import os import logging from dotenv import load_dotenv load_dotenv() # --- Logging Setup --- logger = logging.getLogger(__name__) if not logger.handlers: logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s' ) _MODULE_BASE_DIR = os.path.dirname(os.path.abspath(__file__)) # API Authentication for n8n (Basic Auth) API_USERNAME = os.getenv("API_USERNAME", "admin") API_PASSWORD = os.getenv("API_PASSWORD", "password") # Admin fallback credentials for dashboard (used when users.csv is missing or unavailable) ADMIN_USERNAME = os.getenv('FLASK_ADMIN_USERNAME', 'admin') ADMIN_PASSWORD = os.getenv('FLASK_ADMIN_PASSWORD', '1234') # URL Fetcher configs (Generalized from Rentry) URL_FETCH_ENABLED = os.getenv("URL_FETCH_ENABLED", "False").lower() == "true" EXTERNAL_URL = os.getenv("EXTERNAL_URL", os.getenv("RENTRY_URL", "")) URL_UPDATE_PERIOD_MINUTES = int(os.getenv("URL_UPDATE_PERIOD_MINUTES", os.getenv("RENTRY_UPDATE_PERIOD_MINUTES", "60"))) # CSV Configuration RAG_CSV_MAX_RESULTS = int(os.getenv("RAG_CSV_MAX_RESULTS", "5")) RAG_CSV_CONFIDENCE_THRESHOLD = float(os.getenv("RAG_CSV_CONFIDENCE_THRESHOLD", "0.5")) RAG_FAISS_INDEX_SUBDIR_NAME = "faiss_index" RAG_STORAGE_PARENT_DIR = os.getenv("RAG_STORAGE_DIR", os.path.join(_MODULE_BASE_DIR, "faiss_storage")) RAG_SOURCES_DIR = os.getenv("SOURCES_DIR", os.path.join(_MODULE_BASE_DIR, "sources")) RAG_CHUNKED_SOURCES_FILENAME = "pre_chunked_sources.json" os.makedirs(RAG_SOURCES_DIR, exist_ok=True) os.makedirs(RAG_STORAGE_PARENT_DIR, exist_ok=True) # Embedding and model configuration RAG_EMBEDDING_MODEL_NAME = os.getenv("RAG_EMBEDDING_MODEL", "BAAI/bge-small-en") RAG_EMBEDDING_USE_GPU = os.getenv("RAG_EMBEDDING_GPU", "False").lower() == "true" RAG_LOAD_INDEX_ON_STARTUP = os.getenv("RAG_LOAD_INDEX", "True").lower() == "true" # Retrieval Settings RAG_INITIAL_FETCH_K = int(os.getenv("RAG_INITIAL_FETCH_K", 20)) RAG_RERANKER_K = int(os.getenv("RAG_RERANKER_K", 5)) RAG_MAX_FILES_FOR_INCREMENTAL = int(os.getenv("RAG_MAX_FILES_FOR_INCREMENTAL", "50")) # Chunk configuration RAG_CHUNK_SIZE = int(os.getenv("RAG_CHUNK_SIZE", 2000)) RAG_CHUNK_OVERLAP = int(os.getenv("RAG_CHUNK_OVERLAP", 150)) # Reranker configuration RAG_RERANKER_MODEL_NAME = os.getenv("RAG_RERANKER_MODEL", "jinaai/jina-reranker-v2-base-multilingual") RAG_RERANKER_ENABLED = os.getenv("RAG_RERANKER_ENABLED", "True").lower() == "true" # GDrive configuration for RAG sources GDRIVE_SOURCES_ENABLED = os.getenv("GDRIVE_SOURCES_ENABLED", "False").lower() == "true" GDRIVE_FOLDER_ID_OR_URL = os.getenv("GDRIVE_FOLDER_URL") # GDrive configuration for downloading a pre-built FAISS index GDRIVE_INDEX_ENABLED = os.getenv("GDRIVE_INDEX_ENABLED", "False").lower() == "true" GDRIVE_INDEX_ID_OR_URL = os.getenv("GDRIVE_INDEX_URL") # GDrive configuration for downloading users.csv GDRIVE_USERS_CSV_ENABLED = os.getenv("GDRIVE_USERS_CSV_ENABLED", "False").lower() == "true" GDRIVE_USERS_CSV_ID_OR_URL = os.getenv("GDRIVE_USERS_CSV_URL") RAG_DETAILED_LOGGING = os.getenv("RAG_DETAILED_LOGGING", "True").lower() == "true" logger.info(f"RAG Config Loaded - Chunk Size: {RAG_CHUNK_SIZE}, Chunk Overlap: {RAG_CHUNK_OVERLAP}") logger.info(f"Embedding Model: {RAG_EMBEDDING_MODEL_NAME}") logger.info(f"Reranker Model: {RAG_RERANKER_MODEL_NAME}") logger.info(f"Retrieval Pipeline: Initial Fetch K={RAG_INITIAL_FETCH_K}, Reranker Final K={RAG_RERANKER_K}") logger.info(f"CSV Filters: Max Results={RAG_CSV_MAX_RESULTS}, Threshold={RAG_CSV_CONFIDENCE_THRESHOLD}") logger.info(f"URL Fetching: {'ENABLED' if URL_FETCH_ENABLED else 'DISABLED'}") logger.info(f"Detailed Logging: {'ENABLED' if RAG_DETAILED_LOGGING else 'DISABLED'}") logger.info(f"GDrive Sources Download: {'ENABLED' if GDRIVE_SOURCES_ENABLED else 'DISABLED'}") logger.info(f"GDrive Pre-built Index Download: {'ENABLED' if GDRIVE_INDEX_ENABLED else 'DISABLED'}") logger.info(f"GDrive users.csv Download: {'ENABLED' if GDRIVE_USERS_CSV_ENABLED else 'DISABLED'}")