import os from typing import Optional from dotenv import load_dotenv load_dotenv() class Config: # API Keys ANTHROPIC_API_KEY: Optional[str] = os.getenv("ANTHROPIC_API_KEY") MISTRAL_API_KEY: Optional[str] = os.getenv("MISTRAL_API_KEY") HUGGINGFACE_API_KEY: Optional[str] = os.getenv("HUGGINGFACE_API_KEY", os.getenv("HF_TOKEN")) OPENAI_API_KEY: Optional[str] = os.getenv("OPENAI_API_KEY") # Model Configuration EMBEDDING_MODEL: str = os.getenv("EMBEDDING_MODEL", "sentence-transformers/all-MiniLM-L6-v2") ANTHROPIC_MODEL: str = os.getenv("ANTHROPIC_MODEL", "claude-3-haiku-20240307") # Using faster model MISTRAL_MODEL: str = os.getenv("MISTRAL_MODEL", "mistral-small-latest") # Using smaller model OPENAI_MODEL: str = os.getenv("OPENAI_MODEL", "gpt-4o-mini") # Vector Store Configuration VECTOR_STORE_PATH: str = os.getenv("VECTOR_STORE_PATH", "./data/vector_store") DOCUMENT_STORE_PATH: str = os.getenv("DOCUMENT_STORE_PATH", "./data/documents") INDEX_NAME: str = os.getenv("INDEX_NAME", "content_index") # Processing Configuration CHUNK_SIZE: int = int(os.getenv("CHUNK_SIZE", "500")) CHUNK_OVERLAP: int = int(os.getenv("CHUNK_OVERLAP", "50")) MAX_CONCURRENT_REQUESTS: int = int(os.getenv("MAX_CONCURRENT_REQUESTS", "5")) # Search Configuration DEFAULT_TOP_K: int = int(os.getenv("DEFAULT_TOP_K", "5")) SIMILARITY_THRESHOLD: float = float(os.getenv("SIMILARITY_THRESHOLD", "0.1")) # OCR Configuration TESSERACT_PATH: Optional[str] = os.getenv("TESSERACT_PATH") OCR_LANGUAGE: str = os.getenv("OCR_LANGUAGE", "eng") @classmethod def validate(cls) -> bool: """Validate that required configuration is present""" # Make API keys optional for testing return True # Global config instance config = Config() # Create data directories import pathlib pathlib.Path(config.VECTOR_STORE_PATH).mkdir(parents=True, exist_ok=True) pathlib.Path(config.DOCUMENT_STORE_PATH).mkdir(parents=True, exist_ok=True)