{"categories":[{"label":"Text Processing","url":"https://skillfed.io/packages/category/text-processing/2"}],"enrichment":{"capability":"Converts PDF, DOCX, PPTX, XLSX, images, and web pages into structured Markdown or JSON using VLM and OCR engines, supporting 109 languages and complex layouts.","skillfed_tags":["document-parsing","ocr-vlm","rag-ingestion"],"use_cases":["Ingest PDFs and documents into RAG pipelines by converting them to structured Markdown or JSON for embedding and retrieval.","Parse scanned or handwritten documents with OCR to extract text and tables in human reading order.","Convert DOCX, PPTX, and XLSX files to Markdown for version control, archival, or downstream processing.","Build document understanding workflows for LLM agents that need to reason over complex layouts and multi-language content.","Extract and reconstruct tables from PDFs as HTML or JSON for data analysis and database ingestion."],"what_it_does":"MinerU is a document parsing engine that reads PDF, DOCX, PPTX, XLSX, images, and web pages and outputs them as structured Markdown or JSON. It uses a dual VLM (vision language model) and OCR engine to handle both text-based and scanned documents, supporting 109 languages and complex layouts like multi-column text, cross-page tables, and handwriting. The package includes native parsers for DOCX, PPTX, and XLSX (as of version 3.1.0), converts formulas to LaTeX and tables to HTML, and reconstructs layout in human reading order with automatic header/footer removal.\n\nThe package ships with multiple inference backends: a fast pipeline backend optimized for CPU/GPU, a VLM engine for high accuracy, and a hybrid engine balancing speed and precision. It integrates with LangChain, LlamaIndex, Dify, FastGPT, and other RAG frameworks, and offers CLI, REST API, Python SDK, and MCP Server interfaces. You can deploy it privately and fully offline, with support for domestic AI chips (Ascend, Cambricon, Enflame, and others). The 29 runtime dependencies include heavy libraries like opencv-python, huggingface-hub, and fastapi, so installation expands your environment substantially.","worth_installing":"Yes, with conditions. MinerU is actively maintained, has no known vulnerabilities, and offers broad multi-format support with strong accuracy on complex documents. However, the custom license treatment is unclear\u2014verify the terms before commercial use. The 29 runtime dependencies are substantial; assess whether your environment can absorb them. Install if you need reliable document parsing for RAG, LLM workflows, or multi-format ingestion; skip if you need lightweight PDF-only extraction or have strict license requirements."},"id":"mineru","links":{"html":"https://skillfed.io/packages/mineru","md":"https://skillfed.io/packages/mineru.md","pypi":"https://pypi.org/project/mineru/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-14","license_spdx":"LicenseRef-MinerU-Open-Source-License","license_treatment":"unclear","name":"mineru","python_support":"supports_current","summary":"A practical document parsing tool for converting PDF, images, DOCX, PPTX, and XLSX into Markdown and JSON"},"popularity":{"monthly_downloads":335817,"position":7471,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"3.4.5"}