Extract text from PDFs into Markdown for LLM and RAG pipelines.
npx skills add https://github.com/boazcstrike/opencode --skill extracting-pdf-text
Please help me install this Agent Skill. Skill: extracting-pdf-text Source: https://github.com/boazcstrike/opencode/tree/main/skills/extracting-pdf-text Command: npx skills add https://github.com/boazcstrike/opencode --skill extracting-pdf-text
This skill addresses the challenge of converting PDF documents, including text-based, table-heavy, and scanned images, into a format that Large Language Models (LLMs) can effectively process for tasks like Retrieval Augmented Generation (RAG) or in-depth document analysis.
Use the extracting-pdf-text skill to extract all text from the attached file 'report.pdf' into 'output.md'.
High-intent search queries and answers about installing and using this skill.
To extract text from scanned PDFs for LLM processing, you can use OCR tools like pytesseract or the Mistral OCR API to convert image-based documents into machine-readable text suitable for RAG pipelines.
Parsing PDF tables for Retrieval Augmented Generation is best handled by pdfplumber, which accurately extracts structured table data and formats it for optimal consumption by Large Language Models.
Converting a research paper PDF into markdown for document analysis involves extracting text content using local tools like PyMuPDF, then formatting the output into a structured markdown file for LLM summarization and question-answering.
Yes, you can use PyMuPDF and pdfplumber together for text extraction, allowing you to handle both standard text-based PDFs and documents with complex tables by leveraging each tool's specific extraction strengths.
Extracting PDF text for RAG pipelines does not strictly require an API key, as local libraries like PyMuPDF and pytesseract work offline, but using the Mistral OCR API for high-accuracy scanned document extraction will require one.
Text extraction fails on image-heavy PDF documents because standard libraries cannot read embedded images, requiring OCR via pytesseract or Mistral OCR to successfully process and extract the scanned content.
ZurybrExtract text, tables, and OCR data from PDFs into Markdown.
jackjin1997Build end-to-end RAG pipelines with document loading, chunking, and vector storage.
zhangzhang-111-iDesigns RAG pipelines with chunking, embedding, retrieval, and evaluation strategies.
bahayonghangExtract text, merge, split, rotate, and watermark PDFs using Python libraries.
