fixing melodyflow

app.py

@@ -152,20 +152,27 @@ def transform_with_melodyflow_api(audio_path, variation, custom_prompt="", solve
         # Determine the prompt to use
         if custom_prompt.strip():
             prompt_text = custom_prompt.strip()
-            status_msg = f"✅ Transformed with custom prompt: '{prompt_text}' (flowstep: {flowstep})"
+            status_msg = f"✅ Transformed with custom prompt: '{prompt_text}' (flowstep: {flowstep}, {effective_steps} steps)"
         else:
             prompt_text = VARIATION_PROMPTS.get(variation, f"transform this audio to {variation} style")
-            status_msg = f"✅ Transformed with {variation} style (flowstep: {flowstep})"
+            status_msg = f"✅ Transformed with {variation} style (flowstep: {flowstep}, {effective_steps} steps)"
         
-        # Set steps based on solver (from your original logic)
-        steps = 64 if solver == "midpoint" else 128
+        # Set steps based on solver and the fact we're doing editing
+        # Facebook's space automatically reduces steps for editing:
+        # EULER: divides by 5, MIDPOINT: divides by 2
+        if solver == "midpoint":
+            base_steps = 128
+            effective_steps = base_steps // 2  # 64 effective steps
+        else:  # euler
+            base_steps = 125  
+            effective_steps = base_steps // 5  # 25 effective steps
         
-        # Call the MelodyFlow API
+        # Call the MelodyFlow API with the base steps (it will auto-reduce)
         result = client.predict(
             model="facebook/melodyflow-t24-30secs",
             text=prompt_text,
             solver=solver,
-            steps=steps,
+            steps=base_steps,  # Will be auto-reduced to effective_steps by the space
             target_flowstep=flowstep,  # This is the key parameter!
             regularize=solver == "euler",  # Regularize for euler, not for midpoint
             regularization_strength=0.2,
@@ -209,6 +216,10 @@ with gr.Blocks() as iface:
         4. **Repeat** the cycle to create infinite musical journeys!
         
         The models run with different PyTorch versions, so we use the Facebook MelodyFlow space via API.
+        
+        **Performance Note**: For audio transformation, MelodyFlow automatically uses fewer steps than generation:
+        - EULER solver: 25 effective steps (fast, good quality)
+        - MIDPOINT solver: 64 effective steps (slower, potentially higher quality)
         """)
 
     # ========== STEP 1: GENERATE ==========
@@ -249,7 +260,8 @@ with gr.Blocks() as iface:
         transform_solver = gr.Dropdown(
             label="Solver",
             choices=["euler", "midpoint"],
-            value="euler"
+            value="euler",
+            info="EULER: faster (25 steps), MIDPOINT: slower but potentially higher quality (64 steps)"
         )
         transform_flowstep = gr.Slider(
             label="Transform Intensity (Flowstep)",