Code Editor for app.py

import streamlit as st
from diffusers import StableDiffusionPipeline
import torch
from PIL import Image
import numpy as np

# Set page config
st.set_page_config(page_title="AI Image Generator", layout="wide")

# Title
st.title("🎨 AI Image Generator")

# Sidebar controls
with st.sidebar:
    st.header("Generation Settings")
    prompt = st.text_area("Enter your prompt", 
                         "A beautiful sunset over mountains, digital art")
    
    num_steps = st.slider("Number of inference steps", 
                         min_value=1, max_value=100, value=30)
    
    guidance_scale = st.slider("Guidance Scale", 
                             min_value=1.0, max_value=20.0, value=7.5, 
                             step=0.5)
    
    seed = st.number_input("Random Seed", 
                          min_value=0, max_value=999999999, value=42)

# Initialize model on first run
@st.cache_resource
def load_model():
    model_id = "runwayml/stable-diffusion-v1-5"
    pipe = StableDiffusionPipeline.from_pretrained(
        model_id,
        torch_dtype=torch.float32
    )
    return pipe

# Main content
st.write("## Image Generation")

if 'generated_image' not in st.session_state:
    st.session_state.generated_image = None

# Generate button
if st.button("Generate Image"):
    with st.spinner("Generating your image... Please wait"):
        try:
            # Set random seed for reproducibility
            torch.manual_seed(seed)
            np.random.seed(seed)
            
            # Load model
            pipe = load_model()
            
            # Generate image
            image = pipe(
                prompt=prompt,
                num_inference_steps=num_steps,
                guidance_scale=guidance_scale
            ).images[0]
            
            # Store the generated image
            st.session_state.generated_image = image
            
            # Display the image
            st.image(image, caption=prompt, use_column_width=True)
            
        except Exception as e:
            st.error(f"An error occurred: {str(e)}")

# Display previously generated image if it exists
elif st.session_state.generated_image is not None:
    st.image(st.session_state.generated_image, 
            caption="Previously generated image", 
            use_column_width=True)

# Instructions
st.write("## How to use")
st.write("""
1. Enter your text prompt describing the image you want to generate
2. Adjust the generation settings if desired:
   - Number of inference steps: Higher values give better quality but take longer
   - Guidance Scale: How closely the image follows the prompt
   - Random Seed: Controls randomness for reproducibility
3. Click 'Generate Image' to create your image
""")

# Warning about compute requirements
st.warning("""
⚠️ Note: This app requires significant computational resources. 
The first generation might take longer as the model needs to be loaded.
""")

# Footer
st.markdown("---")
st.markdown("Made with ❤️ using Stable Diffusion")