language_detect
Guess the language of a text among 20 languages (en es fr de pt it nl ca ro pl cs sv da no fi hu tr id ru el) by comparing its character 1-3-gram ranking with bundled profiles, the out-of-place method of Cavnar and Trenkle (1994). Returns the top candidates with distances and scores, and "unknown" when the text is too short, too far from every profile or too close between two languages. A heuristic: short texts and close languages are unreliable. Profiles are counts from Unicode CLDR 48.2 locale data (Unicode License); no UDHR text was used.
Install
/tools install language_detect /tools install language_detect@1.0.0
In a console session, or let the model find it in normal mode: axlr_catalog describes it and axlr_install_tool asks for the same install card. The card reads catalog axlr · language_detect 1.0.0 · verified once the index signature, the manifest digest and every file digest check out. Then the model runs it with axlr_run_tool language_detect; each run is approved as a local_exec.
Arguments
One JSON object on stdin, validated against the schema before the program starts.
| name | type | required | default | meaning |
|---|---|---|---|---|
text | string | yes | length ≤ 100000 | |
top_k | integer | no | 3 | ≥ 1; ≤ 20 |
languages | array of string | no | Restrict the candidates to these | |
max_distance | number | no | 0.6 | unknown above this distance. ≥ 0; ≤ 1 |
min_margin | number | no | 0.01 | unknown when the best two are closer than this. ≥ 0; ≤ 1 |
Input schema (JSON)
{
"type": "object",
"required": [
"text"
],
"additionalProperties": false,
"properties": {
"text": {
"type": "string",
"maxLength": 100000
},
"top_k": {
"type": "integer",
"minimum": 1,
"maximum": 20,
"default": 3
},
"languages": {
"type": "array",
"items": {
"type": "string",
"enum": [
"en",
"es",
"fr",
"de",
"pt",
"it",
"nl",
"ca",
"ro",
"pl",
"cs",
"sv",
"da",
"no",
"fi",
"hu",
"tr",
"id",
"ru",
"el"
]
},
"description": "Restrict the candidates to these"
},
"max_distance": {
"type": "number",
"minimum": 0,
"maximum": 1,
"default": 0.6,
"description": "unknown above this distance"
},
"min_margin": {
"type": "number",
"minimum": 0,
"maximum": 1,
"default": 0.01,
"description": "unknown when the best two are closer than this"
}
}
}Example
Input
{
"text": "Paris est la capitale de la France et le chef-lieu de la région Île-de-France."
}Output (stdout)
{
"language": "fr",
"name": "French",
"reliable": true,
"candidates": [
{
"language": "fr",
"distance": 0.3919,
"score": 0.6081
},
{
"language": "it"
},
{
"language": "en"
}
]
}Files
The command the install card registers is python3 language_detect.py, run in the workspace with PATH and HOME as its only environment. Each file's SHA-256 is in the signed index; the console checks them before showing the card and again before writing.
language_detect.py · sha256 eb631c82ffab37fb019086cb4bf6746687e48cab40d6fc843d87fedfa5cc3cd9
#!/usr/bin/env python3
"""Guess the language of a text with character n-grams (Cavnar & Trenkle 1994, "N-Gram-Based
Text Categorization"): the text's 1-3-grams ranked by frequency are compared with the bundled
ranked profiles of 20 languages (profiles.json, counted from Unicode CLDR locale data by
tools/catalog/data/language_detect.py), and the "out-of-place" distance picks the language.
A heuristic: short texts and closely related languages (Danish/Norwegian, Spanish/Catalan)
are unreliable, and a text in a language without a profile is still matched to the nearest one
unless it is too far from all of them.
Input (JSON on stdin):
text the text (required)
top_k how many candidates to return, 1-20 (default 3)
languages restrict the candidates to these codes, e.g. ["es", "ca", "pt"]
max_distance "unknown" when the best distance is above this (default 0.6)
min_margin "unknown" when the best two distances differ by less than this (default 0.01)
"""
import json
import pathlib
import sys
import unicodedata
MAX_CHARS = 100000
DEFAULTS = {"top_k": 3, "max_distance": 0.6, "min_margin": 0.01}
RELIABLE_LETTERS = 30
def fail(message):
print(json.dumps({"error": message}, ensure_ascii=False))
sys.exit(2)
def words(text):
text = unicodedata.normalize("NFC", text).lower()
return "".join(c if c.isalpha() else " " for c in text).split()
def ngrams(word_list):
for word in word_list:
padded = f" {word} "
for n in (1, 2, 3):
for i in range(len(padded) - n + 1):
gram = padded[i:i + n]
if gram.strip():
yield gram
def ranked(counts, size):
return [g for g, _ in sorted(counts.items(), key=lambda item: (-item[1], item[0]))[:size]]
def number(request, key, low, high, integer=False):
value = request.get(key, DEFAULTS[key])
if isinstance(value, bool) or not isinstance(value, (int, float)) or (integer and not isinstance(value, int)):
fail(f"{key} must be {'an integer' if integer else 'a number'} from {low} to {high}")
if not low <= value <= high:
fail(f"{key} must be from {low} to {high}")
return value
def main():
try:
request = json.load(sys.stdin)
except ValueError as error:
fail(f"stdin is not JSON: {error}")
if not isinstance(request, dict):
fail("input must be a JSON object")
extra = sorted(set(request) - {"text", "top_k", "languages", "max_distance", "min_margin"})
if extra:
fail(f"unknown field: {extra[0]}")
text = request.get("text")
if not isinstance(text, str):
fail("text must be a string")
if len(text) > MAX_CHARS:
fail(f"text is longer than {MAX_CHARS} characters")
top_k = number(request, "top_k", 1, 20, integer=True)
max_distance = number(request, "max_distance", 0, 1)
min_margin = number(request, "min_margin", 0, 1)
data = json.loads((pathlib.Path(__file__).parent / "profiles.json").read_text(encoding="utf-8"))
profiles = data["profiles"]
chosen = list(profiles)
if "languages" in request:
wanted = request["languages"]
if not isinstance(wanted, list) or not wanted or not all(isinstance(c, str) for c in wanted):
fail("languages must be a non-empty list of language codes")
unknown = [c for c in wanted if c not in profiles]
if unknown:
fail(f"no profile for {unknown[0]!r}; profiles: {', '.join(profiles)}")
chosen = list(dict.fromkeys(wanted))
word_list = words(text)
letters = sum(len(w) for w in word_list)
counts = {}
for gram in ngrams(word_list):
counts[gram] = counts.get(gram, 0) + 1
size = max(len(p["ngrams"]) for p in profiles.values())
document = ranked(counts, size)
candidates = []
for code in chosen:
rank = {g: i for i, g in enumerate(ranked(profiles[code]["ngrams"], size))}
if document:
total = sum(abs(rank[g] - i) if g in rank else size for i, g in enumerate(document))
distance = total / (len(document) * size)
else:
distance = 1.0
candidates.append((distance, code))
candidates.sort()
best_distance, best = candidates[0]
margin = candidates[1][0] - best_distance if len(candidates) > 1 else 1.0
reason = None
if letters < 3:
reason = "too short: fewer than 3 letters"
elif best_distance >= 1.0:
reason = "none of the text's n-grams is in any profile (another script or language)"
elif best_distance > max_distance:
reason = f"best distance {best_distance:.4f} is above max_distance {max_distance}: probably a language without a profile"
elif margin < min_margin:
reason = f"{best} and {candidates[1][1]} are too close (margin {margin:.4f} < min_margin {min_margin})"
language = "unknown" if reason else best
result = {
"language": language,
"name": profiles[best]["name"] if not reason else None,
"reliable": not reason and letters >= RELIABLE_LETTERS,
}
if reason:
result["reason"] = reason
elif letters < RELIABLE_LETTERS:
result["reason"] = f"short text ({letters} letters): treat the guess with caution"
result.update({
"margin": round(margin, 4),
"candidates": [{"language": c, "name": profiles[c]["name"], "distance": round(d, 4), "score": round(1 - d, 4)} for d, c in candidates[:top_k]],
"letters": letters,
"ngrams_compared": len(document),
"thresholds": {"max_distance": max_distance, "min_margin": min_margin},
"method": "Cavnar & Trenkle (1994) out-of-place distance between ranked character 1-3-gram profiles; distance 0 = same ranking, 1 = nothing in common; score = 1 - distance",
"note": "a heuristic: short texts, mixed-language texts and close languages (da/no, es/ca/pt) are unreliable; only the 20 profiled languages can be named",
"source": {"corpus": data["corpus"], "licence": data["corpus_licence"], "generated": data["generated"], "generator": data["generator"],
"udhr_not_used": data["udhr_not_used"]},
})
print(json.dumps(result, ensure_ascii=False))
if __name__ == "__main__":
main()
profiles.json · sha256 91d0c9b1f98b8087bae47bfa41036228c68359a6cf89900ff5e47f776351ed94
{
"generated": "2026-10-18",
"generator": "tools/catalog/data/language_detect.py",
"method": "character 1-3-grams of space-padded words, the 500 most frequent per language (ties by code point order), as counts; no source text is stored",
"corpus": "Unicode CLDR 48.2 locale data: common/main/<lang>.xml display names and labels, and common/annotations/<lang>.xml emoji names and keywords",
"corpus_url": "https://raw.githubusercontent.com/unicode-org/cldr/release-48-2/",
"corpus_licence": "Unicode License v3",
"udhr_not_used": "unicode.org/udhr says: \"Effective January 2024, the Unicode Consortium is no longer hosting the UDHR in Unicode project\". The UN terms of use allow copies \"for the User's personal, non-commercial use, without any right to resell or redistribute them or to compile or create derivative works therefrom\". The successor project UDHR in XML (efele.net, github.com/eric-muller/udhr) has no licence, only \"The UDHR and all its translations are obviously part of our commons.\" None is a clear permissive licence, so no UDHR text was used.",
"unicode_license_notice": [
"UNICODE LICENSE V3",
"",
"COPYRIGHT AND PERMISSION NOTICE",
"",
"Copyright © 2004-2026 Unicode, Inc.",
"",
"NOTICE TO USER: Carefully read the following legal agreement. BY",
"DOWNLOADING, INSTALLING, COPYING OR OTHERWISE USING DATA FILES, AND/OR",
"SOFTWARE, YOU UNEQUIVOCALLY ACCEPT, AND AGREE TO BE BOUND BY, ALL OF THE",
"TERMS AND CONDITIONS OF THIS AGREEMENT. IF YOU DO NOT AGREE, DO NOT",
"DOWNLOAD, INSTALL, COPY, DISTRIBUTE OR USE THE DATA FILES OR SOFTWARE.",
"",
"Permission is hereby granted, free of charge, to any person obtaining a",
"copy of data files and any associated documentation (the \"Data Files\") or",
"software and any associated documentation (the \"Software\") to deal in the",
"Data Files or Software without restriction, including without limitation",
"the rights to use, copy, modify, merge, publish, distribute, and/or sell",
"copies of the Data Files or Software, and to permit persons to whom the",
"Data Files or Software are furnished to do so, provided that either (a)",
"this copyright and permission notice appear with all copies of the Data",
"Files or Software, or (b) this copyright and permission notice appear in",
"associated Documentation.",
"",
"THE DATA FILES AND SOFTWARE ARE PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY",
"KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF",
"MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OF",
"THIRD PARTY RIGHTS.",
"",
"IN NO EVENT SHALL THE COPYRIGHT HOLDER OR HOLDERS INCLUDED IN THIS NOTICE",
"BE LIABLE FOR ANY CLAIM, OR ANY SPECIAL INDIRECT OR CONSEQUENTIAL DAMAGES,",
"OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,",
"WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION,",
"ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THE DATA",
"FILES OR SOFTWARE.",
"",
"Except as contained in this notice, the name of a copyright holder shall",
"not be used in advertising or otherwise to promote the sale, use or other",
"dealings in these Data Files or Software without prior written",
"authorization of the copyright holder.",
"",
"SPDX-License-Identifier: Unicode-3.0"
],
"fetched": "2026-10-18",
"profiles": {
"en": {
"name": "English",
"corpus_strings": 16242,
"corpus_letters": 118377,
"ngrams": {
"e": 11721,
"a": 11258,
"i": 8965,
"r": 8726,
"o": 8301,
"n": 8250,
"t": 7921,
"s": 6916,
"l": 6312,
"c": 4873,
"d": 4152,
"m": 3842,
"h": 3787,
"u": 3642,
"g": 3532,
"p": 3323,
"e ": 3120,
"b": 2569,
"n ": 2440,
" s": 2274,
"in": 2236,
"w": 2216,
"f": 2112,
"an": 2062,
"t ": 1963,
"y": 1913,
"ar": 1867,
"s ": 1814,
"er": 1802,
"k": 1746,
" c": 1645,
"d ": 1490,
"on": 1461,
" m": 1418,
" b": 1413,
"ng": 1392,
"r ": 1384,
" f": 1350,
"le": 1323,
" p": 1268,
" a": 1258,
" t": 1231,
"g ": 1200,
"al": 1193,
"ma": 1156,
"l ": 1107,
"y ": 1101,
"re": 1056,
"ing": 1045,
"ng ": 1024,
"ra": 1022,
"te": 1018,
"ti": 1013,
" d": 1012,
"at": 1010,
"ri": 1007,
" h": 933,
"ro": 913,
" w": 899,
"st": 893,
"th": 867,
"v": 857,
"es": 853,
"en": 843,
"or": 842,
" l": 837,
"on ": 822,
"er ": 804,
"ic": 804,
" r": 803,
"ed": 790,
"se": 776,
"ac": 763,
"ea": 760,
"ce": 756,
"lo": 755,
"nt": 753,
"li": 749,
"la": 742,
"an ": 739,
"h ": 731,
"it": 722,
"ow": 674,
"he": 670,
"ha": 666,
"ca": 656,
"ne": 653,
"pe": 649,
"nd": 644,
"ed ": 628,
" e": 625,
"a ": 625,
"il": 618,
"le ": 617,
"o ": 617,
"ll": 613,
" g": 603,
"is": 593,
"k ": 593,
"me": 592,
"tr": 589,
" o": 583,
"di": 579,
"ol": 568,
"ta": 555,
"ig": 553,
"ch": 552,
" i": 546,
"to": 545,
"rt": 544,
"as": 541,
"de": 537,
"et": 531,
" n": 527,
"ni": 525,
"om": 522,
" ma": 518,
"el": 517,
"al ": 514,
"co": 514,
"ho": 514,
"mo": 514,
"hi": 510,
"ou": 509,
"fa": 508,
"io": 507,
"ce ": 502,
"ia": 493,
"ir": 493,
"ba": 488,
"oo": 482,
" fa": 481,
"sh": 477,
"ur": 476,
"rd": 474,
"ai": 461,
"w ": 450,
"ve": 448,
"un": 433,
"cl": 430,
"ion": 429,
"ck": 424,
"pa": 423,
"po": 415,
"man": 414,
"am": 413,
"si": 413,
"ot": 411,
"mi": 407,
"ut": 407,
"wa": 404,
"ter": 402,
"us": 402,
"ee": 401,
"p ": 398,
"ge": 395,
"m ": 392,
"ke": 389,
"i ": 383,
"rs": 383,
" k": 382,
"da": 382,
"gh": 373,
"ow ": 373,
"ace": 372,
"x": 369,
"j": 368,
"rr": 368,
" mo": 365,
" ba": 360,
"ard": 360,
"bo": 358,
"q": 348,
" ar": 347,
"ad": 342,
"in ": 341,
"ap": 340,
"op": 340,
"tio": 340,
"so": 339,
" in": 338,
"ag": 336,
"c ": 336,
"se ": 336,
"no": 333,
"per": 333,
"ss": 332,
" co": 331,
"ati": 329,
"ht": 329,
"im": 329,
"na": 327,
" u": 326,
"igh": 326,
"bi": 323,
"do": 323,
"th ": 323,
"fi": 320,
" ca": 315,
"wi": 314,
"ght": 312,
"we": 312,
"bu": 309,
" ha": 308,
"fac": 308,
"qu": 304,
"ar ": 302,
"sa": 302,
"wo": 301,
"row": 300,
"z": 300,
"and": 295,
"es ": 295,
"ec": 293,
"ua": 293,
"ds": 288,
"nc": 286,
"be": 282,
"ci": 279,
"pi": 276,
" tr": 273,
"ds ": 270,
" di": 269,
"bl": 268,
"gr": 268,
"ay": 267,
"em": 267,
"nd ": 266,
"tu": 265,
" bu": 262,
" do": 262,
" pe": 261,
"os": 261,
" wo": 260,
"ers": 259,
"ian": 259,
"arr": 258,
"et ": 256,
" cl": 254,
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"nt ": 253,
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" st": 250,
"rro": 250,
"st ": 249,
"up": 249,
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"ss ": 136,
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"x ": 135,
"her": 134,
"oll": 134,
"ria": 134,
" bi": 133,
" pi": 133,
"own": 133,
"rs ": 133,
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"are": 132,
"ess": 132,
"nim": 132,
"oa": 132,
"fe": 131,
"ok": 131,
"ot ": 131,
"rea": 131,
" te": 130,
"ack": 130,
"ble": 130,
"nti": 130,
"ope": 130,
"ain": 129,
"air": 129,
"ath": 129,
"car": 129,
"res": 129,
" ta": 128,
"eg": 128,
"nk": 128,
"sy": 128,
"son": 127,
"uar": 127,
"day": 126,
"era": 126,
"lle": 126,
"mu": 126,
"pu": 126,
" ci": 125,
" pr": 125,
"but": 125,
"of": 125,
"ov": 125,
"wit": 125,
"gu": 124,
" bl": 123,
"ted": 123,
"twa": 123,
"hu": 122,
"ste": 122,
" q": 121,
" wh": 121,
"mar": 121,
"oin": 121,
"tto": 121,
"ist": 120,
"tur": 120,
"nu": 119,
"tor": 119,
" cu": 118,
"go ": 118,
"ls": 118,
"ly ": 118,
"me ": 118,
"rso": 118,
"che": 116,
"hol": 116,
"nta": 116,
"u ": 116,
"ago": 115
}
},
"es": {
"name": "Spanish",
"corpus_strings": 12005,
"corpus_letters": 118704,
"ngrams": {
"a": 15990,
"e": 11944,
"o": 10854,
"r": 9521,
"i": 8001,
"n": 7602,
"c": 6962,
"l": 6026,
"s": 5569,
"d": 5433,
"a ": 5318,
"t": 5085,
"o ": 4737,
"u": 4115,
"m": 3739,
"e ": 3070,
"p": 2787,
" c": 2693,
"b": 2630,
" d": 2181,
"h": 2102,
"de": 2083,
"er": 2012,
"ra": 2008,
"s ": 1955,
"ar": 1872,
"g": 1824,
" de": 1709,
" m": 1661,
"n ": 1626,
" p": 1519,
"an": 1514,
"co": 1511,
"en": 1502,
" a": 1467,
"ca": 1420,
"la": 1345,
"re": 1343,
"do": 1319,
"on": 1304,
"de ": 1298,
"or": 1270,
"nt": 1234,
"ta": 1200,
"es": 1194,
"f": 1193,
"ad": 1154,
"te": 1141,
"as": 1138,
"al": 1137,
"ri": 1125,
" s": 1120,
"ci": 1103,
"j": 1097,
"ma": 1082,
"r ": 1041,
"ro": 1029,
"v": 1029,
"in": 1025,
"le": 1016,
" e": 1005,
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}
}
Where it is served
The registry serves only AXLR clients, so a browser gets 403; fetch with a User-Agent that starts with axlr:
curl -A axlr-docs/1.0 -O https://registry.underpassai.com/tools/language_detect/1.0.0/manifest.json
curl -A axlr-docs/1.0 -O https://registry.underpassai.com/tools/language_detect/1.0.0/language_detect.py
curl -A axlr-docs/1.0 -O https://registry.underpassai.com/tools/language_detect/1.0.0/profiles.json