SemanticPDF: Drag, Drop, Semantic Search - SemanticPDF is a simple, privacy-focused application that makes it easy to upload a PDF file and perform a semantic search on contents.

Python program for searching pdf text, ranking the results and exporting highlighted search results in pdf. Uses trie structure, stack, heap, page graph. Converts queries to postfix notation. Allows for logical expressions and phrases. Offers did you mean functionality.

Use semantic search on PDFs locally

In Development

DocuVisQA(Document Visual Question Answering) is a Python project that leverages Google's Generative AI and Langchain for document processing, text splitting, and question answering. It also supports image processing with Streamlit for interactive UI.

vue功能最全的pdf组件，支持渲染、页码提取与跳转、文件加载完成监听、页面变化监听、文本搜索、关键词高亮、目录提取

Programa que busca uma lista de nomes das Partes Processuais nos PDFs do Diário Oficial.

A document indexing daemon that can populate Elasticsearch indexes with the contents and metadata of a number of document types including PDF, image scans, etc. Used to power Facile Search, however can be re-used for anything that requires search indexing for scanned documents.

Given a set of PDFs and the query, the most relevant pdf can be found with the help of TF-IDF. The code has not used any library to implement TF-IDF

Are you short on time?! Can't you search all the PDFs one by one for the content you want?! Well, PDF-Founder is here...

Resume search application using openai RAG and file search . A demo application which shows power of RAG from openai to simplify resume screening . Open source VLM model example to follow

A decentralized AI platform, crafted exclusively for students to revolutionize learning experience.

PDF Parser built in Rust

A web interface that allows searching for PDFs by their content

Website in PHP to index all pdf content and easy way to find any text

Live website to parse multiple PDFs using PDF.js to find matching text

🚀 Revolutionize your data interaction with a cutting-edge chatbot built on Retrieval-Augmented Generation (RAG) and OpenAI’s GPT-4. Upload documents, create custom knowledge bases, and get precise, contextual answers. Ideal for research, business operations, customer support, and more!