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import os
from dotenv import load_dotenv
from pathlib import Path
# env_path = Path(__file__).resolve().parent.parent / '.env'
# load_dotenv(dotenv_path=env_path, override=True)
load_dotenv(override=True)
class Config:
API_KEY = os.getenv('OPENAI_API_KEY')
MODEL_ID = os.getenv('MODEL_ID')
MODEL_BASENAME = os.getenv('MODEL_BASENAME')
COLLECTION_NAME = os.getenv('COLLECTION_NAME')
PERSIST_DIRECTORY = os.path.join(os.path.dirname(__file__),'vector_store')
os.makedirs(PERSIST_DIRECTORY, exist_ok=True)
UPLOAD_DIR = os.path.join(os.path.dirname(__file__),'uploads')
os.makedirs(UPLOAD_DIR, exist_ok=True)
LOG_DIR = os.path.join(os.path.dirname(__file__),'log_dir')
os.makedirs(LOG_DIR, exist_ok=True)
MODELS_PATH = os.path.join(os.path.dirname(__file__),'models')
CACHE_DIR = os.path.join(os.path.dirname(__file__),'models')
# os.makedirs(CACHE_DIR, exist_ok=True)
# MODELS_PATH = '/models'
MODEL_NAME = "sentence-transformers/all-mpnet-base-v2"
MODEL_KWARGS = {'device': 'cpu'}
ENCODE_KWARGS = {'normalize_embeddings': False}
CHUNK_SIZE = 1024
CHUNK_OVERLAP = 200 |