compact UI: remove instrumental checkbox, lock steps, scroll fix, timing labels, LoRA+LM same row

app.py

@@ -506,7 +506,7 @@ def gradio_main():
     _train_log_lines = []
 
     # -- Generate tab handler --
-    def generate_music(caption, lyrics, instrumental, bpm, duration, seed,
+    def generate_music(caption, lyrics, bpm, duration, seed,
                        steps, lora_select, lm_model_select,
                        progress=gr.Progress(track_tqdm=True)):
         if not _training_lock.acquire(blocking=False):
@@ -515,7 +515,7 @@ def gradio_main():
         if not _server_ok():
             return None, "ace-server not running. Check logs."
 
-        if instrumental or not lyrics or lyrics.strip() == "":
+        if not lyrics or lyrics.strip() == "":
             lyrics = "[Instrumental]"
 
         actual_seed = None if seed is None or int(seed) < 0 else int(seed)
@@ -946,7 +946,7 @@ def gradio_main():
     # -- Build UI --
     CSS = """
     .compact-row { gap: 8px !important; }
-    .status-box textarea { font-family: monospace; font-size: 13px; }
+    .status-box textarea { font-family: monospace; font-size: 13px; overflow-y: auto !important; }
     """
 
     with gr.Blocks(title="ACE-Step 1.5 XL (CPU)") as demo:
@@ -956,14 +956,14 @@ def gradio_main():
             # Tab 1: Generate Music
             # ============================================================
             with gr.Tab("Generate Music"):
-                gr.Markdown("**[ACE-Step 1.5 XL](https://github.com/ace-step/ACE-Step-1.5)** GGUF Q4_K_M via [acestep.cpp](https://github.com/ServeurpersoCom/acestep.cpp)")
+                gr.Markdown("**[ACE-Step 1.5 XL](https://github.com/ace-step/ACE-Step-1.5)** GGUF Q4_K_M via [acestep.cpp](https://github.com/ServeurpersoCom/acestep.cpp) | ~5 min for 10s audio")
                 with gr.Row(elem_classes="compact-row"):
                     with gr.Column(scale=3):
                         audio_out = gr.Audio(label="Output", type="filepath")
                         status = gr.Textbox(
                             label="Status",
                             interactive=False,
-                            lines=2,
+                            lines=1,
                             elem_classes="status-box",
                         )
                         caption = gr.Textbox(
@@ -975,36 +975,36 @@ def gradio_main():
                             label="Lyrics",
                             lines=3,
                             value="[Instrumental]",
-                            placeholder="Enter lyrics or [Instrumental] for no vocals",
+                            placeholder="Enter lyrics here, or leave empty for instrumental (no vocals)",
                         )
                     with gr.Column(scale=2):
                         gen_btn = gr.Button("Generate Music", variant="primary")
                         with gr.Row(elem_classes="compact-row"):
-                            instrumental = gr.Checkbox(label="Instrumental", value=True)
                             bpm = gr.Number(label="BPM", value=120, minimum=0, maximum=300)
+                            seed = gr.Number(label="Seed (-1=random)", value=-1)
                         with gr.Row(elem_classes="compact-row"):
                             duration = gr.Slider(
                                 label="Duration (s)", minimum=10, maximum=120,
                                 value=10, step=5,
                             )
                             steps = gr.Slider(
-                                label="Steps", minimum=1, maximum=32,
-                                value=8, step=1,
+                                label="Steps (8 for turbo)", minimum=1, maximum=32,
+                                value=8, step=1, interactive=False,
+                            )
+                        with gr.Row(elem_classes="compact-row"):
+                            lora_select = gr.Dropdown(
+                                label="LoRA", choices=_list_lora_choices(),
+                                value="None (no LoRA)",
+                                allow_custom_value=True,
+                            )
+                            lm_model_select = gr.Dropdown(
+                                label="LM Model", choices=_lm_model_choices(),
+                                value=DEFAULT_LM,
                             )
-                        seed = gr.Number(label="Seed (-1=random)", value=-1)
-                        lora_select = gr.Dropdown(
-                            label="LoRA", choices=_list_lora_choices(),
-                            value="None (no LoRA)",
-                            allow_custom_value=True,
-                        )
-                        lm_model_select = gr.Dropdown(
-                            label="LM Model", choices=_lm_model_choices(),
-                            value=DEFAULT_LM,
-                        )
 
                 gen_btn.click(
                     fn=generate_music,
-                    inputs=[caption, lyrics, instrumental, bpm, duration,
+                    inputs=[caption, lyrics, bpm, duration,
                             seed, steps, lora_select, lm_model_select],
                     outputs=[audio_out, status],
                     api_name="generate",
@@ -1014,13 +1014,15 @@ def gradio_main():
             # Tab 2: Train LoRA
             # ============================================================
             with gr.Tab("Train LoRA"):
-                gr.Markdown("LoRA training ported from [Side-Step](https://github.com/koda-dernet/Side-Step) | Model: [ACE-Step 1.5](https://github.com/ace-step/ACE-Step-1.5)")
+                gr.Markdown("LoRA training ported from [Side-Step](https://github.com/koda-dernet/Side-Step) | Model: [ACE-Step 1.5](https://github.com/ace-step/ACE-Step-1.5) | ~8h for 3 files @ 200 epochs")
                 with gr.Row(elem_classes="compact-row"):
                     with gr.Column(scale=3):
                         train_log = gr.Textbox(
                             label="Training Log",
                             interactive=False,
                             lines=12,
+                            max_lines=50,
+                            autoscroll=True,
                             elem_classes="status-box",
                         )
                         train_output_file = gr.File(label="Trained LoRA (download)", visible=False)
@@ -1036,7 +1038,7 @@ def gradio_main():
                             cancel_btn = gr.Button("Cancel Training", variant="stop", visible=False, scale=1)
                         lora_name = gr.Textbox(label="LoRA Name", value="my-lora")
                         train_epochs = gr.Slider(
-                            label="Epochs (200 recommended, ~6h on CPU)",
+                            label="Epochs (200 recommended ~6h on CPU, best 500)",
                             minimum=1, maximum=1000,
                             value=200, step=1,
                         )