Add exception handling for cases when no Piper model exists.

src/synthesize.py

@@ -9,7 +9,7 @@ from scipy.io import wavfile
 from transformers import pipeline
 import os
 import numpy as np
-from gradio_client import Client, file
+from gradio_client import Client, handle_file
 
 
 def synth_mms(text:str, model:str):
@@ -130,7 +130,7 @@ def synth_toucan(text:str, model:str):
     result = client.predict(
     		prompt=text,
     		language=model,
-    		reference_audio=file('https://github.com/gradio-app/gradio/raw/main/test/test_files/audio_sample.wav'),
+    		reference_audio=handle_file('https://github.com/gradio-app/gradio/raw/main/test/test_files/audio_sample.wav'),
     		voice_seed=123,
     		prosody_creativity=0.1,
     		duration_scaling_factor=1,
@@ -153,14 +153,17 @@ def synth_piper(text:str, model:str):
 
     NOTES: (1) This uses a Huggingface Gradio Space to compute via the API.
     '''
-    client = Client("k2-fsa/text-to-speech")
-    result =  client.predict(
-    		language=model[0],
-    		repo_id=model[1],
-    		text=text,
-    		sid="0",
-    		speed=1,
-    		api_name="/process"
-    )
-    sampling_rate, wav = wavfile.read(result[0])
-    return wav, sampling_rate
+    if model is not None:
+        client = Client("k2-fsa/text-to-speech")
+        result =  client.predict(
+        		language=model[0],
+        		repo_id=model[1],
+        		text=text,
+        		sid="0",
+        		speed=1,
+        		api_name="/process"
+        )
+        sampling_rate, wav = wavfile.read(result[0])
+        return wav, sampling_rate
+    else:
+        return None