config.py

import os
from typing import Optional
from dotenv import load_dotenv 

load_dotenv()


class Config:
    # API Keys
    NEBIUS_API_KEY: Optional[str] = os.getenv("NEBIUS_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"))
    
    # NEBIUS Configuration (OpenAI OSS models)
    NEBIUS_BASE_URL: str = os.getenv("NEBIUS_BASE_URL", "https://api.studio.nebius.com/v1/")
    NEBIUS_MODEL: str = os.getenv("NEBIUS_MODEL", "openai/gpt-oss-120b")
    
    # Model Configuration
    EMBEDDING_MODEL: str = os.getenv("EMBEDDING_MODEL", "sentence-transformers/all-MiniLM-L6-v2")
    MISTRAL_MODEL: str = os.getenv("MISTRAL_MODEL", "mistral-small-latest")  # Using smaller model
    
    # 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)