For the more curious: there is also Unstract open source for pipeline. Lets us plug in your AI stack eg. OS llm models, vector db, ocr parsers etc.
I’ve been working on an OCR pipeline specifically optimized for machine learning dataset preparation. It’s designed to process complex academic materials — including math formulas, tables, figures, and multilingual text — and output clean, structured formats like JSON and Markdown.
Some features: • Multi-stage OCR combining DocLayout-YOLO, Google Vision, MathPix, and Gemini Pro Vision • Extracts and understands diagrams, tables, LaTeX-style math, and multilingual text (Japanese/Korean/English) • Highly tuned for ML training pipelines, including dataset generation and preprocessing for RAG or fine-tuning tasks
Sample outputs and real exam-based examples are included (EJU Biology, UTokyo Math, etc.) Would love to hear any feedback or ideas for improvement.