# -*- coding: utf-8 -*-
# SPDX-FileCopyrightText: 2016-2025 PyThaiNLP Project
# SPDX-FileType: SOURCE
# SPDX-License-Identifier: Apache-2.0
from typing import List, Union
[docs]
class Translate:
"""
Machine Translation
"""
[docs]
def __init__(
self,
src_lang: str,
target_lang: str,
engine: str = "default",
use_gpu: bool = False,
) -> None:
"""
:param str src_lang: source language
:param str target_lang: target language
:param str engine: machine translation engine
:param bool use_gpu: load model using GPU (Default is False)
**Options for engine*
* *default* - The default engine for each language.
* *small100* - A multilingual machine translation model (covering 100 languages)
**Options for source & target language**
* *th* - *en* - Thai to English
* *en* - *th* - English to Thai
* *th* - *zh* - Thai to Chinese
* *zh* - *th* - Chinese to Thai
* *th* - *fr* - Thai to French
* *th* - *xx* - Thai to xx (xx is language code). It uses small100 model.
* *xx* - *th* - xx to Thai (xx is language code). It uses small100 model.
:Example:
Translate text from Thai to English::
from pythainlp.translate import Translate
th2en = Translate("th", "en")
th2en.translate("ฉันรักแมว")
# output: I love cat.
"""
self.model = None
self.engine = engine
self.src_lang = src_lang
self.use_gpu = use_gpu
self.target_lang = target_lang
self.load_model()
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def load_model(self):
src_lang = self.src_lang
target_lang = self.target_lang
use_gpu = self.use_gpu
if self.engine == "small100":
from .small100 import Small100Translator
self.model = Small100Translator(use_gpu)
elif src_lang == "th" and target_lang == "en":
from pythainlp.translate.en_th import ThEnTranslator
self.model = ThEnTranslator(use_gpu)
elif src_lang == "en" and target_lang == "th":
from pythainlp.translate.en_th import EnThTranslator
self.model = EnThTranslator(use_gpu)
elif src_lang == "th" and target_lang == "zh":
from pythainlp.translate.zh_th import ThZhTranslator
self.model = ThZhTranslator(use_gpu)
elif src_lang == "zh" and target_lang == "th":
from pythainlp.translate.zh_th import ZhThTranslator
self.model = ZhThTranslator(use_gpu)
elif src_lang == "th" and target_lang == "fr":
from pythainlp.translate.th_fr import ThFrTranslator
self.model = ThFrTranslator(use_gpu)
else:
raise ValueError("Not support language!")
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def translate(self, text: str) -> str:
"""
Translate text
:param str text: input text in source language
:return: translated text in target language
:rtype: str
"""
if self.engine == "small100":
return self.model.translate(text, tgt_lang=self.target_lang)
return self.model.translate(text)
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def word_translate(
word: str,
src: str,
target: str,
engine: str="word2word"
) -> Union[List[str], None]:
"""
Translate word from source language to target language.
:param str word: text
:param str src: src language
:param str target: target language
:param str engine: Word translate engine (the default engine is word2word)
:return: return list word translate or None
:rtype: Union[List[str], None]
:Example:
Translate word from Thai to English::
from pythainlp.translate import word_translate
print(word_translate("แมว","th","en"))
# output: ['cat', 'cats', 'kitty', 'kitten', 'Cat']
Translate word from English to Thai::
from pythainlp.translate import word_translate
print(word_translate("cat","en","th"))
# output: ['แมว', 'แมวป่า', 'ข่วน', 'เลี้ยง', 'อาหาร']
"""
if engine=="word2word":
from .word2word_translate import translate
return translate(word=word, src=src, target=target)
else:
raise NotImplementedError(
f"pythainlp.translate.word_translate isn't support {engine}."
)