import gradio as gr
from diffusers import StableDiffusionPipeline
import torch
import time

# MODELLER
MODELS = {
    "Realistic": "visionpy_realistic",
    "Anime": "visionpy_anime"
}

# MODEL YÜKLEME
def load_model(mode):
    pipe = StableDiffusionPipeline.from_pretrained(
        MODELS[mode],
        torch_dtype=torch.float16
    ).to("cuda")
    # Hız optimizasyonu
    # xFormers destekleniyorsa uncomment:
    # pipe.enable_xformers_memory_efficient_attention()
    return pipe

# ANA ÜRETİM FONKSİYONU
def generate(prompt, mode, res):
    pipe = load_model(mode)
    start_time = time.time()

    # Çözünürlük
    if res == "512p":
        w, h = 512, 512
        steps = 20
    elif res == "1024p":
        w, h = 1024, 1024
        steps = 25
    else:
        w, h = 512, 512
        steps = 20

    image = pipe(prompt, height=h, width=w, num_inference_steps=steps, guidance_scale=7.5).images[0]

    elapsed = time.time() - start_time
    return image, f"{elapsed:.2f} saniyede üretildi!"

# GRADIO ARAYÜZÜ
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown(
        "<h1 style='text-align:center'>🌟 Hh — VisionPy Ultra HD (11s Mode)</h1>"
        "<p style='text-align:center'>Anime / Realistic Modları, 512-1024p hızlı üretim, Light Theme</p>"
    )

    with gr.Row():
        prompt = gr.Textbox(label="Prompt", placeholder="ör: fantastik şehir ultra yüksek çözünürlük")
        mode = gr.Dropdown(["Realistic", "Anime"], label="Mod")
        res = gr.Dropdown(["512p", "1024p"], label="Çözünürlük (Hızlı Mod)")

    out = gr.Image(label="Sonuç")
    time_label = gr.Label(label="Üretim Süresi")

    btn = gr.Button("ÜRET")
    btn.click(generate, inputs=[prompt, mode, res], outputs=[out, time_label])

demo.launch()