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API · /stemmer-api

Stemmer API

healthy 3,255 Subscribers

Reduce words to their linguistic root (stem) with the classic Snowball stemming algorithms — running → run, fishing → fish, nationalization → nation — across 24 languages including English, German, French, Spanish, Italian, Portuguese, Dutch, Russian, Arabic, Finnish, Swedish and more. Stem a whole text (every word, returning both the per-word mapping and the fully stemmed text) or a single word. Stemming is the core normalisation step behind search engines, query expansion, text indexing, keyword matching and NLP preprocessing. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 4 endpoints. Distinct from sentiment/NLP analysis and fuzzy string matching.

#stemming #nlp #text #search #snowball #developer-tools
api.oanor.com/stemmer-api
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Machine-readable spec so AI agents can integrate this API.

/api/stemmer-api/openapi.json
/api/stemmer-api/llms.txt

Discovery: GET /api/index.json lists every API.

API health

healthy
Uptime
100.00%
Server probes · 24h
Avg latency
86 ms
Server probes · 24h
Subscribers
3,255
active
Total calls
60
last 7 days
status Full status page → · 16 probes/24h

Pricing

Pick a tier — billed monthly, cancel anytime.

Free

Free

  • 1,100 calls / month
  • 2 requests / second
  • Hard cap (429 above quota, no overage)
  • 1,100 calls/month
  • 2 req/sec
  • 24 languages
  • No credit card
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Starter

€2.80 /month

  • 9,500 calls / month
  • 8 requests / second
  • Hard cap (429 above quota, no overage)
  • 9.5k calls/month
  • 8 req/sec
  • Whole-text + per-word
  • Email support
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Pro

€22.40 /month

  • 142,000 calls / month
  • 20 requests / second
  • Hard cap (429 above quota, no overage)
  • 142k calls/month
  • 20 req/sec
  • Search-index pipelines
  • Priority support
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Mega

€58.40 /month

  • 730,000 calls / month
  • 50 requests / second
  • Hard cap (429 above quota, no overage)
  • 730k calls/month
  • 50 req/sec
  • Platform scale
  • Dedicated SLA
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Related APIs

Other APIs with overlapping tags.

N-gram API

Generate n-grams from text, with frequency counts — entirely locally. The ngrams endpoint breaks text into contiguous sequences of n tokens and returns each distinct n-gram with how often it occurs, ranked by frequency: word n-grams (unigrams, bigrams, trigrams and beyond) for phrase and collocation analysis, or character n-grams (shingles) for fuzzy matching, language detection and indexing. The range endpoint produces every size from a minimum to a maximum in a single call (for example 1–3 grams), which is exactly what you need to build feature vectors. Choose word or character mode, whether to lower-case first, and a top-N limit to keep only the most frequent. Word tokenization is Unicode-aware and keeps internal apostrophes and hyphens (don't, well-known) as single tokens. Everything runs locally and deterministically, so it is fast and private. Ideal for text mining and NLP feature extraction, language modelling and autocomplete, search indexing and shingling, plagiarism and similarity detection, and keyword and collocation analysis. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This produces n-grams and counts; for extractive summaries and keywords use a summarize API and for grapheme/character counting use a text-segmentation API.

api.oanor.com/ngram-api

Summarize API

Summarize text and pull out its keywords — no AI key, no external model. The summarize endpoint is extractive: it scores every sentence by word frequency and position and returns the most representative ones (ask for a fixed number of sentences or a fraction of the original), keeping the author's exact wording and order. The keywords endpoint ranks the most salient terms with their counts and a relative score, filtering out stopwords. Because it is deterministic and runs locally, the same text always gives the same result, instantly and privately. Perfect for article previews and TL;DRs, search snippets, tagging and content triage, and feeding shorter context to downstream tools. Pure local computation — no third-party service; send long text via POST. Live, nothing stored. 3 endpoints. Distinct from sentiment/NLP analysis, stopword lists and Unicode text segmentation.

api.oanor.com/summarize-api

Readability API

Score how easy a piece of text is to read using the standard, peer-reviewed readability formulas — Flesch Reading Ease, Flesch-Kincaid Grade, Gunning Fog, SMOG, Coleman-Liau and the Automated Readability Index. Pass text and get all six scores back together with the underlying counts (words, sentences, syllables, complex and polysyllabic words, letters and characters), an averaged grade level, an estimated reading time and a plain-English interpretation of the reading ease. A second endpoint counts syllables for a word or for every word in a phrase. Supply text inline via ?text=, as a query parameter or in a request body; everything is computed locally with no network calls, so it is fast and deterministic. Built for content and copywriting tools, SEO and editorial workflows, education and accessibility (plain-language) checks, and UX-writing review. A readability scorer — distinct from sentiment/NLP analysis (nlp), spelling and grammar checking (grammar), the case and text utilities (text) and string similarity (similarity). No upstream key, no cache.

api.oanor.com/readability-api

Hugging Face API

The Hugging Face Hub as an API — the central, open registry of machine-learning models and datasets that powers much of the modern AI ecosystem. This API wraps the public huggingface.co Hub into clean JSON. /v1/models searches the Hub's models and lets you filter by task (pipeline_tag — e.g. text-generation, text-to-image, image-classification, automatic-speech-recognition, sentence-similarity) and by library (transformers, diffusers, sentence-transformers, …), sorted by downloads, likes, last-modified, created or trending score — each model returned with its id, author, task, library, download and like counts, license, tags and timestamps. /v1/model?id=google-bert/bert-base-uncased returns a single model's full metadata. /v1/datasets searches ML datasets the same way, and /v1/dataset?id=ILSVRC/imagenet-1k returns a single dataset's metadata. Ids are in org/name form (take them from the search endpoints). Ideal for ML and MLOps tooling, model-discovery and comparison sites, AI leaderboards and dashboards, and AI assistants that recommend models. Data comes from the public Hugging Face Hub (free to use). This is the AI/ML model and dataset hub — distinct from software-package registries (npm, PyPI, Maven, NuGet) and academic paper indexes (arXiv).

api.oanor.com/huggingface-api

Frequently asked questions

Quick answers about pricing, quotas, and integration.

How do I get an API key for Stemmer API?
Sign up for free at oanor.com, generate an API key from the developer dashboard, and call Stemmer API with the x-oanor-key header. No credit card needed for the free tier.
What's the rate limit for Stemmer API?
Free tier allows 1 request per second. Paid plans scale up to 50 requests per second on the Mega tier. Hard limits return HTTP 429 above the quota — no surprise overage charges.
How much does Stemmer API cost?
Stemmer API has a free tier with 100 calls / month. Paid plans start at €2.80 / month with higher quotas and faster rate limits.
Can I cancel my subscription anytime?
Yes. Plans are billed monthly and you can cancel anytime from your billing dashboard. No long-term contracts and no cancellation fee.
Is Stemmer API GDPR-compliant?
All requests to Stemmer API go through our EU-based gateway. Your upstream API key never leaves our server and no personal data is shared with the upstream provider beyond the request you send.

Pick an endpoint from the list on the left to see its details and try it.

Code snippets

Sign up to get an API key, then call any path under your slug.

curl https://api.oanor.com/stemmer-api/SOME_PATH \
  -H "x-oanor-key: oanor_test_..."
const res = await fetch("https://api.oanor.com/stemmer-api/SOME_PATH", {
  headers: { "x-oanor-key": "oanor_test_..." }
});
const data = await res.json();
$ch = curl_init("https://api.oanor.com/stemmer-api/SOME_PATH");
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_HTTPHEADER, ["x-oanor-key: oanor_test_..."]);
$response = curl_exec($ch);
import requests
r = requests.get(
    "https://api.oanor.com/stemmer-api/SOME_PATH",
    headers={"x-oanor-key": "oanor_test_..."},
)
print(r.json())

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