Update app.py

app.py

@@ -80,7 +80,7 @@ def predict(music_prompt, melody, duration, model):
     return file.name
 
 css="""
-#col-container {max-width: 510px; margin-left: auto; margin-right: auto;}
+#col-container {max-width: 910px; margin-left: auto; margin-right: auto;}
 a {text-decoration-line: underline; font-weight: 600;}
 """
 
@@ -96,31 +96,32 @@ with gr.Blocks(css=css) as demo:
             for longer sequences, more control and no queue.</p>
             """
         )
-            
-        with gr.Column():
-            uploaded_sound = gr.Audio(type="numpy", label="Input", source="upload")
-            chosen_track = gr.Radio(["vocals", "bass", "drums", "other", "all-in"], label="Track", info="Which track from your audio do you want to mashup ?", value="vocals")
-            load_sound_btn = gr.Button('Load your sound')
-            #split_vocals = gr.Audio(type="filepath", label="Vocals")
-            #split_bass = gr.Audio(type="filepath", label="Bass")
-            #split_drums = gr.Audio(type="filepath", label="Drums")
-            #split_others = gr.Audio(type="filepath", label="Other")
-        with gr.Row():
-            music_prompt = gr.Textbox(label="Musical Prompt", info="Describe what kind of music you wish for", interactive=True)
-            melody = gr.Audio(source="upload", type="numpy", label="Track Condition (from previous step)", interactive=False)
-        with gr.Row():
-            model = gr.Radio(["melody", "medium", "small", "large"], label="Model", value="melody", interactive=True)
-        with gr.Row():
-            duration = gr.Slider(minimum=1, maximum=30, value=10, step=1, label="Generated Music Duration", interactive=True)
-        with gr.Row():
-            submit = gr.Button("Submit")
-        #with gr.Row():
-        #   topk = gr.Number(label="Top-k", value=250, interactive=True)
-        #   topp = gr.Number(label="Top-p", value=0, interactive=True)
-        #   temperature = gr.Number(label="Temperature", value=1.0, interactive=True)
-        #   cfg_coef = gr.Number(label="Classifier Free Guidance", value=3.0, interactive=True)
-        
-        output = gr.Audio(label="Generated Music")
+        with gr.Row():    
+            with gr.Column():
+                uploaded_sound = gr.Audio(type="numpy", label="Input", source="upload")
+                chosen_track = gr.Radio(["vocals", "bass", "drums", "other", "all-in"], label="Track", info="Which track from your audio do you want to mashup ?", value="vocals")
+                load_sound_btn = gr.Button('Load your sound')
+                #split_vocals = gr.Audio(type="filepath", label="Vocals")
+                #split_bass = gr.Audio(type="filepath", label="Bass")
+                #split_drums = gr.Audio(type="filepath", label="Drums")
+                #split_others = gr.Audio(type="filepath", label="Other")
+            with gr.Column():
+                with gr.Row():
+                    music_prompt = gr.Textbox(label="Musical Prompt", info="Describe what kind of music you wish for", interactive=True)
+                    melody = gr.Audio(source="upload", type="numpy", label="Track Condition (from previous step)", interactive=False)
+                with gr.Row():
+                    model = gr.Radio(["melody", "medium", "small", "large"], label="Model", value="melody", interactive=True)
+                with gr.Row():
+                    duration = gr.Slider(minimum=1, maximum=30, value=10, step=1, label="Generated Music Duration", interactive=True)
+                with gr.Row():
+                    submit = gr.Button("Submit")
+                #with gr.Row():
+                #   topk = gr.Number(label="Top-k", value=250, interactive=True)
+                #   topp = gr.Number(label="Top-p", value=0, interactive=True)
+                #   temperature = gr.Number(label="Temperature", value=1.0, interactive=True)
+                #   cfg_coef = gr.Number(label="Classifier Free Guidance", value=3.0, interactive=True)
+                
+                output = gr.Audio(label="Generated Music")
     load_sound_btn.click(split_process, inputs=[uploaded_sound, chosen_track], outputs=[melody])
     submit.click(predict, inputs=[music_prompt, melody, duration, model], outputs=[output])