config/settings.py

import os
from pathlib import Path
from dotenv import load_dotenv

load_dotenv()


class Settings:
    GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
    MAX_FILE_SIZE_MB = 50
    SUPPORTED_FILE_TYPES = [
        "pdf",
        "txt",
        "png",
        "jpg",
        "jpeg",
        "docx",
        "xlsx",
        "csv",
        "md",
        "json",
        "xml",
        "html",
        "py",
        "js",
        "ts",
        "doc",
        "xls",
        "ppt",
        "pptx",
    ]
    # Use /tmp for temporary files on Hugging Face Spaces (or override with TEMP_DIR env var)
    TEMP_DIR = Path(os.getenv("TEMP_DIR", "/tmp/data_extractor_temp"))
    DOCKER_IMAGE = os.getenv("DOCKER_IMAGE", "python:3.12-slim")
    COORDINATOR_MODEL = os.getenv("COORDINATOR_MODEL", "gemini-2.5-pro")
    PROMPT_ENGINEER_MODEL = os.getenv("PROMPT_ENGINEER_MODEL", "gemini-2.5-pro")
    DATA_EXTRACTOR_MODEL = os.getenv("DATA_EXTRACTOR_MODEL", "gemini-2.5-pro")
    DATA_ARRANGER_MODEL = os.getenv("DATA_ARRANGER_MODEL", "gemini-2.5-pro")
    CODE_GENERATOR_MODEL = os.getenv("CODE_GENERATOR_MODEL", "gemini-2.5-pro")

    COORDINATOR_MODEL_THINKING_BUDGET=2048
    PROMPT_ENGINEER_MODEL_THINKING_BUDGET=2048
    DATA_EXTRACTOR_MODEL_THINKING_BUDGET=-1
    DATA_ARRANGER_MODEL_THINKING_BUDGET=3072
    CODE_GENERATOR_MODEL_THINKING_BUDGET=3072

    @classmethod
    def validate_config(cls):
        """Validate configuration and create necessary directories."""
        errors = []
        warnings = []
        
        # Check required API keys
        if not cls.GOOGLE_API_KEY:
            errors.append("GOOGLE_API_KEY is required - get it from Google AI Studio")
            
        # Check for optional but recommended API keys
        openai_key = os.getenv("OPENAI_API_KEY")
        if not openai_key:
            warnings.append("OPENAI_API_KEY not set - OpenAI models will not be available")
            
        # Validate and create temp directory
        try:
            cls.TEMP_DIR.mkdir(exist_ok=True, parents=True)
            # Test write permissions
            test_file = cls.TEMP_DIR / ".write_test"
            try:
                test_file.write_text("test")
                test_file.unlink()
            except Exception as e:
                errors.append(f"Cannot write to temp directory {cls.TEMP_DIR}: {e}")
        except Exception as e:
            errors.append(f"Cannot create temp directory {cls.TEMP_DIR}: {e}")
            
        # Validate file size limits
        if cls.MAX_FILE_SIZE_MB <= 0:
            errors.append("MAX_FILE_SIZE_MB must be positive")
        elif cls.MAX_FILE_SIZE_MB > 100:
            warnings.append(f"MAX_FILE_SIZE_MB ({cls.MAX_FILE_SIZE_MB}) is very large")
            
        # Validate supported file types
        if not cls.SUPPORTED_FILE_TYPES:
            errors.append("SUPPORTED_FILE_TYPES cannot be empty")
            
        # Validate model names
        model_fields = ['DATA_EXTRACTOR_MODEL', 'DATA_ARRANGER_MODEL', 'CODE_GENERATOR_MODEL']
        for field in model_fields:
            model_name = getattr(cls, field)
            if not model_name:
                errors.append(f"{field} cannot be empty")
            elif not model_name.startswith(('gemini-', 'gpt-', 'claude-')):
                warnings.append(f"{field} '{model_name}' may not be a valid model name")
                
        # Return validation results
        if errors:
            error_msg = "Configuration validation failed:\n" + "\n".join(f"- {error}" for error in errors)
            if warnings:
                error_msg += "\n\nWarnings:\n" + "\n".join(f"- {warning}" for warning in warnings)
            raise ValueError(error_msg)
            
        if warnings:
            import logging
            logger = logging.getLogger(__name__)
            logger.warning("Configuration warnings:\n" + "\n".join(f"- {warning}" for warning in warnings))
            
        return True
    
    @classmethod
    def get_debug_info(cls):
        """Get debug information about current configuration."""
        import platform
        import sys
        
        return {
            "python_version": sys.version,
            "platform": platform.platform(),
            "temp_dir": str(cls.TEMP_DIR),
            "temp_dir_exists": cls.TEMP_DIR.exists(),
            "supported_file_types": len(cls.SUPPORTED_FILE_TYPES),
            "max_file_size_mb": cls.MAX_FILE_SIZE_MB,
            "has_google_api_key": bool(cls.GOOGLE_API_KEY),
            "has_openai_api_key": bool(os.getenv("OPENAI_API_KEY")),
            "models": {
                "data_extractor": cls.DATA_EXTRACTOR_MODEL,
                "data_arranger": cls.DATA_ARRANGER_MODEL, 
                "code_generator": cls.CODE_GENERATOR_MODEL
            }
        }


settings = Settings()