Update main/app/tabs/inference/inference.py

main/app/tabs/inference/inference.py

@@ -16,7 +16,7 @@ def inference_tabs():
                     with gr.Row():
                         model_pth = gr.Dropdown(label=translations["model_name"], choices=model_name, value=model_name[0] if len(model_name) >= 1 else "", interactive=True, allow_custom_value=True)
                         model_index = gr.Dropdown(label=translations["index_path"], choices=index_path, value=index_path[0] if len(index_path) >= 1 else "", interactive=True, allow_custom_value=True)
-                    refesh = gr.Button(translations["refesh"])
+                        refesh = gr.Button(translations["refesh"])
                 
         with gr.Row(): 
             with gr.Column():
@@ -312,6 +312,7 @@ def inference_tabs():
             with gr.Row():
                 model_pth0 = gr.Dropdown(label=translations["model_name"], choices=model_name, value=model_name[0] if len(model_name) >= 1 else "", interactive=True, allow_custom_value=True)
                 model_index0 = gr.Dropdown(label=translations["index_path"], choices=index_path, value=index_path[0] if len(index_path) >= 1 else "", interactive=True, allow_custom_value=True)
+                refesh1 = gr.Button(translations["refesh"])
                     
         with gr.Row():
             with gr.Column():
@@ -332,7 +333,7 @@ def inference_tabs():
                 tts_voice = gr.Dropdown(label=translations["voice"], choices=edgetts, interactive=True, value="vi-VN-NamMinhNeural")
                 tts_pitch = gr.Slider(minimum=-20, maximum=20, step=1, info=translations["pitch_info_2"], label=translations["pitch"], value=0, interactive=True)
             with gr.Column():
-                refesh1 = gr.Button(translations["refesh"])
+                
                 with gr.Row():
                     index_strength0 = gr.Slider(label=translations["index_strength"], info=translations["index_strength_info"], minimum=0, maximum=1, value=0.5, step=0.01, interactive=True, visible=model_index0.value != "")
                 with gr.Accordion(translations["output_path"], open=False):
@@ -457,7 +458,21 @@ def inference_tabs():
             gr.Markdown(translations["convert_with_whisper_info"])
         with gr.Row():
             with gr.Column():
+                
+                with gr.Accordion(translations["model_accordion"] + " 1", open=True):
+                    with gr.Row():
+                        model_pth2 = gr.Dropdown(label=translations["model_name"], choices=model_name, value=model_name[0] if len(model_name) >= 1 else "", interactive=True, allow_custom_value=True)
+                        model_index2 = gr.Dropdown(label=translations["index_path"], choices=index_path, value=index_path[0] if len(index_path) >= 1 else "", interactive=True, allow_custom_value=True)
+                        
+                        refesh2 = gr.Button(translations["refesh"])
+                with gr.Accordion(translations["model_accordion"] + " 2", open=True):
+                    with gr.Row():
+                        model_pth3 = gr.Dropdown(label=translations["model_name"], choices=model_name, value=model_name[0] if len(model_name) >= 1 else "", interactive=True, allow_custom_value=True)
+                        model_index3 = gr.Dropdown(label=translations["index_path"], choices=index_path, value=index_path[0] if len(index_path) >= 1 else "", interactive=True, allow_custom_value=True)
+                        refesh3 = gr.Button(translations["refesh"])
+                    
                 with gr.Group():
+                
                     with gr.Row():
                         cleaner2 = gr.Checkbox(label=translations["clear_audio"], value=False, interactive=True)
                         autotune2 = gr.Checkbox(label=translations["autotune"], value=False, interactive=True)
@@ -470,12 +485,7 @@ def inference_tabs():
                 convert_button3 = gr.Button(translations["convert_audio"], variant="primary")
         with gr.Row():
             with gr.Column():
-                with gr.Accordion(translations["model_accordion"] + " 1", open=True):
-                    with gr.Row():
-                        model_pth2 = gr.Dropdown(label=translations["model_name"], choices=model_name, value=model_name[0] if len(model_name) >= 1 else "", interactive=True, allow_custom_value=True)
-                        model_index2 = gr.Dropdown(label=translations["index_path"], choices=index_path, value=index_path[0] if len(index_path) >= 1 else "", interactive=True, allow_custom_value=True)
-                    with gr.Row():
-                        refesh2 = gr.Button(translations["refesh"])
+                    
                     with gr.Row():
                         pitch3 = gr.Slider(minimum=-20, maximum=20, step=1, info=translations["pitch_info"], label=translations["pitch"], value=0, interactive=True)
                         index_strength2 = gr.Slider(label=translations["index_strength"], info=translations["index_strength_info"], minimum=0, maximum=1, value=0.5, step=0.01, interactive=True, visible=model_index2.value != "")
@@ -489,12 +499,7 @@ def inference_tabs():
                     with gr.Row():
                         input2 = gr.File(label=translations["drop_audio"], file_types=[".wav", ".mp3", ".flac", ".ogg", ".opus", ".m4a", ".mp4", ".aac", ".alac", ".wma", ".aiff", ".webm", ".ac3"])
             with gr.Column():
-                with gr.Accordion(translations["model_accordion"] + " 2", open=True):
-                    with gr.Row():
-                        model_pth3 = gr.Dropdown(label=translations["model_name"], choices=model_name, value=model_name[0] if len(model_name) >= 1 else "", interactive=True, allow_custom_value=True)
-                        model_index3 = gr.Dropdown(label=translations["index_path"], choices=index_path, value=index_path[0] if len(index_path) >= 1 else "", interactive=True, allow_custom_value=True)
-                    with gr.Row():
-                        refesh3 = gr.Button(translations["refesh"])
+                
                     with gr.Row():
                         pitch4 = gr.Slider(minimum=-20, maximum=20, step=1, info=translations["pitch_info"], label=translations["pitch"], value=0, interactive=True)
                         index_strength3 = gr.Slider(label=translations["index_strength"], info=translations["index_strength_info"], minimum=0, maximum=1, value=0.5, step=0.01, interactive=True, visible=model_index3.value != "")