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"""
Configuration settings for the arXivCSRAG application.
"""
import os
import torch
from pathlib import Path
from dotenv import load_dotenv
from huggingface_hub import whoami
# Load environment variables
load_dotenv()
# user = whoami(token=os.getenv('HF_TOKEN'))
# Base paths
ROOT_DIR = Path(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
TEMP_DIR = ROOT_DIR / 'temp'
if not TEMP_DIR.exists(): TEMP_DIR.mkdir(parents=True, exist_ok=True)
# PDF Extraction Configuration
PDF_EXTRACTION_CONFIG = {
'infer_table_structure' : True,
'strategy' : 'hi_res',
'extract_image_block_types' : ['Image'],
'extract_image_block_to_payload': True,
'chunking_strategy' : 'by_title',
'max_characters' : 10000,
'combine_text_under_n_chars' : 2000,
'new_after_n_chars' : 6000
}
# LLM & Embedding model Configuration
MODEL_NAME = 'gemini-2.5-flash-lite-preview-06-17'
# EMBEDDING_MODEL = 'BAAI/bge-base-en-v1.5'
EMBEDDING_MODEL = 'BAAI/bge-m3' # Multi-lingual BGE model
DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'
# Vector Store Configuration
COLLECTION_NAME = 'arXiv_CS_RAG' |