{"repo":"agentii-ai/DocMeld","free":true,"listed":false,"github":"https://github.com/agentii-ai/DocMeld","clone":"git clone https://github.com/agentii-ai/DocMeld.git","description":"Lightweight Doc-to-agent-ready knowledge pipeline. Three-stage Bronze→Silver→Gold architecture extracts structured elements, page content, and AI-enriched metadata from research papers and books. Generate PRDs, workflows, topic clusters, and Claude Code skills from PDFs. No OCR required.","language":"Python","stars":100,"topics":["claude-code","claude-skills","doc-converter","harness-engineering","ocr","pdf-converter","workflow","agent-use-ready","ai-agents","docling"],"license":null,"category":"media-processing","readme_excerpt":"DocMeld Lightweight Doc to agent-ready knowledge pipeline Quick Start • Architecture • Python API • CLI • Configuration • Contributing --- DocMeld converts PDF, Word, and PowerPoint documents into structured, agent-consumable formats through a three-stage pipeline — without requiring expensive OCR, VLM, or multimodal models. Built for the age of AI agents, it bridges the gap between static documents and the structured knowledge that LLMs need. Most tools stop at format conversion. DocMeld goes further: Document → Structured Elements → Page Knowledge → AI-Enriched Metadata , producing outputs ready for RAG pipelines, agent systems, and downstream AI workflows. Supported formats: .pdf , .docx , .doc (via LibreOffice), .pptx , .ppt (via LibreOffice). Why DocMeld? DocMeld MinerU Docling Marker MarkItDown --- --- --- --- --- --- No ML models required ✅ ❌ ❌ ❌ ✅ Runs fully offline (core) ✅ ❌ ✅ ✅ ✅ Agent-ready outputs ✅ ❌ ❌ ❌ ❌ AI metadata enrichment ✅ ❌ ❌ ❌ ❌ Lightweight install ✅ ❌ ❌ ❌ ✅ MIT license ✅ ❌ (AGPL) ✅ ❌ (GPL) ✅ Swappable backends ✅ ❌ N/A ❌ ❌ Quick Start Installation Optional backends for richer formats: Legacy .doc / .ppt additionally require LibreOffice ( soffice ) on your PATH. Process your first document Or from the command line: That's it. Your document is now structured JSON, page-by-page JSONL, and (optionally) AI-enriched metadata. Pipeline Architecture DocMeld uses a three-stage medallion architecture. Each stage is independently runnable and idempotent — re-runn","default_branch":null,"files":null,"tree":[],"storefront":"/r/agentii-ai","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/agentii-ai/DocMeld/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}