Update app.py

app.py

@@ -158,37 +158,15 @@ def zip_directory(directory_path, audio_name):
                 zipf.write(file_path, arcname)
     return zip_file
 
-# Function to upload zip file to Hugging Face Hub
-def upload_to_huggingface(zip_file, repo_id, hf_token):
-    api = HfApi()
-    api.upload_file(
-        path_or_fileobj=zip_file,
-        path_in_repo=os.path.basename(zip_file),
-        repo_id=repo_id,
-        token=hf_token
-    )
-    return f"File uploaded to {repo_id}/{os.path.basename(zip_file)}"
 
 # Gradio interface
 def process_audio(url, audio_name):
     file_path = download_youtube_audio(url, audio_name)
     dataset_path = slice_audio(file_path, audio_name)
     zip_file = zip_directory(dataset_path, audio_name)
-    return zip_file
+    return zip_file, print(f"{zip_file} successfully processed")
+
 
-# upload to hf
-def push_to_hub(hf_token, repo_id):
-    zip_file = zip_directory(dataset_path, audio_name)
-    upload_message = upload_to_huggingface(zip_file, repo_id, hf_token)
-    return upload_message
-    
-# create new repository (optional)
-def create_new_repo(repoid):
-    try:
-        create_repo(repoid)
-        return f"Repo '{repoid}' created successfully!"
-    except Exception as e:
-        return str(e)
 
 
 negra = gr.themes.Base(
@@ -198,27 +176,19 @@ negra = gr.themes.Base(
 
 with gr.Blocks(theme=negra) as demo:
     gr.Markdown("# <div style='text-align: center;'> RVC DATASET MAKER</div>")
-    gr.Markdown(" <div style='text-align: center;'> only work for audio only vocal!</div>")
+    gr.Markdown(" <div style='text-align: center;'> only work for vocal only audio!</div>")
     with gr.Tabs():
         with gr.TabItem("make dataset"):
             with gr.Row():
                 url_input = gr.Textbox(label="YouTube URL", placeholder="https://youtu.be/ZdoiTX1f1tU?si=hZ96tryqaPIYfwg1")
             with gr.Row():
                 audio_name_input = gr.Textbox(label="Audio Name", placeholder="Amy")
-            with gr.Row():
-                with gr.Accordion("Export dataset to huggingface (optional)", visible=False):
-                    with gr.Row():
-                        hf_token_input = gr.Textbox(label="Hugging Face Token")
-                        repo_id_input = gr.Textbox(label="Repository ID")
-                        with gr.Row():
-                            push_hub = gr.Button("Hugging Face Upload")
-                            upload_output = gr.Textbox(label="Hugging Face Upload Status")
             with gr.Row():
                 result_output = gr.File(label="Download Sliced Audio Zip")
+                result_process = gr.Textbox(label="Sliced Audio output")
             with gr.Row():
                 run_button = gr.Button("Slice 👾 Audio")
-                run_button.click(fn=process_audio, inputs=[url_input, audio_name_input], outputs=[result_output])
-                push_hub.click(fn=push_to_hub, inputs=[result_output, hf_token_input, repo_id_input], outputs=[upload_output])
+                run_button.click(fn=process_audio, inputs=[url_input, audio_name_input], outputs=[result_output, result_process])
         with gr.TabItem("note"):
             with gr.Row():
                 gr.Markdown(