handler.py

import requests
from PIL import Image
from transformers import Blip2Processor, Blip2ForConditionalGeneration
from typing import Dict, List, Any
import torch
import base64
from io import BytesIO

class EndpointHandler():
    def __init__(self, path=""):
        self.processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b")
        self.model = Blip2ForConditionalGeneration.from_pretrained("Salesforce/blip2-opt-2.7b")

        self.device = "cuda" if torch.cuda.is_available() else "cpu"
        self.model.to(self.device)

    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
        image_encoded = data.pop("inputs", data)
        text = data["text"]

        # image = Image.open(image_path)
        image = self.decode_base64_image(image_encoded)

        processed = self.processor(images=image, text=text, return_tensors="pt").to(self.device)

        out = self.model.generate(**processed)

        return self.processor.decode(out[0], skip_special_tokens=True)
    
    def decode_base64_image(self, image_string):
        base64_image = base64.b64decode(image_string)
        buffer = BytesIO(base64_image)
        image = Image.open(buffer)
        return image