Spaces:
Running
Running
| import gradio as gr | |
| import requests | |
| from PIL import Image | |
| import io | |
| import PIL | |
| import os | |
| from dotenv import load_dotenv | |
| # Load environment variables from .env file | |
| load_dotenv() | |
| API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0" | |
| headers = os.getenv("SEECRET_TOKEN") | |
| def generate_image(prompt): | |
| response = requests.post(API_URL, headers=headers, json={"inputs": prompt}) | |
| if response.status_code == 200: | |
| image_bytes = response.content | |
| try: | |
| image = Image.open(io.BytesIO(image_bytes)) | |
| return image | |
| except PIL.UnidentifiedImageError as e: | |
| return None | |
| else: | |
| return None | |
| iface = gr.Interface( | |
| fn=generate_image, | |
| inputs="text", | |
| outputs="image", | |
| title="π Prompt to Image Generator π", | |
| description="Generate stunning images from your prompts using an AI model.", | |
| layout="wide", | |
| theme="huggingface", | |
| examples=[ | |
| ["A surreal painting of a floating city at sunset"], | |
| ["An abstract landscape with vibrant colors and geometric shapes"] | |
| ] | |
| ) | |
| iface.launch() | |