Upload handler.py

handler.py

@@ -0,0 +1,34 @@
+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-6.7b")
+        self.model = Blip2ForConditionalGeneration.from_pretrained("Salesforce/blip2-opt-6.7b")
+
+        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