- add custom endpoint handler

handler.py

@@ -0,0 +1,36 @@
+from typing import Dict, List, Any
+
+import torch as torch
+from transformers import pipeline
+
+
+class EndpointHandler():
+
+
+
+    def __init__(self, path=""):
+        device = 0 if torch.cuda.is_available() else "cpu"
+        self.pipe = pipeline(
+            task="automatic-speech-recognition",
+            model="openai/whisper-large",
+            chunk_length_s=30,
+            device=device,
+        )
+        self.pipe.model.config.forced_decoder_ids = self.pipe.tokenizer.get_decoder_prompt_ids(language="nl", task="transcribe")
+
+    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
+        """
+        #print request
+        print("request")
+        print(data)
+        # get inputs
+        inputs = data.pop("inputs", data)
+
+        text = self.pipe(inputs)["text"]
+        return text