Create app.py

app.py

@@ -0,0 +1,54 @@
+import gradio as gr
+import torch
+from diffusers import StableDiffusionPipeline
+from PIL import Image
+import traceback
+from typing import Optional
+
+model_id: str = "runwayml/stable-diffusion-v1-5"
+device: str = "cpu"  # force CPU usage for compatibility
+
+image_generator_pipe: Optional[StableDiffusionPipeline] = None
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
+image_generator_pipe = pipe.to(device)
+
+def generate_image_sd(prompt: str, negative_prompt: str, guidance_scale: float, num_inference_steps: int) -> Image.Image:
+    with torch.no_grad():
+        output = image_generator_pipe(
+            prompt=prompt,
+            negative_prompt=negative_prompt,
+            guidance_scale=guidance_scale,
+            num_inference_steps=num_inference_steps
+        )
+        image = output.images[0] if output.images else None
+
+    if not image:
+        raise RuntimeError("No image was returned from the generation pipeline.")
+
+    print(f"Image generated in {end_time - start_time:.2f} seconds.")
+    return image
+
+    with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    with gr.Row():
+        with gr.Column(scale=1):
+            prompt = gr.Textbox(label="Prompt", placeholder="A beautiful futuristic city skyline at night")
+            neg_prompt = gr.Textbox(label="Negative Prompt", placeholder="blurry, distorted, watermark")
+            guidance = gr.Slider(1.0, 15.0, value=7.5, step=0.5, label="Guidance Scale")
+            steps = gr.Slider(10, 50, value=25, step=1, label="Inference Steps")
+            generate_btn = gr.Button("Generate Image")
+
+        with gr.Column(scale=1):
+            output_image = gr.Image(label="Generated Image", type="pil")
+
+    generate_btn.click(
+        fn=generate_image_sd,
+        inputs=[prompt, neg_prompt, guidance, steps],
+        outputs=output_image
+    )
+
+if __name__ == "__main__":
+    if not image_generator_pipe:
+        print("WARNING: Image generator pipeline is not available. UI will launch, but generation will fail.")
+    demo.launch(server_name="0.0.0.0", server_port=7860)
+
+