app.py

import streamlit as st
from PIL import Image
from io import BytesIO
import base64
from diffusers import StableDiffusionPipeline
import torch

# Initialize the Stable Diffusion model
model_id = "stabilityai/stable-diffusion-3-medium"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
pipe.to("cpu")

def generate_image(prompt, negative_prompt=None, temperature=1.0, steps=50, image_size=(512, 512)):
    # Generate an image using the Stable Diffusion pipeline
    image = pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=steps, guidance_scale=temperature).images[0]
    # Resize image
    image = image.resize(image_size)
    
    # Convert image to base64
    buffered = BytesIO()
    image.save(buffered, format="PNG")
    img_str = base64.b64encode(buffered.getvalue()).decode('utf-8')
    return img_str

def main():
    st.title("Stable Diffusion Image Generation API")
    st.write("Generate images using Stable Diffusion and get them in base64 format.")
    
    # Get parameters from URL
    query_params = st.experimental_get_query_params()
    prompt = query_params.get("prompt", [""])[0]
    negative_prompt = query_params.get("negative_prompt", [None])[0]
    temperature = float(query_params.get("temperature", [1.0])[0])
    steps = int(query_params.get("steps", [50])[0])
    image_size = tuple(map(int, query_params.get("image_size", ["512,512"])[0].split(",")))
    
    if prompt:
        st.write("Generating image with parameters:")
        st.write(f"Prompt: {prompt}")
        st.write(f"Negative Prompt: {negative_prompt}")
        st.write(f"Temperature: {temperature}")
        st.write(f"Steps: {steps}")
        st.write(f"Image Size: {image_size}")
        
        # Generate the image
        img_base64 = generate_image(prompt, negative_prompt, temperature, steps, image_size)
        
        # Display the image
        st.image(f"data:image/png;base64,{img_base64}", caption="Generated Image")
        
        # Provide the base64 image string
        st.text_area("Base64 Image String", value=img_base64, height=200)
    
if __name__ == "__main__":
    main()