README.md

metadata

title: ResearchLens
emoji: 🔎
colorFrom: blue
colorTo: indigo
sdk: static
app_file: index.html
pinned: false
license: mit
short_description: Multilingual document intelligence in the browser

ResearchLens

A privacy-conscious, browser-first multilingual NLP application for academic, policy and business documents.

This Static Space analyzes English, Spanish and Portuguese text without server-side compute or a generative API. It provides document metrics, an extractive summary, lexical signals and multilingual topic indicators. PDF extraction is performed in the browser with PDF.js.

Why a Static Space?

The portfolio uses scarce compute only where machine-learning inference materially adds value. ResearchLens relies on transparent analytical NLP, so moving it to a Static Space makes the project faster to share, cheaper to maintain and more privacy-friendly.

Capabilities

• paste text or upload PDF/TXT/Markdown
• English, Spanish and Portuguese language detection
• word, sentence and paragraph metrics
• reading-time estimate
• lexical diversity
• extractive summarization
• unigram and bigram lexical signals
• multilingual topic scoring
• fully client-side analysis

Technical design

• Vanilla JavaScript
• deterministic NLP heuristics
• PDF.js for browser-side PDF text extraction
• no backend
• no API keys
• no external generative AI service

Limitations

• Scanned/image-only PDFs require OCR and may not extract text.
• Language detection is heuristic.
• Extractive summaries preserve source sentences but can miss nuance.
• Topic signals are based on a curated lexicon rather than a learned classifier.
• Results are analytical signals, not factual verification.

License

MIT for project code. PDF.js is loaded from its public distribution and remains subject to its own license.