Update app.py

app.py

@@ -8,8 +8,8 @@ from huggingface_hub import hf_hub_download
 # from modules.v2.vc_wrapper import VoiceConversionWrapper 
 
 # --- CONFIGURATION (UPDATE YOUR_USERNAME HERE) ---
-# Replace 'YOUR_USERNAME' with your actual Hugging Face username
-MODEL_REPO_ID = "Bajiyo/dhanush_seedvc" 
+# Your correct model repository ID
+MODEL_REPO_ID = "Bajiyo/dhanush_seedvc"
 CFM_FILE = "CFM_epoch_00651_step_21500.pth"
 AR_FILE = "AR_epoch_00651_step_21500.pth"
 # -----------------------------------------------
@@ -84,18 +84,14 @@ def main(args):
     # load_models handles the download and initialization now
     vc_wrapper = load_models(args)
     
-    # Define wrapper function for Gradio to ensure arguments are handled correctly
-    @gr.gradio()
-    @spaces.GPU # Ensures conversion runs on the specified GPU if available
+    # Define wrapper function for Gradio. NO DECORATORS HERE.
     def convert_voice_wrapper(source_audio_path, target_audio_path, diffusion_steps,
                               length_adjust, intelligibility_cfg_rate, similarity_cfg_rate,
                               top_p, temperature, repetition_penalty, convert_style, 
                               anonymization_only, stream_output=True):
         """
-        Wrapper function for vc_wrapper.convert_voice_with_streaming that can be decorated.
+        Wrapper function for vc_wrapper.convert_voice_with_streaming.
         """
-        # Ensure correct type for the stream_output argument if needed, 
-        # though the main function is now calling convert_voice_with_streaming directly
         yield from vc_wrapper.convert_voice_with_streaming(
             source_audio_path=source_audio_path,
             target_audio_path=target_audio_path,
@@ -160,14 +156,13 @@ def main(args):
         title="Seed Voice Conversion V2",
         examples=examples,
         cache_examples=False,
-    ).queue().launch(share=False) # Changed share=True to share=False for Spaces deployment
+    ).queue().launch(share=False)
 
 if __name__ == "__main__":
     import argparse
     parser = argparse.ArgumentParser()
     parser.add_argument("--compile", action="store_true", help="Compile the model using torch.compile")
     # These arguments are now effectively ignored/not needed since we download the models
-    # but we keep them to maintain compatibility with the original script structure.
     parser.add_argument("--ar-checkpoint-path", type=str, default=None,
                         help="Path to custom checkpoint file (overridden by HF download in Space)")
     parser.add_argument("--cfm-checkpoint-path", type=str, default=None,