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import os
from dotenv import load_dotenv
load_dotenv()
class Settings:
GROQ_API_KEY = os.getenv("GROQ_API_KEY")
# Multilingual Model Settings
VIETNAMESE_EMBEDDING_MODEL = 'keepitreal/vietnamese-sbert'
VIETNAMESE_LLM_MODEL = "llama-3.1-8b-instant"
MULTILINGUAL_EMBEDDING_MODEL = 'Qwen/Qwen3-Embedding-0.6B'
MULTILINGUAL_LLM_MODEL = "llama-3.1-8b-instant"
# Fallback models in case primary models fail
FALLBACK_MULTILINGUAL_EMBEDDING_MODEL = 'sentence-transformers/all-MiniLM-L6-v2'
# Default models (fallback)
DEFAULT_EMBEDDING_MODEL = 'dangvantuan/vietnamese-embedding'
DEFAULT_LLM_MODEL = "Vietnamese_LLaMA2_13B_8K_SFT_General_Domain_Knowledge"
WHISPER_MODEL = "whisper-large-v3-turbo"
# TTS Settings
MAX_CHUNK_LENGTH = 200
SUPPORTED_LANGUAGES = {
'vi': 'vi', 'en': 'en', 'fr': 'fr', 'es': 'es',
'de': 'de', 'ja': 'ja', 'ko': 'ko', 'zh': 'zh'
}
# RAG Settings
EMBEDDING_DIMENSION = 768 # For Vietnamese model
MULTILINGUAL_EMBEDDING_DIMENSION = 4096 # For Nemotron model
TOP_K_RESULTS = 3
# SpeechBrain VAD Settings
VAD_MODEL = "speechbrain/vad-crdnn-libriparty"
VAD_THRESHOLD = 0.5
VAD_MIN_SILENCE_DURATION = 0.5
VAD_SPEECH_PAD_DURATION = 0.1
SAMPLE_RATE = 16000
settings = Settings() |