add custom handler

handler.py

@@ -0,0 +1,30 @@
+from typing import Dict, List, Any
+from transformers import pipeline
+from PIL import Image    
+import requests
+
+class EndpointHandler():
+    def __init__(self, path="."):
+        self.pipeline = pipeline("image-to-text", model=path)
+
+    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """
+        data args:
+            inputs (:obj: `str`)
+            date (:obj: `str`)
+        Return:
+            A :obj:`list` | `dict`: will be serialized and returned
+        """
+        # get inputs
+        prompt = "USER: <image>\nWhat's in the image\nASSISTANT:"
+        default_url = "https://cdn.faire.com/fastly/3c335e5c06d3027964ee8351093784c94dfa264e5eb26430c803f4ab3c44da84.jpeg"
+
+        image = Image.open(requests.get(url, stream=True).raw)
+
+        url = data.pop("image_url", default_url)
+
+        # run normal prediction
+        outputs = self.pipeline(image, prompt=prompt, generate_kwargs={"max_new_tokens": 200})
+        print(outputs)
+        
+        return outputs