Project Overview: RAG CV Builder

RAG CV Builder is a high-performance, NestJS-based backend application designed to revolutionize CV management through Retrieval-Augmented Generation (RAG) capabilities. It provides a robust infrastructure for building, managing, and optimizing professional resumes while integrating advanced features like AI-driven mock interviews.

🚀 Key Features

• RAG-Powered CV Management: Leverages Retrieval-Augmented Generation to assist users in building and refining CVs with intelligent data retrieval.

• AI Mock Interviews: A dedicated module that includes WebSocket-based real-time events, structured data flow, and customizable interview configurations.

• Secure Authentication: Fully integrated with Clerk to ensure secure user management and identity verification.

• High Performance & Scalability: Utilizes Redis and Cache Manager for optimized data retrieval and system responsiveness.

• Clean Architecture: Built with a modular design that enforces a clear separation of concerns, making the system maintainable and extensible.

• Type Safety: Developed using TypeScript 5.7 and Prisma 7 to ensure end-to-end type safety across the database and application logic.

📂 Project Structure & Development

The backend is organized into a highly structured environment to support collaborative development:

• Modular Data Flow: The system architecture follows a strict module structure, particularly for complex features like the Mock Interview engine.

• API Excellence: Comprehensive API documentation is provided via Swagger/OpenAPI, allowing for easy integration and testing.

• Strict Conventions: The project adheres to predefined code conventions, standardized error handling, and environment configurations to maintain high code quality.

• Automated Workflow: Uses Git hooks and standardized commit practices to ensure a consistent development lifecycle.

💡 Notable Modules: Mock Interview

A standout component of this project is the Mock Interview feature, which includes:

• WebSocket Integration: Supports real-time communication for interactive interview sessions.

• Configurable Logic: Allows for specific configurations to tailor the interview experience to different industries or roles.

• Structured Data Handling: Detailed documentation on data flow and event handling ensures the AI-driven interview process is seamless.