Update app.py

app.py

@@ -1,6 +1,32 @@
 import gradio as gr
+from diffusers import DiffusionPipeline, StableDiffusionXLImg2ImgPipeline
+import torch
+from PIL import Image
 
+# Load the pipeline
+prj_path = "jkcg/furniture-chair"
+model = "stabilityai/stable-diffusion-xl-base-1.0"
+pipe = DiffusionPipeline.from_pretrained(
+     model,
+     torch_dtype=torch.float16,
+)
+pipe.to("cuda")
+pipe.load_lora_weights(prj_path, weight_name="pytorch_lora_weights.safetensors")
 
-examples = [["a photo of furnichair-texx in empty room, 8K, virtual staging"]]
+def generate_image(prompt, seed):
+    generator = torch.Generator("cuda").manual_seed(seed)
+    image = pipe(prompt=prompt, generator=generator).images[0]
+    return image
 
-gr.load("models/jkcg/furniture-chair", examples=examples).launch()
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=generate_image,
+    inputs=[
+        gr.Textbox(label="Prompt", value="photo of a furnichair-texx in an empty room"),
+        gr.Slider(label="Seed", minimum=0, maximum=10000, step=1, value=42)
+    ],
+    outputs=gr.Image(label="Generated Image")
+)
+
+# Launch the interface
+interface.launch(share=True)