Files
VRCT/src-python/models/translation/translation_translator.py

193 lines
8.6 KiB
Python

from os import path as os_path
from deepl import DeepLClient
try:
from translators import translate_text as other_web_Translator
ENABLE_TRANSLATORS = True
except Exception:
other_web_Translator = None # type: ignore
ENABLE_TRANSLATORS = False
from .translation_languages import translation_lang
from .translation_utils import ctranslate2_weights
import ctranslate2
import transformers
from utils import errorLogging, getBestComputeType
import warnings
from typing import Any, Optional, Tuple
warnings.filterwarnings("ignore")
class Translator:
"""High-level translator facade.
This class wraps multiple backends (DeepL, DeepL API, Google, Bing, Papago,
and CTranslate2 local models). Optional dependencies may be unavailable at
runtime; methods degrade gracefully and return False or an empty string on
failure (kept compatible with existing behavior).
"""
def __init__(self) -> None:
self.deepl_client: Optional[DeepLClient] = None
self.ctranslate2_translator: Any = None
self.ctranslate2_tokenizer: Any = None
self.is_loaded_ctranslate2_model: bool = False
self.is_changed_translator_parameters: bool = False
self.is_enable_translators: bool = ENABLE_TRANSLATORS
def authenticationDeepLAuthKey(self, authkey: str) -> bool:
"""Authenticate DeepL API with the provided key.
Returns True on success, False on failure.
"""
result = True
try:
self.deepl_client = DeepLClient(authkey)
# quick smoke test
self.deepl_client.translate_text(" ", target_lang="EN-US")
except Exception:
errorLogging()
self.deepl_client = None
result = False
return result
def changeCTranslate2Model(self, path: str, model_type: str, device: str = "cpu", device_index: int = 0, compute_type: str = "auto") -> None:
"""Load a CTranslate2 model from weights.
This sets internal translator/tokenizer objects and flips
``is_loaded_ctranslate2_model`` on success.
"""
self.is_loaded_ctranslate2_model = False
directory_name = ctranslate2_weights[model_type]["directory_name"]
tokenizer = ctranslate2_weights[model_type]["tokenizer"]
weight_path = os_path.join(path, "weights", "ctranslate2", directory_name)
tokenizer_path = os_path.join(path, "weights", "ctranslate2", directory_name, "tokenizer")
if compute_type == "auto":
compute_type = getBestComputeType(device, device_index)
self.ctranslate2_translator = ctranslate2.Translator(
weight_path,
device=device,
device_index=device_index,
compute_type=compute_type,
inter_threads=1,
intra_threads=4,
)
try:
self.ctranslate2_tokenizer = transformers.AutoTokenizer.from_pretrained(tokenizer, cache_dir=tokenizer_path)
except Exception:
errorLogging()
tokenizer_path = os_path.join("./weights", "ctranslate2", directory_name, "tokenizer")
self.ctranslate2_tokenizer = transformers.AutoTokenizer.from_pretrained(tokenizer, cache_dir=tokenizer_path)
self.is_loaded_ctranslate2_model = True
def isLoadedCTranslate2Model(self) -> bool:
return self.is_loaded_ctranslate2_model
def isChangedTranslatorParameters(self) -> bool:
return self.is_changed_translator_parameters
def setChangedTranslatorParameters(self, is_changed: bool) -> None:
self.is_changed_translator_parameters = is_changed
def translateCTranslate2(self, message: str, source_language: str, target_language: str) -> Any:
"""Translate using a loaded CTranslate2 model.
Returns a string on success or False on failure (keeps legacy behavior).
"""
result: Any = False
if self.is_loaded_ctranslate2_model is True:
try:
self.ctranslate2_tokenizer.src_lang = source_language
source = self.ctranslate2_tokenizer.convert_ids_to_tokens(self.ctranslate2_tokenizer.encode(message))
target_prefix = [self.ctranslate2_tokenizer.lang_code_to_token[target_language]]
results = self.ctranslate2_translator.translate_batch([source], target_prefix=[target_prefix])
target = results[0].hypotheses[0][1:]
result = self.ctranslate2_tokenizer.decode(self.ctranslate2_tokenizer.convert_tokens_to_ids(target))
except Exception:
errorLogging()
return result
@staticmethod
def getLanguageCode(translator_name: str, target_country: str, source_language: str, target_language: str) -> Tuple[str, str]:
"""Resolve a friendly language name to translator-specific codes.
Returns (source_code, target_code).
"""
match translator_name:
case "DeepL_API":
if target_language == "English":
if target_country in ["United States", "Canada", "Philippines"]:
target_language = "English American"
else:
target_language = "English British"
elif target_language == "Portuguese":
if target_country in ["Portugal"]:
target_language = "Portuguese European"
else:
target_language = "Portuguese Brazilian"
case _:
pass
source_language = translation_lang[translator_name]["source"][source_language]
target_language = translation_lang[translator_name]["target"][target_language]
return source_language, target_language
def translate(self, translator_name: str, source_language: str, target_language: str, target_country: str, message: str) -> Any:
"""Translate `message` using the named translator backend.
Returns translated string on success, or False on failure. When
source_language == target_language the original message is returned.
"""
try:
if source_language == target_language:
return message
result: Any = ""
source_language, target_language = self.getLanguageCode(translator_name, target_country, source_language, target_language)
match translator_name:
case "DeepL":
if self.is_enable_translators is True and other_web_Translator is not None:
result = other_web_Translator(
query_text=message,
translator="deepl",
from_language=source_language,
to_language=target_language,
)
case "DeepL_API":
if self.is_enable_translators is True:
if self.deepl_client is None:
result = False
else:
result = self.deepl_client.translate_text(message, source_lang=source_language, target_lang=target_language).text
case "Google":
if self.is_enable_translators is True and other_web_Translator is not None:
result = other_web_Translator(
query_text=message,
translator="google",
from_language=source_language,
to_language=target_language,
)
case "Bing":
if self.is_enable_translators is True and other_web_Translator is not None:
result = other_web_Translator(
query_text=message,
translator="bing",
from_language=source_language,
to_language=target_language,
)
case "Papago":
if self.is_enable_translators is True and other_web_Translator is not None:
result = other_web_Translator(
query_text=message,
translator="papago",
from_language=source_language,
to_language=target_language,
)
case "CTranslate2":
result = self.translateCTranslate2(message=message, source_language=source_language, target_language=target_language)
except Exception:
errorLogging()
result = False
return result