import gradio as gr
from diffusers import DiffusionPipeline
import torch

pipe = DiffusionPipeline.from_pretrained(
    "AMRDIAB20/sd15-charify-merged"
)

def generate(prompt, guidance):
    image = pipe(
        prompt,
        num_inference_steps=30,  # ✅ عدد خطوات ثابت
        guidance_scale=guidance,
        height=512,
        width=512
    ).images[0]
    return image

gr.Interface(
    fn=generate,
    inputs=[
        gr.Textbox(label="Prompt", value="Charify-style, cartoon character"),
        gr.Slider(1.0, 12.0, value=7.5, label="Guidance Scale")
    ],
    outputs=gr.Image(type="pil"),
    title="Charify-style, cartoon character",
    description="Charify-style, cartoon character, using the merged Charify LoRA model."
).launch()