146 lines
4.7 KiB
Python
146 lines
4.7 KiB
Python
from openai import OpenAI
|
|
from langchain_openai import ChatOpenAI
|
|
from pydantic import SecretStr
|
|
|
|
try:
|
|
from .translation_languages import translation_lang
|
|
from .translation_utils import loadPromptConfig
|
|
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 loadPromptConfig
|
|
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 = loadPromptConfig(root_path, "translation_groq.yml")
|
|
self.supported_languages = list(translation_lang["Groq_API"]["source"].keys())
|
|
self.prompt_template = prompt_config["system_prompt"]
|
|
|
|
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 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.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"))
|