GDGC-MET / GDGC-MET/SmartCampus-VibeCoding

AI Chatbot for Student Queries

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#2 0 comments 0 reactions 1 assignee Assigned to @umeshpagere View on GitHub
good first issue Hacktoberfest 2025
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Description

🧠 Project Overview

The AI Chatbot for Student Queries is an intelligent virtual assistant designed to help students instantly access campus-related information anytime, anywhere. It acts as a 24×7 digital guide that can answer questions about college events, class schedules, and facilities in a simple, conversational way.

This chatbot uses Natural Language Understanding (NLU) to interpret student queries and respond intelligently. The goal is to make campus information easily accessible — without needing to browse websites or contact faculty.

🚀 Key Features
• 🗓 Event Information:
Students can ask questions like “What events are happening this week?” or “Is there a workshop today?” and instantly get event details.
• 📚 Timetable Access:
Provides personalized class schedules, timings, and faculty info — e.g., “When is my next class?” or “Where is my Data Structures lecture?”
• 🏫 Facility Details:
Students can ask about campus facilities — “What time does the library close?” or “Is the gym open on Sunday?”
• 💬 Natural Conversations:
The chatbot understands everyday language using NLU-based intent detection.
• 🌐 Simple Chat Interface:
A modern, user-friendly frontend built with React + Tailwind, featuring smooth chat animations and dark/light mode.
• ⚡ Real-Time Backend:
Flask-based backend that connects the chat interface with the NLU engine and local database.

⚙️ Tech Stack

Component Technology Used
Frontend React.js + Tailwind CSS
Backend Flask (Python)
NLU / Intent Detection Rasa NLU / Custom keyword model
Database SQLite / JSON files
Hosting Local or Cloud (Render, Vercel, or Railway)

🧩 System Flow
1. The student sends a query in natural language.
2. The chatbot identifies intent (like get_event_info or get_timetable).
3. It fetches relevant data from the database.
4. The response is formatted and displayed in the chat UI.

Student → Chat UI → Flask Backend → NLU Model → Database → Response → UI

🌟 Future Enhancements
• Integrate voice recognition for hands-free use.
• Add LLM-based fallback (e.g., GPT API) for open-ended queries.
• Enable personalization with student login (show individual schedules).
• Support for multi-language interaction (English, Hindi, Marathi, etc.).
• Deploy on Telegram / WhatsApp for easier accessibility.

💡 Vision

To make campus life smoother by providing every student with a smart, instant, and friendly way to access college information — powered by AI.

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