MarkItDown - Make any document AI friendly (by microsoft) MarkItDown is a Python utility designed for converting various file types—including PDFs, Word documents, and images—into Markdown format, emphasizing compatibility with Large Language Models (LLMs) for text analysis. This tool supports a wide range of formats while maintaining essential document structures, as well as integrating seamlessly with existing LLM applications through its Model Context Protocol (MCP). Recent updates introduced breaking changes that require users to adapt their implementations, particularly concerning file handling and dependencies. https://github.com/microsoft/markitdown Someone created a pallatform for this here: https://markitdown.pro/ #MarkItDown #Microsoft #Python #LLM #LargeLanguageModels #Markdown #DocumentConversion #AI #TextAnalysis #ModelContextProtocol #PDFtoMarkdown #WordtoMarkdown #Imagetomarkdown #markitdownpro #Langchain #LlamaIndex #DataConnectors #AIworkflows

And of course someone just had .. just had to try it out ! This guy literally recreated the entire system usng N8N ! Check this out ! The article explains how the author recreated Anthropic’s recently published multi-agent research system entirely with the low-code automation platform n8n, eliminating the need for traditional software engineering. Central to the solution is a clearly separated set of AI agents—Customer Support, Lead (Orchestrator), multiple parallel Search Subagents, and a Copywriter—that collaborate through n8n workflows, external APIs, and structured JSON outputs to turn a vague user request into a polished, PDF research report in about seven minutes. By sharing the architecture, tools (e.g., Brave Search, ScrapingAnt, OpenRouter, Markdown Master), and a ready-to-use template, the author encourages product managers to develop AI intuition, automate knowledge-heavy tasks, and build impressive portfolio projects. #n8n #anthropic #multiagent #lowcode #automation #zapier #makecom #aiagents #orchestrator #bravesearch #scrapingant #openrouter #markdownmaster #workflowautomation #nocode #aiworkflow #productmanager #airesearch #pdfgeneration #jsonoutput #aiportfolio #knowledgeautomation #aicollaboration #workflowbuilder #aiintegration https://www.productcompass.pm/p/multi-agent-research-system

MarkItDown is a Python tool designed to convert various file types, including PDFs, Word documents, and audio files, into Markdown format, facilitating text analysis and integration with large language models (LLMs). The tool emphasizes the preservation of document structure during conversion and introduces a protocol for interactive LLM functionalities. Its recent updates have clarified dependencies and broadened support for different file formats, catering to developers and users alike. Key Points - MarkItDown is a Python utility specifically for converting multiple document types into Markdown format optimized for text analysis and LLM applications. - The tool supports a wide array of file formats including PDF, PowerPoint, Word, Excel, images, audio, HTML, and even YouTube URLs. - Recent updates addressed breaking changes in functionality, requiring a binary file-like object in conversion methods and revising the DocumentConverter interface. - Users can install MarkItDown through pip with optional dependencies tailored to specific file formats for more customized installations. - Plugins are supported, which allows third-party contributions to extend MarkItDown's capabilities, although they are disabled by default. - The integration of Microsoft Document Intelligence is available for enhanced conversion features, specifically for PDF files. - MarkItDown requires Python 3.10 or higher, and it is recommended to use a virtual environment for installation to prevent dependency issues. #MarkItDown #python #markdown #llms #textanalysis #pdfconversion #documentconversion #microsoftdocumentintelligence #pypdf #unstructured #doctr #virtualenv #pip #opensource https://github.com/microsoft/markitdown

Full Stack PRD Guide for Vibe Coders 📝 https://github.com/cpjet64/vibecoding/blob/main/prd-guide.md Hey Vibe Coders! To help with product definition and avoid scope creep, here’s a guide for creating effective Product Requirements Documents (PRDs). Step 1: Create a "prd.md" Document 📋 Make a markdown file named "prd.md" as your product roadmap. A template is available at the end. Step 2: Document Each Product Component ⚙️ For each component (user flows, features, interfaces): - Key functionality (e.g., authentication) - User stories/acceptance criteria - Technical constraints - Priority level (must-have, should-have, nice-to-have) Step 3: Add Overall Product Metrics 📊 Key success metrics to document: - Key Performance Indicators (KPIs) - User acquisition and retention rates - Conversion goals - Engagement benchmarks Step 4: Consult Advanced AI 🤖 Engage in detailed discussions with AI like ChatGPT 4.5 or Claude 3.7. Discuss various aspects of your PRD, challenge assumptions, and gather insights. PRD Principles to Remember 🔑 - Focus on the WHAT, not the HOW - Requirements should be measurable - Link each feature to a user need - Prioritize to prevent scope creep Recommended PRD Components 🛠️ Include sections such as: - Product vision/goals - User personas/maps - Feature breakdowns - Non-functional requirements - Metrics/analytics plans - User research insights User Research Integration 💻👥 Incorporate user research by documenting: - User pain points/needs - User quotes/inspiration - User segments and distinct requirements - Edge cases and accessibility requirements - Testing plans for validation Feature Prioritization 🎯 Use frameworks like MoSCoW, RICE scoring, and ROI analysis to prioritize features. Stakeholder Management 👥 Document approval processes, feedback loops, and change management procedures. Establish communication plans. Product Analytics & Measurement 📊 Define success metrics, instrument tracking, and set up reporting for user behavior. User Experience Design 🎨 Link your PRD to user experience through flow diagrams, UI requirements, accessibility, and performance expectations. Technical Considerations 🔧 Align product requirements with technical planning, covering API needs, security, and third-party dependencies. Release Planning & Timeline 📅 Plan your release strategy, milestones, timelines, testing phases, and post-launch monitoring. Keep your products well-defined and focused! ✌️ Document Versions Latest versions of this guide are available on GitHub and X.com.