965bee818a
- 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
124 lines
4.6 KiB
Python
124 lines
4.6 KiB
Python
from openai import OpenAI
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from langchain_openai import ChatOpenAI
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from pydantic import SecretStr
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import yaml
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from os import path as os_path
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def _authentication_check(api_key: str, base_url: str | None = None) -> bool:
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"""Check if the provided API key is valid by attempting to list models.
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"""
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try:
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client = OpenAI(api_key=api_key, base_url=base_url)
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client.models.list()
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return True
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except Exception:
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return False
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def _get_available_text_models(api_key: str, base_url: str | None = None) -> list[str]:
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"""Extract the list of available text models from the LM Studio.
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"""
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client = OpenAI(api_key=api_key, base_url=base_url)
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res = client.models.list()
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allowed_models = []
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for model in res.data:
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allowed_models.append(model.id)
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allowed_models.sort()
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return allowed_models
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def _load_prompt_config(root_path: str = None) -> dict:
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prompt_filename = "translation_lmstudio.yml"
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# PyInstaller 展開後
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if root_path and os_path.exists(os_path.join(root_path, "_internal", "prompt", prompt_filename)):
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prompt_path = os_path.join(root_path, "_internal", "prompt", prompt_filename)
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# src-python 直下実行
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elif os_path.exists(os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)):
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prompt_path = os_path.join(os_path.dirname(__file__), "models", "translation", "prompt", prompt_filename)
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# translation フォルダ直下実行
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elif os_path.exists(os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)):
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prompt_path = os_path.join(os_path.dirname(__file__), "prompt", prompt_filename)
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else:
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raise FileNotFoundError(f"Prompt file not found: {prompt_filename}")
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with open(prompt_path, "r", encoding="utf-8") as f:
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return yaml.safe_load(f)
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class LMStudioClient:
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"""LM Studio Translation simple wrapper.
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prompt/translation_lmstudio.yml から system_prompt / supported_languages を読み込む。
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"""
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def __init__(self, base_url: str | None = None, root_path: str = None):
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self.api_key = "lmstudio"
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self.model = None
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self.base_url = base_url # None の場合は公式エンドポイント
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prompt_config = _load_prompt_config(root_path)
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self.supported_languages = prompt_config["supported_languages"]
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self.prompt_template = prompt_config["system_prompt"]
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self.openai_llm = None
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def getBaseURL(self) -> str | None:
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return self.base_url
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def setBaseURL(self, base_url: str | None) -> None:
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result = _authentication_check(api_key=self.api_key, base_url=base_url)
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if result:
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self.base_url = base_url
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return result
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def getModelList(self) -> list[str]:
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return _get_available_text_models(api_key=self.api_key, base_url=self.base_url) if self.base_url else []
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def getModel(self) -> str:
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return self.model
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def setModel(self, model: str) -> bool:
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if model in self.getModelList():
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self.model = model
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return True
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else:
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return False
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def updateClient(self) -> None:
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self.openai_llm = ChatOpenAI(
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base_url=self.base_url,
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model=self.model,
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api_key=SecretStr(self.api_key),
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streaming=False,
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)
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def translate(self, text: str, input_lang: str, output_lang: str) -> str:
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system_prompt = self.prompt_template.format(
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supported_languages=self.supported_languages,
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input_lang=input_lang,
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output_lang=output_lang,
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)
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messages = [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": text},
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]
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resp = self.openai_llm.invoke(messages)
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content = ""
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if isinstance(resp.content, str):
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content = resp.content
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elif isinstance(resp.content, list):
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for part in resp.content:
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if isinstance(part, str):
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content += part
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elif isinstance(part, dict) and "content" in part and isinstance(part["content"], str):
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content += part["content"]
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return content.strip()
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if __name__ == "__main__":
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AUTH_KEY = "lm-studio"
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client = LMStudioClient(base_url="http://192.168.68.110:1234/v1")
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models = client.getModelList()
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print(models)
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# if models:
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# print("Available models:", models)
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# model = input("Select a model: ")
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client.setModel("google/gemma-3n-e4b")
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client.updateClient()
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print(client.translate("こんにちは世界", "Japanese", "English")) |