app.py

# app.py (النسخة النهائية - مع تصحيح SyntaxError الثاني)

import gradio as gr
import numpy as np
import random
import torch
from diffusers import DiffusionPipeline
import time

# --- 1. Settings and Constants ---
DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
DTYPE = torch.float16 if torch.cuda.is_available() else torch.float32

MODEL_ID = "YourUsername/Takween-v1" 
BASE_MODEL_ID = "runwayml/stable-diffusion-v1-5"
MAX_SEED = np.iinfo(np.int32).max

LOGO_SVG = """
<svg xmlns="http://www.w3.org/2000/svg" width="48" height="48" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
  <path d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2z"></path>
  <path d="M7 7h10v2H7z"></path>
  <path d="M12 7v10"></path>
</svg>
"""

# --- 2. Model Loading ---
try:
    pipe = DiffusionPipeline.from_pretrained(MODEL_ID, torch_dtype=DTYPE, safety_checker=None)
    print(f"✅ Trained model '{MODEL_ID}' loaded successfully.")
except Exception:
    print(f"❌ Could not load trained model '{MODEL_ID}'. Loading base model.")
    pipe = DiffusionPipeline.from_pretrained(BASE_MODEL_ID, torch_dtype=DTYPE, safety_checker=None)

pipe = pipe.to(DEVICE)

# --- 3. Professional Theme (Golden Version) ---
theme = gr.themes.Base(
    primary_hue=gr.themes.colors.amber,
    secondary_hue=gr.themes.colors.neutral,
    font=[gr.themes.GoogleFont("IBM Plex Sans"), "system-ui", "sans-serif"],
).set(
    body_background_fill="*neutral_50",
    block_background_fill="white",
    block_border_width="1px",
    block_shadow="*shadow_drop_lg",
    button_primary_background_fill="*primary_500",
    button_primary_background_fill_hover="*primary_600",
)

# --- 4. Inference Function with UI Updates (Corrected) ---
def infer(prompt, negative_prompt, guidance_scale, num_inference_steps, seed, randomize_seed):
    if randomize_seed:
        seed = random.randint(0, MAX_SEED)
    
    # =======================================================
    # <<< تم تعديل هذا الجزء لحل مشكلة SyntaxError >>>
    # الخطوة 1: إنشاء المولد على الجهاز الصحيح
    generator = torch.Generator(device=DEVICE)
    # الخطوة 2: تحديد البذرة للمولد
    generator.manual_seed(seed)
    # =======================================================
    
    yield {
        output_image: gr.update(value=None, interactive=False, visible=True),
        run_button: gr.update(interactive=False, value="Generating..."),
    }
    
    image = pipe(
        prompt=prompt,
        negative_prompt=negative_prompt,
        guidance_scale=guidance_scale,
        num_inference_steps=int(num_inference_steps),
        generator=generator,
    ).images[0]
    
    yield {
        output_image: gr.update(value=image, interactive=True),
        output_seed: gr.update(value=seed),
        run_button: gr.update(interactive=True, value="Generate Again"),
    }

# --- 5. Professional UI Layout ---
with gr.Blocks(theme=theme, css="#footer {text-align: center;}") as demo:
    with gr.Row():
        gr.HTML(f"<div style='display: flex; align-items: center; gap: 12px;'>{LOGO_SVG}<h1>Takween Project</h1></div>")
    gr.Markdown("#### A specialized model for generating precise geometric images from text descriptions.")
    gr.HTML("<hr>")
    with gr.Row():
        with gr.Column(scale=1):
            prompt = gr.Textbox(label="Prompt", placeholder="A red circle with thick black borders...", lines=3)
            negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Low quality, blurry, distorted...")
            with gr.Accordion("Advanced Settings", open=False):
                guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=20.0, value=7.5, step=0.1)
                num_inference_steps = gr.Slider(label="Number of Steps", minimum=10, maximum=100, value=30, step=1)
                with gr.Row():
                    seed = gr.Number(label="Seed", value=0, precision=0)
                    randomize_seed = gr.Checkbox(label="Randomize", value=True)
            run_button = gr.Button("Generate Image", variant="primary")
            gr.Examples(examples=["A filled red circle with a thick black border", "An outline blue triangle positioned to the left of a yellow square", "A green star overlapping a purple rectangle"], inputs=[prompt])
        with gr.Column(scale=2):
            output_image = gr.Image(label="Generated Image", interactive=False, height=512)
            output_seed = gr.Textbox(label="Seed Used", interactive=False)
    gr.HTML("<hr>")
    with gr.Accordion("Team and Acknowledgments", open=False):
        gr.Markdown("""
        <div style='text-align: left;'>
            <h4><b>Development Team:</b></h4>
            <ul>
                <li>Osama Saeed</li>
                <li>Tareq Al-Omari</li>
            </ul>
            <hr>
            <h4><b>Special Thanks:</b></h4>
            <p>We extend our sincere gratitude for the guidance and support of:</p>
            <ul>
                <li><b>Dr. Akram Al-Sabari</b> (Professor of AI and Machine Learning)</li>
                <li><b>Eng. Faten Al-Hayafi</b> (Practical Side Instructor)</li>
            </ul>
        </div>
        """)
    gr.Markdown("<p id='footer'>© 2025 Takween Project. Developed by Osama Saeed & Tareq Al-Omari. All rights reserved.</p>")
    
    run_button.click(
        fn=infer,
        inputs=[prompt, negative_prompt, guidance_scale, num_inference_steps, seed, randomize_seed],
        outputs=[output_image, output_seed, run_button],
    )

# --- 6. Launch the App ---
if __name__ == "__main__":
    demo.launch()