One signal

A Hugging Face community article sets out a useful document pipeline for AI applications: detect the file type, extract and preserve its structure, normalise to Markdown, validate, then chunk for retrieval or model use. The point is simple but consequential: text extraction alone can scramble tables, headings and reading order before a model ever gets a turn.

Why it matters

The author, who is building the browser-based conversion toolkit MDFold, recommends distinguishing ordinary PDFs from searchable scans and image-only scans, which need OCR. They also advise checking table reconstruction and reading order, and waiting until after normalisation and validation to split content into chunks.

Discuss: What deserves priority in an AI document pipeline: preserving readable structure, or retaining the original layout and metadata?

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