A Python package for converting PDFs to markdown while extracting images and tables, generate descriptive text descriptions for extracted tables/images using several LLM clients. And many more functionalities. Markdrop is available on PyPI.

Docling with Ollama - RAG on Local Files with Local Models

Collection of PDF parsing libraries like AI based docling, claude, openai, llama-vision, unstructured-io, and pdfminer, pymupdf, pdfplumber etc for efficient snapshot, text, table, and metadata extraction.

Chat to your Database GenAI Chatbot

A python library and CLI tool to convert PDF files to CSV files.

Autonomous agent networks for task automation that requires multi-step reasoning

OpenHealth, AI Health Assistant | Powered by Your Data

Docling4j brings the functionalities of Docling in document understanding to Java® projects

Parse documents using AI - any document converted to markdown suitable for RAG applications

Developed an intelligent AI chatbot utilizing the DeepSeek LLM, designed for efficient interaction with large documents such as textbooks and study materials. Integrated Docling for parsing and processing large files, and implemented a Retrieval-Augmented Generation (RAG) pipeline using FAISS and Sentence Transformers to optimize context retrieval

A Python package for converting PDFs to markdown while extracting images and tables, generate descriptive text descriptions for extracted tables/images using several LLM clients. And many more functionalities. Markdrop is available on PyPI.

This repo contains codes for RAG using docling on colab notebook with langchain, milvus, huggingface embedding model and LLM

🧙‍♂️AI-powered tool to optimize your CV with job-specific keywords and align it to your dream job.

📄 A template for project for creating a chainlit application, using a locally run model via ollama and qdrant vector database for document retrieval.

Retrieval-Augmented Generation server with Pinecone and OpenAI

OnnxTR OCR plugin for Docling

convert pdf document to audiobook cli

Agentic RAG-based system with nursing handbooks and transes as knowledge base for my bebiloves

This project is an AI-powered Contract Risk Assessment and Legal Assistant designed to analyze legal documents, extract key clauses, assess risks, and provide actionable recommendations. Additionally, a fine-tuned conversational chatbot is integrated for interactive legal Q&A based on contract-specific knowledge.

An intelligent document Q&A application that leverages AI to extract insights from various document types. This application combines document processing capabilities with vector database storage, advanced table extraction, mathematical formula rendering, and OCR to create a comprehensive Retrieval Augmented Generation (RAG) system.