chunks.md
Turn your files into clean markdown. Processed locally.
What it does
chunks.md turns PDFs and images into clean, AI-ready markdown — entirely in your browser. No uploads, no servers, no sign-ups. Drop your files, pick an OCR model, and get structured text you can paste straight into ChatGPT, Claude, or your RAG pipeline. Powered by 7 on-device OCR models (including PaddleOCR v5, SmolDocling, and manga-ocr), everything runs locally via ONNX Runtime Web. Your documents never leave your device. Free and unlimited.
Does the same job
all alternatives →- PTPDF to MD by LLMs – Extract Text/Tables/Image Descriptives by GPT4o2024 · github.com · ▲191
I've developed a Python API service that uses GPT-4o for OCR on PDFs. It features parallel processing and batch handling for improved performance. Not only does it convert PDF to markdown, but it also describes the images within the PDF using captions like `[Image: This picture shows 4 people waving]`. In testing with NASA's Apollo 17 flight documents, it successfully converted complex, multi-oriented pages into well-structured Markdown. The project is open-source and available on GitHub. Feedback is welcome.
- BABuilt a tool solve the nightmare of chunking tables in PDF vs. MarkdownNov 2025 · github.com · ▲15
Hey HN, solo dev here. After years of frustration with how LLMs handle complex documents, especially PDFs with tables, I decided to build a solution myself. My approach uses a Markdown conversion step to preserve the table structure, which seems to work surprisingly well for chunking. This little parser is the first public piece of a much larger, privacy-focused AI platform I'm building. I'm pretty much running on fumes financially, so any feedback, critique, or support is massively appreciated. Happy to answer any questions about the approach!
- YCYou can now cut and paste from scanned documents in Firefox2024 · ▲33
I just realized you can now open a PDF document in Firefox and select text directly from scanned images embedded in the document (so basically transparently reliable doing OCR). It is also surprisingly reliable, only sometimes mistaking a "oh" for a "zero" in a long string of numbers. I neither know when this was introduced nor who added this feature, but from the bottom of my heart: thank you, thank you, thank you, you have made my daily life a lot easier. I also haven't really explored the limits of the feature and under what conditions it starts failing, but: in my daily workflow so far,…
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