Update app.py

app.py

@@ -9,13 +9,13 @@ has_cuda = torch.cuda.is_available()
 device = torch.device('cpu' if not has_cuda else 'cuda')    
 pipe = pipe.to(device)
 
-def inference(diffusion_prompt):
+def convert(prompt):
     samples = 4
     generator = torch.Generator(device=device)
     torch.cuda.empty_cache()
     with autocast("cuda"):
         images_list = pipe(
-            [diffusion_prompt] * samples,
+            [prompt] * samples,
             height=256, width=384,
             num_inference_steps=50,
         )
@@ -25,15 +25,7 @@ def inference(diffusion_prompt):
     return images
 
 
-with gr.Blocks() as demo:
-    gr.Markdown("# Text to Image Generator")
-    with gr.Row():
-                prompt = gr.Textbox(
-                    lines=1,
-                    placeholder="Enter your prompt..",
-                    interactive=True,
-                    label="Prompt"
-                )
-                submit = gr.Button("Run")
-    submit.click(fn=inference, inputs=[prompt], outputs=[images])
-demo.launch()
+gr.Interface(convert,
+             inputs = [gr.inputs.Textbox(label="Enter text")],    
+             outputs = [gr.outputs.Image(label="Generated Image")], 
+             title="Text to Image Generation").launch()