There are 4 repositories under pdf-processing topic.
Document chatbot — multiple files, topics, chat windows and chat history. Powered by GPT.
MCP server for seamless document format conversion and processing
Multiple and Large PDF Documents Text Extraction.
The Privacy Firewall for LLMs
A boilerplate solution for processing image and PDF documents for regulated industries, with lineage and pipeline operations metadata services.
Official Python client library for Nutrient Document Web Services API - PDF processing, OCR, watermarking, and document manipulation with automatic Office format conversion
This library provides a type-safe and ergonomic interface for document processing operations including conversion, merging, compression, watermarking, and text extraction using Nutrient DWS Processor API.
Anthropic's Contextual Retrieval implementation with visual chunk comparison. Preview context enrichment before/after embedding.
Python scripts that converts PDF files to text, splits them into chunks, and stores their vector representations using GPT4All embeddings in a Chroma DB. It also provides a script to query the Chroma DB for similarity search based on user input.
Local, privacy-friendly resume analysis: convert, classify, and get advice using TF‑IDF, Logistic Regression, and sentence-transformer embeddings.
AI-powered RAG-based tool for summarizing, extracting insights, and answering questions about research papers with high accuracy
A NPM Package built on top of pdf-lib that provides functonalities like merge, rotate, split,download pdf to disk and many more...
LangGraphRAG: A terminal-based Retrieval-Augmented Generation system using LangGraph. Features include message history caching, query transformation, and vector database retrieval. Ideal for NLP researchers and developers working on advanced conversational AI and information retrieval systems.
A powerful, multi-modal Telegram bot leveraging cutting-edge AI technologies including Gemini, DeepSeek, OpenRouter, and 50+ AI models for comprehensive conversational assistance, media processing, and collaborative features with MCP (Model Context Protocol) integration.
📚 AI-Powered Book EPUB Knowledge Extractor & Summarizer Transform your PDF books into structured knowledge effortlessly! This tool leverages AI to analyze books page by page, extracting key insights, definitions, and concepts, and organizes them into Markdown summaries for easier study
Built with pdf-actions NPM package.
A Python library for extracting tables from PDF documents using computer vision and image processing techniques. It converts PDF pages to images, detects tables, recognizes their structure, and outputs clean data in JSON format.
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.
An all-in-one GUI management toolkit built with PyQt6, offering a suite of tools for file synchronization, media organization, PDF merging, code formatting, and more.
MistralOCR is an open-source application that transforms documents into structured data using Mistral AI's OCR capabilities. Built with FastAPI and Streamlit, it provides an intuitive interface for extracting and processing text from PDFs and images, making document digitization effortless and accurate.
Local RAG app with zero-config Docker setup. FastAPI + Streamlit + Qdrant + Ollama. Just run `docker-compose up --build`! 🚀
PdfSnipper is a lightweight and efficient Python package designed to simplify the management of PDF files, pages, and their conversions during various NLP, Computer Vision (CV), or other data processing tasks. The package eliminates the need for repetitive code by providing intuitive, ready-to-use functions for common PDF-related operations.
A powerful Retrieval Augmented Generation (RAG) application built with NVIDIA AI endpoints and Streamlit. This solution enables intelligent document analysis and question-answering using state-of-the-art language models, featuring multi-PDF processing, FAISS vector store integration, and advanced prompt engineering.
A Streamlit-based app for asking questions directly from uploaded documents using Gemini embeddings and a language model. Supports PDF, TXT, and DOCX files. Fast, simple, and powerful document-based QA.
State-of-the-art Optical Character Recognition (OCR) with Vision Language Model (VLM) integration for enhanced accuracy and optimal document processing.
This is some useful mini projects that I had worked for self-learning Python programming.
An intelligent, enterprise-grade document management system that automatically sorts, renames, and archives digital documents using state-of-the-art OCR and AI technology.
[100% Complete] 🎉 Production-ready Adobe CC automation suite. 5,750+ lines: PowerShell + Python. User provisioning, ML license optimization, PDF workflows, compliance auditing. Docker/K8s/Terraform ready.
A side project to easily get and annotate questions and answers to the PsychometryBot project DB using computer vision and pdf parsing
Terminal-based platform where specialized AI experts (Legal, Tech, Business) engage in real-time debates and collaborative problem-solving to provide multi-perspective analysis for complex decisions.
A lightweight, cross-platform .NET library for building RAG (Retrieval-Augmented Generation) pipelines with local embedding models and SQLite vector storage. Perfect for developers who need privacy-focused, offline-capable document search and AI-powered question answering without external API dependencies.
This project uses OCR and a BART-based NLP pipeline to extract and summarize landlord, tenant, property, and contract details from scanned lease agreements. It combines Tesseract OCR, pdf2image, and HuggingFace Transformers to deliver structured legal summaries in JSON format.
Professional document converter with Desktop & Web versions. Unlimited PDF processing, multi-file support. Supports kindergarten project.
AI-powered job search assistant that reads newspapers daily, finds jobs matching your resume using GPT, and alerts you via Telegram. 2025
OllamaMulti-RAG 🚀 is a multimodal AI chat app combining Whisper AI for audio, LLaVA for images, and Chroma DB for PDFs, enhanced with Ollama and OpenAI API. 📄 Built for AI enthusiasts, it welcomes contributions—features, bug fixes, or optimizations—to advance practical multimodal AI research and development collaboratively.