Update app.py

app.py

@@ -30,9 +30,24 @@ class timer:
 if not path.exists(cache_path):
     os.makedirs(cache_path, exist_ok=True)
 
+def load_and_fuse_lora_weights(pipe, lora_models):
+    for repo, file_path, lora_scale in lora_models:
+        lora_weights_path = hf_hub_download(repo_id=repo, filename=file_path)
+        pipe.load_lora_weights(lora_weights_path)
+        pipe.fuse_lora(lora_scale=lora_scale)
+
+# List of LoRA models and their corresponding scales
+lora_models = [
+    ("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors", 0.125),
+    # Add more LoRA models here
+    ("mrcuddle/live2d-model-maker", "LIVE2D-FLUX.safetensors", 0.8),
+]
+
 pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
-pipe.load_lora_weights(hf_hub_download("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors"))
-pipe.fuse_lora(lora_scale=0.125)
+
+# Load and fuse LoRA weights
+load_and_fuse_lora_weights(pipe, lora_models)
+
 pipe.to(device="cuda", dtype=torch.bfloat16)
 
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
@@ -53,24 +68,31 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
                     placeholder="E.g., A serene landscape with mountains and a lake at sunset",
                     lines=3
                 )
-                
+
+                # Hidden textbox for the preset prompt
+                preset_prompt = gr.Textbox(
+                    label="Preset Prompt",
+                    value="live2d,guijiaoxiansheng,separate hand,separate feet,separate head,full body,solo,white background,simple background, CharacterDesignFLUX, reference sheet,white background,simple background,multiple views, upper body, front, from side, color palette reference, high_detailed, captured in high detail, magic particles, multiple references",
+                    visible=False
+                )
+
                 with gr.Accordion("Advanced Settings", open=False):
                     with gr.Group():
                         with gr.Row():
                             height = gr.Slider(label="Height", minimum=256, maximum=1152, step=64, value=1024)
                             width = gr.Slider(label="Width", minimum=256, maximum=1152, step=64, value=1024)
-                        
+
                         with gr.Row():
                             steps = gr.Slider(label="Inference Steps", minimum=6, maximum=25, step=1, value=8)
                             scales = gr.Slider(label="Guidance Scale", minimum=0.0, maximum=5.0, step=0.1, value=3.5)
-                        
+
                         seed = gr.Number(label="Seed (for reproducibility)", value=3413, precision=0)
-                
+
                 generate_btn = gr.Button("Generate Image", variant="primary", scale=1)
 
         with gr.Column(scale=4):
             output = gr.Image(label="Your Generated Image")
-    
+
     gr.Markdown(
         """
         <div style="max-width: 650px; margin: 2rem auto; padding: 1rem; border-radius: 10px; background-color: #f0f0f0;">
@@ -86,11 +108,13 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
     )
 
     @spaces.GPU
-    def process_image(height, width, steps, scales, prompt, seed):
+    def process_image(height, width, steps, scales, prompt, seed, preset_prompt):
         global pipe
         with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16), timer("inference"):
+            # Concatenate the preset prompt with the user's input prompt
+            full_prompt = f"{preset_prompt} {prompt}"
             return pipe(
-                prompt=[prompt],
+                prompt=[full_prompt],
                 generator=torch.Generator().manual_seed(int(seed)),
                 num_inference_steps=int(steps),
                 guidance_scale=float(scales),
@@ -101,7 +125,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
 
     generate_btn.click(
         process_image,
-        inputs=[height, width, steps, scales, prompt, seed],
+        inputs=[height, width, steps, scales, prompt, seed, preset_prompt],
         outputs=output
     )