import requests
from typing import Optional, Dict, Any, Union
import os
import rembg
import numpy as np
from PIL import Image
import io
import base64
import re

def remove_background(
    image_input: Union[str, bytes, np.ndarray, Image.Image],
    model_name: str = "u2net"
) -> Dict[str, Any]:
    """
    Remove background from an image.
    
    Args:
        image_input: Can be one of:
            - URL string
            - Data URL string (base64 encoded)
            - Image bytes
            - NumPy array
            - PIL Image
        model_name: Background removal model to use
    
    Returns:
        Dictionary with result information and processed image data
    """
    
    try:
        # Initialize session
        session = rembg.new_session(model_name=model_name)
        
        # Handle different input types
        if isinstance(image_input, str):
            if image_input.startswith('http://') or image_input.startswith('https://'):
                # If input is a URL, download the image
                response = requests.get(image_input, timeout=30)
                response.raise_for_status()
                input_data = response.content
                source_info = f"URL: {image_input}"
            elif image_input.startswith('data:'):
                # If input is a data URL (base64 encoded string)
                # Extract the base64 part after the comma
                base64_data = re.sub('^data:image/.+;base64,', '', image_input)
                input_data = base64.b64decode(base64_data)
                source_info = "data URL"
            else:
                return {
                    "success": False,
                    "error": f"Unsupported string input format: {image_input[:30]}...",
                    "image_data": None
                }
        elif isinstance(image_input, bytes):
            # If input is bytes, use directly
            input_data = image_input
            source_info = "image bytes"
        elif isinstance(image_input, np.ndarray):
            # If input is numpy array, convert to bytes
            pil_img = Image.fromarray(image_input)
            buffer = io.BytesIO()
            pil_img.save(buffer, format="PNG")
            input_data = buffer.getvalue()
            source_info = "numpy array"
        elif isinstance(image_input, Image.Image):
            # If input is PIL Image, convert to bytes
            buffer = io.BytesIO()
            image_input.save(buffer, format="PNG")
            input_data = buffer.getvalue()
            source_info = "PIL Image"
        else:
            return {
                "success": False,
                "error": f"Unsupported input type: {type(image_input)}",
                "image_data": None
            }
        
        # Remove background
        output_data = rembg.remove(input_data, session=session)
        
        return {
            "success": True,
            "message": f"Background removed from {source_info} using {model_name} model",
            "image_data": output_data,
            "model_used": model_name
        }
        
    except requests.RequestException as e:
        return {
            "success": False,
            "error": f"Failed to download image: {str(e)}",
            "image_data": None
        }
    except Exception as e:
        return {
            "success": False,
            "error": f"Failed to process image: {str(e)}",
            "image_data": None
        }