use list for JSON serialization

handler.py

@@ -32,7 +32,7 @@ class EndpointHandler():
 
         # Create JSON response
         response = {
-            "audio_data": audio_data,
+            "audio_data": audio_data.tolist(),
             "sampling_rate": sampling_rate
         }
 

test.py

@@ -13,7 +13,8 @@ payload = {"inputs": "Lowfi hiphop with deep bass"}
 pred=my_handler(payload)
 
 
-audio_data = pred["audio_data"]
+audio_data = np.array(pred["audio_data"], dtype=np.float32)
+
 sampling_rate = pred["sampling_rate"]
 
 # Write the audio data to a WAV file
@@ -21,3 +22,4 @@ output_file_path = "output.wav"  # Specify the file path
 sf.write(output_file_path, audio_data, sampling_rate)
 
 print("Audio file saved successfully.")
+

test_api.py

@@ -3,7 +3,7 @@ import base64
 import soundfile as sf
 import numpy as np
 
-API_URL = "https://gij43le0roc2pmst.us-east-1.aws.endpoints.huggingface.cloud"
+API_URL = "https://dcixo8iy1d0t2cq9.us-east-1.aws.endpoints.huggingface.cloud"
 headers = {
 	"Accept" : "application/json",
 	"Authorization": "Bearer token",
@@ -21,20 +21,11 @@ response = query({
 
 print(response)
 
-# Extract audio data and sampling rate from the JSON response
-audio_base64 = response["audio_base64"]
+audio_data = response["audio_data"]
 sampling_rate = response["sampling_rate"]
 
-# Decode the base64-encoded audio data
-audio_binary = base64.b64decode(audio_base64)
-# Convert binary audio data to a NumPy array
-audio_np = np.frombuffer(audio_binary, dtype=np.int16)
-
-# Print the shape of the audio data
-print("Shape of audio data:", audio_np.shape)
-
 # Write the audio data to a WAV file
 output_file_path = "output.wav"  # Specify the file path
-sf.write(output_file_path, audio_np, sampling_rate)
+sf.write(output_file_path, audio_data, sampling_rate)
 
 print("Audio file saved successfully.")