forked from mirrors/LibreTranslate
improve auto-detect for batch requests with multiple languages
This commit is contained in:
parent
6ec94ee9cf
commit
c29cecbb63
2 changed files with 44 additions and 23 deletions
52
app/app.py
52
app/app.py
|
@ -360,43 +360,61 @@ def create_app(args):
|
|||
)
|
||||
|
||||
if source_lang == "auto":
|
||||
candidate_langs = detect_languages(q)
|
||||
source_langs = []
|
||||
if batch:
|
||||
auto_detect_texts = q
|
||||
else:
|
||||
auto_detect_texts = [q]
|
||||
|
||||
overall_candidates = detect_languages(q)
|
||||
|
||||
for text_to_check in auto_detect_texts:
|
||||
if len(text_to_check) > 40:
|
||||
candidate_langs = detect_languages(text_to_check)
|
||||
else:
|
||||
# Unable to accurately detect languages for short texts
|
||||
candidate_langs = overall_candidates
|
||||
source_langs.append(candidate_langs[0]["language"])
|
||||
|
||||
if args.debug:
|
||||
print(candidate_langs)
|
||||
print(text_to_check, candidate_langs)
|
||||
print("Auto detected: %s" % candidate_langs[0]["language"])
|
||||
else:
|
||||
if batch:
|
||||
source_langs = [source_lang for text in q]
|
||||
else:
|
||||
source_langs = [source_lang]
|
||||
|
||||
source_lang = candidate_langs[0]["language"]
|
||||
src_langs = [next(iter([l for l in languages if l.code == source_lang]), None) for source_lang in source_langs]
|
||||
|
||||
if args.debug:
|
||||
print("Auto detected: %s" % source_lang)
|
||||
for idx, lang in enumerate(src_langs):
|
||||
if lang is None:
|
||||
abort(400, description="%s is not supported" % source_langs[idx])
|
||||
|
||||
src_lang = next(iter([l for l in languages if l.code == source_lang]), None)
|
||||
tgt_lang = next(iter([l for l in languages if l.code == target_lang]), None)
|
||||
|
||||
if src_lang is None:
|
||||
abort(400, description="%s is not supported" % source_lang)
|
||||
if tgt_lang is None:
|
||||
abort(400, description="%s is not supported" % target_lang)
|
||||
|
||||
translator = src_lang.get_translation(tgt_lang)
|
||||
|
||||
try:
|
||||
if batch:
|
||||
results = []
|
||||
for idx, text in enumerate(q):
|
||||
translator = src_langs[idx].get_translation(tgt_lang)
|
||||
results.append(translator.translate(
|
||||
transliterate(text, target_lang=source_langs[idx])
|
||||
))
|
||||
return jsonify(
|
||||
{
|
||||
"translatedText": [
|
||||
translator.translate(
|
||||
transliterate(text, target_lang=source_lang)
|
||||
)
|
||||
for text in q
|
||||
]
|
||||
"translatedText": results
|
||||
}
|
||||
)
|
||||
else:
|
||||
translator = src_langs[0].get_translation(tgt_lang)
|
||||
return jsonify(
|
||||
{
|
||||
"translatedText": translator.translate(
|
||||
transliterate(q, target_lang=source_lang)
|
||||
transliterate(q, target_lang=source_langs[0])
|
||||
)
|
||||
}
|
||||
)
|
||||
|
|
|
@ -22,16 +22,19 @@ def detect_languages(text):
|
|||
candidates = []
|
||||
for t in text:
|
||||
try:
|
||||
candidates.extend(Detector(t).languages)
|
||||
d = Detector(t).languages
|
||||
for i in range(len(d)):
|
||||
d[i].text_length = len(t)
|
||||
candidates.extend(d)
|
||||
except UnknownLanguage:
|
||||
pass
|
||||
|
||||
# total read bytes of the provided text
|
||||
read_bytes_total = sum(c.read_bytes for c in candidates)
|
||||
text_length_total = sum(c.text_length for c in candidates)
|
||||
|
||||
# only use candidates that are supported by argostranslate
|
||||
candidate_langs = list(
|
||||
filter(lambda l: l.read_bytes != 0 and l.code in __lang_codes, candidates)
|
||||
filter(lambda l: l.text_length != 0 and l.code in __lang_codes, candidates)
|
||||
)
|
||||
|
||||
# this happens if no language could be detected
|
||||
|
@ -50,7 +53,7 @@ def detect_languages(text):
|
|||
# if more than one is present, calculate the average confidence
|
||||
lang = lc[0]
|
||||
lang.confidence = sum(l.confidence for l in lc) / len(lc)
|
||||
lang.read_bytes = sum(l.read_bytes for l in lc)
|
||||
lang.text_length = sum(l.text_length for l in lc)
|
||||
temp_average_list.append(lang)
|
||||
elif lc:
|
||||
# otherwise just add it to the temporary list
|
||||
|
@ -62,7 +65,7 @@ def detect_languages(text):
|
|||
|
||||
# sort the candidates descending based on the detected confidence
|
||||
candidate_langs.sort(
|
||||
key=lambda l: (l.confidence * l.read_bytes) / read_bytes_total, reverse=True
|
||||
key=lambda l: (l.confidence * l.text_length) / text_length_total, reverse=True
|
||||
)
|
||||
|
||||
return [{"confidence": l.confidence, "language": l.code} for l in candidate_langs]
|
||||
|
|
Loading…
Reference in a new issue