The primary objective of the TechRepair project is to develop a centralized digital platform that connects users needing electronic repair services or spare parts with sellers who offer them. It aims to simplify the booking, purchasing, and communication processes through a user-friendly interface and AI-powered chatbot support. For users, the platform offers functionalities such as service and part search by category, online booking, payments, and tracking bookings. For sellers, it provides tools to add services and spare parts, manage bookings, and update order statuses.
This project introduces TechRepair, a comprehensive web-based platform designed to bridge the gap between customers in need of electronic device repairs and sellers offering spare parts and repair services. The system supports two main user roles: User and Seller. Sellers can register, log in, add spare parts and services categorized by type, and manage bookings made by users. Users, on the other hand, can browse categorized items, book or purchase services, and make payments. A unique feature of TechRepair is its AI-powered chatbot integrated into the user dashboard, which assists users by providing real-time information about available spare parts, services, and their booking status.Developed with Java (Spring Boot) for backend logic, ReactJS for a responsive and dynamic frontend, and MySQL for data persistence, the platform ensures a scalable and user-friendly solution for electronic repair services.
Keywords: Electronic Repair Services, Spare Parts Booking, AI Chatbot, Spring Boot, ReactJS, MySQL, Service Marketplace.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

HARDWARE REQUIREMENTS:
Β· Processor: Intel i3 or higher
Β· RAM: 4GB minimum
Β· Hard Disk: 160GB minimum
SOFTWARE SYSTEM CONFIGURATION:
Β· Operating System: Windows 7/8/10
Β· Frontend: ReactJS
Β· Backend: Spring Boot with java
Β· Database: MySQL
Β· AI API: Gemini API for chatbot
Β· IDE: IntelliJ IDEA & VS Code