MinerU | Transform Complex Documents into LLM-ready Markdown for Agentic Workflows
MinerU
Introduction
MinerU is an open-source, high-performance data processing tool designed to convert complex PDF documents into machine-readable formats like Markdown and JSON. It is specifically engineered to handle the challenges of document layout analysis, table extraction, and formula recognition, making it an essential utility for LLM pre-training and data pipeline construction.
Use Cases
LLM Data Pre-training
Converting vast amounts of academic and technical PDFs into clean, structured text for training large language models.
Document Digitization
Transforming legacy physical or scanned documents into editable and searchable digital formats.
Financial Report Analysis
Extracting complex tables and financial data from PDF reports for automated quantitative analysis.
Academic Research
Parsing research papers to extract formulas and structured content for knowledge graph construction.
Enterprise Knowledge Management
Indexing internal documentation and manuals to improve searchability and information retrieval within an organization.
Features & Benefits
Advanced Layout Analysis
Utilizes deep learning models to accurately identify and segment document regions like headers, footers, and sidebars.
Formula Recognition
Capable of converting complex mathematical formulas into LaTeX format for scientific accuracy.
Table Extraction
High-precision extraction of tabular data, maintaining structure and relationships within the converted output.
Multi-format Support
Outputs data in structured Markdown and JSON formats, facilitating easy integration with downstream AI applications.
High-Performance Pipeline
Optimized for batch processing, allowing for efficient handling of large-scale document datasets.
