LMStudio と Ollama の翻訳バックエンドを追加・統合。

- 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。

src-python/config.py

@@ -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"

src-python/controller.py

@@ -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

src-python/model.py

@@ -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)

src-python/models/translation/translation_gemini.py

@@ -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"]
 

src-python/models/translation/translation_languages.py

@@ -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",
@@ -709,4 +708,6 @@ dict_openai_languages = {
     "Vietnamese": "Vietnamese",
 }
 
-translation_lang["OpenAI_API"] = {"source": dict_openai_languages, "target": 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}

src-python/models/translation/translation_lmstudio.py

@@ -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")
-    client.updateClient()
-    print(client.translate("こんにちは世界", "Japanese", "English"))
+    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"))

src-python/models/translation/translation_ollama.py

@@ -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 []
 
@@ -111,5 +103,5 @@ if __name__ == "__main__":
         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"))
+        client.updateClient()
+        print(client.translate("こんにちは世界", "Japanese", "English"))

src-python/models/translation/translation_openai.py

@@ -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"]
 

src-python/models/translation/translation_plamo.py

@@ -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"]
 

src-python/models/translation/translation_translator.py

@@ -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(

src-python/models/translation/translation_utils.py

@@ -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):