random2345t6 / config.py
SakibAhmed's picture
Upload 4 files
56313b7 verified
import os
import logging
# --- Logging Setup ---
logger = logging.getLogger(__name__)
if not logger.handlers:
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
# --- Configuration Constants ---
_BOT_API_KEY_ENV = os.getenv('BOT_API_KEY')
GROQ_API_KEY = _BOT_API_KEY_ENV
if not GROQ_API_KEY:
logger.critical("CRITICAL: BOT_API_KEY environment variable not found. Groq services will fail.")
FALLBACK_LLM_MODEL_NAME = os.getenv("GROQ_FALLBACK_MODEL", "llama-3.3-70b-versatile")
_MODULE_BASE_DIR = os.path.dirname(os.path.abspath(__file__))
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_LLM_MODEL_NAME = os.getenv("RAG_LLM_MODEL", "llama-3.3-70b-versatile")
RAG_LLM_TEMPERATURE = float(os.getenv("RAG_TEMPERATURE", 0.1))
RAG_LOAD_INDEX_ON_STARTUP = os.getenv("RAG_LOAD_INDEX", "True").lower() == "true"
# MODIFIED: New retrieval and reranking K values for explicit control
RAG_INITIAL_FETCH_K = int(os.getenv("RAG_INITIAL_FETCH_K", 20))
RAG_RERANKER_K = int(os.getenv("RAG_RERANKER_K", 5))
# Incremental update limit
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", 1000))
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")
# --- NEW: 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")
# Detailed logging configuration
RAG_DETAILED_LOGGING = os.getenv("RAG_DETAILED_LOGGING", "True").lower() == "true"
# --- End of Configuration Constants ---
logger.info(f"RAG Configuration 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"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'}")