import os
from transformers import AutoModel, AutoTokenizer
from PIL import Image
import torch
 
class OCRModel:
    _instance = None

    def __new__(cls):
        if cls._instance is None:
            cls._instance = super(OCRModel, cls).__new__(cls)
            cls._instance.initialize()
        return cls._instance

    def initialize(self):
        # تحميل النموذج مرة واحدة وتخزينه محلياً
        model_path = os.getenv('MODEL_PATH', 'RufusRubin777/GOT-OCR2_0_CPU')
        
        self.tokenizer = AutoTokenizer.from_pretrained(
            model_path, 
            trust_remote_code=True,
            local_files_only=False  # سيتم تحميل الملفات إذا لم تكن موجودة
        )
        
        self.model = AutoModel.from_pretrained(
            model_path,
            trust_remote_code=True,
            low_cpu_mem_usage=True,
            device_map='cpu',  # سيختار أفضل جهاز متاح
            use_safetensors=True,
            pad_token_id=self.tokenizer.eos_token_id
        )
        
        self.model = self.model.eval()

        
    def process_image(self, image_stream):
        try:
            # فتح الصورة من الذاكرة
            image = Image.open(image_stream)
            
            with torch.no_grad():
                result = self.model.chat(self.tokenizer, image, ocr_type='format')
            return result
        except Exception as e:
            return f"Error processing image: {str(e)}"