/tools namespace · APlicious

Sentiment analysis API — positive/negative/neutral at document or sentence level

POST any text to /tools/text/sentiment and get back a compound sentiment score plus per-sentence breakdown — useful for product review analysis, social listening, and feedback triage without building an NLP pipeline.

2granularity levels

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POST /api/v1/tools/text/sentiment

const res = await fetch('https://aplicious.com/api/v1/tools/text/sentiment', {
  method: 'POST',
  headers: { 'X-API-Key': 'lapi_live_••••', 'Content-Type': 'application/json' },
  body: JSON.stringify({ text: 'The delivery was fast but the packaging was damaged.', granularity: 'sentences' }),
});
const { data } = await res.json();
// { overall: { compound: 0.12, positive: 0.45, negative: 0.33, neutral: 0.22 },
//   sentences: [ { text: "delivery was fast", compound: 0.72 }, ... ] }

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What's included in /tools

Document-level scoring

Compound score from -1 (strongly negative) to +1 (strongly positive) for the full text block.

Sentence-level breakdown

Set granularity:'sentences' to get sentiment scores for each sentence — find the exact complaint in a long review.

Positive / Negative / Neutral percentages

Three-way classification percentages alongside the compound score for histogram-style dashboards.

Language-agnostic

Works on English text and many other languages — pair with /text/detect-language first for multilingual pipelines.

Pairs with /text/summarize

Summarize a long review, then score the summary sentiment in two calls.

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Free tier — 250 calls/month, no credit card. Upgrade when you need more.

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Frequently asked questions

What granularity options are available?

'document' returns a single score for the whole text. 'sentences' scores each sentence individually.

What is the compound score?

A normalized value between -1 and +1 — positive means overall positive, negative means overall negative, near-zero is neutral.

Is this useful for product reviews?

Yes — sentence-level granularity lets you pinpoint which aspect (shipping, quality, support) drove a mixed review.

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