from diffusers import DiffusionPipeline
import gradio as gr
import torch

# Check device availability
device = "cuda" if torch.cuda.is_available() else "cpu"

# Load DiffusionPipeline model
pipeline = DiffusionPipeline.from_pretrained("anusha-bhambore/live-eventful")
pipeline = pipeline.to(device)

def generate_image_interface(prompt, negative_prompt, gender, age, num_inference_steps=50, weight=640):
    params = {
        'prompt': prompt, 
        'num_inference_steps': num_inference_steps, 
        'num_images_per_prompt': 2, 
        'height': int(1.2 * weight),
        'weight': weight, 
        'negative_prompt': negative_prompt,
        'gender': gender, 
        'age': age 
    }

    img = pipeline(**params).images
    return img[0], img[1]

description = "Experience the magic of personalized birthday event design with our innovative web app! Simply input your preferences and prompts, and watch as your creative ideas transform into stunning, one-of-a-kind birthday event images."

# Deploy the interface with shareable link
demo = gr.Interface(
    fn=generate_image_interface,
    title="Birthday Events",
    inputs=["text", "text", "text", "text", gr.Slider(1, 100), gr.Slider(512, 640)],
    outputs=["image", "image"],
    description=description
)
demo.launch(share=True)