ollamark is a command-line client for Ollama with markdown support. It allows users to execute prompts with various options like model selection, system prompts, temperature control, and output formatting (JSON, HTML).
A cat(1) clone with syntax highlighting and Git integration.
MDColor is a Python script designed for Linux terminals that takes Markdown text via piped input and outputs a colorized and styled version directly to your terminal. It enhances readability by applying ANSI escape codes for bold, italic, headers, code blocks (with syntax highlighting via Pygments for supported languages), lists, links, and more.
MarkItDown is an open-source Python utility that simplifies converting diverse file formats into Markdown, designed to prepare data for LLMs and RAG systems. It handles various file types, preserves document structure, and integrates with LLMs for tasks like image description.
This article details a method for converting PDFs to Markdown using a local LLM (Gemma 3 via Ollama), focusing on privacy and efficiency. It involves rendering PDF pages as images and then using the LLM for content extraction, even from scanned PDFs.
The article provides a tutorial on creating checklists in Markdown for GitHub repositories, issues, and pull requests. It explains how to make task lists more manageable and introduces GitHub’s functionality to enhance these lists for better project tracking and task management.
Mods is a tool to add AI to your command line and pipelines, using Large Language Models to format command output in Markdown, JSON, and other text-based formats.
A comprehensive guide to formatting text in Discord, including colors, bold, italics, underlines, strikethrough, code blocks, and spoiler tags.
The article presents ten lesser-known but highly useful GitHub Actions that can enhance workflow automation, focusing on tasks like YAML validation, markdown link checking, auto-assignment of PRs, commit message linting, dependency caching, Slack notifications, license compliance checking, PR size labeling, security scanning, and Jira integration.
ReaderLM-v2 is a 1.5B parameter language model developed by Jina AI, designed for converting raw HTML into clean markdown and JSON with high accuracy and improved handling of longer contexts. It supports multilingual text in 29 languages and offers advanced features such as direct HTML-to-JSON extraction. The model improves upon its predecessor by addressing issues like repetition in long sequences and enhancing markdown syntax generation.
