agentskillexchange Parse multilingual documents for agent ingestion with dots.ocr
Use dots.ocr when an agent needs repeatable multilingual document layout parsing before retrieval, extraction, review, or downstream automation.
Prerequisites
Python, vLLM or Hugging Face Transformers, dots.mocr model weights
Installation
Use the upstream install or setup path that matches your environment:
- conda create -n dots_mocr python=3.12
- conda activate dots_mocr
- git clone https://github.com/rednote-hilab/dots.mocr.git
- pip install -e .
Requirements and caveats from upstream:
- OCRVerse results are derived from various code formats (e.g., SVG, Python), whereas results for Gemini 3 Pro and dots.mocr are based specifically on SVG code.
- If you have trouble with the installation, try our Docker Image for an easier setup, and follow these steps:
- We highly recommend using vLLM for deployment and inference. Since vLLM version 0.11.0, Dots OCR has been officially integrated into vLLM with verified performance and you can use vLLM docker image directly (e.g,...
Basic usage or getting-started notes:
cd dots.mocr
💡Note: Please use a directory name without periods (e.g., DotsMOCR instead of dots.mocr) for the model save path. This is a temporary workaround pending our integration with Transformers.
python3 tools/download_model.py
Extracted from upstream docs: https://raw.githubusercontent.com/rednote-hilab/dots.ocr/HEAD/README.md