import os
import gradio as gr

api_key = os.getenv('HF_API_KEY')

# with gr.Blocks() as demo:
#     gr.load("fffiloni/sd-xl-custom-model", api_key=api_key, hf_token=api_key, src="spaces")

from gradio_client import Client


def predict(prompt):
    client = Client("fffiloni/sd-xl-custom-model")
    result = client.predict(
    		custom_model="lichorosario/dott_remastered_style_lora_sdxl",
    		api_name="/load_model"
    )

    client = Client("fffiloni/sd-xl-custom-model")
    result = client.predict(
		custom_model="lichorosario/dott_remastered_style_lora_sdxl",
		weight_name="dott_style.safetensors",
		prompt=prompt,
		inf_steps=25,
		guidance_scale=12,
		width=1024,
		height=512,
		seed=-1,
		lora_weight=1,
		api_name="/infer"
    )

    return result

with gr.Blocks() as demo:
    inputs = gr.Textbox(label="Prompt")
    outputs = [gr.Image(label="Image"), gr.Textbox(label="Seed")]
    greet_btn = gr.Button("Generate")
    greet_btn.click(fn=predict, inputs=inputs, outputs=outputs, api_name="predict")

demo.launch()