Create app.py

app.py

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+import streamlit as st
+from diffusers import DiffusionPipeline
+import torch
+from PIL import Image
+from io import BytesIO
+
+# Load the diffusion pipeline
+@st.cache_resource
+def load_pipeline():
+    return DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0").to("cuda" if torch.cuda.is_available() else "cpu")
+
+pipeline = load_pipeline()
+
+def generate_image(prompt):
+    # Generate image
+    with torch.no_grad():
+        result = pipeline(prompt).images[0]
+    return result
+
+def main():
+    st.title("Stable Diffusion Image Generator")
+
+    # Get user input
+    prompt = st.text_input("Enter a prompt for image generation:")
+    
+    if st.button("Generate Image"):
+        if prompt:
+            # Generate and display the image
+            image = generate_image(prompt)
+            st.image(image, caption="Generated Image")
+        else:
+            st.warning("Please enter a prompt.")
+
+if __name__ == "__main__":
+    main()