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An AI-powered scientific literature search engine that uses OpenAI's language models to analyze research papers. It enables users to extract data, ask complex questions, and perform ad hoc literature reviews, handling hundreds of papers simultaneously without needing metadata.
A repository that contains some personal and shared code for PDF Processing Utilities. This is only for educational purposes please do not redistribute.
This repository contains a Python-based search engine designed for parsing and searching PDF documents. It was made for a data science and algorithms class. The project features advanced search capabilities, including PageRank, graph structures, trie-based indexing, intelligent query handling...
This application facilitates the comparison of two PDF files. Differences are presented in a table, color-coded as red (deletions), green (additions), and orange (moved text). Users can save the results in Excel format. It is designed to check whether annotations have been taken into account during the comparison process.
This project is a web application built using the Flask framework that allows users to upload a PDF file containing text and converts it into a new PDF file where each page of the original PDF is represented as an image. The application will use the PyMuPDF library to read and convert the text pages into images and also to write the new PDF file.