翻訳バックエンドを拡張・リファクタリング:OpenAI/Plamo/Gemini クライアントを追加・改修し、プロンプトを YAML から読み込むように変更。各クライアントでモデル一覧取得・認証・クライアント更新機能を実装し、Translator/Model 層の対応メソッドを追加。Controller と mainloop にプラモ・ジェミニ・OpenAI の認証/モデル操作エンドポイントを追加・整備。config のモデル/API設定をプロパティ化して既定値を None に変更し、選択肢リストを初期化。translation_languages に OpenAI 用マッピングを追加。requirements ファイルの依存記述を調整。

This commit is contained in:
misyaguziya
2025-10-16 18:09:08 +09:00
parent f8466bd6e4
commit 526fd4d5aa
13 changed files with 842 additions and 337 deletions

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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 only GPT models suitable for translation and chat applications (plus those with fine-tuning)
"""
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
root = getattr(model, "root", "")
# 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transcribe, diarize含む
"search", # 検索補助モデル
"transcribe", # 音声→文字起こし
"diarize", # 話者分離
"vision" # 画像入力系旧gpt-4-visionなど
]
# 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 for kw in exclude_keywords):
continue
# GPTモデルまたはFine-tune GPTモデルのみ対象
if model_id.startswith("gpt-"):
allowed_models.append(model_id)
elif model_id.startswith("ft:") and root.startswith("gpt-"):
allowed_models.append(model_id)
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。
"""
def __init__(self, base_url: str | None = None, root_path: str = None):
self.api_key = None
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 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, self.base_url)
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.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 = "OPENAI_API_KEY"
client = OpenAIClient()
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"))