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import requests
import io
from PIL import Image
import gradio as gr
import os
# Assuming you've set up API_TOKEN and other constants as before
def generate_image(prompt, negative_prompt=None, guidance_scale=7.5, width=1024, height=768, num_inference_steps=30):
payload = {
"inputs": prompt,
"parameters": {
"width": width,
"height": height,
"guidance_scale": guidance_scale,
"num_inference_steps": num_inference_steps,
},
}
# Include negative prompt in the payload if provided
if negative_prompt:
payload["parameters"]["negative_prompt"] = negative_prompt
response = requests.post(API_URL, headers=headers, json=payload)
image_bytes = response.content
image = Image.open(io.BytesIO(image_bytes))
return image
# Define Gradio interface components
iface = gr.Interface(
fn=generate_image,
inputs=[
gr.Textbox(label="Prompt", placeholder="Enter your prompt here..."),
gr.Textbox(label="Negative Prompt", placeholder="Enter a negative prompt here (optional)..."),
gr.Slider(label="Guidance Scale", minimum=1, maximum=20, step=0.1, default=7.5),
gr.Slider(label="Width", minimum=768, maximum=1024, step=1, default=1024),
gr.Slider(label="Height", minimum=768, maximum=1024, step=1, default=768),
gr.Slider(label="Number of Inference Steps", minimum=20, maximum=50, step=1, default=30)
],
outputs=gr.Image(type="pil"),
title="Stable Diffusion XL Image Generator",
description="Generate images with Stable Diffusion XL. Provide a prompt, optionally specify a negative prompt, and adjust other parameters as desired."
)
# Launch the Gradio app
iface.launch()
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