Update app.py

app.py

@@ -15,10 +15,15 @@ pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
 
 lora_repo = "kaytoo2022/kaytoo2022-flux"
 trigger_word = ""  # Leave trigger_word blank if not used.
-pipe.load_lora_weights(lora_repo)
+pipe.load_lora_weights(lora_repo, adapter_name='kaytoo')
 
-# lora_ghibli = 'alvarobartt/ghibli-characters-flux-lora'
-# pipe.load_lora_weights(lora_ghibli)
+lora_ghibli = 'alvarobartt/ghibli-characters-flux-lora'
+pipe.load_lora_weights(lora_ghibli, adapter_name='ghibli')
+
+lora_repo_anime = "aleksa-codes/flux-ghibsky-illustration"
+pipe.load_lora_weights(lora_repo_anime, adapter_name='ghibsky')
+
+pipe.set_adapters(["kaytoo", "ghibli", "ghibsky"], adapter_weights=[0.85, 0.65, 0.65])
 
 pipe.to("cuda")
 
@@ -65,11 +70,13 @@ example_width = 1152
 example_height = 896
 example_seed = 3981632454
 example_lora_scale = 0.85
+example_lora_scale_ghibli = 0.65
+example_lora_scale_ghibsky = 0.65
 
 def load_example():
     # Load example image from file
     example_image = Image.open(example_image_path)
-    return example_prompt, example_cfg_scale, example_steps, True, example_seed, example_width, example_height, example_lora_scale, example_image
+    return example_prompt, example_cfg_scale, example_steps, True, example_seed, example_width, example_height, example_lora_scale, example_lora_scale_ghibli, example_lora_scale_ghibsky, example_image
 
 with gr.Blocks() as app:
     gr.Markdown("# Flux Lora Image Generator")
@@ -84,12 +91,14 @@ with gr.Blocks() as app:
             randomize_seed = gr.Checkbox(True, label="Randomize seed")
             seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=example_seed)
             lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=1, step=0.01, value=example_lora_scale)
+            lora_scale_ghibli = gr.Slider(label="LoRA Scale (ghibli)", minimum=0, maximum=1, step=0.01, value=example_lora_scale_ghibli)
+            lora_scale_ghibsky = gr.Slider(label="LoRA Scale (ghibli)", minimum=0, maximum=1, step=0.01, value=example_lora_scale_ghibsky)
         with gr.Column(scale=1):
             result = gr.Image(label="Generated Image")
             gr.Markdown("Generate images using Flux and a text prompt.\nUse `b3lla dog` in the prompt to trigger generating an image of Bella the dog.\n[[non-commercial license, Flux.1 Dev](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md)]")
 
     # Automatically load example data and image when the interface is launched
-    app.load(load_example, inputs=[], outputs=[prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale, result])
+    app.load(load_example, inputs=[], outputs=[prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale, lora_scale_ghibli, lora_scale_ghibsky, result])
     
     generate_button.click(
         run_lora,