AI Powered College Enquiry Chatbot

Abstract

Educational institutions receive numerous enquiries from students and parents regarding admissions, courses, fees, examinations, and placements. Handling these enquiries manually increases the workload of administrative staff and may lead to delayed or inconsistent responses. To overcome this problem, this project presents an AI-Powered College Enquiry Chatbot that automates common college-related queries using Retrieval-Augmented Generation (RAG).The system is developed using a three-tier architecture consisting of a React frontend, Node.js/Express.js backend, and MongoDB database. The chatbot uses LangChain and Google Generative AI to understand user queries and generate relevant responses. Frequently Asked Questions (FAQs) are converted into vector embeddings and stored in a vector store. When a user submits a query, the system performs similarity search to identify the most relevant FAQ. If the similarity score satisfies a predefined confidence threshold, the retrieved information is provided to the language model to generate a suitable response. If no relevant information is found, the chatbot provides a safe fallback response, reducing the possibility of incorrect or hallucinated answers.The system also provides an administrative dashboard for managing FAQ content and monitoring chatbot performance. JWT authentication and bcrypt password hashing are used to secure administrator access. User conversations and feedback are stored in MongoDB along with useful metadata such as category, confidence score, and fallback status. This helps administrators identify missing information and improve the chatbot's knowledge base.