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app.py

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+# app.py
+
+import streamlit as st
+from diffusers import StableDiffusionPipeline
+import torch
+from PIL import Image
+import io
+
+# Load model once
+@st.cache_resource
+def load_model():
+    pipe = StableDiffusionPipeline.from_pretrained(
+        "runwayml/stable-diffusion-v1-5",  # You can change this to another model
+        torch_dtype=torch.float16
+    )
+    return pipe.to("cuda")
+
+# Streamlit app UI
+st.title("🧠 AI Image Generator (Stable Diffusion)")
+st.markdown("Generate original, multidimensional images using Stable Diffusion!")
+
+prompt = st.text_area("Enter your creative prompt:", 
+                      "A multi-dimensional alien city with glowing fractals, floating geometry, cosmic lighting, 8K resolution")
+
+guidance = st.slider("Creativity (Guidance Scale)", 1.0, 20.0, 8.5)
+
+if st.button("Generate Image"):
+    with st.spinner("Generating image..."):
+        pipe = load_model()
+        image = pipe(prompt, guidance_scale=guidance).images[0]
+
+        st.image(image, caption="Generated Image", use_column_width=True)
+
+        # Download button
+        buf = io.BytesIO()
+        image.save(buf, format="PNG")
+        byte_im = buf.getvalue()
+        st.download_button("Download Image", byte_im, "generated.png", "image/png")

requirements.txt

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+streamlit
+torch
+torchvision
+torchaudio
+diffusers
+transformers
+accelerate
+safetensors
+Pillow