Update app.py

app.py

@@ -7,7 +7,6 @@ def install_parler_tts():
 # Call the function to install parler-tts
 install_parler_tts()
 
-
 import gradio as gr
 import requests
 import os
@@ -278,16 +277,13 @@ def generate_answer(message, choice):
 def bot(history, choice, tts_model):
     if not history:
         return history
+    
     response, addresses = generate_answer(history[-1][0], choice)
     history[-1][1] = ""
-    
-    # Generate audio for the entire response in a separate thread
+
+    # Generate audio and process output prompt in parallel
     with concurrent.futures.ThreadPoolExecutor() as executor:
-        if tts_model == "ElevenLabs":
-            audio_future = executor.submit(generate_audio_elevenlabs, response)
-        else:
-            audio_future = executor.submit(generate_audio_parler_tts, response)
-        
+        audio_future = executor.submit(generate_audio, tts_model, response)
         for character in response:
             history[-1][1] += character
             time.sleep(0.05)  # Adjust the speed of text appearance
@@ -296,6 +292,12 @@ def bot(history, choice, tts_model):
         audio_path = audio_future.result()
         yield history, audio_path
 
+def generate_audio(tts_model, text):
+    if tts_model == "ElevenLabs":
+        return generate_audio_elevenlabs(text)
+    else:
+        return generate_audio_parler_tts(text)
+
 def add_message(history, message):
     history.append((message, None))
     return history, gr.Textbox(value="", interactive=True, placeholder="Enter message or upload file...", show_label=False)
@@ -522,7 +524,7 @@ def generate_audio_parler_tts(text):
     input_ids = tokenizer(description, return_tensors="pt").input_ids.to(device)
     prompt_input_ids = tokenizer(text, return_tensors="pt").input_ids.to(device)
 
-    generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids)
+    generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids, max_new_tokens=200)
     audio_arr = generation.cpu().numpy().squeeze()
     
     with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as f: