import os 
import huggingface_hub as hf_hub
import gradio as gr

client = hf_hub.InferenceClient(token = os.environ['HF_TOKEN'])
client.headers["x-use-cache"] = "0"

def image_interface(prompt, negative_prompt, guidance_scale, steps):
    response = client.text_to_image(
        prompt = prompt,
        negative_prompt = negative_prompt,
        model = 'segmind/Segmind-Vega',
        guidance_scale = guidance_scale,
        num_inference_steps = steps, 
    )

    return response

app = gr.Interface(
    fn = image_interface, 
    inputs = [
        gr.Textbox(label = 'Prompt'), 
        gr.Textbox(label = 'Negative Prompt'), 
        gr.Slider(minimum = 1, maximum = 30, value = 7, step = 0.5, label = 'Guidance Scale', show_label = True),
        gr.Slider(minimum = 10, maximum = 100, value = 50, step = 10, label = 'Number of Inference Steps', show_label = True)
    ], 
    outputs = 'image', 
    title = 'Stable Diffusion XL',
    description = 'Vinay Kumar Thakur'
)

app.launch()