IdeaWell

Project ideas from Hacker News discussions.

Lightweight PDF parser with layout, tables, formulas and bounding boxes

Original Article

Hacker News Discussion

📝 Discussion Summary (Click to expand)

Theme 1 – Praise for table and formula extraction
- “The table and formula extraction features are especially interesting.” – thatcher
- “The table and formula extraction look great.” – JaumeGar

Theme 2 – Interest in workflow integration and preprocessing
- “Can this be integrated into Zotero? Most of the PDFs I read are research papers and extracting tables and formulas directly from my zotero collection would be super handy.” – thatcher
- “Do you know if this one can also crop the PDF to a region of interest before converting to markdown?” – coinfused

Theme 3 – Concerns about extraction accuracy/quality
- “I just tried this and the results look very off. I put in the MiniSat[1] Paper, and the result appears catastrophically wrong.” – antonly (with linked image showing the issue)

🚀 Project Ideas

ZoteroPDFExtract

Summary

  • A Zotero plugin that runs the lightweight document extraction pipeline on selected PDF attachments, preserving tables, formulas, figures, and bounding boxes, and stores the extracted Markdown/JSON as notes linked to the item.
  • Core value: enables researchers to instantly get structured, location‑aware content from their Zotero library for note‑taking, RAG, or citation workflows without leaving Zotero.

Details

Key Value
Target Audience Academics, researchers, and students who use Zotero for managing PDFs
Core Feature One‑click extraction of PDFs to structured Markdown/JSON with bounding‑box metadata, saved as Zotero notes
Tech Stack Python/Rust extraction core; Zotero plugin via JavaScript/TypeScript (Zotero API); optional Pyodide/WASM for client‑side processing
Difficulty Medium
Monetization Hobby
#### Notes
- HN commenter thatcher said: “My immediate question is: can this be integrated into Zotero? Most of the PDFs I read are research papers and extracting tables and formulas directly from my zotero collection would be super handy.”
- Potential for discussion: could spark a thread on improving scholarly workflows, open‑source plugin ecosystems, and enable RAG over personal libraries directly from Zotero.

PDFRegionExtract

Summary

  • A desktop/web tool that lets users visually select a region of interest on a PDF page, then runs the extraction pipeline on that cropped slice to output Markdown/JSON with preserved structure.
  • Core value: solves the need to extract only specific tables, figures, or formulas without processing the whole document, reducing noise and improving accuracy.

Details

Key Value
Target Audience Data analysts, lawyers, journalists, and anyone needing to extract specific content from PDFs
Core Feature Interactive PDF viewer with rectangle selection, automatic cropping, invocation of extraction library, export to Markdown/JSON/Excel/Word
Tech Stack Frontend: React + PDF.js; Backend: Python extraction service (FastAPI) or WASM build of the extraction lib; packaging via Electron or Docker
Difficulty Medium
Monetization Hobby
#### Notes
- HN user coinfused asked: “Do you know if this one can also crop the PDF to a region of interest before converting to markdown?”
- Practical utility: enables targeted extraction for legal discovery, financial statement parsing, or scanning specific figures from research papers, fostering discussion on UI‑driven document processing.

PDFExtractBench

Summary

  • An open‑source benchmarking suite that runs multiple PDF extraction tools (including the user's lib, anydoc, etc.) on a curated corpus of PDFs and reports metrics on table/formula/figure preservation, reading order, and bounding‑box accuracy.
  • Core value: gives developers and users objective data to choose the best extractor for their use case, highlighting strengths/weaknesses.

Details

Key Value
Target Audience Developers building document pipelines, researchers evaluating OCR/extraction libraries
Core Feature CLI or web UI that runs a suite of extractors, generates side‑by‑side diffs, visual heatmaps of bounding‑box differences, and exports summary reports (CSV/JSON)
Tech Stack Python orchestration; Docker to isolate each extractor; optional Streamlit/HuggingFace Spaces for UI; extraction libs as dependencies
Difficulty High
Monetization Revenue-ready: subscription tiers (free limited runs, paid for private corpora and higher throughput)
#### Notes
- HN user phenomen mentioned using anydoc and wanting to test the new lib; antonly reported catastrophic failures on a sample PDF, showing need for comparative testing.
- Potential for discussion: would generate lively HN threads about extraction trade‑offs, encourage open‑source collaboration, and help users pick the right tool for RAG pipelines.

Read Later