nougat VS langchain4j

https://github.com/facebookresearch/nougat/tree/main

If you're looking for more e2e math / latex aware OCR checkout https://github.com/facebookresearch/nougat

git clone --recurse-submodules https://github.com/facebookresearch/nougat.git PyProject

> For the scientific literature, we need a ChatGPT equivalent to reconstruct LaTeX source that can reproduce each page. (We really need a successor to LaTeX that isn't such an arcane language, and can author fixed and flowable text with equal ease.)

Check out Nougat: OCRing scientific papers with a deep net trained end to end. It was released by Meta a few days ago.

“PDF format leads to a loss of semantic information, particularly for mathematical expressions. We propose Nougat (Neural Optical Understanding for Academic Documents), a Visual Transformer model that performs an Optical Character Recognition (OCR) task for processing scientific documents into a markup language, and demonstrate the effectiveness of our model on a new dataset of scientific documents.”

https://facebookresearch.github.io/nougat/

The paper (and examples) as HTML: https://facebookresearch.github.io/nougat/

Repo with code, including a CLI tool for converting a PDF to Mathpix Markdown: https://github.com/facebookresearch/nougat

The goal of LangChain4j is to simplify the integration of AI and LLM capabilities into Java applications. The project lives on GitHub, and has a separate repository with demo applications. I first learned about LangChain4j at the Devoxx conference in Antwerp in October last year. Lize Raes gave an impressive presentation with 12 demos. In the last demo, she asked the application to give some answers based on a provided text. And that was exactly what I was looking for to be able to interact with an existing dataset.

Please take a look: https://github.com/langchain4j/langchain4j