Create app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+from diffusers import DiffusionPipeline
+
+# Load the DiffusionPipeline and LORA weights
+pipeline = DiffusionPipeline.from_pretrained("stablediffusionapi/juggernaut-xl-v5")
+pipeline.load_lora_weights("Kvikontent/kviimager2.0")
+
+# Define the function to handle user input and generate the image
+def generate_image(prompt):
+    image = pipeline(prompt)
+    return image
+
+# Create a Gradio interface
+iface = gr.Interface(
+    fn=generate_image,
+    inputs="text",
+    outputs="image",
+    title="KVIImager 2.0 Demo",
+    description="Enter a prompt to generate an image"
+)
+
+# Add examples for the user input
+examples = [
+    "Sunset over the ocean",
+    "Starry night sky"
+]
+
+iface.set_config(
+    examples=examples
+)
+
+# Launch the Gradio interface
+iface.launch()