Wink Nlp

WinkNLP is a JavaScript NLP library built for developers who need fast, accurate text analysis without leaving the JS ecosystem. It runs on Node.js and in browsers with full TypeScript support, so you can process text on the server or client using the same code. The library ships with a complete NLP pipeline covering tokenization, sentence boundary detection, negation handling, sentiment analysis, part-of-speech tagging, named entity recognition, and custom entity recognition. Its declarative API lets you analyze text in just a few lines of code—most examples run in 30–40 lines—and you can mark tokens, sentences, or entities directly in the output using HTML tags for quick visualization. Performance is a headline feature: on an M1 MacBook Pro, WinkNLP processes raw text at speeds over 650,000 tokens/second for the full pipeline, while the tokenizer alone hits nearly 4 million tokens/second. Compact pre-trained language models start under 3MB, which keeps load times short and makes the library viable for low-end smartphone browsers and offline or edge applications. The tokenizer is lossless and multilingual, handling scripts like Spanish, Devanagari, and emoji in a single pass. The library includes utilities that extend beyond the core pipeline: a BM25 vectorizer, multiple similarity measures (Cosine, Tversky, Sørensen-Dice, Otsuka-Ochiai), and helpers for bag-of-words, frequency tables, stop word removal, lemmatization, stemming, and computing Flesch reading ease scores. Its API exposes two helpers—`its` and `as`—that give you fine-grained control over what data you extract and how you reduce it, so you can filter tokens by part-of-speech, entity type, or shape. With ~100% test coverage and Open Source Security Foundation compliance, WinkNLP is positioned as a production-grade choice for teams that want reliability without outsourcing text processing to a cloud API. Licensed under MIT, WinkNLP is free for commercial and proprietary use, and it runs entirely