Update app.py

app.py

@@ -1,3 +1,4 @@
+from huggingface_hub import hf_hub_download
 from diffusers import StableDiffusionPipeline
 from safetensors.torch import load_file
 import torch
@@ -6,18 +7,22 @@ def load_pipeline(base_model_path, lora_path):
     # Load base SD-v1.5 pipeline
     pipeline = StableDiffusionPipeline.from_pretrained(base_model_path)
 
+    # Download the LoRA file
+    lora_path = hf_hub_download(repo_id=lora_repo_id, filename=lora_filename)
+
     # Load LoRA weights
     lora_state_dict = load_file(lora_path)
     pipeline.unet.load_attn_procs(lora_state_dict)
 
     return pipeline
 
-# Correct paths
-base_model_path = "runwayml/stable-diffusion-v1-5"  # Use a valid Hugging Face repo ID
-lora_path = "https://huggingface.co/maria26/Floor_Plan_LoRA/blob/main/model.safetensors"  # Ensure LoRA file is available locally
+# Define parameters
+base_model_path = "runwayml/stable-diffusion-v1-5"
+lora_repo_id = "maria26/Floor_Plan_LoRA"
+lora_filename = "model.safetensors"
 
 # Load the pipeline
-pipeline = load_pipeline(base_model_path, lora_path)
+pipeline = load_pipeline(base_model_path, lora_repo_id, lora_filename)
 
 def predict(prompt):
     result = pipeline(prompt).images[0]