Merge branch 'develop' into copy_and_paste

src-python/models/translation/prompt/translation_gemini.yml

@@ -1,7 +0,0 @@
-system_prompt: |
-  You are a helpful translation assistant.
-  Supported languages:
-  {supported_languages}
-
-  Translate the user provided text from {input_lang} to {output_lang}.
-  Return ONLY the translated text. Do not add quotes or extra commentary.

src-python/models/translation/prompt/translation_lmstudio.yml

@@ -1,7 +0,0 @@
-system_prompt: |
-  You are a helpful translation assistant.
-  Supported languages:
-  {supported_languages}
-
-  Translate the user provided text from {input_lang} to {output_lang}.
-  Return ONLY the translated text. Do not add quotes or extra commentary.

src-python/models/translation/prompt/translation_ollama.yml

@@ -1,7 +0,0 @@
-system_prompt: |
-  You are a helpful translation assistant.
-  Supported languages:
-  {supported_languages}
-
-  Translate the user provided text from {input_lang} to {output_lang}.
-  Return ONLY the translated text. Do not add quotes or extra commentary.

src-python/models/translation/prompt/translation_openai.yml

@@ -1,7 +0,0 @@
-system_prompt: |
-  You are a helpful translation assistant.
-  Supported languages:
-  {supported_languages}
-
-  Translate the user provided text from {input_lang} to {output_lang}.
-  Return ONLY the translated text. Do not add quotes or extra commentary.

src-python/models/translation/translation_gemini.py

@@ -4,14 +4,14 @@ from langchain_google_genai import ChatGoogleGenerativeAI
 
 try:
     from .translation_languages import translation_lang
-    from .translation_utils import loadPromptConfig
+    from .translation_utils import loadTranslatePromptConfig
 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_languages import translation_lang
-    from translation_utils import loadPromptConfig
+    from translation_utils import loadTranslatePromptConfig
 
 logger = logging.getLogger("langchain_google_genai")
 logger.setLevel(logging.ERROR)
@@ -57,9 +57,19 @@ class GeminiClient:
         self.model = None
 
         # プロンプト設定をYAMLファイルから読み込む
-        prompt_config = loadPromptConfig(root_path, "translation_gemini.yml")
+        prompt_config = loadTranslatePromptConfig(root_path, "translation_gemini.yml")
         self.supported_languages = list(translation_lang["Gemini_API"]["source"].keys())
         self.prompt_template = prompt_config["system_prompt"]
+        # history config (optional)
+        self.history_cfg = prompt_config.get("history", {
+            "use_history": False,
+            "sources": [],
+            "max_messages": 0,
+            "max_chars": 0,
+            "header_template": "",
+            "item_template": "[{source}] {role}: {text}",
+        })
+        self._context_history: list[dict] = []
 
         self.gemini_llm = None
 
@@ -91,6 +101,16 @@ class GeminiClient:
             api_key=self.api_key,
         )
 
+    def setContextHistory(self, history_items: list[dict]) -> None:
+        """Set recent conversation history for prompt injection.
+
+        Each item should be a dict containing:
+        - source: "chat" | "mic" | "speaker"
+        - text: message string
+        - timestamp: ISO format datetime string
+        """
+        self._context_history = history_items or []
+
     def translate(self, text: str, input_lang: str, output_lang: str) -> str:
         system_prompt = self.prompt_template.format(
             supported_languages=self.supported_languages,
@@ -98,6 +118,41 @@ class GeminiClient:
             output_lang=output_lang
         )
 
+        # Inject recent conversation history if enabled by YAML config
+        if self.history_cfg.get("use_history"):
+            allowed_sources = set(self.history_cfg.get("sources", []))
+            max_messages = int(self.history_cfg.get("max_messages", 0))
+            max_chars = int(self.history_cfg.get("max_chars", 0))
+            item_tmpl = self.history_cfg.get("item_template", "[{source}] {role}: {text}")
+            header_tmpl = self.history_cfg.get("header_template", "{history}")
+
+            filtered = [h for h in self._context_history if h.get("source") in allowed_sources]
+            recent = filtered[-max_messages:] if max_messages > 0 else filtered
+            formatted_items = []
+            for h in recent:
+                # Format timestamp as HH:MM to save tokens
+                timestamp_str = ''
+                if 'timestamp' in h:
+                    from datetime import datetime
+                    try:
+                        ts = datetime.fromisoformat(h['timestamp'])
+                        timestamp_str = ts.strftime('%H:%M')
+                    except:
+                        timestamp_str = ''
+                formatted_items.append(
+                    item_tmpl.format(
+                        timestamp=timestamp_str,
+                        source=h.get("source", ""),
+                        text=h.get("text", ""),
+                    )
+                )
+            history_blob = "\n".join(formatted_items).strip()
+            if max_chars and len(history_blob) > max_chars:
+                history_blob = history_blob[-max_chars:]
+            history_header = header_tmpl.format(max_messages=max_messages, history=history_blob)
+            if history_header:
+                system_prompt = f"{system_prompt}\n\n{history_header}"
+
         messages = [
             {"role": "system", "content": system_prompt},
             {"role": "user", "content": text}

src-python/models/translation/translation_groq.py

@@ -0,0 +1,201 @@
+from openai import OpenAI
+from langchain_openai import ChatOpenAI
+from pydantic import SecretStr
+
+try:
+    from .translation_languages import translation_lang
+    from .translation_utils import loadTranslatePromptConfig
+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_languages import translation_lang, loadTranslationLanguages
+    from translation_utils import loadTranslatePromptConfig
+    translation_lang = loadTranslationLanguages(path=".", force=True)
+
+def _authentication_check(api_key: str) -> bool:
+    """Check if the provided API key is valid by attempting to list models.
+    """
+    try:
+        client = OpenAI(
+            api_key=api_key,
+            base_url="https://api.groq.com/openai/v1",
+        )
+        client.models.list()
+        return True
+    except Exception:
+        return False
+
+def _get_available_text_models(api_key: str) -> list[str]:
+    """Extract only Groq models suitable for translation and chat applications.
+    """
+    client = OpenAI(
+        api_key=api_key,
+        base_url="https://api.groq.com/openai/v1",
+    )
+    res = client.models.list()
+    allowed_models = []
+
+    for model in res.data:
+        model_id = model.id
+
+        # 除外対象のキーワード
+        exclude_keywords = [
+            "whisper",       # 音声認識
+            "embedding",     # 埋め込み
+            "image",         # 画像生成
+            "tts",           # 音声合成
+            "audio",         # 音声系
+            "search",        # 検索補助モデル
+            "transcribe",    # 音声→文字起こし
+            "diarize",       # 話者分離
+            "vision"         # 画像入力系
+        ]
+
+        # 除外キーワードが含まれているモデルをスキップ
+        if any(kw in model_id.lower() for kw in exclude_keywords):
+            continue
+
+        # テキスト処理用モデルのみ対象
+        allowed_models.append(model_id)
+
+    allowed_models.sort()
+    return allowed_models
+
+class GroqClient:
+    """Groq API Translation wrapper using OpenAI-compatible endpoint.
+    
+    Groq provides a fast LLM inference platform with an OpenAI-compatible API.
+    The API endpoint: https://api.groq.com/openai/v1
+    """
+    def __init__(self, root_path: str = None):
+        self.api_key = None
+        self.model = None
+        self.base_url = "https://api.groq.com/openai/v1"
+
+        prompt_config = loadTranslatePromptConfig(root_path, "translation_groq.yml")
+        self.supported_languages = list(translation_lang["Groq_API"]["source"].keys())
+        self.prompt_template = prompt_config["system_prompt"]
+        # history config (optional)
+        self.history_cfg = prompt_config.get("history", {
+            "use_history": False,
+            "sources": [],
+            "max_messages": 0,
+            "max_chars": 0,
+            "header_template": "",
+            "item_template": "[{source}] {role}: {text}",
+        })
+        self._context_history: list[dict] = []
+
+        self.groq_llm = None
+
+    def getModelList(self) -> list[str]:
+        return _get_available_text_models(self.api_key) if self.api_key else []
+
+    def getAuthKey(self) -> str:
+        return self.api_key
+
+    def setAuthKey(self, api_key: str) -> bool:
+        result = _authentication_check(api_key)
+        if result:
+            self.api_key = api_key
+        return result
+
+    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.groq_llm = ChatOpenAI(
+            base_url=self.base_url,
+            model=self.model,
+            api_key=SecretStr(self.api_key),
+            streaming=False,
+        )
+
+    def setContextHistory(self, history_items: list[dict]) -> None:
+        """Set recent conversation history for prompt injection.
+
+        Each item should be a dict containing:
+        - source: "chat" | "mic" | "speaker"
+        - text: message string
+        - timestamp: ISO format datetime string
+        """
+        self._context_history = history_items or []
+
+    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,
+        )
+
+        # Inject recent conversation history if enabled by YAML config
+        if self.history_cfg.get("use_history"):
+            allowed_sources = set(self.history_cfg.get("sources", []))
+            max_messages = int(self.history_cfg.get("max_messages", 0))
+            max_chars = int(self.history_cfg.get("max_chars", 0))
+            item_tmpl = self.history_cfg.get("item_template", "[{source}] {role}: {text}")
+            header_tmpl = self.history_cfg.get("header_template", "{history}")
+
+            filtered = [h for h in self._context_history if h.get("source") in allowed_sources]
+            recent = filtered[-max_messages:] if max_messages > 0 else filtered
+            formatted_items = []
+            for h in recent:
+                # Format timestamp as HH:MM to save tokens
+                timestamp_str = ''
+                if 'timestamp' in h:
+                    from datetime import datetime
+                    try:
+                        ts = datetime.fromisoformat(h['timestamp'])
+                        timestamp_str = ts.strftime('%H:%M')
+                    except:
+                        timestamp_str = ''
+                formatted_items.append(
+                    item_tmpl.format(
+                        timestamp=timestamp_str,
+                        source=h.get("source", ""),
+                        text=h.get("text", ""),
+                    )
+                )
+            history_blob = "\n".join(formatted_items).strip()
+            if max_chars and len(history_blob) > max_chars:
+                history_blob = history_blob[-max_chars:]
+            history_header = header_tmpl.format(max_messages=max_messages, history=history_blob)
+            if history_header:
+                system_prompt = f"{system_prompt}\n\n{history_header}"
+
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": text},
+        ]
+
+        resp = self.groq_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 = "GROQ_API_KEY"
+    client = GroqClient()
+    client.setAuthKey(AUTH_KEY)
+    models = client.getModelList()
+    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_languages.py

@@ -41,14 +41,14 @@ def _load_languages(path: str, filename: str) -> str:
     Returns:
         Absolute path to the resource file
     """
-    if os.path.exists(os.path.join(path, "_internal", "languages", "languages.yml")):
-        languages_path =  os.path.join(path, "_internal", "languages", "languages.yml")
-    elif os.path.exists(os.path.join(os.path.dirname(os.path.abspath(__file__)), "models", "translation", "languages", "languages.yml")):
-        languages_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "models", "translation", "languages", "languages.yml")
-    elif os.path.exists(os.path.join(os.path.dirname(os.path.abspath(__file__)), "languages", "languages.yml")):
-        languages_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "languages", "languages.yml")
+    if os.path.exists(os.path.join(path, "_internal", "translation_settings", "languages", filename)):
+        languages_path =  os.path.join(path, "_internal", "translation_settings", "languages", filename)
+    elif os.path.exists(os.path.join(os.path.dirname(os.path.abspath(__file__)), "models", "translation", "translation_settings", "languages", filename)):
+        languages_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "models", "translation", "translation_settings", "languages", filename)
+    elif os.path.exists(os.path.join(os.path.dirname(os.path.abspath(__file__)), "translation_settings", "languages", filename)):
+        languages_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "translation_settings", "languages", filename)
     else:
-        raise FileNotFoundError(f"Prompt file not found: {filename}")
+        raise FileNotFoundError(f"Languages file not found: {filename}")
     with open(languages_path, "r", encoding="utf-8") as f:
         return yaml.safe_load(f)
 
@@ -99,7 +99,7 @@ def loadTranslationLanguages(path: str, force: bool = False) -> Dict[str, Any]:
         if _loaded and not force:
             return translation_lang
 
-        data = _load_languages(path, "languages/languages.yml")
+        data = _load_languages(path, "languages.yml")
 
         if not isinstance(data, dict):
             raise ValueError(

src-python/models/translation/translation_lmstudio.py

@@ -1,40 +1,42 @@
-from openai import OpenAI
 from langchain_openai import ChatOpenAI
 from pydantic import SecretStr
+import requests
 
 try:
     from .translation_languages import translation_lang
-    from .translation_utils import loadPromptConfig
+    from .translation_utils import loadTranslatePromptConfig
 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_languages import translation_lang
-    from translation_utils import loadPromptConfig
+    sys.path.append(os_path.dirname(os_path.abspath(__file__)))
+    from translation_languages import translation_lang, loadTranslationLanguages
+    from translation_utils import loadTranslatePromptConfig
+    translation_lang = loadTranslationLanguages(path=".", force=True)
 
-def _authentication_check(api_key: str, base_url: str | None = None) -> bool:
+def _authentication_check(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
+        response = requests.get(f"{base_url}/models", timeout=0.2)
+        if response.status_code == 200:
+            return True
+        else:
+            return False
     except Exception:
         return False
 
-def _get_available_text_models(api_key: str, base_url: str | None = None) -> list[str]:
+def _get_available_text_models(base_url: str | None = None) -> list[str]:
     """Extract the list of available text models from the LM Studio.
     """
     try:
-        client = OpenAI(api_key=api_key, base_url=base_url)
-        res = client.models.list()
-        models = res.data
+        response = requests.get(f"{base_url}/models", timeout=0.2)
+        models = response.json()["data"]
     except Exception:
         models = []
 
     allowed_models = []
     for model in models:
-        allowed_models.append(model.id)
+        allowed_models.append(model["id"])
 
     allowed_models.sort()
     return allowed_models
@@ -48,9 +50,19 @@ 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 = loadPromptConfig(root_path, "translation_lmstudio.yml")
+        prompt_config = loadTranslatePromptConfig(root_path, "translation_lmstudio.yml")
         self.supported_languages = list(translation_lang["LMStudio"]["source"].keys())
         self.prompt_template = prompt_config["system_prompt"]
+        # history config (optional)
+        self.history_cfg = prompt_config.get("history", {
+            "use_history": False,
+            "sources": [],
+            "max_messages": 0,
+            "max_chars": 0,
+            "header_template": "",
+            "item_template": "[{source}] {role}: {text}",
+        })
+        self._context_history: list[dict] = []
 
         self.openai_llm = None
 
@@ -58,13 +70,13 @@ class LMStudioClient:
         return self.base_url
 
     def setBaseURL(self, base_url: str | None) -> None:
-        result = _authentication_check(api_key=self.api_key, base_url=base_url)
+        result = _authentication_check(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 []
+        return _get_available_text_models(base_url=self.base_url) if self.base_url else []
 
     def getModel(self) -> str:
         return self.model
@@ -84,12 +96,58 @@ class LMStudioClient:
             streaming=False,
         )
 
+    def setContextHistory(self, history_items: list[dict]) -> None:
+        """Set recent conversation history for prompt injection.
+
+        Each item should be a dict containing:
+        - source: "chat" | "mic" | "speaker"
+        - text: message string
+        - timestamp: ISO format datetime string
+        """
+        self._context_history = history_items or []
+
     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,
         )
+
+        # Inject recent conversation history if enabled by YAML config
+        if self.history_cfg.get("use_history"):
+            allowed_sources = set(self.history_cfg.get("sources", []))
+            max_messages = int(self.history_cfg.get("max_messages", 0))
+            max_chars = int(self.history_cfg.get("max_chars", 0))
+            item_tmpl = self.history_cfg.get("item_template", "[{source}] {role}: {text}")
+            header_tmpl = self.history_cfg.get("header_template", "{history}")
+
+            filtered = [h for h in self._context_history if h.get("source") in allowed_sources]
+            recent = filtered[-max_messages:] if max_messages > 0 else filtered
+            formatted_items = []
+            for h in recent:
+                # Format timestamp as HH:MM to save tokens
+                timestamp_str = ''
+                if 'timestamp' in h:
+                    from datetime import datetime
+                    try:
+                        ts = datetime.fromisoformat(h['timestamp'])
+                        timestamp_str = ts.strftime('%H:%M')
+                    except:
+                        timestamp_str = ''
+                formatted_items.append(
+                    item_tmpl.format(
+                        timestamp=timestamp_str,
+                        source=h.get("source", ""),
+                        text=h.get("text", ""),
+                    )
+                )
+            history_blob = "\n".join(formatted_items).strip()
+            if max_chars and len(history_blob) > max_chars:
+                history_blob = history_blob[-max_chars:]
+            history_header = header_tmpl.format(max_messages=max_messages, history=history_blob)
+            if history_header:
+                system_prompt = f"{system_prompt}\n\n{history_header}"
+
         messages = [
             {"role": "system", "content": system_prompt},
             {"role": "user", "content": text},
@@ -108,7 +166,7 @@ class LMStudioClient:
         return content.strip()
 
 if __name__ == "__main__":
-    client = LMStudioClient(base_url="http://192.168.68.110:1234/v1")
+    client = LMStudioClient(base_url="http://127.0.0.1:1234/v1")
     models = client.getModelList()
     if models:
         print("Available models:", models)

src-python/models/translation/translation_ollama.py

@@ -3,19 +3,20 @@ from langchain_ollama import ChatOllama
 
 try:
     from .translation_languages import translation_lang
-    from .translation_utils import loadPromptConfig
+    from .translation_utils import loadTranslatePromptConfig
 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_languages import translation_lang
-    from translation_utils import loadPromptConfig
+    sys.path.append(os_path.dirname(os_path.abspath(__file__)))
+    from translation_languages import translation_lang, loadTranslationLanguages
+    from translation_utils import loadTranslatePromptConfig
+    translation_lang = loadTranslationLanguages(path=".", force=True)
 
 def _authentication_check(base_url: str | None = None) -> bool:
     """Check authentication for Ollama API.
     """
     try:
-        response = requests.get(f"{base_url}")
+        response = requests.get(f"{base_url}", timeout=0.2)
         if response.status_code == 200:
             return True
         else:
@@ -47,9 +48,19 @@ class OllamaClient:
         self.model = None
         self.base_url = "http://localhost:11434"
 
-        prompt_config = loadPromptConfig(root_path, "translation_ollama.yml")
+        prompt_config = loadTranslatePromptConfig(root_path, "translation_ollama.yml")
         self.supported_languages = list(translation_lang["Ollama"]["source"].keys())
         self.prompt_template = prompt_config["system_prompt"]
+        # history config (optional)
+        self.history_cfg = prompt_config.get("history", {
+            "use_history": False,
+            "sources": [],
+            "max_messages": 0,
+            "max_chars": 0,
+            "header_template": "",
+            "item_template": "[{source}] {role}: {text}",
+        })
+        self._context_history: list[dict] = []
 
         self.openai_llm = None
 
@@ -78,12 +89,58 @@ class OllamaClient:
             streaming=False,
         )
 
+    def setContextHistory(self, history_items: list[dict]) -> None:
+        """Set recent conversation history for prompt injection.
+
+        Each item should be a dict containing:
+        - source: "chat" | "mic" | "speaker"
+        - text: message string
+        - timestamp: ISO format datetime string
+        """
+        self._context_history = history_items or []
+
     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,
         )
+
+        # Inject recent conversation history if enabled by YAML config
+        if self.history_cfg.get("use_history"):
+            allowed_sources = set(self.history_cfg.get("sources", []))
+            max_messages = int(self.history_cfg.get("max_messages", 0))
+            max_chars = int(self.history_cfg.get("max_chars", 0))
+            item_tmpl = self.history_cfg.get("item_template", "[{source}] {role}: {text}")
+            header_tmpl = self.history_cfg.get("header_template", "{history}")
+
+            filtered = [h for h in self._context_history if h.get("source") in allowed_sources]
+            recent = filtered[-max_messages:] if max_messages > 0 else filtered
+            formatted_items = []
+            for h in recent:
+                # Format timestamp as HH:MM to save tokens
+                timestamp_str = ''
+                if 'timestamp' in h:
+                    from datetime import datetime
+                    try:
+                        ts = datetime.fromisoformat(h['timestamp'])
+                        timestamp_str = ts.strftime('%H:%M')
+                    except:
+                        timestamp_str = ''
+                formatted_items.append(
+                    item_tmpl.format(
+                        timestamp=timestamp_str,
+                        source=h.get("source", ""),
+                        text=h.get("text", ""),
+                    )
+                )
+            history_blob = "\n".join(formatted_items).strip()
+            if max_chars and len(history_blob) > max_chars:
+                history_blob = history_blob[-max_chars:]
+            history_header = header_tmpl.format(max_messages=max_messages, history=history_blob)
+            if history_header:
+                system_prompt = f"{system_prompt}\n\n{history_header}"
+
         messages = [
             {"role": "system", "content": system_prompt},
             {"role": "user", "content": text},

src-python/models/translation/translation_openai.py

@@ -4,13 +4,14 @@ from pydantic import SecretStr
 
 try:
     from .translation_languages import translation_lang
-    from .translation_utils import loadPromptConfig
+    from .translation_utils import loadTranslatePromptConfig
 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_languages import translation_lang
-    from translation_utils import loadPromptConfig
+    from translation_languages import translation_lang, loadTranslationLanguages
+    from translation_utils import loadTranslatePromptConfig
+    translation_lang = loadTranslationLanguages(path=".", force=True)
 
 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.
@@ -68,9 +69,19 @@ 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 = loadPromptConfig(root_path, "translation_openai.yml")
+        prompt_config = loadTranslatePromptConfig(root_path, "translation_openai.yml")
         self.supported_languages = list(translation_lang["OpenAI_API"]["source"].keys())
         self.prompt_template = prompt_config["system_prompt"]
+        # history config (optional)
+        self.history_cfg = prompt_config.get("history", {
+            "use_history": False,
+            "sources": [],
+            "max_messages": 0,
+            "max_chars": 0,
+            "header_template": "",
+            "item_template": "[{source}] {role}: {text}",
+        })
+        self._context_history: list[dict] = []
 
         self.openai_llm = None
 
@@ -104,12 +115,62 @@ class OpenAIClient:
             streaming=False,
         )
 
+    def setContextHistory(self, history_items: list[dict]) -> None:
+        """Set recent conversation history for prompt injection.
+
+        Each item should be a dict containing:
+        - source: "chat" | "mic" | "speaker"
+        - text: message string
+        - timestamp: ISO format datetime string
+        """
+        self._context_history = history_items or []
+
     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,
         )
+
+        # Inject recent conversation history if enabled by YAML config
+        if self.history_cfg.get("use_history"):
+            allowed_sources = set(self.history_cfg.get("sources", []))
+            max_messages = int(self.history_cfg.get("max_messages", 0))
+            max_chars = int(self.history_cfg.get("max_chars", 0))
+            item_tmpl = self.history_cfg.get("item_template", "[{source}] {role}: {text}")
+            header_tmpl = self.history_cfg.get("header_template", "{history}")
+
+            # filter by source and take newest N
+            filtered = [h for h in self._context_history if h.get("source") in allowed_sources]
+            recent = filtered[-max_messages:] if max_messages > 0 else filtered
+            # format items
+            formatted_items = []
+            for h in recent:
+                # Format timestamp as HH:MM to save tokens
+                timestamp_str = ''
+                if 'timestamp' in h:
+                    from datetime import datetime
+                    try:
+                        ts = datetime.fromisoformat(h['timestamp'])
+                        timestamp_str = ts.strftime('%H:%M')
+                    except:
+                        timestamp_str = ''
+                formatted_items.append(
+                    item_tmpl.format(
+                        timestamp=timestamp_str,
+                        source=h.get("source", ""),
+                        text=h.get("text", ""),
+                    )
+                )
+            history_blob = "\n".join(formatted_items).strip()
+            # truncate by char limit to mitigate token use
+            if max_chars and len(history_blob) > max_chars:
+                history_blob = history_blob[-max_chars:]
+            # assemble header and append to system prompt
+            history_header = header_tmpl.format(max_messages=max_messages, history=history_blob)
+            if history_header:
+                system_prompt = f"{system_prompt}\n\n{history_header}"
+
         messages = [
             {"role": "system", "content": system_prompt},
             {"role": "user", "content": text},
@@ -128,7 +189,7 @@ class OpenAIClient:
         return content.strip()
 
 if __name__ == "__main__":
-    AUTH_KEY = "OPENAI_API_KEY"
+    AUTH_KEY = input("OPENAI_API_KEY: ")
     client = OpenAIClient()
     client.setAuthKey(AUTH_KEY)
     models = client.getModelList()

src-python/models/translation/translation_openrouter.py

@@ -0,0 +1,199 @@
+import requests
+from openai import OpenAI
+from langchain_openai import ChatOpenAI
+from pydantic import SecretStr
+
+try:
+    from .translation_languages import translation_lang
+    from .translation_utils import loadTranslatePromptConfig
+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_languages import translation_lang, loadTranslationLanguages
+    from translation_utils import loadTranslatePromptConfig
+    translation_lang = loadTranslationLanguages(path=".", force=True)
+
+def _authentication_check(api_key: str) -> bool:
+    """Check if the provided API key is valid by attempting to list models.
+    """
+
+    url = "https://openrouter.ai/api/v1/auth/key"
+    headers = {
+        "Authorization": f"Bearer {api_key}"
+    }
+
+    r = requests.get(url, headers=headers, timeout=10)
+
+    return r.status_code == 200
+
+def _get_available_text_models(api_key: str, base_url: str | None = None) -> list[str]:
+    """Extract only OpenRouter models suitable for translation and chat applications.
+    """
+    client = OpenAI(api_key=api_key, base_url=base_url)
+    res = client.models.list()
+    allowed_models = []
+
+    for model in res.data:
+        model_id = model.id
+
+        # 除外対象のキーワード
+        exclude_keywords = [
+            "whisper",       # 音声認識
+            "embedding",     # 埋め込み
+            "image",         # 画像生成
+            "tts",           # 音声合成
+            "audio",         # 音声系
+            "search",        # 検索補助モデル
+            "transcribe",    # 音声→文字起こし
+            "diarize",       # 話者分離
+            "vision"         # 画像入力系
+        ]
+
+        # 除外キーワードが含まれているモデルをスキップ
+        if any(kw in model_id.lower() for kw in exclude_keywords):
+            continue
+
+        # テキスト処理用モデルのみ対象
+        allowed_models.append(model_id)
+
+    allowed_models.sort()
+    return allowed_models
+
+class OpenRouterClient:
+    """OpenRouter API Translation wrapper using OpenAI-compatible endpoint.
+    
+    OpenRouter provides access to various LLM models via a unified API.
+    The API endpoint: https://openrouter.ai/api/v1
+    """
+    def __init__(self, root_path: str = None):
+        self.api_key = None
+        self.model = None
+        self.base_url = "https://openrouter.ai/api/v1"
+
+        prompt_config = loadTranslatePromptConfig(root_path, "translation_openrouter.yml")
+        self.supported_languages = list(translation_lang["OpenRouter_API"]["source"].keys())
+        self.prompt_template = prompt_config["system_prompt"]
+        # history config (optional)
+        self.history_cfg = prompt_config.get("history", {
+            "use_history": False,
+            "sources": [],
+            "max_messages": 0,
+            "max_chars": 0,
+            "header_template": "",
+            "item_template": "[{source}] {role}: {text}",
+        })
+        self._context_history: list[dict] = []
+
+        self.openrouter_llm = None
+
+    def getModelList(self) -> list[str]:
+        return _get_available_text_models(self.api_key, self.base_url) if self.api_key else []
+
+    def getAuthKey(self) -> str:
+        return self.api_key
+
+    def setAuthKey(self, api_key: str) -> bool:
+        result = _authentication_check(api_key)
+        if result:
+            self.api_key = api_key
+        return result
+
+    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.openrouter_llm = ChatOpenAI(
+            base_url=self.base_url,
+            model=self.model,
+            api_key=SecretStr(self.api_key),
+            streaming=False,
+        )
+
+    def setContextHistory(self, history_items: list[dict]) -> None:
+        """Set recent conversation history for prompt injection.
+
+        Each item should be a dict containing:
+        - source: "chat" | "mic" | "speaker"
+        - text: message string
+        - timestamp: ISO format datetime string
+        """
+        self._context_history = history_items or []
+
+    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,
+        )
+
+        # Inject recent conversation history if enabled by YAML config
+        if self.history_cfg.get("use_history"):
+            allowed_sources = set(self.history_cfg.get("sources", []))
+            max_messages = int(self.history_cfg.get("max_messages", 0))
+            max_chars = int(self.history_cfg.get("max_chars", 0))
+            item_tmpl = self.history_cfg.get("item_template", "[{source}] {role}: {text}")
+            header_tmpl = self.history_cfg.get("header_template", "{history}")
+
+            filtered = [h for h in self._context_history if h.get("source") in allowed_sources]
+            recent = filtered[-max_messages:] if max_messages > 0 else filtered
+            formatted_items = []
+            for h in recent:
+                # Format timestamp as HH:MM to save tokens
+                timestamp_str = ''
+                if 'timestamp' in h:
+                    from datetime import datetime
+                    try:
+                        ts = datetime.fromisoformat(h['timestamp'])
+                        timestamp_str = ts.strftime('%H:%M')
+                    except:
+                        timestamp_str = ''
+                formatted_items.append(
+                    item_tmpl.format(
+                        timestamp=timestamp_str,
+                        source=h.get("source", ""),
+                        text=h.get("text", ""),
+                    )
+                )
+            history_blob = "\n".join(formatted_items).strip()
+            if max_chars and len(history_blob) > max_chars:
+                history_blob = history_blob[-max_chars:]
+            history_header = header_tmpl.format(max_messages=max_messages, history=history_blob)
+            if history_header:
+                system_prompt = f"{system_prompt}\n\n{history_header}"
+
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": text},
+        ]
+
+        resp = self.openrouter_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 = input("OPENROUTER_API_KEY: ")
+    client = OpenRouterClient()
+    client.setAuthKey(AUTH_KEY)
+    models = client.getModelList()
+    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_plamo.py

@@ -4,13 +4,14 @@ from pydantic import SecretStr
 
 try:
     from .translation_languages import translation_lang
-    from .translation_utils import loadPromptConfig
+    from .translation_utils import loadTranslatePromptConfig
 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_languages import translation_lang
-    from translation_utils import loadPromptConfig
+    from translation_languages import translation_lang, loadTranslationLanguages
+    from translation_utils import loadTranslatePromptConfig
+    translation_lang = loadTranslationLanguages(path=".", force=True)
 
 BASE_URL = "https://api.platform.preferredai.jp/v1"
 
@@ -43,9 +44,19 @@ class PlamoClient:
         self.base_url = BASE_URL
         self.model = None
 
-        prompt_config = loadPromptConfig(root_path, "translation_plamo.yml")
+        prompt_config = loadTranslatePromptConfig(root_path, "translation_plamo.yml")
         self.supported_languages = list(translation_lang["Plamo_API"]["source"].keys())
         self.prompt_template = prompt_config["system_prompt"]
+        # history config (optional)
+        self.history_cfg = prompt_config.get("history", {
+            "use_history": False,
+            "sources": [],
+            "max_messages": 0,
+            "max_chars": 0,
+            "header_template": "",
+            "item_template": "[{source}] {role}: {text}",
+        })
+        self._context_history: list[dict] = []
 
         self.plamo_llm = None
 
@@ -79,12 +90,58 @@ class PlamoClient:
             api_key=SecretStr(self.api_key),
         )
 
+    def setContextHistory(self, history_items: list[dict]) -> None:
+        """Set recent conversation history for prompt injection.
+
+        Each item should be a dict containing:
+        - source: "chat" | "mic" | "speaker"
+        - text: message string
+        - timestamp: ISO format datetime string
+        """
+        self._context_history = history_items or []
+
     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
         )
+
+        # Inject recent conversation history if enabled by YAML config
+        if self.history_cfg.get("use_history"):
+            allowed_sources = set(self.history_cfg.get("sources", []))
+            max_messages = int(self.history_cfg.get("max_messages", 0))
+            max_chars = int(self.history_cfg.get("max_chars", 0))
+            item_tmpl = self.history_cfg.get("item_template", "[{source}] {role}: {text}")
+            header_tmpl = self.history_cfg.get("header_template", "{history}")
+
+            filtered = [h for h in self._context_history if h.get("source") in allowed_sources]
+            recent = filtered[-max_messages:] if max_messages > 0 else filtered
+            formatted_items = []
+            for h in recent:
+                # Format timestamp as HH:MM to save tokens
+                timestamp_str = ''
+                if 'timestamp' in h:
+                    from datetime import datetime
+                    try:
+                        ts = datetime.fromisoformat(h['timestamp'])
+                        timestamp_str = ts.strftime('%H:%M')
+                    except:
+                        timestamp_str = ''
+                formatted_items.append(
+                    item_tmpl.format(
+                        timestamp=timestamp_str,
+                        source=h.get("source", ""),
+                        text=h.get("text", ""),
+                    )
+                )
+            history_blob = "\n".join(formatted_items).strip()
+            if max_chars and len(history_blob) > max_chars:
+                history_blob = history_blob[-max_chars:]
+            history_header = header_tmpl.format(max_messages=max_messages, history=history_blob)
+            if history_header:
+                system_prompt = f"{system_prompt}\n\n{history_header}"
+
         messages = [
             {"role": "system", "content": system_prompt},
             {"role": "user", "content": text},

src-python/models/translation/translation_settings/languages/languages.yml

@@ -769,3 +769,11 @@ LMStudio:
 Ollama:
   source: *openai_langs
   target: *openai_langs
+
+Groq_API:
+  source: *openai_langs
+  target: *openai_langs
+
+OpenRouter_API:
+  source: *openai_langs
+  target: *openai_langs

src-python/models/translation/translation_settings/prompt/translation_gemini.yml

@@ -0,0 +1,16 @@
+system_prompt: |
+  You are a helpful translation assistant.
+  Supported languages:
+  {supported_languages}
+
+  Translate the user provided text from {input_lang} to {output_lang}.
+  Return ONLY the translated text. Do not add quotes or extra commentary.
+history:
+  use_history: true
+  sources: [chat, mic, speaker]
+  max_messages: 5
+  max_chars: 4000
+  header_template: |
+    Conversation context (recent {max_messages} messages):
+    {history}
+  item_template: "[{timestamp}][{source}] {text}"

src-python/models/translation/translation_settings/prompt/translation_groq.yml

@@ -0,0 +1,16 @@
+system_prompt: |
+  You are a helpful translation assistant.
+  Supported languages:
+  {supported_languages}
+
+  Translate the user provided text from {input_lang} to {output_lang}.
+  Return ONLY the translated text. Do not add quotes or extra commentary.
+history:
+  use_history: true
+  sources: [chat, mic, speaker]
+  max_messages: 5
+  max_chars: 4000
+  header_template: |
+    Conversation context (recent {max_messages} messages):
+    {history}
+  item_template: "[{timestamp}][{source}] {text}"

src-python/models/translation/translation_settings/prompt/translation_lmstudio.yml

@@ -0,0 +1,16 @@
+system_prompt: |
+  You are a helpful translation assistant.
+  Supported languages:
+  {supported_languages}
+
+  Translate the user provided text from {input_lang} to {output_lang}.
+  Return ONLY the translated text. Do not add quotes or extra commentary.
+history:
+  use_history: true
+  sources: [chat, mic, speaker]
+  max_messages: 5
+  max_chars: 4000
+  header_template: |
+    Conversation context (recent {max_messages} messages):
+    {history}
+  item_template: "[{timestamp}][{source}] {text}"

src-python/models/translation/translation_settings/prompt/translation_ollama.yml

@@ -0,0 +1,16 @@
+system_prompt: |
+  You are a helpful translation assistant.
+  Supported languages:
+  {supported_languages}
+
+  Translate the user provided text from {input_lang} to {output_lang}.
+  Return ONLY the translated text. Do not add quotes or extra commentary.
+history:
+  use_history: true
+  sources: [chat, mic, speaker]
+  max_messages: 5
+  max_chars: 4000
+  header_template: |
+    Conversation context (recent {max_messages} messages):
+    {history}
+  item_template: "[{timestamp}][{source}] {text}"

src-python/models/translation/translation_settings/prompt/translation_openai.yml

@@ -0,0 +1,16 @@
+system_prompt: |
+  You are a helpful translation assistant.
+  Supported languages:
+  {supported_languages}
+
+  Translate the user provided text from {input_lang} to {output_lang}.
+  Return ONLY the translated text. Do not add quotes or extra commentary.
+history:
+  use_history: true
+  sources: [chat, mic, speaker] # 取り込み対象の履歴種別
+  max_messages: 5               # 注入する履歴件数の上限（新しい順）
+  max_chars: 4000               # 履歴整形後の最大文字数（超過時は先頭を切り捨て）
+  header_template: |
+    Conversation context (recent {max_messages} messages):
+    {history}
+  item_template: "[{timestamp}][{source}] {text}"

src-python/models/translation/translation_settings/prompt/translation_openrouter.yml

@@ -0,0 +1,16 @@
+system_prompt: |
+  You are a helpful translation assistant.
+  Supported languages:
+  {supported_languages}
+
+  Translate the user provided text from {input_lang} to {output_lang}.
+  Return ONLY the translated text. Do not add quotes or extra commentary.
+history:
+  use_history: true
+  sources: [chat, mic, speaker]
+  max_messages: 5
+  max_chars: 4000
+  header_template: |
+    Conversation context (recent {max_messages} messages):
+    {history}
+  item_template: "[{timestamp}][{source}] {text}"

src-python/models/translation/translation_settings/prompt/translation_plamo.yml

@@ -4,4 +4,13 @@ system_prompt: |
   {supported_languages}
 
   Translate the following text from {input_lang} to {output_lang}.
-  output only the translated text without any additional commentary.
+  output only the translated text without any additional commentary.
+history:
+  use_history: true
+  sources: [chat, mic, speaker]
+  max_messages: 5
+  max_chars: 4000
+  header_template: |
+    Conversation context (recent {max_messages} messages):
+    {history}
+  item_template: "[{timestamp}][{source}] {text}"

src-python/models/translation/translation_translator.py

@@ -15,6 +15,8 @@ try:
     from .translation_openai import OpenAIClient
     from .translation_lmstudio import LMStudioClient
     from .translation_ollama import OllamaClient
+    from .translation_groq import GroqClient
+    from .translation_openrouter import OpenRouterClient
 except Exception:
     import sys
     sys.path.append(os_path.dirname(os_path.dirname(os_path.dirname(os_path.abspath(__file__)))))
@@ -25,6 +27,8 @@ except Exception:
     from translation_openai import OpenAIClient
     from translation_lmstudio import LMStudioClient
     from translation_ollama import OllamaClient
+    from translation_groq import GroqClient
+    from translation_openrouter import OpenRouterClient
 
 import ctranslate2
 import transformers
@@ -50,6 +54,8 @@ class Translator:
         self.plamo_client: Optional[PlamoClient] = None
         self.gemini_client: Optional[GeminiClient] = None
         self.openai_client: Optional[OpenAIClient] = None
+        self.groq_client: Optional[GroqClient] = None
+        self.openrouter_client: Optional[OpenRouterClient] = None
         self.lmstudio_client: LMStudioClient[LMStudioClient] = None
         self.ollama_client: OllamaClient[OllamaClient] = None
         self.ctranslate2_translator: Any = None
@@ -176,6 +182,84 @@ class Translator:
         """Update the OpenAI client (fetch available models)."""
         self.openai_client.updateClient()
 
+    def authenticationGroqAuthKey(self, auth_key: str, root_path: str = None) -> bool:
+        """Authenticate Groq API with the provided key.
+
+        Returns True on success, False on failure.
+        """
+        self.groq_client = GroqClient(root_path=root_path)
+        if self.groq_client.setAuthKey(auth_key):
+            return True
+        else:
+            self.groq_client = None
+            return False
+
+    def getGroqModelList(self) -> list[str]:
+        """Get available Groq models.
+
+        Returns a list of model names, or an empty list on failure.
+        """
+        if self.groq_client is None:
+            return []
+        return self.groq_client.getModelList()
+
+    def setGroqModel(self, model: str) -> bool:
+        """Change the Groq model used for translation.
+
+        Returns True on success, False on failure.
+        """
+        if self.groq_client is None:
+            return False
+        return self.groq_client.setModel(model)
+
+    def updateGroqClient(self) -> None:
+        """Update the Groq client (fetch available models)."""
+        self.groq_client.updateClient()
+
+    def authenticationOpenRouterAuthKey(self, auth_key: str, root_path: str = None) -> bool:
+        """Authenticate OpenRouter API with the provided key.
+
+        Returns True on success, False on failure.
+        """
+        self.openrouter_client = OpenRouterClient(root_path=root_path)
+        if self.openrouter_client.setAuthKey(auth_key):
+            return True
+        else:
+            self.openrouter_client = None
+            return False
+
+    def getOpenRouterModelList(self) -> list[str]:
+        """Get available OpenRouter models.
+
+        Returns a list of model names, or an empty list on failure.
+        """
+        if self.openrouter_client is None:
+            return []
+        return self.openrouter_client.getModelList()
+
+    def setOpenRouterModel(self, model: str) -> bool:
+        """Change the OpenRouter model used for translation.
+
+        Returns True on success, False on failure.
+        """
+        if self.openrouter_client is None:
+            return False
+        return self.openrouter_client.setModel(model)
+
+    def updateOpenRouterClient(self) -> None:
+        """Update the OpenRouter client (fetch available models)."""
+        self.openrouter_client.updateClient()
+
+    def getLMStudioConnected(self) -> bool:
+        """Get LM Studio connection status.
+
+        Returns True if connected, False otherwise.
+        """
+        if self.lmstudio_client is None:
+            return False
+        else:
+            return True
+
     def setLMStudioClientURL(self, base_url: str | None = None, root_path: str = None) -> bool:
         """Authenticate LM Studio with the provided base URL.
 
@@ -207,13 +291,26 @@ class Translator:
         """Update the LM Studio client (fetch available models)."""
         self.lmstudio_client.updateClient()
 
+    def getOllamaConnected(self) -> bool:
+        """Get Ollama connection status.
+
+        Returns True if connected, False otherwise.
+        """
+        if self.ollama_client is None:
+            return False
+        else:
+            return True
+
     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()
+        result = self.ollama_client.authenticationCheck()
+        if result is False:
+            self.ollama_client = None
+        return result
 
     def getOllamaModelList(self, root_path: str = None) -> bool:
         """Initialize Ollama client and fetch available models.
@@ -328,9 +425,18 @@ class Translator:
                 target_language = translation_lang[translator_name]["target"][target_language]
         return source_language, target_language
 
-    def translate(self, translator_name: str, weight_type: str, source_language: str, target_language: str, target_country: str, message: str) -> Any:
+    def translate(self, translator_name: str, weight_type: str, source_language: str, target_language: str, target_country: str, message: str, context_history: Optional[list[dict]] = None) -> Any:
         """Translate `message` using the named translator backend.
 
+        Args:
+            translator_name: Name of the translator backend to use
+            weight_type: Model weight type for CTranslate2
+            source_language: Source language name
+            target_language: Target language name
+            target_country: Target country for locale-specific translations
+            message: Text to translate
+            context_history: Optional conversation context (Chat/Mic/Speaker messages)
+
         Returns translated string on success, or False on failure. When
         source_language == target_language the original message is returned.
         """
@@ -363,6 +469,8 @@ class Translator:
                     if self.plamo_client is None:
                         result = False
                     else:
+                        if context_history:
+                            self.plamo_client.setContextHistory(context_history)
                         result = self.plamo_client.translate(
                             message,
                             input_lang=source_language,
@@ -372,6 +480,8 @@ class Translator:
                     if self.gemini_client is None:
                         result = False
                     else:
+                        if context_history:
+                            self.gemini_client.setContextHistory(context_history)
                         result = self.gemini_client.translate(
                             message,
                             input_lang=source_language,
@@ -381,15 +491,41 @@ class Translator:
                     if self.openai_client is None:
                         result = False
                     else:
+                        if context_history:
+                            self.openai_client.setContextHistory(context_history)
                         result = self.openai_client.translate(
                             message,
                             input_lang=source_language,
                             output_lang=target_language,
                         )
+                case "Groq_API":
+                    if self.groq_client is None:
+                        result = False
+                    else:
+                        if context_history:
+                            self.groq_client.setContextHistory(context_history)
+                        result = self.groq_client.translate(
+                            message,
+                            input_lang=source_language,
+                            output_lang=target_language,
+                        )
+                case "OpenRouter_API":
+                    if self.openrouter_client is None:
+                        result = False
+                    else:
+                        if context_history:
+                            self.openrouter_client.setContextHistory(context_history)
+                        result = self.openrouter_client.translate(
+                            message,
+                            input_lang=source_language,
+                            output_lang=target_language,
+                        )
                 case "LMStudio":
                     if self.lmstudio_client is None:
                         result = False
                     else:
+                        if context_history:
+                            self.lmstudio_client.setContextHistory(context_history)
                         result = self.lmstudio_client.translate(
                             message,
                             input_lang=source_language,
@@ -399,6 +535,8 @@ class Translator:
                     if self.ollama_client is None:
                         result = False
                     else:
+                        if context_history:
+                            self.ollama_client.setContextHistory(context_history)
                         result = self.ollama_client.translate(
                             message,
                             input_lang=source_language,

src-python/models/translation/translation_utils.py

@@ -101,16 +101,16 @@ 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:
+def loadTranslatePromptConfig(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)
+    if root_path and prompt_filename and os_path.exists(os_path.join(root_path, "_internal", "translation_settings", "prompt", prompt_filename)):
+        prompt_path = os_path.join(root_path, "_internal", "translation_settings", "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)
+    elif prompt_filename and os_path.exists(os_path.join(os_path.dirname(__file__), "models", "translation", "translation_settings", "prompt", prompt_filename)):
+        prompt_path = os_path.join(os_path.dirname(__file__), "models", "translation", "translation_settings", "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)
+    elif prompt_filename and os_path.exists(os_path.join(os_path.dirname(__file__), "translation_settings", "prompt", prompt_filename)):
+        prompt_path = os_path.join(os_path.dirname(__file__), "translation_settings", "prompt", prompt_filename)
     else:
         raise FileNotFoundError(f"Prompt file not found: {prompt_filename}")
     with open(prompt_path, "r", encoding="utf-8") as f: