from typing import Dict, List, Any
from transformers import Pipeline
from transformers import BlipProcessor, BlipForConditionalGeneration
from PIL import Image
from io import BytesIO
import base64
import json

class EndpointHandler():
    def __init__(self, path=""):
        self.processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
        self.model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base").to("cuda")
        
    def __call__(self, data):
        info=data['inputs']
        img=info.pop('image',data)
        image_bytes=base64.b64decode(img)
        raw_images = Image.open(BytesIO(image_bytes))
        
        inputs = self.processor(raw_images, return_tensors="pt").to("cuda")

        out = self.model.generate(**inputs)
        # print(self.processor.decode(out[0], skip_special_tokens=True))
        return {'text':self.processor.decode(out[0], skip_special_tokens=True)}
    
if __name__=="__main__":
    my_handler=EndpointHandler(path='.')
    test_payload={"inputs": "/home/ubuntu/guoling/1.png"}
    test_result=my_handler(test_payload)
    print(test_result)