AIAny
AI Infra2024
Icon for item

MinerU

Converts PDFs, images, and Office documents into Markdown or JSON for retrieval, extraction, and agent workflows, with OCR, layout analysis, formula handling, and multiple runtime modes.

Introduction

Document parsing looks solved until the input is a scanned paper, formula-heavy PDF, or mixed Office file headed into a RAG pipeline. The core value is turning messy human documents into structured machine input.

What Sets It Apart

It handles PDFs, images, DOCX, PPTX, and XLSX, then emits Markdown and JSON aimed at retrieval, extraction, and LLM workflows. Layout analysis, OCR, and post-processing give tables, formulas, and document structure a better chance of surviving conversion.

Who Should Use It

Great fit if your AI workflow depends on complex document ingestion for RAG or data production. Look elsewhere if you need a tiny dependency-free parser or a fully managed SaaS with no local runtime choices.

Information

  • Websitegithub.com
  • AuthorsOpenDataLab
  • Published date2024/07/05

Categories

More Items

Enables RL post-training with million-token prompts under a fixed GPU budget by evaluating shared prompt state without autograd, retaining only minimal model state, and replaying short response branches; instantiated as GRPO and demonstrated on Qwen3.6-27B and GLM-5.2 up to multi-million token execution.

GitHub
AI Infra2026

Defines OpenTelemetry semantic conventions for generative AI telemetry — spans, metrics, and events for GenAI clients, the Model Context Protocol (MCP), and provider-specific integrations. Includes YAML models, human-readable docs, and reference implementations to standardize observability across GenAI deployments.

GitHub
AI Infra2024

Provides a lightweight build platform for HIP and ROCm that supports building ROCm, PyTorch, and JAX from source, multi-architecture nightly releases, and integrated CI/CD and developer tooling for Linux and Windows.