nevproject/PonyDiffusionV10

1import gradio as gr2import requests3from PIL import Image4from io import BytesIO5import os6 7 8 9# Load API Token from environment variable10API_TOKEN = os.getenv("HF_API_TOKEN")  # Ensure you've set this environment variable11 12# Hugging Face Inference API URL13API_URL = "https://api-inference.huggingface.co/models/Benevolent/PonyDiffusionV10"14 15# Function to call Hugging Face API and get the generated image16def generate_image(prompt):17    headers = {"Authorization": f"Bearer {API_TOKEN}"}18    data = {"inputs": prompt}19    20    response = requests.post(API_URL, headers=headers, json=data)21    22    if response.status_code == 200:23        image_bytes = BytesIO(response.content)24        image = Image.open(image_bytes)25        return image26    else:27        return f"Error: {response.status_code}, {response.text}"28 29# Create Gradio interface30def create_ui():31    with gr.Blocks() as ui:32        gr.Markdown("## PonyDiffusionV10 - Text to Image Generator")33        34        with gr.Row():35            prompt_input = gr.Textbox(label="Enter a Prompt", placeholder="Describe the image you want to generate", lines=3)36            generate_button = gr.Button("Generate Image")37        38        with gr.Row():39            output_image = gr.Image(label="Generated Image")40        41        # Link the button to the function42        generate_button.click(fn=generate_image, inputs=prompt_input, outputs=output_image)43    44    return ui45 46# Run the interface47if __name__ == "__main__":48    create_ui().launch()