fix: handle multiple safetensors in repo

app.py

@@ -24,6 +24,7 @@ def generate_video(
     prompt,
     negative_prompt,
     lora_id,
+    lora_weight_name,
     lora_scale,
     scheduler_type,
     flow_shift,
@@ -55,7 +56,22 @@ def generate_video(
     
     # Load LoRA weights if provided
     if lora_id and lora_id.strip():
-        pipe.load_lora_weights(lora_id)
+        try:
+            # If a specific weight name is provided, use it
+            if lora_weight_name and lora_weight_name.strip():
+                pipe.load_lora_weights(lora_id, weight_name=lora_weight_name)
+            else:
+                pipe.load_lora_weights(lora_id)
+            
+            # Set lora scale if applicable
+            if hasattr(pipe, "set_adapters_scale") and lora_scale is not None:
+                pipe.set_adapters_scale(lora_scale)
+        except ValueError as e:
+            # Return informative error if there are multiple safetensors and no weight name
+            if "more than one weights file" in str(e):
+                return f"Error: The repository '{lora_id}' contains multiple safetensors files. Please specify a weight name using the 'LoRA Weight Name' field."
+            else:
+                return f"Error loading LoRA weights: {str(e)}"
     
     # Enable CPU offload for low VRAM
     pipe.enable_model_cpu_offload()
@@ -79,7 +95,16 @@ def generate_video(
 
 # Create the Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("# Wan Video Generation with ZeroGPU")
+    gr.Markdown("# Wan 2.1 T2V 1.3B with LoRA")
+    gr.HTML("""
+    <p align="center">
+    <svg version="1.1" viewBox="0 0 1200 295" xmlns="http://www.w3.org/2000/svg" xmlns:v="https://vecta.io/nano" width="400">
+        <path d='M195.43 109.93a.18.18 0 0 1-.27-.03l-.17-.26a.13.12-43.2 0 1 .01-.16q21.87-21.98 42.02-37.95c17.57-13.93 36.61-26.36 57.23-34.01q13.26-4.92 24.23-4.1c10.91.81 18.01 8.05 19.12 18.82.79 7.76-.64 15.73-3.29 23.37q-5.87 16.92-15.46 32.47a1.05 1.02-40.3 0 0-.09.91q11.79 32.3 2.48 63.6c-13.06 43.95-53.78 72.83-99.49 71.06q-16.32-.64-30.92-6.27a1.88 1.88 0 0 0-1.65.15c-12.54 7.69-26.93 14.55-41.16 17.68-4.99 1.1-9.54.6-16.14.62a6.31 6.04 50.1 0 1-1.35-.15c-19.69-4.51-18.03-25.43-12.71-40.65q5.95-17.05 15.9-32.34a.89.88 50.1 0 0 .07-.82c-13.76-32.93-7.8-71.64 14.32-99.05q20.75-25.73 51.75-33.99 29.88-7.96 59.38 2.25a.18.18 0 0 1 .04.32l-11.17 7.52a1.18 1.17-55 0 1-.93.17q-26.82-6.3-51.8 2.83c-24.65 9.02-43.94 28.53-52.73 53.27q-8.3 23.33-2.99 48.49.7 3.32 3.15 10.35c7.87 22.55 24.1 40.02 45.62 50.35a.52.51 43.2 0 1 .03.91l-10.31 5.96a.7.68-44.3 0 1-.69 0q-27.53-15.57-41.3-43.86a.1.09-44.1 0 0-.17 0q-6.59 11.46-11.16 23.67c-4.39 11.73-11.35 38.04 10.45 38.5q6.38.13 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+    </svg>
+    <p align="center">
+    💻 <a href="https://www.markury.dev/"><b>Website</b></a> &nbsp&nbsp | &nbsp&nbsp 🤗 <a href="https://huggingface.co/markury"><b>Hugging Face</b></a> &nbsp&nbsp | &nbsp&nbsp 💿 <a href="https://thebulge.xyz"><b>Discord</b></a>
+    </p>
+    """)
     
     with gr.Row():
         with gr.Column(scale=1):
@@ -106,11 +131,18 @@ with gr.Blocks() as demo:
                     label="LoRA ID (e.g., benjamin-paine/steamboat-willie-1.3b)",
                     value="benjamin-paine/steamboat-willie-1.3b"
                 )
+            
+            with gr.Row():
+                lora_weight_name = gr.Textbox(
+                    label="LoRA Weight Name (optional, specify for repos with multiple .safetensors files)",
+                    value="",
+                    info="Example: adapter_model.safetensors, pytorch_lora_weights.safetensors, etc."
+                )
                 lora_scale = gr.Slider(
                     label="LoRA Scale",
                     minimum=0.0,
                     maximum=1.0,
-                    value=0.75,
+                    value=1.00,
                     step=0.05
                 )
             
@@ -134,15 +166,15 @@ with gr.Blocks() as demo:
                     label="Height",
                     minimum=256,
                     maximum=1024,
-                    value=480,
+                    value=832,
                     step=32
                 )
                 width = gr.Slider(
                     label="Width",
                     minimum=256,
                     maximum=1792,
-                    value=832,
-                    step=32
+                    value=480,
+                    step=30
                 )
             
             with gr.Row():
@@ -150,7 +182,7 @@ with gr.Blocks() as demo:
                     label="Number of Frames (4k+1 is recommended, e.g. 81)",
                     minimum=17,
                     maximum=129,
-                    value=81,
+                    value=33,
                     step=4
                 )
                 output_fps = gr.Slider(
@@ -189,6 +221,7 @@ with gr.Blocks() as demo:
             prompt,
             negative_prompt,
             lora_id,
+            lora_weight_name,
             lora_scale,
             scheduler_type,
             flow_shift,
@@ -208,6 +241,10 @@ with gr.Blocks() as demo:
     - For larger resolution videos, try higher values of flow shift (7.0-12.0)
     - Number of frames should be of the form 4k+1 (e.g., 49, 81, 65)
     - The model is memory intensive, so adjust resolution according to available VRAM
+    
+    ## Using LoRAs with multiple safetensors files:
+    If you encounter an error stating "more than one weights file", you need to specify the exact weight file name in the "LoRA Weight Name" field.
+    You can find this by browsing the repository on Hugging Face and looking for the safetensors files (common names include: adapter_model.safetensors, pytorch_lora_weights.safetensors).
     """)
 
 demo.launch()