feat: add jwt code

handler.py

@@ -0,0 +1,33 @@
+from typing import Dict
+from transformers import pipeline
+import requests
+import jwt
+
+SAMPLE_RATE = 16000
+
+PUBLIC_KEY = b"-----BEGIN PUBLIC KEY-----MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAu1SU1LfVLPHCozMxH2Mo4lgOEePzNm0tRgeLezV6ffAt0gunVTLw7onLRnrq0/IzW7yWR7QkrmBL7jTKEn5u+qKhbwKfBstIs+bMY2Zkp18gnTxKLxoS2tFczGkPLPgizskuemMghRniWaoLcyehkd3qqGElvW/VDL5AaWTg0nLVkjRo9z+40RQzuVaE8AkAFmxZzow3x+VJYKdjykkJ0iT9wCS0DRTXu269V264Vf/3jvredZiKRkgwlL9xNAwxXFg0x/XFw005UWVRIkdgcKWTjpBP2dPwVZ4WWC+9aGVd+Gyn1o0CLelf4rEjGoXbAAEgAqeGUxrcIlbjXfbcmwIDAQAB-----END PUBLIC KEY-----"
+
+
+class EndpointHandler:
+    def __init__(self, path=""):
+        print(requests.get("https://google.com").text)
+        self.pipeline = pipeline(
+            "automatic-speech-recognition", model="openai/whisper-base"
+        )
+
+    def __call__(self, data: Dict[str, bytes]) -> Dict[str, str]:
+        """
+        Args:
+            data (:obj:):
+                includes the deserialized audio file as bytes
+        Return:
+            A :obj:`dict`:. base64 encoded image
+        """
+        # process input
+        token = data.pop("token", None)
+        if token is None:
+            raise RuntimeError("missing token")
+        decoded = jwt.decode(token, PUBLIC_KEY, algorithms=["RS512"])
+        print("received input from jti=", decoded["jti"])
+
+        return pipeline(*data)

requirements.txt

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+pyjwt[crypto]
+requests