olmOCR is an open-source toolkit developed by the Allen Institute for Artificial Intelligence (AI2), designed to linearize PDF documents for training large language models (LLMs). The toolkit addresses the challenges posed by the complex structure of traditional PDF documents, which are difficult to directly use for model training, by converting them into a format suitable for LLM processing. It supports various functionalities, including natural text parsing, multi-version comparison, language filtering, and SEO spam removal. olmOCR's key advantage lies in its efficient handling of large numbers of PDF documents and its ability to improve the accuracy and efficiency of text parsing through optimized prompting strategies and model fine-tuning. This toolkit is suitable for researchers and developers who need to process large amounts of PDF data, especially in the fields of natural language processing and machine learning.