Hey DEV community! 👋
Analyzing N-grams (Unigrams, Bigrams, Trigrams) is essential for spotting natural phrase patterns and evaluating linguistic structure in text. However, pasting long-form drafts into web tools that process data on backend servers often raises privacy concerns.
To fix this, I vibe-coded a lightweight N-gram Analyzer that processes everything 100% in your browser.
🛠️ Key Technical Highlights:
- Zero Backend Latency: 100% client-side JavaScript execution. Text parsing, tokenization, and phrase extraction run locally with complete privacy.
- Instant Phrase Breakdown: Seamlessly extracts Unigrams, Bigrams, and Trigrams to audit contextual phrasing and frequency distribution on the fly.
- Vibe Coding Workflow: Leveraged LLM prompts to rapidly construct sliding-window algorithms and clean UI array renderings for frequency tables.
💡 Vibe Coding Insight:
Implementing sliding window algorithms for Bigram/Trigram extraction in plain JS can get tricky around sentence boundaries and punctuation. Prompting the AI to isolate array transformation logic into pure, testable functions made debugging edge cases effortless while maintaining sub-second performance.
🔗 Try it out & Share Feedback:
I'd love your thoughts on the parsing speed or suggestions for additional NLP filters!
👉 Live Demo: Online N-gram Analyzer
Do you use N-gram analysis in your content processing or search workflows?
Top comments (1)
If you give it a try with your own text, let me know how it performs! Would love to hear your feedback or feature suggestions. 👇