9e88cff889
- Updated paths for translation settings in backend.spec and backend_cuda.spec to reflect new directory structure. - Renamed loadPromptConfig to loadTranslatePromptConfig in translation utility files for consistency. - Created new YAML files for translation prompts (gemini, groq, lmstudio, ollama, openai, openrouter, plamo) with standardized system prompts. - Added languages.yml file to define language mappings for various translation backends.
120 lines
4.1 KiB
Python
120 lines
4.1 KiB
Python
from langchain_openai import ChatOpenAI
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from pydantic import SecretStr
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import requests
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try:
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from .translation_languages import translation_lang
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from .translation_utils import loadTranslatePromptConfig
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except Exception:
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import sys
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from os import path as os_path
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sys.path.append(os_path.dirname(os_path.abspath(__file__)))
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from translation_languages import translation_lang, loadTranslationLanguages
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from translation_utils import loadTranslatePromptConfig
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translation_lang = loadTranslationLanguages(path=".", force=True)
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def _authentication_check(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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response = requests.get(f"{base_url}/models", timeout=0.2)
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if response.status_code == 200:
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return True
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else:
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return False
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except Exception:
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return False
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def _get_available_text_models(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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try:
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response = requests.get(f"{base_url}/models", timeout=0.2)
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models = response.json()["data"]
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except Exception:
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models = []
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allowed_models = []
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for model in models:
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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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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 = loadTranslatePromptConfig(root_path, "translation_lmstudio.yml")
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self.supported_languages = list(translation_lang["LMStudio"]["source"].keys())
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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(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(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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client = LMStudioClient(base_url="http://127.0.0.1:1234/v1")
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models = client.getModelList()
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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(model)
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client.updateClient()
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print(client.translate("こんにちは世界", "Japanese", "English")) |