Update app.py

app.py

@@ -143,8 +143,8 @@ def slice_audio(file_path, audio_name):
     for i, chunk in enumerate(chunks):
         if len(chunk.shape) > 1:
             chunk = chunk.T
-        sf.write(f'dataset/{audio_name}/split_{i}.wav', chunk, sr)
-    return f"dataset/{audio_name}/"
+        sf.write(f'dataset/{audio_name}/{audio_name}/split_{i}.wav', chunk, sr)
+    return f"dataset/{audio_name}"
 
 # Function to zip the dataset directory
 def zip_directory(directory_path,  audio_name):
@@ -180,14 +180,20 @@ with gr.Blocks() as demo:
     with gr.Tabs():
         with gr.TabItem("make dataset"):
             with gr.Row():
-    url_input = gr.Textbox(label="YouTube URL")
-    audio_name_input = gr.Textbox(label="Audio Name")
-    hf_token_input = gr.Textbox(label="Hugging Face Token", type="password")
-    repo_id_input = gr.Textbox(label="Repository ID")
-    result_output = gr.File(label="Download Sliced Audio Zip")
-    upload_output = gr.Textbox(label="Hugging Face Upload Status")
-
-    run_button = gr.Button("Download and Slice Audio")
-    run_button.click(fn=process_audio, inputs=[url_input, audio_name_input, hf_token_input, repo_id_input], outputs=[result_output, upload_output])
-
+                url_input = gr.Textbox(label="YouTube URL")
+                audio_name_input = gr.Textbox(label="Audio Name")
+            with gr.Row():
+                with gr.Accordion("Export dataset to huggingface"):
+                    with gr.Row():
+                        hf_token_input = gr.Textbox(label="Hugging Face Token", type="password")
+                        repo_id_input = gr.Textbox(label="Repository ID")
+                        upload_output = gr.Textbox(label="Hugging Face Upload Status")
+            with gr.Row():
+                result_output = gr.File(label="Download Sliced Audio Zip")
+            with gr.Row():
+                run_button = gr.Button("Download and Slice Audio")
+                run_button.click(fn=process_audio, inputs=[url_input, audio_name_input, hf_token_input, repo_id_input], outputs=[result_output, upload_output])
+                
+    
+    
 demo.launch()