Detect profanity
API · /profanity-api
Profanity Filter API
Detect and censor profanity in user-generated text across 24 languages — for comment moderation, chat filtering, username and form validation, and trust-and-safety pipelines. Send any text and get back whether it contains profanity, the exact bad words found and which languages they belong to; or get the text back with every bad word masked (choose your own mask character). Matching is word-boundary aware (so "Scunthorpe" and "Penistone" are not flagged) and normalises common leetspeak (sh1t, @ss) before matching. Target a specific language (or several) or scan all 24 at once. Powered by the well-known LDNOOBW word lists, bundled in — so the service is fully self-contained: no third-party calls, no rate limits, always available. Live, no cache. 4 endpoints. No upstream key.
API salute
salutare- Tempo di attività
- 100.00%
- Sondaggi del server · 24 ore su 24
- Latenza media
- 71 ms
- Sondaggi del server · 24 ore su 24
- Abbonati
- 3,531
- attiva
- Chiamate totali
- 76
- ultimi 7 giorni
Prezzi
Scegli un livello: fatturazione mensile, annullamento in qualsiasi momento.
Free
Gratis
- 1,820 chiamate/mese
- 2 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 1,820 calls/month
- 2 req/sec
- 24 languages, check + clean
- No credit card
Starter
€6.50 /mese
- 40,000 chiamate/mese
- 8 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 40k calls/month
- 8 req/sec
- Comment / chat moderation
- Email support
Pro
€23.00 /mese
- 215,000 chiamate/mese
- 20 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 215k calls/month
- 20 req/sec
- Trust-and-safety pipelines
- Priority support
Mega
€57.00 /mese
- 1,060,000 chiamate/mese
- 50 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 1.06M llamadas/mes
- 50 req/seg
- Moderación a escala de plataforma
- SLA dedicado
Costruito da
Correlato APIs
Altro APIs con tag sovrapposti.
Emoji Strip API
Strip, extract and count emoji in any text. The strip endpoint removes every emoji from a string — or replaces each one with a marker you choose — and gets multi-code-point emoji right: ZWJ sequences like the family 👩👩👧👦, skin-tone modifiers (👍🏽), country flags (🇩🇪), keycaps (1️⃣) and variation selectors all count as a single emoji, so nothing is left half-deleted. The extract endpoint lists every emoji it finds with its position in the text and returns per-emoji and unique counts, ideal for analytics and moderation. A bare ©, ® or ™ is deliberately left alone unless it carries an emoji variation selector, and plain digits are never touched. Perfect for cleaning user input before search indexing or storage, sanitising usernames and display names, moderation and analytics, and preparing text for systems that choke on emoji. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This cleans and extracts emoji from text; to look an emoji up by name or shortcode use an emoji database API, and to count graphemes use a text-segmentation API.
api.oanor.com/emojistrip-api
NSFW Detection API
Moderate images automatically with on-device machine learning. Classify any image across five categories — neutral, drawing, sexy, porn and hentai — and receive per-class probabilities, the top class, a combined NSFW score and a clear verdict (safe, questionable or nsfw). A simpler check endpoint returns a single safe/unsafe decision against a threshold you choose, ideal for upload gates and user-generated-content pipelines. Supply an image by public URL, base64 or a raw binary request body; only public http/https URLs are accepted and private or internal hosts are blocked, and large images are downscaled automatically. Runs locally on TensorFlow (NSFWJS / MobileNetV2) — no third-party upstream and no per-image cloud cost — with a warm model that keeps inference fast. Ideal for community platforms, marketplaces, dating and chat apps, and any service that accepts user images.
api.oanor.com/nsfw-api
Keyboard Layout API
Re-mapeia texto entre layouts de teclado — a correção para texto digitado com o teclado configurado no layout errado. O endpoint remap recebe texto, um layout de origem e um layout de destino, e reescreve cada caractere para aquele produzido pela mesma tecla física no outro layout. Assim, texto digitado acidentalmente em um teclado configurado para Dvorak enquanto você queria QWERTY (ou o inverso) é recuperado exatamente, e como o mapeamento preserva a posição, ele faz ida e volta perfeitamente. Suporta QWERTY (US), Dvorak e Colemak, incluindo os símbolos shiftados, e deixa caracteres que não estão em uma tecla remapeável (espaços e acentos) intocados. O endpoint layouts retorna o mapa completo de teclas para cada layout. Tudo é computado localmente e deterministicamente, então é instantâneo e privado. Ideal para corrigir digitação no layout errado, construir editores de texto e ferramentas IME, auxílios de aprendizado de layout e pesquisa entre layouts. Computação local pura — sem chave, sem serviço de terceiros, instantâneo. Ao vivo, nada armazenado. 3 endpoints. Isso remapeia entre layouts de teclado; para cifras clássicas (César, ROT13, Morse) use uma API de cifra.
api.oanor.com/keyboardlayout-api
Entropy API
Measure the information content of text. The analyze endpoint computes the Shannon entropy in bits per symbol, the total information in bits and bytes, the maximum possible entropy for the alphabet that was actually used, and a normalized 0–1 score that says how uniform (random-looking) the distribution is — over Unicode code points or raw UTF-8 bytes. The frequency endpoint returns the full character-frequency distribution, most common symbol first, with counts and percentages, showing control characters escaped and bytes as hex. It is exact, deterministic and runs entirely locally with no network calls, so it is instant and private. Ideal for randomness and password-quality checks, estimating how compressible data is, language and classical-cipher analysis, spotting low-variety or repetitive input, and feature extraction for text classification. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This measures information content; for password-strength scoring use a password API, for number statistics use a statistics API, and for grapheme/character counts use a text-segmentation API.
api.oanor.com/entropy-api
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Frammenti di codice
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curl https://api.oanor.com/profanity-api/SOME_PATH \
-H "x-oanor-key: oanor_test_..."
const res = await fetch("https://api.oanor.com/profanity-api/SOME_PATH", {
headers: { "x-oanor-key": "oanor_test_..." }
});
const data = await res.json();
$ch = curl_init("https://api.oanor.com/profanity-api/SOME_PATH");
curl_setopt($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/profanity-api/SOME_PATH",
headers={"x-oanor-key": "oanor_test_..."},
)
print(r.json())
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