⚡ VeriResume: ATS Optimization Engine

VeriResume is a high-performance full-stack web application designed to automatically tailor resumes to specific job descriptions using LLMs. It generates a pixel-perfect, ATS-compliant Harvard OCS format resume by seamlessly interpolating and rewriting your experiences against targeted technical requirements.

Built with bleeding-edge technologies, VeriResume provides a premium, consumer-grade experience with real-time UI/UX, robust background task processing, and a high-fidelity client-side PDF rendering engine.

🚀 Key Features

• Intelligent AI Fabrication: Driven by nvidia/nemotron-3-super-120b-a12b:free (via OpenRouter), the engine automatically blends and rewrites project history for 100% job description matching without dropping authentic context.
• Harvard OCS Renderer: Instead of generic templates, VeriResume programmatically renders the industry-standard Harvard A4 plain-text Resume style to ensure maximum Applicant Tracking System (ATS) compatibility.
• Intelligent Pagination Engine: A bespoke block-level pagination algorithm automatically prevents text overflow and slice-cutting by tracking exact Times-New-Roman kerning heights and natively splitting onto multiple distinct pages before export.
• Side-by-Side Audit Workflow: The modern "Audit" dashboard allows users to compare their exact changes and additions in a sticky, side-by-side grid before exporting identical layouts to PDF.
• Credits & Transaction Engine: Manages user limits utilizing a pessimistic credit transaction layer synced to Supabase data models.

💻 Tech Stack

Frontend (User Interface)

• Framework: Next.js 16 (App Router)
• Styling: Tailwind CSS + Shadcn UI Components
• Rendering: html-to-image and jsPDF for seamless high-res PDF extraction without color space crashes
• Animation: Native CSS + Radix UI Primitives

Backend (AI & Logic)

• Framework: Django (Python) + Django REST Framework
• Background Processing: Celery + Redis (for handling slow LLM response iterations securely)
• AI Integrations: OpenRouter (openai wrapper package) for highly configurable prompt injection
• Parsing: PyPDF2 and docx2txt for ingesting legacy resumes

Infrastructure (Data & Auth)

• Database: Supabase (PostgreSQL)
• Authentication: Supabase Auth (Magic Links, OAuth)
• Storage: Supabase Storage Buckets

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🛠️ Installation & Setup

1. Clone the repository:

   git clone https://github.com/yourusername/veriresume.git
   cd veriresume

2. Frontend Setup: Navigate into the Next.js workspace and install dependencies.

   cd Frontend
   npm install
   npm run dev

3. Backend Setup: Navigate to the Django workspace, create a virtual environment, and boot it.

   cd Backend
   python -m venv venv
   source venv/Scripts/activate # or venv/bin/activate on Mac
   pip install -r requirements.txt
   python manage.py migrate
   python manage.py runserver

4. Environment Variables: You will need to construct .env files in both the Frontend/ and Backend/ directories.

   • Frontend: Requires NEXT_PUBLIC_SUPABASE_URL and NEXT_PUBLIC_SUPABASE_ANON_KEY.
   • Backend: Requires SUPABASE_URL, SUPABASE_ANON_KEY, SUPABASE_SERVICE_ROLE_KEY, and OPENAI_API_KEY (mapped to OpenRouter).

📄 License

This project is licensed under the MIT License.