Update app.py

app.py

@@ -18,12 +18,12 @@ index_paths = []
 
 with gr.Blocks(title="RVC UI") as app:
     gr.Markdown("<center><h1> RVC UI 🗣️")
-    gr.Markdown("this ui not done yet!")
+    gr.Markdown("<h1>this ui not done yet!")
     models = gr.Dropdown(label="voice model", choices=sorted(names))
     clean_button = gr.Button("Unload model to save GPU memory", variant="primary")
     spk_item = gr.Slider(minimum=0,maximum=2333,step=1,label="Select Speaker/Singer ID",value=0,visible=False,interactive=False,)
     clean_button.click(fn=clean, inputs=[], outputs=[models], api_name="infer_clean")
-    modelinfo = gr.Textbox(label="Model info", max_lines=8)
+    modelinfo = gr.Textbox(label="Model info", max_lines=8, visible=False)
     with gr.TabItem("Single inference"):
         pith_voice = gr.Number(label="Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12)",value=0,)
         input_audio0 = gr.Audio(label="The audio file to be processed",type="filepath")
@@ -35,12 +35,12 @@ with gr.Blocks(title="RVC UI") as app:
             protect0 = gr.Slider(minimum=0,maximum=0.5,label="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy",value=0.33,step=0.01,interactive=True)
             filter_radius0 = gr.Slider(minimum=0,maximum=7,label=("If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness."),value=3,step=1,interactive=True)                             
             f0_file = gr.File(label="F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation",visible=False,)
-            but0 = gr.Button("Convert", variant="primary")
+            but0 = gr.Button("Convert", variant="primary", type="filepath")
             vc_output1 = gr.Textbox(label="Output information")
             vc_output2 = gr.Audio(label="Export audio (click on the three dots in the lower right corner to download)")
             #refresh_button.click(fn=change_choices,inputs=[],outputs=[models, file_index2],api_name="infer_refresh")
     with gr.TabItem("Batch inference"):
-        gr.Markdown("Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').")
+        gr.Markdown(f"<center>Batch conversion\n. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').")
         vc_transform1 = gr.Number(label="Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12)", value=0)
         dir_input = gr.Textbox(label="Enter the path of the audio folder to be processed (copy it from the address bar of the file manager)", placeholder="C:\\Users\\Desktop\\input_vocal_dir")
         inputs = gr.File(file_count="multiple", label="Multiple audio files can also be imported. If a folder path exists, this input is ignored.")