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import requests |
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import io |
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from PIL import Image |
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import gradio as gr |
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import os |
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API_TOKEN = os.getenv("HF_API_TOKEN") |
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if not API_TOKEN: |
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raise ValueError("Hugging Face API token not found. Please set the HF_API_TOKEN environment variable.") |
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API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0" |
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headers = {"Authorization": f"Bearer {API_TOKEN}"} |
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def generate_image(prompt, negative_prompt, guidance_scale, width, height, num_inference_steps): |
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payload = { |
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"inputs": prompt, |
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"parameters": { |
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"negative_prompt": negative_prompt, |
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"guidance_scale": guidance_scale, |
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"width": width, |
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"height": height, |
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"num_inference_steps": num_inference_steps, |
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}, |
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} |
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response = requests.post(API_URL, headers=headers, json=payload) |
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image_bytes = response.content |
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image = Image.open(io.BytesIO(image_bytes)) |
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return image |
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iface = gr.Interface( |
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fn=generate_image, |
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inputs=[ |
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gr.Textbox(label="Prompt", placeholder="Enter your prompt here..."), |
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gr.Textbox(label="Negative Prompt", placeholder="Enter a negative prompt here (optional)...", optional=True), |
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gr.Slider(label="Guidance Scale", minimum=1, maximum=20, step=0.1, value=7.5), |
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gr.Slider(label="Width", minimum=768, maximum=1024, step=1, value=1024), |
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gr.Slider(label="Height", minimum=768, maximum=1024, step=1, value=768), |
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gr.Slider(label="Number of Inference Steps", minimum=20, maximum=50, step=1, value=30) |
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], |
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outputs=gr.Image(type="pil"), |
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title="Stable Diffusion XL Image Generator", |
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description="Generate images with Stable Diffusion XL. Provide a prompt, optionally specify a negative prompt, and adjust other parameters as desired." |
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) |
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iface.launch() |
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