#Pdf-to-markdown
Showing 13 of 13 repositories tagged #pdf-to-markdown, ranked by stars
Extract and convert data from any document, images, pdfs, word doc, ppt or URL into multiple formats (Markdown, JSON, CSV, HTML) with intelligent structured data extraction and advanced OCR.
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.
PDF to markdown using vision LLMs — tables, layouts, and structure preserved
The fastest PDF library for Python and Rust. Text extraction, image extraction, markdown conversion, PDF creation & editing. 0.8ms mean, 5× faster than industry leaders, 100% pass rate on 3,830 PDFs. MIT/Apache-2.0.
📄 The PDF intelligence layer for AI agents — Agent Document Twin, evidence-first extraction, visual crops, OCR provenance, trust reports, and benchmark-gated releases. MCP server for Claude, Cursor, VS Code, and any MCP client.
A math workspace for screenshot OCR, handwriting-to-LaTeX, editing, preview, and symbolic computation, powered by MathCraft OCR and MathLive.
Turn PDFs into clean, structured Markdown
Turn any document into clean, AI-ready Markdown. Local-first desktop app: reads scanned PDFs, batches folders, runs offline, and uses far fewer tokens than vision models.
Open-source toolkit for reliable RAG pipelines: convert PDFs to Markdown, clean documents, inspect chunks, compare chunking strategies, and enrich metadata for LLM applications.
AI-Native document parser: PDF, Office & images → clean Markdown with LaTeX, tables & OCR. Zero-dependency CLI & skill for Claude Code, Cursor & AI agents.
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.
PDF extraction that checks its own work. #2 reading order accuracy — zero AI, zero GPU, zero cost.
Open-source PDF-to-Markdown post-processor with footnotes, LaTeX normalization, figure links, and YAML metadata. Supports Marker, MinerU, PyMuPDF, and Docling. Includes a self-hosted web UI.