Update app.py

app.py

@@ -7,21 +7,12 @@ import spaces
 
 device=torch.device('cuda')
 
-# Load the model and LoRA weights
-pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
-print(prompt)
-    
-if style=='shou_xin':
-    prompt= "shou_xin, " + prompt
-    pipe.load_lora_weights("Datou1111/shou_xin", weight_name="shou_xin.safetensors")
-else:
-    prompt= "sketched style, " + prompt
-    pipe.load_lora_weights("Shakker-Labs/FLUX.1-dev-LoRA-Children-Simple-Sketch", weight_name="FLUX-dev-lora-children-simple-sketch.safetensors")
-    
 
 
-pipe.fuse_lora(lora_scale=1.5)
-pipe.to("cuda")
+ 
+
+
+
 
 # Load the NSFW classifier
 image_classifier = pipeline("image-classification", model="Falconsai/nsfw_image_detection",device=device)
@@ -40,7 +31,18 @@ def generate_sketch(prompt,style, num_inference_steps, guidance_scale):
     #for result in text_classification:
     #    if result['label'] == 'nsfw' and result['score'] > NSFW_THRESHOLD: 
     #        return gr.update(visible=False),gr.Text(value="Inappropriate prompt detected. Please try another prompt.")
-   
+    print(prompt)
+    
+    pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
+    if style=='shou_xin':
+        prompt= "shou_xin, " + prompt
+        pipe.load_lora_weights("Datou1111/shou_xin", weight_name="shou_xin.safetensors")
+    else:
+        prompt= "sketched style, " + prompt
+        pipe.load_lora_weights("Shakker-Labs/FLUX.1-dev-LoRA-Children-Simple-Sketch", weight_name="FLUX-dev-lora-children-simple-sketch.safetensors")
+    
+    pipe.fuse_lora(lora_scale=1.5)
+    pipe.to("cuda")
         
     image = pipe("sketched style, " + prompt, 
                  num_inference_steps=num_inference_steps,