Create app.py

app.py

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+import gradio as gr
+from diffusers import StableDiffusionPipeline
+import torch
+import os
+
+# Retrieve Hugging Face API key from environment variables (Hugging Face Secrets)
+hf_token = os.getenv("HF_TOKEN")
+
+# Load the Stable Diffusion model in CPU mode
+pipe = StableDiffusionPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-2",
+    torch_dtype=torch.float32,  # Ensure compatibility with CPU
+    use_auth_token=hf_token
+)
+
+# Force model to run on CPU
+pipe.to("cpu")
+
+# Optimize performance for CPU execution
+pipe.enable_attention_slicing()
+
+# Define image generation function
+def generate_image(prompt):
+    try:
+        image = pipe(prompt).images[0]
+        return image
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=generate_image,
+    inputs=gr.Textbox(label="Enter your prompt"),
+    outputs=gr.Image(label="Generated Image"),
+    title="Stable Diffusion (CPU Optimized)",
+    description="Generate AI-generated images using Stable Diffusion on CPU. No GPU required!"
+)
+
+if __name__ == "__main__":
+    iface.launch(share=True)