| """Automatic response-language identification with Lingua and fastText. |
| |
| Low-confidence detections pass the language check. |
| """ |
| import json,re,collections,hashlib |
| from pathlib import Path |
|
|
| FALLBACK_LANGUAGES={'am','ti','ne','prs'} |
| LID_CODES={'amh_Ethi':'am','tir_Ethi':'ti','npi_Deva':'ne','prs_Arab':'prs','pes_Arab':'fa', |
| 'eng_Latn':'en','fra_Latn':'fr','hin_Deva':'hi','arb_Arab':'ar','ary_Arab':'ar','arz_Arab':'ar', |
| 'deu_Latn':'de','rus_Cyrl':'ru','ukr_Cyrl':'uk','zho_Hans':'zh','zho_Hant':'zh','yue_Hant':'zh', |
| 'urd_Arab':'ur','heb_Hebr':'he','ben_Beng':'bn','hye_Armn':'hy','azj_Latn':'az', |
| 'spa_Latn':'es','por_Latn':'pt','pol_Latn':'pl','tam_Taml':'ta','tha_Thai':'th','tur_Latn':'tr'} |
|
|
| class FastTextFallback: |
| """Pinned local model, loaded without remote code or text uploads.""" |
| def __init__(self,path,manifest): |
| config=json.loads(Path(manifest).read_text());path=Path(path) |
| for key in ['probability_threshold','margin_threshold']: |
| value=config[key] |
| if type(value) not in {int,float} or not 0<=value<=1:raise ValueError('invalid language threshold: '+key) |
| h=hashlib.sha256() |
| with path.open('rb') as f: |
| for chunk in iter(lambda:f.read(1024*1024),b''):h.update(chunk) |
| if h.hexdigest()!=config['sha256']:raise ValueError('language model checksum mismatch') |
| import fasttext |
| self.model=fasttext.load_model(str(path));self.metadata=config |
| required={'__label__amh_Ethi','__label__tir_Ethi','__label__npi_Deva','__label__prs_Arab','__label__pes_Arab'} |
| if not required<=set(self.model.get_labels()):raise ValueError('language model lacks required classes') |
| def candidates(self,text): |
| |
| |
| result=self.model.f.predict(text.replace('\n',' ')+'\n',10,0.0,'strict') |
| return [(label.removeprefix('__label__'),float(prob)) for prob,label in result] |
|
|
| def fallback_classify(backend,text,query): |
| details=[];codes=[];uncertain=False |
| for start in range(0,len(text),800): |
| chunk=text[start:start+800] |
| if sum(c.isalpha() for c in chunk)<20:continue |
| candidates=backend.candidates(chunk);mass=collections.Counter() |
| for label,p in candidates: |
| code=LID_CODES.get(label,label) |
| |
| if query=='prs' and code=='fa':code='prs' |
| mass[code]+=p |
| ranked=mass.most_common();code,p=ranked[0] if ranked else (None,0.);p=min(p,1.) |
| second=ranked[1][1] if len(ranked)>1 else 0. |
| reliable=(p>=backend.metadata.get('probability_threshold',.80) and |
| p-second>=backend.metadata.get('margin_threshold',.20)) |
| details.append(dict(detected=code,confidence=p,margin=p-second,reliable=reliable,candidates=candidates)) |
| if reliable:codes.append(code) |
| else:uncertain=True |
| status=('same' if uncertain or not codes else 'mixed' if len(set(codes))>1 else 'same' if codes[0]==query else 'different') |
| return status,dict(backend='fasttext_lid218',windows=details) |
| def clean(s): |
| s=re.sub(r'<think>[\s\S]*?</think>',' ',s,flags=re.I) |
| s=re.sub(r'```[\s\S]*?```',' ',s);s=re.sub(r'^\s*>.*$',' ',s,flags=re.M) |
| s=re.sub(r'https?://\S+',' ',s) |
| |
| |
| s=re.sub(r'(?<![A-Za-z0-9_])D\d{4,}(?![A-Za-z0-9_])',' ',s) |
| return re.sub(r'\s+',' ',s).strip() |
| def classify(detector,text,query,fallback=None): |
| s=clean(text) |
| if not any(c.isalnum() for c in s):return 'no_answer',{'reason':'no prose'} |
| if query in FALLBACK_LANGUAGES and fallback is None: |
| raise ValueError('provide the pinned fastText fallback model for Amharic, Tigrinya, Nepali or Dari') |
| if query in FALLBACK_LANGUAGES and fallback is not None: |
| if sum(c.isalpha() for c in s)<20:return 'same',{'reason':'insufficient language evidence'} |
| return fallback_classify(fallback,s,query) |
| if sum(c.isalpha() for c in s)<40:return 'same',{'reason':'insufficient language evidence'} |
| codes=[];uncertain=False;details=[] |
| for start in range(0,len(s),800): |
| chunk=s[start:start+800] |
| if sum(c.isalpha() for c in chunk)<40:continue |
| v=detector.compute_language_confidence_values(chunk) |
| if not v:uncertain=True;continue |
| first=v[0];second=v[1].value if len(v)>1 else 0;code=first.language.iso_code_639_1.name.lower() |
| han=sum('\u3400'<=c<='\u9fff' for c in chunk);kana=sum('\u3040'<=c<='\u30ff' for c in chunk);letters=sum(c.isalpha() for c in chunk) |
| if code=='ja' and han/max(letters,1)>=.6 and kana/max(letters,1)<.05:code='zh' |
| reliable=first.value>=.7 and first.value-second>=.15 |
| |
| if ((query=='uk' and code in {'kk','ru','be'}) or |
| (query=='hi' and code in {'mr','ne'}) or |
| (query=='zh' and code=='en' and han/max(letters,1)>.1)): |
| reliable=False |
| if not reliable:uncertain=True |
| else:codes.append(code) |
| details.append({'detected':code,'confidence':first.value,'margin':first.value-second,'reliable':reliable}) |
| if uncertain or not codes:return 'same',{'windows':details} |
| if len(set(codes))>1:return 'mixed',{'windows':details} |
| return ('same' if codes[0]==query else 'different'),{'windows':details} |
|
|
