Knowledge Agents and Management in the Cloud
E2M converts various file types (doc, docx, epub, html, htm, url, pdf, ppt, pptx, mp3, m4a) into Markdown. It’s easy to install, with dedicated parsers and converters, supporting custom configs. E2M offers an all-in-one, flexible, and open-source solution.
Easily deployable and scalable backend server that efficiently converts various document formats (pdf, docx, pptx, html, images, etc) into Markdown. With support for both CPU and GPU processing, it is Ideal for large-scale workflows, it offers text/table extraction, OCR, and batch processing with sync/async endpoints.
Parse PDFs into markdown using Vision LLMs
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.
smart-llm-loader is a lightweight yet powerful Python package that transforms any document into LLM-ready chunks. Spend less time on preprocessing headaches and more time building what matters. From RAG systems to chatbots to document Q&A, SmartLLMLoader handles the heavy lifting so you can focus on creating exceptional AI applications.
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.
Turn a supported list of filetypes (e.g. .docx) into a markdown structured text file. Also optionally defangs indicators and extract texts from images. Built for threat intel use-cases.
Quick way to convert files (PDF, DOCX, HTML, PPTX, Images) to (MD, JSON, YAML) using Docling and Streamlit
RAG-Ingest: A tool for converting PDFs to markdown and indexing them for enhanced Retrieval Augmented Generation (RAG) capabilities.
DocuParse is a high-performance tool for converting PDF documents into clean, structured Markdown files. Designed for speed and accuracy, it extracts and formats content while minimizing errors like hallucinations and repetitions.
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