Update handler.py

handler.py

@@ -3,13 +3,15 @@ from transformers import pipeline
 from datasets import load_dataset
 import soundfile as sf
 from huggingface_hub.inference_api import InferenceApi
+from typing import Dict, List, Any
+
 
 class EndpointHandler:
-    def __init__(self):
+    def __init__(self, path=""):
         self.api = InferenceApi(repo_id="microsoft/speecht5_tts", task="text-to-speech")
         self.embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
 
-    def __call__(self, data):
+    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
         text = data.get("inputs", "")
         # Extract speaker_embedding using the index from your dataset, or replace with your own logic.
         speaker_embedding = torch.tensor(self.embeddings_dataset[7306]["xvector"]).unsqueeze(0)