Fix compatibility issues with stable diffusers version

- Use stable diffusers 0.30.3 instead of git dev version
- Use transformers 4.44.2 for compatibility
- Remove PEFT dependency causing import errors
- Switch back to single LoRA selection instead of simultaneous loading
- Download all LoRAs at startup but load one at a time

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

Co-Authored-By: Claude <[email protected]>

app.py

@@ -40,12 +40,11 @@ def download_lora_from_url(url, filename):
         print(f"Downloaded {filename}")
     return filename
 
-def preload_and_load_all_loras():
-    """Download and load all LoRAs simultaneously at startup"""
+def preload_loras():
+    """Download all LoRAs at startup for later use"""
     global loaded_loras
     
-    print("Downloading and loading all LoRAs...")
-    adapters_to_load = []
+    print("Downloading all LoRAs...")
     
     for lora_name, lora_path in LORAS.items():
         if lora_name == "None" or lora_path is None:
@@ -57,28 +56,12 @@ def preload_and_load_all_loras():
             lora_path = download_lora_from_url(lora_path, filename)
         
         loaded_loras[lora_name] = lora_path
-        adapters_to_load.append(lora_path)
         print(f"Downloaded {lora_name}")
     
-    # Load all LoRAs with different adapter names
-    for i, lora_path in enumerate(adapters_to_load):
-        try:
-            adapter_name = f"adapter_{i}"
-            pipe.load_lora_weights(lora_path, adapter_name=adapter_name)
-            print(f"Loaded adapter {adapter_name}")
-        except Exception as e:
-            print(f"Failed to load {lora_path}: {e}")
-    
-    # Set all adapters as active
-    try:
-        adapter_names = [f"adapter_{i}" for i in range(len(adapters_to_load))]
-        pipe.set_adapters(adapter_names)
-        print(f"All {len(adapters_to_load)} LoRAs active!")
-    except Exception as e:
-        print(f"Failed to activate adapters: {e}")
+    print(f"All {len(loaded_loras)} LoRAs downloaded and ready!")
 
-# Load all LoRAs at startup
-preload_and_load_all_loras()
+# Download all LoRAs at startup
+preload_loras()
 
 torch.cuda.empty_cache()
 
@@ -88,11 +71,19 @@ MAX_IMAGE_SIZE = 2048
 pipe.flux_pipe_call_that_returns_an_iterable_of_images = flux_pipe_call_that_returns_an_iterable_of_images.__get__(pipe)
 
 @spaces.GPU(duration=75)
-def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidance_scale=3.5, num_inference_steps=28, progress=gr.Progress(track_tqdm=True)):
+def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidance_scale=3.5, num_inference_steps=28, lora_selection="None", progress=gr.Progress(track_tqdm=True)):
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
     generator = torch.Generator().manual_seed(seed)
     
+    # Load selected LoRA
+    if lora_selection != "None" and lora_selection in loaded_loras:
+        try:
+            pipe.load_lora_weights(loaded_loras[lora_selection])
+            pipe.fuse_lora(lora_scale=1.0)
+        except Exception as e:
+            print(f"Failed to load LoRA {lora_selection}: {e}")
+    
     for img in pipe.flux_pipe_call_that_returns_an_iterable_of_images(
             prompt=prompt,
             guidance_scale=guidance_scale,
@@ -142,7 +133,12 @@ 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")
+            lora_selection = gr.Dropdown(
+                label="LoRA",
+                choices=list(LORAS.keys()),
+                value="None",
+                info="Select a LoRA to enhance image generation"
+            )
             
             seed = gr.Slider(
                 label="Seed",
@@ -201,7 +197,7 @@ with gr.Blocks(css=css) as demo:
     gr.on(
         triggers=[run_button.click, prompt.submit],
         fn = infer,
-        inputs = [prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
+        inputs = [prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, lora_selection],
         outputs = [result, seed]
     )
 

requirements.txt

@@ -1,8 +1,7 @@
 accelerate
-git+https://github.com/huggingface/diffusers.git
+diffusers==0.30.3
 torch
-transformers>=4.44.0
+transformers==4.44.2
 xformers
 sentencepiece
-peft
 requests