Create handler.py

handler.py

@@ -0,0 +1,26 @@
+from typing import Dict, List, Any
+from transformers import pipeline
+
+class EndpointHandler():
+    def __init__(self, path=""):
+        self.pipeline = pipeline("automatic-speech-recognition",
+                                 model=path, 
+                                 chunk_length_s = 30 , 
+                                 stride_length_s = (3, 0), 
+                                 generate_kwargs = {"language":"pt"} , 
+                                 device = 0
+                                )
+
+    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
+        inputs = data.pop("inputs",data)
+        # run normal prediction
+        prediction = self.pipeline(inputs)
+        return prediction