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LMStudio と Ollama の翻訳バックエンドを追加・統合。

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- config: SELECTABLE_/SELECTED_ の LMStudio/Ollama 項目と LMSTUDIO_URL を追加。
- Controller: LMStudio/Ollama の認証チェック、URL取得/設定、モデル一覧取得/設定のエンドポイントを実装。
- Model/Translator: LMStudio/Ollama 用の認証・モデル一覧・モデル設定・クライアント更新メソッドを追加し、翻訳処理の選択肢に対応。
- translation_* クライアント: 各クライアントでのプロンプト読み込み処理を共通化し、translation_utils.loadPromptConfig を利用するようにリファクタ。
- translation_languages: LMStudio/Ollama 用の言語マッピングを追加。
This commit is contained in:
misyaguziya
2025-10-17 21:48:44 +09:00
parent 965bee818a
commit 7e7b3505a1
11 changed files with 401 additions and 117 deletions
Download Patch File Download Diff File Expand all files Collapse all files

58
src-python/config.py
View File

@@ -338,6 +338,24 @@ class Config:
if isinstance(value, list):
self._SELECTABLE_OPENAI_MODEL_LIST = value
@property
def SELECTABLE_LMSTUDIO_MODEL_LIST(self):
return self._SELECTABLE_LMSTUDIO_MODEL_LIST
@SELECTABLE_LMSTUDIO_MODEL_LIST.setter
def SELECTABLE_LMSTUDIO_MODEL_LIST(self, value):
if isinstance(value, list):
self._SELECTABLE_LMSTUDIO_MODEL_LIST = value
@property
def SELECTABLE_OLLAMA_MODEL_LIST(self):
return self._SELECTABLE_OLLAMA_MODEL_LIST
@SELECTABLE_OLLAMA_MODEL_LIST.setter
def SELECTABLE_OLLAMA_MODEL_LIST(self, value):
if isinstance(value, list):
self._SELECTABLE_OLLAMA_MODEL_LIST = value
# Save Json Data
## Main Window
@property
@@ -957,6 +975,41 @@ class Config:
self._SELECTED_OPENAI_MODEL = value
self.saveConfig(inspect.currentframe().f_code.co_name, value)
@property
@json_serializable('LMSTUDIO_URL')
def LMSTUDIO_URL(self):
return self._LMSTUDIO_URL
@LMSTUDIO_URL.setter
def LMSTUDIO_URL(self, value):
if isinstance(value, str):
self._LMSTUDIO_URL = value
self.saveConfig(inspect.currentframe().f_code.co_name, value)
@property
@json_serializable('SELECTED_LMSTUDIO_MODEL')
def SELECTED_LMSTUDIO_MODEL(self):
return self._SELECTED_LMSTUDIO_MODEL
@SELECTED_LMSTUDIO_MODEL.setter
def SELECTED_LMSTUDIO_MODEL(self, value):
if isinstance(value, str):
if value in self.SELECTABLE_LMSTUDIO_MODEL_LIST:
self._SELECTED_LMSTUDIO_MODEL = value
self.saveConfig(inspect.currentframe().f_code.co_name, value)
@property
@json_serializable('SELECTED_OLLAMA_MODEL')
def SELECTED_OLLAMA_MODEL(self):
return self._SELECTED_OLLAMA_MODEL
@SELECTED_OLLAMA_MODEL.setter
def SELECTED_OLLAMA_MODEL(self, value):
if isinstance(value, str):
if value in self.SELECTABLE_OLLAMA_MODEL_LIST:
self._SELECTED_OLLAMA_MODEL = value
self.saveConfig(inspect.currentframe().f_code.co_name, value)
@property
@json_serializable('AUTO_CLEAR_MESSAGE_BOX')
def AUTO_CLEAR_MESSAGE_BOX(self):
@@ -1234,6 +1287,8 @@ class Config:
self._SELECTABLE_PLAMO_MODEL_LIST = []
self._SELECTABLE_GEMINI_MODEL_LIST = []
self._SELECTABLE_OPENAI_MODEL_LIST = []
self._SELECTABLE_LMSTUDIO_MODEL_LIST = []
self._SELECTABLE_OLLAMA_MODEL_LIST = []
# Save Json Data
## Main Window
@@ -1344,6 +1399,9 @@ class Config:
self._SELECTED_PLAMO_MODEL = None
self._SELECTED_GEMINI_MODEL = None
self._SELECTED_OPENAI_MODEL = None
self._LMSTUDIO_URL = "http://127.0.0.1:1234"
self._SELECTED_LMSTUDIO_MODEL = None
self._SELECTED_OLLAMA_MODEL = None
self._SELECTED_TRANSLATION_COMPUTE_TYPE = "auto"
self._WHISPER_WEIGHT_TYPE = "base"
self._SELECTED_TRANSCRIPTION_COMPUTE_TYPE = "auto"

150
src-python/controller.py
View File

@@ -1877,6 +1877,129 @@ class Controller:
}
return response
def getTranslatorLMStudioURL(self, *args, **kwargs) -> dict:
return {"status":200, "result":config.LMSTUDIO_URL}
def setTranslatorLMStudioURL(self, data, *args, **kwargs) -> dict:
printLog("Set Translator LMStudio URL", data)
try:
data = str(data)
result = model.authenticationTranslatorLMStudio(base_url=data)
if result is True:
config.LMSTUDIO_URL = data
response = {"status":200, "result":config.LMSTUDIO_URL}
else:
response = {
"status":400,
"result":{
"message":"LMStudio URL is not valid",
"data": config.LMSTUDIO_URL
}
}
except Exception as e:
errorLogging()
response = {
"status":400,
"result":{
"message":f"Error {e}",
"data": config.LMSTUDIO_URL
}
}
return response
def getTranslatorLStudioModelList(self, *args, **kwargs) -> dict:
model_list = model.getTranslatorLMStudioModelList()
return {"status":200, "result": model_list}
def getTranslatorLMStudioModel(self, *args, **kwargs) -> dict:
return {"status":200, "result":config.SELECTED_LMSTUDIO_MODEL}
def setTranslatorLMStudioModel(self, data, *args, **kwargs) -> dict:
printLog("Set Translator LMStudio Model", data)
try:
data = str(data)
result = model.setTranslatorLMStudioModel(model=data)
if result is True:
config.SELECTED_LMSTUDIO_MODEL = data
response = {"status":200, "result":config.SELECTED_LMSTUDIO_MODEL}
else:
response = {
"status":400,
"result":{
"message":"LMStudio model is not valid",
"data": config.SELECTED_LMSTUDIO_MODEL
}
}
except Exception as e:
errorLogging()
response = {
"status":400,
"result":{
"message":f"Error {e}",
"data": config.SELECTED_LMSTUDIO_MODEL
}
}
return response
def checkTranslatorLOllamaConnection(self, *args, **kwargs) -> dict:
printLog("Check Translator Lollama Connection")
try:
result = model.authenticationTranslatorOllama()
if result is True:
response = {"status":200, "result":True}
else:
response = {
"status":400,
"result":{
"message":"Cannot connect to Lollama server",
"data": False
}
}
except Exception as e:
errorLogging()
response = {
"status":400,
"result":{
"message":f"Error {e}",
"data": False
}
}
return response
def getTranslatorLOllamaModelList(self, *args, **kwargs) -> dict:
model_list = model.getTranslatorOllamaModelList()
return {"status":200, "result": model_list}
def getTranslatorLOllamaModel(self, *args, **kwargs) -> dict:
return {"status":200, "result":config.SELECTED_OLLAMA_MODEL}
def setTranslatorLOllamaModel(self, data, *args, **kwargs) -> dict:
printLog("Set Translator Lollama Model", data)
try:
data = str(data)
result = model.setTranslatorOllamaModel(model=data)
if result is True:
config.SELECTED_OLLAMA_MODEL = data
response = {"status":200, "result":config.SELECTED_OLLAMA_MODEL}
else:
response = {
"status":400,
"result":{
"message":"Lollama model is not valid",
"data": config.SELECTED_OLLAMA_MODEL
}
}
except Exception as e:
errorLogging()
response = {
"status":400,
"result":{
"message":f"Error {e}",
"data": config.SELECTED_OLLAMA_MODEL
}
}
return response
@staticmethod
def getCtranslate2WeightType(*args, **kwargs) -> dict:
return {"status":200, "result":config.CTRANSLATE2_WEIGHT_TYPE}
@@ -2805,6 +2928,33 @@ class Controller:
auth_keys[engine] = None
config.AUTH_KEYS = auth_keys
printLog("OpenAI API Key is invalid")
case "LMStudio":
printLog("Start check LMStudio API Key")
config.SELECTABLE_TRANSLATION_ENGINE_STATUS[engine] = False
if config.LMSTUDIO_URL is not None:
if model.authenticationTranslatorLMStudio(config.LMSTUDIO_URL) is True:
config.SELECTABLE_TRANSLATION_ENGINE_STATUS[engine] = True
printLog("LMStudio URL is valid")
config.SELECTABLE_LMSTUDIO_MODEL_LIST = model.getTranslatorLMStudioModelList()
if config.SELECTED_LMSTUDIO_MODEL not in config.SELECTABLE_LMSTUDIO_MODEL_LIST:
config.SELECTED_LMSTUDIO_MODEL = config.SELECTABLE_LMSTUDIO_MODEL_LIST[0]
model.setTranslatorLMStudioModel(config.SELECTED_LMSTUDIO_MODEL)
model.updateTranslatorLMStudioClient()
else:
printLog("LMStudio is not available")
case "Ollama":
printLog("Start check Ollama API Key")
config.SELECTABLE_TRANSLATION_ENGINE_STATUS[engine] = False
if model.authenticationTranslatorOllama() is True:
config.SELECTABLE_TRANSLATION_ENGINE_STATUS[engine] = True
printLog("Ollama is available")
config.SELECTABLE_OLLAMA_MODEL_LIST = model.getTranslatorOllamaModelList()
if config.SELECTED_OLLAMA_MODEL not in config.SELECTABLE_OLLAMA_MODEL_LIST:
config.SELECTED_OLLAMA_MODEL = config.SELECTABLE_OLLAMA_MODEL_LIST[0]
model.setTranslatorOllamaModel(config.SELECTED_OLLAMA_MODEL)
model.updateTranslatorOllamaClient()
else:
printLog("Ollama is not available")
case _:
if connected_network is True:
config.SELECTABLE_TRANSLATION_ENGINE_STATUS[engine] = True

32
src-python/model.py
View File

@@ -249,6 +249,38 @@ class Model:
self.ensure_initialized()
self.translator.updateOpenAIClient()
def authenticationTranslatorLMStudio(self, base_url: str) -> bool:
result = self.translator.setLMStudioClientURL(base_url=base_url, root_path=config.PATH_LOCAL)
return result
def getTranslatorLMStudioModelList(self) -> list[str]:
self.ensure_initialized()
return self.translator.getLMStudioModelList()
def setTranslatorLMStudioModel(self, model: str) -> bool:
self.ensure_initialized()
return self.translator.setLMStudioModel(model=model)
def updateTranslatorLMStudioClient(self) -> None:
self.ensure_initialized()
self.translator.updateLMStudioClient()
def authenticationTranslatorOllama(self) -> bool:
result = self.translator.checkOllamaClient(root_path=config.PATH_LOCAL)
return result
def getTranslatorOllamaModelList(self) -> list[str]:
self.ensure_initialized()
return self.translator.getOllamaModelList()
def setTranslatorOllamaModel(self, model: str) -> bool:
self.ensure_initialized()
return self.translator.setOllamaModel(model=model)
def updateTranslatorOllamaClient(self) -> None:
self.ensure_initialized()
self.translator.updateOllamaClient()
def startLogger(self):
self.ensure_initialized()
os_makedirs(config.PATH_LOGS, exist_ok=True)

32
src-python/models/translation/translation_gemini.py
View File

@@ -1,8 +1,15 @@
import logging
from google import genai
from langchain_google_genai import ChatGoogleGenerativeAI
import yaml
from os import path as os_path
try:
from .translation_utils import loadPromptConfig
except Exception:
import sys
from os import path as os_path
print(os_path.dirname(os_path.dirname(os_path.dirname(os_path.abspath(__file__)))))
sys.path.append(os_path.dirname(os_path.dirname(os_path.dirname(os_path.abspath(__file__)))))
from translation_utils import loadPromptConfig
logger = logging.getLogger("langchain_google_genai")
logger.setLevel(logging.ERROR)
@@ -42,32 +49,13 @@ def _get_available_text_models(api_key: str) -> list[str]:
allowed_models.sort()
return allowed_models
def _load_prompt_config(root_path: str = None) -> dict:
"""プロンプト設定をYAMLファイルから読み込む"""
prompt_filename = "translation_gemini.yml"
# PyInstallerでビルドされた場合のパス
if root_path and os_path.exists(os_path.join(root_path, "_internal", "prompt", prompt_filename)):
prompt_path = os_path.join(root_path, "_internal", "prompt", prompt_filename)
# src-pythonフォルダから直接実行している場合のパス
elif os_path.exists(os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)
# translationフォルダから直接実行している場合のパス
elif os_path.exists(os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)
else:
raise FileNotFoundError(f"Prompt file not found: {prompt_filename}")
with open(prompt_path, "r", encoding="utf-8") as f:
return yaml.safe_load(f)
class GeminiClient:
def __init__(self, root_path: str = None):
self.api_key = None
self.model = None
# プロンプト設定をYAMLファイルから読み込む
prompt_config = _load_prompt_config(root_path)
prompt_config = loadPromptConfig(root_path, "translation_gemini.yml")
self.supported_languages = prompt_config["supported_languages"]
self.prompt_template = prompt_config["system_prompt"]

3
src-python/models/translation/translation_languages.py
View File

@@ -665,7 +665,6 @@ dict_gemini_languages = {
translation_lang["Gemini_API"] = {"source":dict_gemini_languages, "target":dict_gemini_languages}
# OpenAI API (Chat Completions) - Gemini とほぼ同等の自然言語名を使用
dict_openai_languages = {
"Arabic": "Arabic",
"Bengali": "Bengali",
@@ -710,3 +709,5 @@ dict_openai_languages = {
}
translation_lang["OpenAI_API"] = {"source": dict_openai_languages, "target": dict_openai_languages}
translation_lang["LMStudio"] = {"source": dict_openai_languages, "target": dict_openai_languages}
translation_lang["Ollama"] = {"source": dict_openai_languages, "target": dict_openai_languages}

38
src-python/models/translation/translation_lmstudio.py
View File

@@ -1,8 +1,14 @@
from openai import OpenAI
from langchain_openai import ChatOpenAI
from pydantic import SecretStr
import yaml
from os import path as os_path
try:
from .translation_utils import loadPromptConfig
except Exception:
import sys
from os import path as os_path
sys.path.append(os_path.dirname(os_path.dirname(os_path.dirname(os_path.abspath(__file__)))))
from translation_utils import loadPromptConfig
def _authentication_check(api_key: str, base_url: str | None = None) -> bool:
"""Check if the provided API key is valid by attempting to list models.
@@ -27,22 +33,6 @@ def _get_available_text_models(api_key: str, base_url: str | None = None) -> lis
allowed_models.sort()
return allowed_models
def _load_prompt_config(root_path: str = None) -> dict:
prompt_filename = "translation_lmstudio.yml"
# PyInstaller 展開後
if root_path and os_path.exists(os_path.join(root_path, "_internal", "prompt", prompt_filename)):
prompt_path = os_path.join(root_path, "_internal", "prompt", prompt_filename)
# src-python 直下実行
elif os_path.exists(os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)
# translation フォルダ直下実行
elif os_path.exists(os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)
else:
raise FileNotFoundError(f"Prompt file not found: {prompt_filename}")
with open(prompt_path, "r", encoding="utf-8") as f:
return yaml.safe_load(f)
class LMStudioClient:
"""LM Studio Translation simple wrapper.
prompt/translation_lmstudio.yml から system_prompt / supported_languages を読み込む。
@@ -52,7 +42,7 @@ class LMStudioClient:
self.model = None
self.base_url = base_url # None の場合は公式エンドポイント
prompt_config = _load_prompt_config(root_path)
prompt_config = loadPromptConfig(root_path, "translation_lmstudio.yml")
self.supported_languages = prompt_config["supported_languages"]
self.prompt_template = prompt_config["system_prompt"]
@@ -112,13 +102,11 @@ class LMStudioClient:
return content.strip()
if __name__ == "__main__":
AUTH_KEY = "lm-studio"
client = LMStudioClient(base_url="http://192.168.68.110:1234/v1")
models = client.getModelList()
print(models)
# if models:
# print("Available models:", models)
# model = input("Select a model: ")
client.setModel("google/gemma-3n-e4b")
if models:
print("Available models:", models)
model = input("Select a model: ")
client.setModel(model)
client.updateClient()
print(client.translate("こんにちは世界", "Japanese", "English"))

32
src-python/models/translation/translation_ollama.py
View File

@@ -1,8 +1,13 @@
import requests
from langchain_ollama import ChatOllama
import yaml
from os import path as os_path
try:
from .translation_utils import loadPromptConfig
except Exception:
import sys
from os import path as os_path
sys.path.append(os_path.dirname(os_path.dirname(os_path.dirname(os_path.abspath(__file__)))))
from translation_utils import loadPromptConfig
def _authentication_check(base_url: str | None = None) -> bool:
"""Check authentication for Ollama API.
@@ -29,22 +34,6 @@ def _get_available_text_models(base_url: str | None = None) -> list[str]:
allowed_models.sort()
return allowed_models
def _load_prompt_config(root_path: str = None) -> dict:
prompt_filename = "translation_ollama.yml"
# PyInstaller 展開後
if root_path and os_path.exists(os_path.join(root_path, "_internal", "prompt", prompt_filename)):
prompt_path = os_path.join(root_path, "_internal", "prompt", prompt_filename)
# src-python 直下実行
elif os_path.exists(os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)
# translation フォルダ直下実行
elif os_path.exists(os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)
else:
raise FileNotFoundError(f"Prompt file not found: {prompt_filename}")
with open(prompt_path, "r", encoding="utf-8") as f:
return yaml.safe_load(f)
class OllamaClient:
"""Ollama Translation simple wrapper.
prompt/translation_ollama.yml から system_prompt / supported_languages を読み込む。
@@ -53,14 +42,17 @@ class OllamaClient:
self.model = None
self.base_url = "http://localhost:11434"
prompt_config = _load_prompt_config(root_path)
prompt_config = loadPromptConfig(root_path)
self.supported_languages = prompt_config["supported_languages"]
self.prompt_template = prompt_config["system_prompt"]
self.openai_llm = None
def authenticationCheck(self) -> bool:
return _authentication_check(self.base_url)
def getModelList(self) -> list[str]:
if _authentication_check(self.base_url):
if self.authenticationCheck():
return _get_available_text_models(self.base_url)
return []

28
src-python/models/translation/translation_openai.py
View File

@@ -1,8 +1,14 @@
from openai import OpenAI
from langchain_openai import ChatOpenAI
from pydantic import SecretStr
import yaml
from os import path as os_path
try:
from .translation_utils import loadPromptConfig
except Exception:
import sys
from os import path as os_path
sys.path.append(os_path.dirname(os_path.dirname(os_path.dirname(os_path.abspath(__file__)))))
from translation_utils import loadPromptConfig
def _authentication_check(api_key: str, base_url: str | None = None) -> bool:
"""Check if the provided API key is valid by attempting to list models.
@@ -51,22 +57,6 @@ def _get_available_text_models(api_key: str, base_url: str | None = None) -> lis
allowed_models.sort()
return allowed_models
def _load_prompt_config(root_path: str = None) -> dict:
prompt_filename = "translation_openai.yml"
# PyInstaller 展開後
if root_path and os_path.exists(os_path.join(root_path, "_internal", "prompt", prompt_filename)):
prompt_path = os_path.join(root_path, "_internal", "prompt", prompt_filename)
# src-python 直下実行
elif os_path.exists(os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)
# translation フォルダ直下実行
elif os_path.exists(os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)
else:
raise FileNotFoundError(f"Prompt file not found: {prompt_filename}")
with open(prompt_path, "r", encoding="utf-8") as f:
return yaml.safe_load(f)
class OpenAIClient:
"""OpenAI Translation simple wrapper.
prompt/translation_openai.yml から system_prompt / supported_languages を読み込む。
@@ -76,7 +66,7 @@ class OpenAIClient:
self.model = None
self.base_url = base_url # None の場合は公式エンドポイント
prompt_config = _load_prompt_config(root_path)
prompt_config = loadPromptConfig(root_path, "translation_openai.yml")
self.supported_languages = prompt_config["supported_languages"]
self.prompt_template = prompt_config["system_prompt"]

31
src-python/models/translation/translation_plamo.py
View File

@@ -1,8 +1,14 @@
from openai import OpenAI
from langchain_openai import ChatOpenAI
from pydantic import SecretStr
import yaml
from os import path as os_path
try:
from .translation_utils import loadPromptConfig
except Exception:
import sys
from os import path as os_path
sys.path.append(os_path.dirname(os_path.dirname(os_path.dirname(os_path.abspath(__file__)))))
from translation_utils import loadPromptConfig
BASE_URL = "https://api.platform.preferredai.jp/v1"
@@ -29,32 +35,13 @@ def _get_available_text_models(api_key: str) -> list[str]:
allowed_models.sort()
return allowed_models
def _load_prompt_config(root_path: str = None) -> dict:
"""プロンプト設定をYAMLファイルから読み込む"""
prompt_filename = "translation_plamo.yml"
# PyInstallerでビルドされた場合のパス
if root_path and os_path.exists(os_path.join(root_path, "_internal", "prompt", prompt_filename)):
prompt_path = os_path.join(root_path, "_internal", "prompt", prompt_filename)
# src-pythonフォルダから直接実行している場合のパス
elif os_path.exists(os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)
# translationフォルダから直接実行している場合のパス
elif os_path.exists(os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)
else:
raise FileNotFoundError(f"Prompt file not found: {prompt_filename}")
with open(prompt_path, "r", encoding="utf-8") as f:
return yaml.safe_load(f)
class PlamoClient:
def __init__(self, root_path: str = None):
self.api_key = None
self.base_url = BASE_URL
self.model = None
prompt_config = _load_prompt_config(root_path)
prompt_config = loadPromptConfig(root_path, "translation_plamo.yml")
self.supported_languages = prompt_config["supported_languages"]
self.prompt_template = prompt_config["system_prompt"]

86
src-python/models/translation/translation_translator.py
View File

@@ -13,15 +13,18 @@ try:
from .translation_plamo import PlamoClient
from .translation_gemini import GeminiClient
from .translation_openai import OpenAIClient
from .translation_lmstudio import LMStudioClient
from .translation_ollama import OllamaClient
except Exception:
import sys
print(os_path.dirname(os_path.dirname(os_path.dirname(os_path.abspath(__file__)))))
sys.path.append(os_path.dirname(os_path.dirname(os_path.dirname(os_path.abspath(__file__)))))
from translation_languages import translation_lang
from translation_utils import ctranslate2_weights
from translation_plamo import PlamoClient
from translation_gemini import GeminiClient
from translation_openai import OpenAIClient
from translation_lmstudio import LMStudioClient
from translation_ollama import OllamaClient
import ctranslate2
import transformers
@@ -47,6 +50,8 @@ class Translator:
self.plamo_client: Optional[PlamoClient] = None
self.gemini_client: Optional[GeminiClient] = None
self.openai_client: Optional[OpenAIClient] = None
self.lmstudio_client: LMStudioClient[LMStudioClient] = None
self.ollama_client: OllamaClient[OllamaClient] = None
self.ctranslate2_translator: Any = None
self.ctranslate2_tokenizer: Any = None
self.is_loaded_ctranslate2_model: bool = False
@@ -171,6 +176,67 @@ class Translator:
"""Update the OpenAI client (fetch available models)."""
self.openai_client.updateClient()
def setLMStudioClientURL(self, base_url: str | None = None, root_path: str = None) -> bool:
"""Authenticate LM Studio with the provided base URL.
Returns True on success, False on failure.
"""
self.lmstudio_client = LMStudioClient(base_url=base_url, root_path=root_path)
result = self.lmstudio_client.setBaseURL(base_url)
if result is False:
self.lmstudio_client = None
return result
def getLMStudioModelList(self) -> list[str]:
"""Get available LM Studio models.
Returns a list of model names, or an empty list on failure.
"""
if self.lmstudio_client is None:
return []
return self.lmstudio_client.getModelList()
def setLMStudioModel(self, model: str) -> bool:
"""Change the LM Studio model used for translation.
"""
if self.lmstudio_client is None:
return False
return self.lmstudio_client.setModel(model)
def updateLMStudioClient(self) -> None:
"""Update the LM Studio client (fetch available models)."""
self.lmstudio_client.updateClient()
def checkOllamaClient(self, root_path: str = None) -> bool:
"""Check if Ollama client is available.
Returns True if Ollama is reachable, False otherwise.
"""
self.ollama_client = OllamaClient(root_path=root_path)
return self.ollama_client.authenticationCheck()
def getOllamaModelList(self, root_path: str = None) -> bool:
"""Initialize Ollama client and fetch available models.
Returns True on success, False on failure.
"""
if self.ollama_client is None:
return []
return self.ollama_client.getModelList()
def setOllamaModel(self, model: str) -> bool:
"""Change the Ollama model used for translation.
Returns True on success, False on failure.
"""
if self.ollama_client is None:
return False
return self.ollama_client.setModel(model)
def updateOllamaClient(self) -> None:
"""Update the Ollama client (fetch available models)."""
self.ollama_client.updateClient()
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.
@@ -320,6 +386,24 @@ class Translator:
input_lang=source_language,
output_lang=target_language,
)
case "LMStudio":
if self.lmstudio_client is None:
result = False
else:
result = self.lmstudio_client.translate(
message,
input_lang=source_language,
output_lang=target_language,
)
case "Ollama":
if self.ollama_client is None:
result = False
else:
result = self.ollama_client.translate(
message,
input_lang=source_language,
output_lang=target_language,
)
case "Google":
if self.is_enable_translators is True and other_web_Translator is not None:
result = other_web_Translator(

18
src-python/models/translation/translation_utils.py
View File

@@ -2,11 +2,10 @@ from os import path as os_path
from os import makedirs as os_makedirs
from requests import get as requests_get
from typing import Callable
import hashlib
import transformers
import ctranslate2
from huggingface_hub import hf_hub_url, list_repo_files
from requests import get as requests_get
import yaml
try:
from utils import errorLogging, getBestComputeType
@@ -102,6 +101,21 @@ def downloadCTranslate2Tokenizer(path: str, weight_type: str = "m2m100_418M-ct2-
tokenizer_path = os_path.join("./weights", "ctranslate2", directory_name, "tokenizer")
transformers.AutoTokenizer.from_pretrained(tokenizer, cache_dir=tokenizer_path)
def loadPromptConfig(root_path: str | None = None, prompt_filename: str | None = None) -> dict:
# PyInstaller 展開後
if root_path and prompt_filename and os_path.exists(os_path.join(root_path, "_internal", "prompt", prompt_filename)):
prompt_path = os_path.join(root_path, "_internal", "prompt", prompt_filename)
# src-python 直下実行
elif prompt_filename and os_path.exists(os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)
# translation フォルダ直下実行
elif prompt_filename and os_path.exists(os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)):
prompt_path = os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)
else:
raise FileNotFoundError(f"Prompt file not found: {prompt_filename}")
with open(prompt_path, "r", encoding="utf-8") as f:
return yaml.safe_load(f)
# テスト用コード（直接実行時のみ）
if __name__ == "__main__":
def progress_callback(percent):