Update app.py

app.py

@@ -6,18 +6,16 @@ from diffusers import (
     AutoencoderKL,
     DPMSolverSinglestepScheduler,
 )
-from huggingface_hub import hf_hub_download
 
 # --- Configuration ---
 # The base model your LoRA was trained on.
 base_model_id = "stabilityai/stable-diffusion-xl-base-1.0"
 
-# --- CORRECTED REPOSITORY PATH ---
-# The path to your LoRA file on the Hugging Face Hub.
-lora_repo_id = "TuringSolutions/EmilyH"  # Corrected from "TuringsSolutions"
-lora_filename = "emilyh.safetensors"
+# --- The file is local, so we just need its name ---
+# The safetensors file is in the same directory as this script.
+lora_file_path = "emilyh.safetensors"
 
-# --- Load the Pipeline (No token needed for public repos) ---
+# --- Load the Pipeline ---
 # Use a recommended VAE for SDXL
 vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
 pipe = StableDiffusionXLPipeline.from_pretrained(
@@ -28,9 +26,8 @@ pipe = StableDiffusionXLPipeline.from_pretrained(
     use_safetensors=True
 )
 
-# --- Load and Fuse the LoRA (No token needed for public repos) ---
-# Download the LoRA file and load the state dict.
-lora_file_path = hf_hub_download(repo_id=lora_repo_id, filename=lora_filename)
+# --- Load the local LoRA file ---
+# No download needed. We just load the local file directly.
 pipe.load_lora_weights(lora_file_path)
 
 # Move the pipeline to the GPU