Update app.py

app.py

@@ -300,62 +300,6 @@ async def demo_conversation():
     # Initialize all models
     await ai_conversation.initialize_models()
 
-#     # Example usage
-#     audio_file = "/content/Recording 2.wav"  # Replace with your audio file path
-#     system_prompt = "You are a helpful assistant. Please provide clear and concise responses."
-
-#     # Process the conversation
-#     result = await ai_conversation.process_conversation(audio_file, system_prompt)
-
-#     if "error" in result:
-#         print(f"Error: {result['error']}")
-#     else:
-#         print(f"Transcribed: {result['transcribed_text']}")
-#         print(f"Thinking: {result['thinking']}")
-#         print(f"Response: {result['response_text']}")
-#         print(f"Audio saved to: {result['output_audio']}")
-#         print(f"Processing times: {result['processing_times']}")
-
-# async def demo_batch_processing():
-#     """Demonstration of batch processing"""
-#     ai_conversation = AsyncAIConversation()
-#     await ai_conversation.initialize_models()
-
-#     # Example batch processing
-#     audio_files = [
-#         "/content/Recording 1.wav",
-#         "/content/Recording 2.wav",
-#         "/content/Recording 3.wav"
-#     ]
-
-#     results = await ai_conversation.batch_process(audio_files)
-
-#     for i, result in enumerate(results):
-#         print(f"File {i+1}: {result}")
-
-# Additional utility function for testing Kokoro TTS standalone
-# async def test_kokoro_tts():
-#     """Test Kokoro TTS functionality standalone"""
-#     try:
-#         tts_synthesizer = KPipeline(lang_code='a')
-        
-#         test_text = "Hello, this is a test of the Kokoro text-to-speech system."
-        
-#         # Generate audio
-#         generator = tts_synthesizer(test_text, voice='af_heart')
-        
-#         for i, (gs, ps, audio) in enumerate(generator):
-#             output_path = f"kokoro_test_{i}.wav"
-#             sf.write(output_path, audio, 24000)
-#             print(f"Test audio {i} saved to: {output_path}")
-            
-#             # Only process first chunk for testing
-#             if i == 0:
-#                 break
-                
-#     except Exception as e:
-#         print(f"Error testing Kokoro TTS: {e}")
-
 
 
 # Create the async function wrapper for Gradio
@@ -411,19 +355,13 @@ with gr.Blocks() as demo:
         outputs=[status_output, response_text_output, response_audio_output, processing_times_output]
     )
 
-# Launch the Gradio interface
-# We need to run the Gradio app within an async context if we're using await inside the handler.
-# However, Gradio's launch already handles the async loop for the button clicks.
-# The key is that ai_conversation.initialize_models() must be awaited *before* launching Gradio.
-
-# Since the notebook already executed the initialization:
-# ai_conversation = AsyncAIConversation()
-# await ai_conversation.initialize_models()
-# We can directly launch the demo.
 
 if __name__ == "__main__":
-    
-    awit demo_conversation()
+
+    def initiate():
+        asyncio.run(demo_conversation())
+
+    initiate()
 
     # Gradio launch itself runs an event loop.
     # Ensure ai_conversation is initialized in the notebook before this cell is run.