Update app.py

app.py

@@ -147,18 +147,23 @@ def run_lora(prompt, negative_prompt, cfg_scale, steps, selected_index, seed, wi
             prompt_mash = f"{trigger_word} {prompt}"
     else:
         prompt_mash = prompt
-
+        
     # Load LoRA weights
     with calculateDuration(f"Loading LoRA weights for {selected_lora['title']}"):
         if "weights" in selected_lora:
-            pipe.load_lora_weights("ostris/OpenFLUX.1", weight_name="openflux1-v0.1.0-fast-lora.safetensors", adapter_name="fast", adapter_weights=[1.0], lora_scale=[1.0])
-            pipe.load_lora_weights(lora_path, weight_name=selected_lora["weights"], adapter_name=selected_lora["repo"], lora_scale=[1.0])
-            pipe.set_adapters(["fast", selected_lora["repo"]], adapter_weights=[1.0, 1.0])
+            pipe.load_lora_weights(lora_path, weight_name=selected_lora["weights"], adapter_name=selected_lora["repo"], lora_scale=[1.0], adapter_weights=lora_scale)
         else:
-            pipe.load_lora_weights("ostris/OpenFLUX.1", weight_name="openflux1-v0.1.0-fast-lora.safetensors", adapter_name="fast", adapter_weights=[1.0], lora_scale=[1.0])
-            pipe.load_lora_weights(lora_path, adapter_name=selected_lora["repo"], lora_scale=[1.0])
-            pipe.set_adapters(["fast", selected_lora["repo"]], adapter_weights=[1.0, 1.0])
-
+            pipe.load_lora_weights(lora_path, adapter_name=selected_lora["repo"], lora_scale=[1.0], adapter_weights=lora_scale)
+    # Load LoRA weights
+ #   with calculateDuration(f"Loading LoRA weights for {selected_lora['title']}"):
+    #    if "weights" in selected_lora:
+    #        pipe.load_lora_weights("ostris/OpenFLUX.1", weight_name="openflux1-v0.1.0-fast-lora.safetensors", adapter_name="soon", adapter_weights=[1.0], lora_scale=[1.0])
+    #        pipe.load_lora_weights(lora_path, weight_name=selected_lora["weights"], adapter_name=selected_lora["repo"], lora_scale=[1.0])
+    #        pipe.set_adapters(["fast", selected_lora["repo"]], adapter_weights=[1.0, 1.0])
+    #    else:
+    #        pipe.load_lora_weights("ostris/OpenFLUX.1", weight_name="openflux1-v0.1.0-fast-lora.safetensors", adapter_name="soon", adapter_weights=[1.0], lora_scale=[1.0])
+    #        pipe.load_lora_weights(lora_path, adapter_name=selected_lora["repo"], lora_scale=[1.0])
+     #       pipe.set_adapters(["fast", selected_lora["repo"]], adapter_weights=[1.0, 1.0])
 
     image = generate_image(prompt, negative_prompt, steps, seed, cfg_scale, width, height, lora_scale)
     pipe.to("cpu")
@@ -220,7 +225,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
             with gr.Column():
                 with gr.Row():
                     cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=3)
-                    steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=6)
+                    steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=20)
                 
                 with gr.Row():
                     width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024)
@@ -228,7 +233,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
                 
                 with gr.Row():
                     seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, randomize=True)
-                    lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=2.0, step=0.01, value=0.85)
+                    lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=2.0, step=0.01, value=1.0)
 
     gallery.select(
         update_selection,