ResumeTex - AI-Powered PDF to LaTeX Resume Converter

Project Overview

ResumeTex is an advanced web application built using modern technologies that transforms traditional PDF resumes into professionally formatted LaTeX documents. With AI-driven processing, users can effortlessly convert their resumes and select from elegant pre-built templates.

My Role

As the sole developer of ResumeTex, I designed and implemented both the frontend and backend of the application. From conceptualizing the architecture to deploying the final product, I handled every aspect of the development process. This included integrating AI services, creating a seamless user experience, and ensuring secure and efficient file management.

Key Contributions:

• Developed the frontend using React.js with Vite, ensuring a responsive and interactive user interface.
• Built the backend with Express.js, integrating Google’s Generative AI (Gemini) for text extraction and processing.
• Implemented secure file storage with Cloudinary and efficient PDF handling using pdf.js and busboy.
• Created dynamic UI elements with framer-motion for engaging animations.
• Ensured performance optimization, security measures, and comprehensive error handling.

Project Goals and Impact

Goals

• Simplify the process of converting traditional PDF resumes into professionally formatted LaTeX documents.
• Provide users with customizable templates for polished resume outputs.
• Leverage AI to enhance text extraction and document structuring.

Impact

• Enabled job seekers and professionals to create high-quality resumes effortlessly.
• Reduced manual effort in converting resumes to LaTeX format.
• Provided a platform for users to directly preview, edit, and download LaTeX-based resumes.

Problem Solved

Before ResumeTex, converting a standard PDF resume to a LaTeX document was a tedious and error-prone process requiring technical expertise. ResumeTex automates this task, saving time and effort while ensuring professional formatting.

Key Features

1. Template Selection

• Multiple LaTeX templates available
• Visual previews of templates for easy selection
• Interactive and user-friendly design

2. AI Processing

• Integration with Google’s Generative AI (Gemini) for precise text extraction and formatting
• Multiple API key support for load balancing
• Smart fallback options when APIs are overloaded

3. File Management

• Automatic file cleanup after 5 minutes for enhanced security
• Secure and efficient file handling
• Support for various PDF formats

4. User Interface

• Responsive design for all devices
• Interactive animations and hover effects using framer-motion
• Toast notifications for progress tracking and error handling
• Smooth PDF previews with progress indicators

5. Security & Performance

• Configured CORS for secure origins
• Environment variable management for sensitive keys
• File size limitations to maintain performance
• Load balancing with multiple API keys

Application Flow

1. Initial Upload:
   • User lands on the homepage (BeforeAfterPage)
   • Selects a preferred LaTeX template (v1 or v2)
   • Uploads a PDF resume via FileUploader
2. Processing Pipeline:
   • PDF Upload → Cloudinary Storage → PDF Text Extraction → Gemini AI Processing → LaTeX Generation → PDF Conversion
3. Result Viewing:
   • User is redirected to ResponsePage to view:
     • PDF preview
     • Generated LaTeX code
     • Option to open in Overleaf for further editing
     • Downloadable PDF option

Tech Stack

Frontend:

• Framework: React.js with Vite
• Styling: TailwindCSS
• Key Libraries:
  • react-router-dom for routing
  • framer-motion for animations
  • react-pdf for seamless PDF preview
  • axios for API calls
  • react-hot-toast for notifications

Backend:

• Framework: Express.js (Node.js)
• Key Services & Libraries:
  • Google’s Generative AI (Gemini) for AI processing
  • Cloudinary for secure file storage
  • pdf.js for PDF text extraction
  • busboy for efficient file upload handling

Security & Performance Enhancements

• CORS configuration for trusted origins
• Environment variable handling for secure key management
• Temporary file storage with automatic cleanup
• Error handling and user feedback through notifications

Additional Features

• PDF proxy viewing
• LaTeX code copying
• Direct integration with Overleaf
• Progress tracking during conversion
• Detailed error handling with user feedback
• Interactive background elements with hover effects

Skills Demonstrated

1. Full-Stack Development: Expertise in creating both frontend and backend solutions for web applications.
2. AI Integration: Seamlessly incorporating AI services like Google’s Generative AI (Gemini) for enhanced processing.
3. Responsive UI Design: Developing user-friendly interfaces with React.js, TailwindCSS, and framer-motion.
4. Secure File Handling: Implementing robust file storage and cleanup mechanisms with Cloudinary and file management libraries.
5. Performance Optimization: Ensuring efficient API handling, load balancing, and comprehensive error management.

Conclusion

ResumeTex showcases a full-stack application combining AI, modern web technologies, and professional document processing. It’s ideal for anyone looking to streamline resume conversion to LaTeX with precision and style.