Create app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+from diffusers import StableDiffusionPipeline
+import torch
+
+# Load the model (takes a few seconds on start)
+model_id = "runwayml/stable-diffusion-v1-5"
+pipe = StableDiffusionPipeline.from_pretrained(
+    model_id, 
+    torch_dtype=torch.float16,
+    revision="fp16",
+    use_auth_token=True
+)
+pipe = pipe.to("cuda")
+
+# Define inference function
+def generate_image(prompt):
+    image = pipe(prompt).images[0]
+    return image
+
+# Create Gradio interface
+description = "Enter a description below and the app will generate an image based on it."
+
+demo = gr.Interface(
+    fn=generate_image,
+    inputs=gr.Textbox(label="Enter image description", placeholder="e.g. A tree on a mountain during sunset"),
+    outputs=gr.Image(type="pil"),
+    title="Text to Image Generator",
+    description=description,
+    theme="default"
+)
+
+if __name__ == "__main__":
+    demo.launch()