Update app.py

app.py

@@ -21,13 +21,13 @@ with gr.Blocks(title="RVC UI") as app:
     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,)
+    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, visible=False)
     with gr.Tabs():
         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="file")
+            input_audio0 = gr.Audio(label="The audio file to be processed",type="filepath")
             file_index1 = gr.File(label="Path to the feature index file. Leave blank to use the selected result from the dropdown")
             with gr.Column():
                 f0method0 = gr.Radio(label="Select the pitch extraction algorithm ('pm': faster extraction but lower-quality speech; 'harvest': better bass but extremely slow; 'crepe': better quality but GPU intensive), 'rmvpe': best quality, and little GPU requirement",choices=(["pm", "dio", "harvest", "crepe", "rmvpe", "fcpe"]),value="rmvpe",interactive=True)
@@ -37,7 +37,7 @@ with gr.Blocks(title="RVC UI") as app:
                 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")
-                vc_output1 = gr.Textbox(label="Output information")
+                vc_output1 = gr.Textbox(label="Output information", interactive=False)
                 vc_output2 = gr.Audio(label="Export audio (click on the three dots in the lower right corner to download)",type="filepath")
                 #refresh_button.click(fn=change_choices,inputs=[],outputs=[models, file_index2],api_name="infer_refresh")
         with gr.TabItem("Batch inference"):