threading

app.py

@@ -1,15 +1,36 @@
 import os
 import requests
 from subprocess import Popen, PIPE
+import time
+import threading
 import gradio as gr
 
-try:
-	# start the process without waiting for a response
-	Popen(['python', 'server.py'], stdout=PIPE, stderr=PIPE)
-except:
-	import logging
-	logging.error(f'Could not run xVASynth.')
-	sys.exit(0)
+
+def run_xvaserver():
+	try:
+		# start the process without waiting for a response
+		xvaserver = Popen(['python', 'server.py'], stdout=PIPE, stderr=PIPE, universal_newlines=True)
+	except:
+		import logging
+		logging.error(f'Could not run xVASynth.')
+		sys.exit(0)
+
+	# Read and print stdout and stderr of the subprocess
+	while True:
+		output = xvaserver.stdout.readline()
+		if output == '' and xvaserver.poll() is not None:
+			break
+		if output:
+			print(output.strip())
+
+		error = xvaserver.stderr.readline()
+		if error == '' and xvaserver.poll() is not None:
+			break
+		if error:
+			print(error.strip(), file=sys.stderr)
+
+	# Wait for the process to exit
+	xvaserver.wait()
 
 def predict(input, pacing):
 	model_type = 'xVAPitch'
@@ -22,35 +43,43 @@ def predict(input, pacing):
 	use_cleanup = 0
 
 	data = {
-	    'modelType': model_type,
-	    'sequence': line,
-	    'pace': pace,
-	    'outfile': save_path,
-	    'vocoder': 'n/a',
-	    'base_lang': language,
-	    'base_emb': base_speaker_emb,
-	    'useSR': use_sr,
-	    'useCleanup': use_cleanup,
+		'modelType': model_type,
+		'sequence': line,
+		'pace': pace,
+		'outfile': save_path,
+		'vocoder': 'n/a',
+		'base_lang': language,
+		'base_emb': base_speaker_emb,
+		'useSR': use_sr,
+		'useCleanup': use_cleanup,
 	}
-	requests.post('http://localhost:8008/synthesize', json=data)
+	requests.post('http://0.0.0.0:8008/synthesize', json=data)
 	return 22100, os.open(save_path, "rb")
 
 input_textbox = gr.Textbox(
-    label="Input Text",
-    lines=1,
-    autofocus=True
+	label="Input Text",
+	lines=1,
+	autofocus=True
 )
 slider = gr.Slider(0.0, 2.0, value=1.0, step=0.1, label="Pacing")
 
 gradio_app = gr.Interface(
-    predict,
-    [
-    	input_textbox,
-    	slider
+	predict,
+	[
+		input_textbox,
+		slider
 	],
-    outputs= "audio",
-    title="xVASynth",
+	outputs= "audio",
+	title="xVASynth",
 )
 
+
 if __name__ == "__main__":
-    gradio_app.launch()
+	# Run the web server in a separate thread
+	web_server_thread = threading.Thread(target=run_xvaserver)
+	web_server_thread.start()
+
+	gradio_app.launch()
+
+	# Wait for the web server thread to finish (shouldn't be reached in normal execution)
+	web_server_thread.join()