Extract text, tables, and metadata from PDFs into Markdown.
npx skills add https://github.com/IndianBoy42/dot-opencode --skill pdf-extraction-indianboy42
Please help me install this Agent Skill. Skill: pdf-extraction Source: https://github.com/IndianBoy42/dot-opencode/tree/main/skills/pdf-extraction Command: npx skills add https://github.com/IndianBoy42/dot-opencode --skill pdf-extraction-indianboy42
PDF documents often contain valuable text, tables, and metadata that are hard to extract, summarize, or repurpose, especially when dealing with scanned files requiring OCR.
Run the default extraction to convert a PDF into Markdown text that can be fed into downstream AI workflows.
High-intent search queries and answers about installing and using this skill.
You can extract tables and text from PDFs for RAG pipelines by converting the document content into structured markdown. This approach uses Python tools like pymupdf4llm and pdfplumber to generate deterministic outputs suitable for downstream LLM ingestion.
Yes, you can extract text from scanned PDFs using OCR capabilities powered by pytesseract and pdf2image. This allows the extraction process to accurately handle image-based documents and convert them into searchable markdown text.
The best way to convert PDF to markdown for LLM ingestion is using a deterministic extraction tool that parses text, tables, and metadata. Relying on libraries like pymupdf4llm ensures the output is structured as chunks suitable for AI workflows.
Yes, pdfplumber supports extracting metadata alongside tables and text from PDF documents. The extracted information is then converted into markdown, ensuring both data and document properties are available for downstream processing.
PDF extraction fails on scanned documents without OCR because the content consists of images rather than embedded text layers. Applying OCR through pytesseract and pdf2image is required to recognize and extract the text from these image-based files.
Yes, you can use this PDF extraction approach for domain-specific documents by combining it with dedicated modules like datasheet-extraction and paper-extraction. These specialized workflows handle unique formatting requirements for technical datasheets and research papers.
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