nlm-ingestor

>tree-based approach to organize and summarize text data, capturing both high-level and low-level details. https://twitter.com/parthsarthi03/status/1753199233241674040 processes documents, organizing content and improving readability by handling sections, paragraphs, links, tables, lists, page continuations, and removing redundancies, watermarks, and applying OCR, with additional support for HTML and other formats through Apache Tika: https://github.com/nlmatics/nlm-ingestor

You can use the library in conjunction with llmsherpa LayoutPDFReader. Some examples are here with notebook: https://github.com/nlmatics/llmsherpa Here's another notebook from the repo with examples: https://github.com/nlmatics/nlm-ingestor/blob/main/notebooks...

The PDF parser is a rule based parser which uses text co-ordinates (boundary box), graphics and font data. The PDF parser works off text layer and also offers a OCR option to automatically use OCR if there are scanned pages in your PDFs. The OCR feature is based off a modified version of tika which uses tesseract underneath. The PDF Parser offers the following features: * Sections and subsections along with their levels. * Paragraphs - combines lines. * Links between sections and paragraphs. * Tables along with the section the tables are found in. * Lists and nested lists. * Join content spread across pages. * Removal of repeating headers and footers. * Watermark removal. * OCR with boundary boxes