Status

• ✅ Frontend completed and deployed
• ✅ GitHub repository structured
• ⚠️ AI responses depend on backend API configuration
• 🔄 Improvements planned (see below)

🔮 Future Enhancements

• Exam-oriented formatting (SPPU / GATE)
• User authentication
• Database-backed answer caching
• Admin dashboard for monitoring workflows
• Security and rate limiting

🎓 Academic & Portfolio Value

This project demonstrates:

• Practical AI integration
• Automation workflows using n8n
• API-based system design
• Cloud deployment experience
• Real-world frontend–backend separation