Create app.py

app.py

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+# 🤖✨ CPU Image Generator (Stable Diffusion)
+
+import torch
+from diffusers import StableDiffusionPipeline
+import gradio as gr
+
+# Load model once at startup (≈3.4 GB; fits HF Space free tier CPU)
+PIPELINE_ID = "runwayml/stable-diffusion-v1-5"
+pipe = StableDiffusionPipeline.from_pretrained(
+    PIPELINE_ID,
+    torch_dtype=torch.float32,
+    safety_checker=None,            # skip NSFW checker
+)
+pipe = pipe.to("cpu")
+
+def generate_image(prompt: str, steps: int):
+    if not prompt:
+        return None
+    image = pipe(prompt, num_inference_steps=steps).images[0]
+    return image
+
+with gr.Blocks(title="🤖✨ AI Image Generator (CPU)") as demo:
+    gr.Markdown(
+        "# 🤖✨ AI Image Generator\n"
+        "Enter a creative prompt, adjust inference steps, and generate a unique image—**100% CPU**."
+    )
+    with gr.Row():
+        prompt_in = gr.Textbox(
+            label="Prompt",
+            placeholder="e.g. A photorealistic portrait of a cyberpunk fox"
+        )
+        steps_in = gr.Slider(
+            minimum=1, maximum=50, value=25, step=1, label="Inference Steps"
+        )
+    run_btn = gr.Button("Generate 🖼️", variant="primary")
+    img_out = gr.Image(label="Generated Image")
+
+    run_btn.click(generate_image, [prompt_in, steps_in], img_out)
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0")