MinerU: Transform Unstructured Documents into Accessible Knowledge with Cloud-Based Mining
June 03, 2025
MinerU
What is this project
MinerU is a domain-general, cloud-based knowledge mining platform built by the OpenDataLab team. It is a complete SaaS solution designed to enable users to easily mine knowledge from unstructured data sources, particularly documents. The platform features a question-answering system that delivers precise, factual answers based on the provided corpus.
Main features
- Document Upload & Management: Supports various file formats for knowledge mining
- RAG (Retrieval-Augmented Generation): Combines information retrieval with language model generation
- In-context Search: Assists users in finding relevant information within documents
- Multi-language Support: Handles various languages including English and Chinese
- Citation Tracking: Sources answers with specific citations from the uploaded documents
- Conversational Interface: Provides a chat-like interaction for knowledge queries
- Open-source Framework: Built on open technologies that can be deployed and customized
How to use it
- Upload Documents: Upload PDF, TXT, DOCX, MD or other document formats to create your knowledge base
- Ask Questions: Use the conversation interface to query information from your documents
- Receive Answers: Get factual responses with citations to the source documents
- Refine Queries: Engage in multi-turn conversations to explore topics in depth
Target audience
- Researchers: For literature review and information extraction
- Business Professionals: For knowledge management and information retrieval
- Data Scientists: For extracting insights from unstructured text data
- Educators: For creating educational resources and answering student questions
- Organizations: For building internal knowledge bases and information systems
Project URL/repository
- Project URL: MinerU on Hugging Face Spaces
- Repository: GitHub - opendatalab/MinerU
Use cases/application scenarios
- Research Assistance: Extracting specific information from academic papers
- Customer Support: Creating knowledge bases for product information and FAQs
- Legal Document Analysis: Finding relevant precedents and clauses in legal texts
- Medical Knowledge Mining: Extracting information from medical literature and guidelines
- Educational Resources: Creating question-answering systems for educational content
- Internal Documentation: Making corporate documentation searchable and accessible