Use TradeRepublic in terminal and mass download all documents

JavaScript bindings for MuPDF

Free open-source web software for signing PDF (alone or with others) and also organize pages, edit medata and compress pdf

Conversion of PDF documents to structured Markdown, optimized for Retrieval Augmented Generation (RAG) and other NLP tasks. Extract text, tables, and images with preserved formatting for enhanced information retrieval and processing.

Translate many large PDF Reports for free using Python.

This sample project provides a preview of the PDF Extract API. Using the sample project and this documentation, you will easily be able to integrate the PDF Extract API in your own server-side code.

A Python + C implementation for image-based PDF page layout analysis and content extraction.

A python tool to extract schedule data from PDF timetables and output it in GTFS.

Making an app so that we can read and extract information from prf easily or chat with our pdfs.

This Python script uses pdfminer.six, PyPDF2, pdf2image to extract information (text, image) from pdf paper.

PDF Query LangChain is a tool that extracts and queries information from PDF documents using advanced language processing. Leveraging LangChain, OpenAI, and Cassandra, this app enables efficient, interactive querying of PDF content. Ideal for data analysis, research, and automated reporting, it simplifies detailed document analysis with ease.

R programs used to extract data from various medical reports in PDF format in order to track important biological variables during Jasper's FIP treatment and recovery

Web app to allow users to batch extract text from images and PDFs

Convert your PDFs into audiobooks effortlessly. Features intelligent text extraction, customizable text-to-speech settings, and efficient processing for low-resource systems.

This project is designed to leverage advanced data engineering techniques for the aggregation and structuring of finance professional development materials.

Billionaires RAG Query uses LLMs and a RAG framework to analyze the world's billionaires list. Extracts tabular data from PDFs, converts to multiple formats, and enables precise queries about net worth, age, and more. Integrates with Poetry and asdf for easy setup and management.