prism-pdfs

byAanal Trivedi

PROMPT: Build a full-stack SaaS web application for automated PDF network map comparison and annotation. 🎯 Product Overview The system allows users to upload "Before" and "After" PDF network maps. The backend processes these files using AI/ML pipelines to detect differences and generates annotated PDFs. 🧱 Core Modules 1. Authentication & User Management JWT-based authentication Role-based access (Admin, User) User invitation via email Bulk user upload (CSV) User profile management 2. Project Management Create, edit, delete projects Each project contains: Name Description Created by Status (Pending, Processing, Completed, Failed) 3. File Upload & Processing Upload "Before" and "After" PDFs Store files securely (S3 or local storage) On upload → trigger async job queue Track processing status 4. Queue System (VERY IMPORTANT) Implement background job processing Use queue system (Celery + Redis or equivalent) Jobs: PDF ingestion AI processing Change detection PDF annotation generation 5. AI Processing Pipeline (Mock initially) Placeholder API endpoints for: Object detection Change detection Rules engine Design system to support future integration with: YOLO models PyMuPDF processing 6. Dashboard UI Home dashboard showing: Total projects In-progress jobs Completed jobs Project list view with filters: Status Date Real-time status updates 7. File Preview & Download Preview PDFs in browser Download annotated output file 8. Notifications Email notification on: User invitation Job completion Job failure 🎨 UI/UX Requirements Clean modern dashboard UI Use color theme: Primary: #1954BF Accent: #F0B70F Responsive design Sidebar navigation Status badges (Processing, Completed, Failed) ⚙️ Tech Stack Preferences Frontend: React (with modern UI library) Backend: Django / FastAPI Database: PostgreSQL Queue: Celery + Redis Storage: AWS S3 (or local fallback) Deployment: Docker + Kubernetes 🔌 API Requirements REST APIs for all modules Proper error handling Pagination, filtering, sorting 🧪 Testing Unit tests for backend API testing Basic UI testing 🚀 Deployment Setup staging and production environments Dockerized services CI/CD pipeline 📊 Additional Requirements Scalable microservice-friendly architecture Logging and monitoring support Secure file handling 🧠 Important Instructions Build production-ready architecture, not prototype Keep backend modular for AI integration later Ensure async processing is reliable and scalable