LM Studio と Ollama の翻訳クライアントとプロンプトを追加、requirements に langchain-ollama を追記

- src-python/models/translation に LM Studio 用 (translation_lmstudio.py / translation_lmstudio.yml) を追加
- Ollama 用クライアント (translation_ollama.py / translation_ollama.yml) を追加
- 各クライアントでプロンプト YAML から system_prompt / supported_languages を読み込み、認証チェック・モデル一覧取得・モデル設定・クライアント更新・translate 呼び出しを実装
- requirements.txt と requirements_cuda.txt に langchain-ollama==0.3.10 を追記

src-python/models/translation/translation_lmstudio.py

@@ -0,0 +1,124 @@
+from openai import OpenAI
+from langchain_openai import ChatOpenAI
+from pydantic import SecretStr
+import yaml
+from os import path as os_path
+
+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.
+    """
+    try:
+        client = OpenAI(api_key=api_key, base_url=base_url)
+        client.models.list()
+        return True
+    except Exception:
+        return False
+
+def _get_available_text_models(api_key: str, base_url: str | None = None) -> list[str]:
+    """Extract the list of available text models from the LM Studio.
+    """
+    client = OpenAI(api_key=api_key, base_url=base_url)
+    res = client.models.list()
+    allowed_models = []
+
+    for model in res.data:
+        allowed_models.append(model.id)
+
+    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。
+    """
+    def __init__(self, base_url: str | None = None, root_path: str = None):
+        self.api_key = "lmstudio"
+        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)
+        self.supported_languages = prompt_config["supported_languages"]
+        self.prompt_template = prompt_config["system_prompt"]
+
+        self.openai_llm = None
+
+    def getBaseURL(self) -> str | None:
+        return self.base_url
+
+    def setBaseURL(self, base_url: str | None) -> None:
+        result = _authentication_check(api_key=self.api_key, base_url=base_url)
+        if result:
+            self.base_url = base_url
+        return result
+
+    def getModelList(self) -> list[str]:
+        return _get_available_text_models(api_key=self.api_key, base_url=self.base_url) if self.base_url else []
+
+    def getModel(self) -> str:
+        return self.model
+
+    def setModel(self, model: str) -> bool:
+        if model in self.getModelList():
+            self.model = model
+            return True
+        else:
+            return False
+
+    def updateClient(self) -> None:
+        self.openai_llm = ChatOpenAI(
+            base_url=self.base_url,
+            model=self.model,
+            api_key=SecretStr(self.api_key),
+            streaming=False,
+        )
+
+    def translate(self, text: str, input_lang: str, output_lang: str) -> str:
+        system_prompt = self.prompt_template.format(
+            supported_languages=self.supported_languages,
+            input_lang=input_lang,
+            output_lang=output_lang,
+        )
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": text},
+        ]
+
+        resp = self.openai_llm.invoke(messages)
+        content = ""
+        if isinstance(resp.content, str):
+            content = resp.content
+        elif isinstance(resp.content, list):
+            for part in resp.content:
+                if isinstance(part, str):
+                    content += part
+                elif isinstance(part, dict) and "content" in part and isinstance(part["content"], str):
+                    content += part["content"]
+        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"))