universal-document-reader

You can extract text from scanned PDFs and images for LLM processing using OCR. This Skill utilizes tesseract-ocr to perform optical character recognition, converting scanned documents and image-based files into clean, structured text that large language models can process effectively.

The best way to convert DOCX and PDF files to text while maintaining structure is using dedicated extraction libraries. This Skill leverages python-docx and pypdf to parse document formats, ensuring the extracted text remains clean and structured for downstream LLM processing.

Yes, you need to install pandoc and poppler-utils to extract text from documents using this Skill. These system dependencies handle format conversion and PDF text extraction, alongside Python libraries like pytesseract and python-pil, to ensure universal document compatibility.

Yes, you can use Python to convert multiple document formats into LLM-ready text. Built with python3, this Skill integrates libraries like pypdf and python-docx to process PDFs, Word files, and images, outputting structured text optimized for large language models.

Text extraction from PDF results in broken text when documents are scanned images rather than text-based files. This Skill resolves unstructured PDF text extraction by applying tesseract OCR, converting image-based content into clean, structured text for LLM processing.