Search Results for "markdown"
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Showing 30 open source projects for "markdown"
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MarkItDown
Python tool for converting files and office documents to Markdown
MarkItDown is a lightweight Python utility developed by Microsoft for converting various files and office documents to Markdown format. It is particularly useful for preparing documents for use with large language models and related text analysis pipelines. -
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PasteMD
Paste Markdown and AI responses into Word Excel instantly fast
PasteMD is a lightweight desktop utility designed to streamline the process of transferring formatted content from the clipboard into office applications such as Word, WPS, and Excel. It primarily targets users who frequently copy content from AI chat tools or web pages and encounter formatting issues, especially with Markdown, tables, and LaTeX formulas. PasteMD operates from the system tray and monitors clipboard content, automatically converting Markdown or HTML into properly formatted documents using Pandoc. With a single global hotkey, users can paste structured content directly into the active application without manual cleanup or reformatting. ... -
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MarkPDFDown
A high-quality PDF to Markdown tool based on large language model
MarkPDFdown is an open-source document processing tool designed to convert PDF files into structured Markdown output that can be easily used for documentation, content pipelines, and AI processing workflows. The project focuses on extracting text, formatting, and structural information from complex PDF documents and transforming that information into clean Markdown that preserves the original hierarchy of headings, paragraphs, tables, and lists. -
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MinerU
A high-quality tool for convert PDF to Markdown and JSON
MinerU is an open-source, high-quality document extraction toolkit focused on converting PDFs (and other document formats) into structured Markdown and JSON. It leverages OCR and layout analysis to preserve semantic structure and metadata, ideal for research and data science workflows. -
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Basic Memory
Persistent AI memory using local Markdown knowledge graphs
Basic Memory is an open source knowledge system that turns AI conversations into persistent, structured knowledge you control. Instead of losing context after each chat, it stores information as simple Markdown files on your device, allowing both you and AI to read and write to the same knowledge base. It uses the Model Context Protocol (MCP) so compatible AI tools can access, update, and build on your notes across sessions. Basic Memory creates a semantic knowledge graph by linking related ideas, making it easier to retrieve, expand, and connect information over time. ... -
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Text Generation Web UI
Oobabooga - The definitive Web UI for local AI, with powerful features
...Notebook mode that resembles OpenAI's playground. Chat mode for conversation and role playing. Instruct mode compatible with Alpaca and Open Assistant formats. Nice HTML output for GPT-4chan. Markdown output for GALACTICA, including LaTeX rendering. Custom chat characters. Advanced chat features (send images, get audio responses with TTS). Very efficient text streaming. Parameter presets, 8-bit mode. Layers splitting across GPU(s), CPU, and disk. CPU mode, FlexGen, DeepSpeed ZeRO-3, API with streaming and without streaming. LLaMA model, including 4-bit GPTQ. ... -
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docext
An on-premises, OCR-free unstructured data extraction
...This allows the system to detect and extract structured elements such as tables, signatures, key fields, and layout information while maintaining semantic understanding of the document content. The toolkit can also convert complex documents into structured markdown representations that preserve formatting and contextual relationships. -
8
Everywhere
Context-aware desktop AI assistant that understands screen content
...It integrates with multiple large language model providers and supports various tools, enabling flexible and extensible AI-powered workflows. Everywhere features a modern design with interactive elements such as markdown rendering, keyboard shortcuts, and voice input capabilities. Additionally, the project emphasizes seamless workflow integration by operating alongside existing applications rather than requiring users to switch. -
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ScrapeGraphAI
Python scraper based on AI
...ScrapeGraphAI is a web scraping python library that uses LLM and direct graph logic to create scraping pipelines for websites and local documents (XML, HTML, JSON, Markdown, etc.). Just say which information you want to extract and the library will do it for you. -
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10
nanochat
The best ChatGPT that $100 can buy
...Its north star is approachability and speed: you can boot a fresh GPU box and drive the whole pipeline via a single script, producing a usable chat model in hours and a clear markdown report of what happened. The code is written to be read—concise training loops, transparent configs, and minimal wrappers—so you can audit each step, tweak it, and rerun without getting lost in framework indirection. -
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Chandra
OCR model for complex documents with layout-aware structured outputs
...It focuses on preserving full document layout, meaning that extracted text is accompanied by positional metadata like bounding boxes for each element. Chandra supports multiple output formats including Markdown, HTML, and JSON, making it suitable for downstream processing and integration into data pipelines. It is capable of handling over 40 languages and is optimized to read difficult inputs such as messy handwriting and multi-column layouts. Chandra can be run locally using transformer-based inference or deployed with a high-performance server setup for large-scale processing. ... -
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ticket
Fast, powerful, git-native ticket tracking in a single bash script
ticket is a lightweight, git-native ticket management tool implemented as a single Bash script that brings powerful issue tracking directly into your Git workflows without requiring a database or complex setup. It stores each ticket as a Markdown file with YAML frontmatter, making them human-readable and easy to version control alongside your code, while also allowing IDEs to jump straight to ticket definitions. The CLI provides common subcommands to create, list, edit, close, and manage dependencies between tickets, enabling clear hierarchical task structures and visual dependency trees. ... -
13
Krixik
Documentation for the Krixik Python client
Small/specialized AI models are an oft-necessary complement—or alternative—to "big AI" offerings. However, infrastructure for small AI tends to be underwhelming, so building with specialized AI can be difficult, time-consuming, and even expensive. Iterating with different models, and particularly with different combinations of these models, can thus be rendered unfeasible. -
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ChatGPT Academic
ChatGPT extension for scientific research work
...Support for markdown tables output by GPT. If the output contains a formula, it will be displayed in tex form and rendered form at the same time, which is convenient for copying and reading. -
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DeepSeek-OCR 2
Visual Causal Flow
DeepSeek-OCR-2 is the second-generation optical character recognition system developed to improve document understanding by introducing a “visual causal flow” mechanism, enabling the encoder to reorder visual tokens in a way that better reflects semantic structure rather than strict raster scan order. It is designed to handle complex layouts and noisy documents by giving the model causal reasoning capabilities that mimic human visual scanning behavior, enhancing OCR performance on documents... -
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files-to-prompt
Concatenate a directory full of files into a single prompt
...It includes rich filtering controls, letting you limit by extension, include or skip hidden files, and ignore paths that match glob patterns or .gitignore rules. The output format is flexible: you can emit plain text, Markdown with fenced code blocks, or a Claude-XML style format designed for structured multi-file prompts. It can read file paths from stdin (including NUL-separated paths), which makes it easy to combine with find, rg, or other shell tools. -
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Automatic text summarizer
Module for automatic summarization of text documents and HTML pages
Sumy is an automatic text summarization library that provides multiple algorithms for extracting key content from documents and articles. Simple library and command line utility for extracting summary from HTML pages or plain texts. The package also contains a simple evaluation framework for text summaries. Implemented summarization methods are described in the documentation. I also maintain a list of alternative implementations of the summarizers in various programming languages. -
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ChatGPT Telegram Bot
A Telegram bot that integrates with OpenAI's official ChatGPT APIs
A Telegram bot that integrates with OpenAI's official ChatGPT, DALL·E and Whisper APIs to provide answers. Ready to use with minimal configuration required. -
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Khoj
An AI personal assistant for your digital brain
Get more done with your open-source AI personal assistant. Khoj is a desktop application to search and chat with your notes, documents, and images. It is an offline-first, open-source AI personal assistant that is accessible from Emacs, Obsidian or your Web browser. Khoj is a thinking tool that is transparent, fun, and easy to engage with. You can build faster and better by using Khoj to search and reason across all your data sources. Khoj learns from your notes and documents to function as... -
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ChatGPT Clone
ChatGPT interface with better UI
ChatGPT Clone demonstrates a ChatGPT-style conversational interface wired to large-language-model backends, packaged so developers can self-host and extend. The goal is to replicate the core chat UX—message history, streaming tokens, code blocks, and system prompts—while letting you plug in different provider APIs or local models. It showcases a clean separation between the web client and the message orchestration layer so you can experiment with prompts, roles, and memory strategies. The... -
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MLJAR Studio
Python package for AutoML on Tabular Data with Feature Engineering
...It abstracts the common way to preprocess the data, construct the machine learning models, and perform hyper-parameter tuning to find the best model. It is no black box, as you can see exactly how the ML pipeline is constructed (with a detailed Markdown report for each ML model). -
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myGPTReader
AI Slack bot for reading, summarizing, and chatting with content
myGPTReader is an AI-powered Slack bot designed to help users read, summarize, and interact with various types of digital content through conversational interfaces. It enables users to quickly understand web pages, documents, and even video content by transforming them into interactive discussions rather than static reading experiences. myGPTReader supports a wide range of file formats, including eBooks, PDFs, and text-based documents, making it flexible for both casual and professional use... -
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ArXiv MCP Server
A Model Context Protocol server for searching and analyzing arXiv
...The project includes packaging and CI to publish to PyPI, plus tests and linting for reliability. Issue threads show feature requests such as extracting embedded LaTeX and improving markdown conversion, reflecting active community use in research flows. It’s designed to be drop-in for MCP clients, giving them typed inputs/outputs and predictable errors around a well-known academic corpus. For developers building research copilots, it removes the glue work of wiring arXiv APIs into an agent toolchain. -
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Mem0
The Memory layer for AI Agents
Mem0 is a self-improving memory layer designed for Large Language Model (LLM) applications, enabling personalized AI experiences that save costs and delight users. It remembers user preferences, adapts to individual needs, and continuously improves over time. Key features include enhancing future conversations by building smarter AI that learns from every interaction, reducing LLM costs by up to 80% through intelligent data filtering, delivering more accurate and personalized AI outputs by... -
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HunyuanOCR
OCR expert VLM powered by Hunyuan's native multimodal architecture
HunyuanOCR is an open-source, end-to-end OCR (optical character recognition) Vision-Language Model (VLM) developed by Tencent‑Hunyuan. It’s designed to unify the entire OCR pipeline, detection, recognition, layout parsing, information extraction, translation, and even subtitle or structured output generation, into a single model inference instead of a cascade of separate tools. Despite being fairly lightweight (about 1 billion parameters), it delivers state-of-the-art performance across a...
