simplify logic

app.py

@@ -84,7 +84,24 @@ def infer(
     num_inference_steps,
     negative_prompt,
     guidance_scale,
+    user_lora_selector,
+    user_lora_weight,
+    gr_lora_loaded,
 ):
+    flash_sdxl_id = "jasperai/flash-sdxl"
+
+    if user_lora_selector == "" or user_lora_selector == "":
+        raise gr.Error("Please select a LoRA before running the inference.")
+
+    if gr_lora_loaded != user_lora_selector:
+        gr.Info("Loading LoRA")
+        pipe.unload_lora_weights()
+        pipe.load_lora_weights(flash_sdxl_id, adapter_name="lora")
+        pipe.load_lora_weights(user_lora_selector, adapter_name="user")
+        pipe.set_adapters(["lora", "user"], adapter_weights=[1.0, user_lora_weight])
+        gr.Info("LoRA Loaded")
+
+        gr_lora_loaded = user_lora_selector
 
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
@@ -102,7 +119,7 @@ def infer(
         generator=generator,
     ).images[0]
 
-    return image
+    return image, gr_lora_loaded
 
 
 css = """
@@ -258,10 +275,6 @@ with gr.Blocks(css=css) as demo:
             negative_prompt.submit,
             guidance_scale.change,
         ],
-        fn=check_and_load_lora_user,
-        inputs=[user_lora_selector, user_lora_weight, gr_lora_loaded],
-        outputs=[gr_lora_loaded],
-    ).success(
         fn=infer,
         inputs=[
             pre_prompt,
@@ -271,8 +284,11 @@ with gr.Blocks(css=css) as demo:
             num_inference_steps,
             negative_prompt,
             guidance_scale,
+            user_lora_selector,
+            user_lora_weight,
+            gr_lora_loaded,
         ],
-        outputs=[result],
+        outputs=[result, gr_lora_loaded],
         show_progress="minimal",
     )