Upload 2 files

handler.py

@@ -1,23 +1,26 @@
 from typing import Dict, List, Any
 from transformers import pipeline
+import scipy.io.wavfile
 
 
 class EndpointHandler:
     def __init__(self, path=""):
-        self.model = pipeline("text-to-speech", "suno/bark")
+        self.synthesiser = pipeline("text-generation", "suno/bark")  # Attempt to create pipeline
 
-    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
-        text_prompt = data.pop("inputs", data)
+    def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:
+        text_prompt = data.get("inputs")
+        if not text_prompt:
+            raise ValueError("Missing required 'inputs' field in request data.")
 
-        # run normal prediction
-        speech_array = self.model(text_prompt,forward_params={"do_sample": True})
-        return speech_array
+        try:
+            speech = self.synthesiser(text_prompt, forward_params={"do_sample": True})
+            audio_data = speech["audio"]  # Assuming audio is in a NumPy array
+            sampling_rate = speech["sampling_rate"]
 
+            # Return audio data as a byte string (adjust format as needed)
+            audio_bytes = audio_data.tobytes()
+            return {"audio": audio_bytes, "sampling_rate": sampling_rate}
+
+        except Exception as e:
+            # Handle potential errors with model loading or usage
+            return {"error": str(e)}

requirements.txt

@@ -1 +1,2 @@
 transformers
+scipy