Review Analyzer

Customer-review intelligence microservice: turn product/app/restaurant/hotel reviews into structured insight. analyze extracts sentiment, a 1-5 star estimate, pros, cons and per-aspect opinions from...

review-analyzer

Customer-review intelligence microservice. Turns product / app / restaurant / hotel reviews into structured insight: sentiment, a 1-5 star estimate, pros/cons, per-aspect opinion mining, theme clustering across many reviews, and fake-review detection.

Every tool has a deterministic heuristic core (opinion lexicon with negation + intensifier handling, aspect-based opinion mining) that runs fully offline with no model. analyze, summary and themes also try an optional LLM (via ../_shared/llm.js) and silently fall back to the heuristic — results are tagged { mode: 'heuristic' | 'llm' }. A missing/down model never throws.

Tools

Tool	Input	Returns
`analyze`	`{ review }`	`{ sentiment, polarity, rating, stars, pros, cons, aspects, confidence }`
`aspects`	`{ review, feature }`	sentiment toward one named feature (e.g. `battery`, `shipping`)
`summary`	`{ review }`	`{ headline, tldr, rating, keywords, topPro, topCon }`
`starEstimate`	`{ review }`	`{ stars, rating, distribution, confidence }`
`themes`	`{ reviews: [..] }`	top recurring themes with quotes, praised/criticized lists, keywords
`spamLikelihood`	`{ review }`	`{ spamLikelihood, label, isSuspicious, flags }`

Usage

import pack from './index.js';

await pack.adapters.analyze({ review: 'Battery life is amazing but the app crashes constantly.' });
// -> { sentiment:'positive'|... , rating, pros:[...], cons:[...], aspects:[{aspect:'reliability',sentiment:'negative'},...] }

pack.adapters.aspects({ review: 'Shipping was super fast, packaging was flimsy.', feature: 'shipping' });
// -> { feature:'shipping', sentiment:'positive', score, evidence:[...] }

await pack.adapters.themes({ reviews: ['Great value!', 'Broke after a week', 'Support was rude'] });
// -> { topThemes:[...], praised:[...], criticized:[...], avgEstimatedRating }

Options: { topN, minMentions, maxQuotes, useLlm:false } (pass useLlm:false to force the offline core and skip the network call).

DRY boundaries

Generic tokenize / bag-of-words / readability of arbitrary prose lives in nlp / a-text;

general keyword extraction in seo. This pack owns review-domain modeling only: opinion polarity, aspect-based opinion mining, star estimation, review-theme clustering, fake-review detection.

Aggregate numeric stats (percentiles, anomalies) live in numbers / statistics — this pack

emits shares/counts, not a stats engine.

Self-contained: the only import is ../_shared/llm.js.