Add multiple LoRAs with simultaneous loading

- Add 5 LoRAs: AntiBlur, Add Details, Face Realism, Ultra Realism, Detailed Hands
- Implement automatic download from HuggingFace URLs
- Load all LoRAs simultaneously at startup for combined effects
- Update UI to show all LoRAs are active by default
- Remove LoRA selection dropdown in favor of all-active approach

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

app.py

@@ -6,6 +6,9 @@ import torch
 from diffusers import  DiffusionPipeline, FlowMatchEulerDiscreteScheduler, AutoencoderTiny, AutoencoderKL
 from transformers import CLIPTextModel, CLIPTokenizer,T5EncoderModel, T5TokenizerFast
 from live_preview_helpers import calculate_shift, retrieve_timesteps, flux_pipe_call_that_returns_an_iterable_of_images
+from huggingface_hub import hf_hub_download
+import os
+import requests
 
 dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -13,6 +16,60 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype).to(device)
 good_vae = AutoencoderKL.from_pretrained("black-forest-labs/FLUX.1-dev", subfolder="vae", torch_dtype=dtype).to(device)
 pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=dtype, vae=taef1).to(device)
+
+# Available LoRAs
+LORAS = {
+    "None": None,
+    "AntiBlur": "Shakker-Labs/FLUX.1-dev-LoRA-AntiBlur",
+    "Add Details": "Shakker-Labs/FLUX.1-dev-LoRA-add-details",
+    "Face Realism": "https://huggingface.co/its-magick/merlin-test-loras/resolve/main/Canopus-LoRA-Flux-FaceRealism.safetensors",
+    "Ultra Realism": "https://huggingface.co/its-magick/merlin-test-loras/resolve/main/Canopus-LoRA-Flux-UltraRealism.safetensors",
+    "Detailed Hands": "https://huggingface.co/its-magick/merlin-test-loras/resolve/main/Detailed_Hands-000001.safetensors"
+}
+
+# Store loaded LoRA paths
+loaded_loras = {}
+
+def download_lora_from_url(url, filename):
+    """Download LoRA file from direct URL"""
+    if not os.path.exists(filename):
+        print(f"Downloading {filename}...")
+        response = requests.get(url)
+        with open(filename, 'wb') as f:
+            f.write(response.content)
+        print(f"Downloaded {filename}")
+    return filename
+
+def preload_and_load_all_loras():
+    """Download and load all LoRAs simultaneously at startup"""
+    global loaded_loras
+    
+    print("Downloading and loading all LoRAs...")
+    lora_weights = []
+    
+    for lora_name, lora_path in LORAS.items():
+        if lora_name == "None" or lora_path is None:
+            continue
+            
+        # Handle direct URL downloads
+        if lora_path.startswith('http'):
+            filename = f"{lora_name.lower().replace(' ', '_')}_lora.safetensors"
+            lora_path = download_lora_from_url(lora_path, filename)
+        
+        loaded_loras[lora_name] = lora_path
+        lora_weights.append(lora_path)
+        print(f"Downloaded {lora_name}")
+    
+    # Load all LoRAs simultaneously
+    if lora_weights:
+        print("Loading all LoRAs simultaneously...")
+        pipe.load_lora_weights(lora_weights)
+        pipe.fuse_lora(lora_scale=1.0)
+        print(f"All {len(lora_weights)} LoRAs loaded and active!")
+
+# Load all LoRAs at startup
+preload_and_load_all_loras()
+
 torch.cuda.empty_cache()
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -75,6 +132,8 @@ with gr.Blocks(css=css) as demo:
         
         with gr.Accordion("Advanced Settings", open=False):
             
+            gr.Markdown("**LoRAs Active:** All LoRAs are loaded and active simultaneously")
+            
             seed = gr.Slider(
                 label="Seed",
                 minimum=0,