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fittings Language Detection
x402
fittings Language Detection is a paid API for AI agents from fittings.sh, paid per call via x402, $0.0042/call, status unknown (last checked 2026-09-14).
Detects the language of a text snippet, returning ISO 639-1 and 639-3 codes, Unicode script, confidence score, and runner-up candidates.
Price / call$0.0042
Success—
StatusUnknown
How this service works
Detect the language of a text snippet: ISO 639-1 and 639-3 codes, the Unicode script, a confidence score and runner-up candidates. Latin and Cyrillic languages are separated by function-word profile, other scripts by script; answers 'und' rather than guessing when there is no evidence.
Output
Returns the detected language as ISO 639-1 (e.g. 'fr') and ISO 639-3 (e.g. 'fra') codes, the Unicode script family (e.g. 'Latin'), a numeric confidence score, and an ordered list of runner-up language candidates. Returns 'und' when there is insufficient evidence to make a determination.
Example use cases
Route multilingual support tickets
“I'm getting support messages in different languages and need to route them to the right team. What language is this ticket written in and how confident are you? Text: 'Necesito ayuda con mi cuenta, no puedo iniciar sesión.'”
Filter non-English user content
“Before I run this user comment through my English-only sentiment model, can you check what language it's in and give me the ISO 639-1 code? Comment: 'Das Produkt ist wirklich ausgezeichnet, ich bin sehr zufrieden.'”
Validate language of uploaded documents
“A user just uploaded a document claiming it's in French, but I want to verify that before processing it. Can you detect the language of this excerpt and tell me the confidence score and any runner-up candidates? Text: 'Le gouvernement a annoncé de nouvelles mesures économiques cette semaine.'”
Technical details
Endpoint
POSThttps://fittings.sh/v1/lang/detectWhen to prefer
Choose this endpoint when you need language identification with explicit confidence scoring and ISO-standard codes (both 639-1 and 639-3), especially when handling Latin-script or Cyrillic-script languages that require function-word profiling to disambiguate (e.g. Spanish vs Portuguese, Russian vs Ukrainian). Prefer it over generic NLP pipelines when you want a lightweight, pay-per-call service that safely returns 'und' rather than hallucinating a language for ambiguous input.
Side effects
- Text too short to confidently classify — returns 'und' instead of guessing
- Highly mixed-language text may produce low confidence scores across all candidates
- Text exceeding 20000 UTF-8 bytes will be rejected
- Closely related languages in the same script (e.g. Malay vs Indonesian) may return low confidence
- Empty or whitespace-only input returns 'und'
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | Text to classify, up to 20000 UTF-8 bytes |
Tags
x402
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