Update app.py

app.py

@@ -11,6 +11,41 @@ print("Running on:", device)
 
 # Download and load model
 base_path = hf_hub_download(repo_id="showlab/OmniConsistency", filename="OmniConsistency.safetensors", local_dir="./Model")
+lora_path = hf_hub_download(
+    repo_id="showlab/OmniConsistency",
+    filename="LoRAs/Ghibli_rank128_bf16.safetensors",
+    local_dir="./LoRAs"
+)
+lora_path = hf_hub_download(
+    repo_id="showlab/OmniConsistency",
+    filename="LoRAs/American_Cartoon_rank128_bf16.safetensors",
+    local_dir="./LoRAs"
+)
+lora_path = hf_hub_download(
+    repo_id="showlab/OmniConsistency",
+    filename="LoRAs/Chinese_Ink_rank128_bf16.safetensors",
+    local_dir="./LoRAs"
+)
+lora_path = hf_hub_download(
+    repo_id="showlab/OmniConsistency",
+    filename="LoRAs/Jojo_rank128_bf16.safetensors",
+    local_dir="./LoRAs"
+)
+lora_path = hf_hub_download(
+    repo_id="showlab/OmniConsistency",
+    filename="LoRAs/Line_rank128_bf16.safetensors",
+    local_dir="./LoRAs"
+)
+lora_path = hf_hub_download(
+    repo_id="showlab/OmniConsistency",
+    filename="LoRAs/Rick_Morty_rank128_bf16.safetensors",
+    local_dir="./LoRAs"
+)
+lora_path = hf_hub_download(
+    repo_id="showlab/OmniConsistency",
+    filename="LoRAs/Vector_rank128_bf16.safetensors",
+    local_dir="./LoRAs"
+)
 
 pipe = FluxPipeline.from_pretrained(
     "black-forest-labs/FLUX.1-dev", 
@@ -19,6 +54,16 @@ pipe = FluxPipeline.from_pretrained(
 
 set_single_lora(pipe.transformer, base_path, lora_weights=[1], cond_size=512)
 
+pipe.unload_lora_weights()
+pipe.load_lora_weights("./LoRAs", weight_name="Ghibli_rank128_bf16.safetensors")
+pipe.load_lora_weights("./LoRAs", weight_name="American_Cartoon_rank128_bf16.safetensors")
+pipe.load_lora_weights("./LoRAs", weight_name="Chinese_Ink_rank128_bf16.safetensors")
+pipe.load_lora_weights("./LoRAs", weight_name="Jojo_rank128_bf16.safetensors")
+pipe.load_lora_weights("./LoRAs", weight_name="Line_rank128_bf16.safetensors")
+pipe.load_lora_weights("./LoRAs", weight_name="Rick_Morty_rank128_bf16.safetensors")
+pipe.load_lora_weights("./LoRAs", weight_name="Vector_rank128_bf16.safetensors")
+
+
 def generate_manga(input_image, prompt):
     spatial_image = [input_image.convert("RGB")]
     image = pipe(