A NPM Package built on top of pdf-lib that provides functonalities like merge, rotate, split,download pdf to disk and many more...

Built with pdf-actions NPM package.

The Document Summarizer leverages Hugging Face’s facebook/bart-large-cnn model to transform lengthy documents into concise summaries. Built with ReactJS (Vite) for the frontend and Flask for the backend, it supports PDF and text files, offering real-time summarization for researchers, students, and professionals.

A web app that allows users to upload PDFs and interact with them through a Q&A interface. The application extracts text from PDFs, generates embeddings, stores them in a FAISS database, and retrieves relevant information to provide context-aware answers using a large language model .

A modern, intelligent invoice processing system with advanced multi-format data extraction capabilities. Process invoices from PDFs, Excel files, and images with smart data recognition.

Azure Document Intelligence Result Processor: A toolset for annotating PDFs based on Azure Document Intelligence analysis results, featuring a React web application and a standalone Python script for processing and visualizing extracted data with confidence indicators.

A powerful Chromium extension that leverages the multiple AI APIs to assist with various text operations, image analysis, and PDF processing.

AI-powered PDF Assistant: Upload PDFs and ask questions about the content with intelligent answers powered by FastAPI and LangChain. Option to check Better Answer for enhanced responses.

A simple Express.js API for embedding watermarks on PDF files using pdf-lib and multer. This project demonstrates how to apply forensic watermarks with user details (or unique identifiers) to each page of a PDF, helping deter unauthorized distribution while maintaining user privacy.